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Discussing the culture of preprints with auditory neuroscientists
Daniela Saderi, Ph.D.
Adriana Bankston

Daniela Saderi, Ph.D.

and 1 more

February 18, 2018
I started writing this memo while on an airplane, flying back from sunny San Diego. While definitely one of the highlights of the trip, the sunshine was not the reason for my visit to Southern California. Instead, I was there with hundreds of other auditory neuroscientists from all over the world to attend the 41th MidWinter Meeting of the Association for Research in Otolaryngology (ARO). 
Agate Analysis by Raman, XRF, and Hyperspectral Imaging Spectroscopy for Provenance...
Aaron J. Celestian

Aaron J. Celestian

and 7 more

February 15, 2018
AbstractThe Getty Museum recently acquired the Borghese-Windsor Cabinet (Figure \ref{620486}), a piece of furniture extensively decorated with agate, lapis lazuli, and other semi-precious stones.  The cabinet is thought to have been built around 1620 for Camillo Borghese (later Pope Paul V).  The Sixtus Cabinet, built around 1585 for Pope Sixtus V (born Felice Peretti di Montalto), is of similar design to the Borghese-Windsor and also ornately decorated with gemstones.  Although there are similarities in gemstones between the two cabinets, the Sixtus and Borghese-Windsor cabinets vary in their agate content.  It was traditionally thought that all agate gemstones acquired during the 16th and 17th centuries were sourced from the Nahe River Valley near Idar-Oberstein, Germany.  It is known that Brazilian agate began to be imported into Germany by the 1800s, but it is possible that some was imported in the 18th century or earlier.  A primary research goal was to determine if the agates in the Borghese-Windsor Cabinet are of single origin, or if they have more than one geologic provenance. Agates are made of SiO2, mostly as the mineral quartz, but also as metastable moganite.  Both quartz and moganite will crystallize together as the agate forms, but moganite is not stable at Earth's surface and will convert to quartz over tens of millions of years \cite{Moxon_2004,Peter_J_Heaney_1995,G_slason_1997}, thus relatively older agate contains less moganite.  Agate from the Idar-Oberstein is Permian in age (around 280 million years old), while agate from Rio Grande do Sul of Brazil generally formed during the Cretaceous (around 120 million years old).  It is thought that Rio Grande do Sul would have been a primary source of material exported to Europe because it is one of Brazil's oldest and largest agate gemstone producers.  Since Cretaceous agate from Brazil is many millions of years younger than Permian agate from Germany, the quartz to moganite ratios between the two localities should be quite different.  The agate gemstones of the Borghese-Windsor Cabinet cannot be removed for detailed Raman mapping experiments.    Because of this, we first analyzed multiple agate specimens from the collections of the Natural History Museum of Los Angeles (NHMLA) and the Smithsonian Institution National Museum of Natural History (NMNH) using three different techniques: Raman mapping, XRF mapping, and hyperspectral imaging. Raman spectroscopy provides an easy method to distinguish the relative quartz:moganite ratios and XRF analysis provides a measure of bulk geochemistry in agates.  Maps have advantages over line scans and point analysis in that they give a better representation of the mineral content, can be used to exclude trace mineral impurities, and yield better counting statistics and averaging.   Hyperspectral imaging provides a range of optical data from IR through UV wavelengths.   
PREreview of "Frequent lack of repressive capacity of promoter DNA methylation identi...
Hector Hernandez-Vargas

Hector Hernandez-Vargas

February 15, 2018
This is a review of the preprint "Frequent lack of repressive capacity of promoter DNA methylation identified through genome-wide epigenomic manipulation" by Ethan Edward Ford,  Matthew R. Grimmer,  Sabine Stolzenburg,  Ozren Bogdanovic,  Alex de Mendoza,  Peggy J. Farnham,  Pilar Blancafort, and  Ryan Lister.The preprint was originally posted on bioRxiv on September 20, 2017 (DOI: https://doi.org/10.1101/170506). 
The State Of Stablecoins- Why They Matter & Five Use Cases
Sheikh Mohammed Irfan
Robert Samuel Keaoakua Lin

Sheikh Mohammed Irfan

and 2 more

February 15, 2018
Price-stable cryptocurrencies, commonly referred to as stablecoins, have received a significant amount of attention recently. Much of this has been in hopes that they can fix some of the issues with cryptocurrency—most notably price instability. However, little analysis has been done with respect to the drivers and investment potential of stablecoins. Stablecoins fulfill different functions of money based on their implementation. As a result, they have unique trade-offs from one another and from physical currency (fiat) itself. Stablecoins offer a similar value proposition to fiat, but the two should not be compared on a one-to-one basis as stablecoins contain unique trade-offs and benefits. These differences will drive the demand for these tokens while enabling specific use cases. The purpose of this paper is to shed light on the adoption and the potential of market share growth for stablecoins given five selected use cases: dollarization, smart contracts, peer to peer (P2P) and peer to business (P2B payments), safe haven for exchanges, and as a reserve currency. We will discuss the opportunities within each of these use cases and assess the factors which will determine the success of stablecoins. Using insights contained in this paper, technologists can think about how best to position themselves in the short, medium, and long term. 
Emerging Countries and Trends in the World Trade Network: A Link Analysis Approach
Yash Raj Lamsal

Yash Raj Lamsal

February 14, 2018
Abstract The landscape in the world trade network has changed in last few decades.  This paper analyses World Trade Network (WTN) from 1990 to 2016, using the trade data available at the International Monetary Fund (IMF) website and presents the evolution of key players in the network using link analysis properties. Link Analysis analyzes the link strength between nodes of a network to evaluate the properties of the network. The paper uses link analysis algorithm such as PageRank, hubs, and authority to evaluate the strength or importance of nodes in the World Trade Network. A higher PageRank represents higher import dependencies, higher authority scores of a country denotes its significance to import from other hub countries, and a higher hub score indicates a country’s significance to export their final product to other authority sectors. The findings show the emergence of Asian countries, especially China, as key players in the world.  Key Words: World Trade Network, link analysis, PageRank, Authority, Hubs Introduction The value of global total export in the year 2016 is almost five (4.96) times the value in the year 1990. This fivefold growth in trade value is largely contributed by Emerging Market Economics (EMEs) \cite{Riad2012}. This indicates trade plays a vital role in the national economy as well as in the international economy. In this context, studying world trade from complex network perspectives provides meaningful insights. World Trade Network (WTN) is weighted directed complex network of countries around the world. In network science, a network is a collection of nodes and links, links are relations between the nodes and, in graph theory, a graph is a collection of vertices and edges, where edges are a relationship between vertices. Graph and Network are terms used interchangeably in this paper. For the WTN nodes are represented by the countries around the world and link represents the relationship between two countries, where the relationship is a flow of trade from one country to another. Study of the WTN applying network and graph theory framework has been growing and could be found in these works of literature \cite{Reyes2014,Deguchi2014}  \cite{Ermann2011,Benedictis2010}. This paper uses link analysis algorithms to analyze the WTN. Link analysis extracts information from a connected structure like the WTN \cite{Chakraborty}. Understanding such connected structure of trade furnish an immense source of information about the world economy, and this paper uses approaches, which was initially adopted to understand the World Wide Web (WWW) \cite{Kleinberg1999}. Link analysis methods are also used to identify the expert in Social Network \cite{Kardan2011}. This paper Link analysis algorithms HITS (Hypertext Induced Topic Search) \cite{Kleinberg1999}and PageRank \cite{Page1998} algorithms are used to find the importance of countries based on the value export amount from one country to another. HITS and PageRank are also among the most frequently cited web information retrieval algorithms (Langville & Meyer, 2005). Link Analysis of the WTN gives importance value to the countries of the WTN.  This paper study and analyze the WTN data from 1990 to 2016 as a weighted-directed network. Using the graph framework and applying link analysis perspectives, the paper tries to figure out the emerging countries and their evolution during the study period. The following section describes the link analysis algorithms used in the study and the subsequent section describes and discusses the finding.Hits Algorithm HITS algorithm is also known as hubs and authorities algorithm (Kleinberg, 1999). This algorithm gives hubs and authority ranking for each member of the network. Hubs score of a node represents the sum of the authority score of all of the nodes which are pointing to this node. The authority score represents the sum of the hub score of all nodes pointing to this node. Hubs and authorities exhibit a mutually reinforcing relationship: a good hub is a node that points to many good authorities; a good authority is a node that is pointed to by many good hubs (Kleinberg, 1999). In the WTN hubs are countries with large export value and export to good authority countries, and authority is a country with large import values and import from good hubs countries.  
DiversityNet: a collaborative benchmark for generative AI models in chemistry
Mostapha Benhenda
Esben Jannik Bjerrum

Mostapha Benhenda

and 3 more

February 08, 2018
Commenting on the document is possible without registration, but for editing, you need to:Register on Authorea: https://www.authorea.com/Join the DiversityNet group: https://www.authorea.com/inst/18886Come back hereCode: https://github.com/startcrowd/DiversityNetBlog post: https://medium.com/the-ai-lab/diversitynet-a-collaborative-benchmark-for-generative-ai-models-in-chemistry-f1b9cc669cbaTelegram chat: https://t.me/joinchat/Go4mTw0drJBrCdal0JWu1gGenerative AI models in chemistry are increasingly popular in the research community. They have applications in drug discovery and organic materials (solar cells, semi-conductors). Their goal is to generate virtual molecules with desired chemical properties (more details in this blog post). However, this flourishing literature still lacks a unified benchmark. Such benchmark would provide a common framework to evaluate and compare different generative models. Moreover, this would allow to formulate best practices for this emerging industry of ‘AI molecule generators’: how much training data is needed, for how long the model should be trained, and so on.That’s what the DiversityNet benchmark is about. DiversityNet continues the tradition of data science benchmarks, after the MoleculeNet benchmark (Stanford) for predictive models in chemistry, and the ImageNet challenge (Stanford) in computer vision.
Alternative method for modelling structural and functional behaviour of a Storage Hyd...
Carlos Graciós
Rosa María

Carlos Graciós

and 4 more

February 07, 2018
1. INTRODUCTION The relevant role of the hydroelectric plants in the world is achieved in their particular energy production because of the great amount of energy production between 30% – 60% accord of the total power generation around the world. The efficiency in terms of the high level actual requirements, depends of the correct balance on the generation, storage and distribution strategies reported in the literature. In the particular requirement of generation issues, the development of high efficient control architectures are preliminary explored by the primary scheme which is analyzed in recent results. Here, it is important to evaluate the performance of each part and whole power generation system to define the adequate law control behaviour. Acord to Lui et al. the transient process in hydropower stations, including the interactions among hydraulics, mechanism, and electricity, is complicated. The closure of guide vanes and spherical valve induces a change in the flow inertia, which causes changes in the turbine rotational speed and hydraulic pressure in the piping system.When the working condition dramatically changes during transients, drastic changes in the waterhammer pressure and high rotational speed may lead to serious accidents that will endanger the safety of the hydraulic structure and turbine unit [1–3] and affect the power grid stability [4]. Therefore, simulating the transient process of hydropower stations is necessary. The calculation accuracy is directly related to the design of the water diversion system, safe operation of the hydropower plant, and power quality. However hydropower generation varies greatly between years with varying inflows, as well as competing water uses, such as flood control, water supply, recreation, and in-stream flow requirements. Given hydropower’s economic value and its role in complex water systems, it is reasonable to monitor and protect the hydropower unit from harmful operation modes. A unit is often operated through rough zone which will cause the unit vibration and the stability performance will decline. Finally, in the case of Great Brittian 1/3 of the cfomplete electrical power is generated by a Hydropower plant installed in Dinorwig Wales with a special characteristics to be demostrated in this report Futhermore, section 2 is devoted to describe the Dinorwig Hydropower Plant(DHP) as structural as functional manner. The hybrid model proposed to define the unsual behaviour for the Plant is developed in section 3. Section 4 shows the Model obtained applying the MLD strategy inserted here. The results using the proposed method are discussed in Section 5. Finally, some conclusions are drawn in Section 6 followed by Acknowledgment and relevant references.
Plant Biology Journal Club 
Elsbeth Walker
Ahmed Ali

Elsbeth Walker

and 10 more

February 07, 2018
Medicago truncatula Zinc-Iron Permease6 provides zinc to rhizobia-infected nodule cells [Isidro Abreu, Angela Saez, Rosario Castro-Rodriguez, Viviana Escudero, Benjamin Rodriguez-Haas,  Marta Senovilla, Camille Laure, Daniel Grolimund, Manuel Tejada-Jimenez, Juan Imperial, Manuel Gonzalez-Guerrero , January 24, 2017 (preprint),  September 21, 2017 (in print), BioRxiv & Wiley-Blackwell]
Calculate tract based weighted means
Do Tromp

Do Tromp

February 05, 2018
Extracting the weighted means of individual fiber pathways can be useful when you want to quantify the microstructure of an entire white matter structure. This is specifically useful for tract based analyses, where you run statistics on specific pathways, and not the whole brain. You can read more on the distinction between tract based and voxel based analyses here: http://www.diffusion-imaging.com/2012/10/voxel-based-versus-track-based.html. The prerequisite steps to get to tract based analyses are described in the tutorials on this website: http://www.diffusion-imaging.com. In the first tutorial we covered how to processed raw diffusion images and calculate tensor images. In the second tutorial we described how to normalize a set of diffusion tensor images (DTI) and run statistics on the normalized brain images (including voxel bases analyses). In the last tutorial we demonstrated who to iteratively delineated fiber pathways of interest using anatomically defined waypoints. Here we will demonstrate and provide code examples on how to calculate a weighted mean scalar value for entire white matter tracts. The principle relies on using the density of tracts running through each voxel as a proportion of the total number of tracts in the volume to get a weighted estimate. Once you have a proportional index map for each fiber pathway of interest you can multiply this weighting factor by the value of the diffusion measure (e.g. FA) in that voxel, to get the weighted scalar value of each voxel. Shout out to Dr. Dan Grupe, who initiated and wrote the core of the weighted mean script. As a note, this script can also be used to extract cluster significance from voxel-wise statistical maps. See an example of this usage at the end of this post. The weighted mean approach allows for differential weighting of voxels within a white matter pathway that have a higher fiber count, which is most frequently observed in areas more central to the white matter tract of interest. At the same time this method will down-weigh voxels at the periphery of the tracts, areas that are often suffering from partial voluming issues, as voxels that contain white matter also overlap gray matter and/or cerebrospinal fluid (CSF). To start off you will need a NifTI-format tract file, for example as can be exported from Trackvis. See more details on how to do this in Tutorial 3. You also need scalars, like FA or MD files. Overview of software packages used in this code: TrackVis  by MGH (download TrackVis here)http://trackvis.org/docs/ fslstats  by FSL (download FSL here)http://fsl.fmrib.ox.ac.uk/fsl/fslwiki/Fslutils fslmaths  by FSL (download FSL here)http://fsl.fmrib.ox.ac.uk/fsl/fslwiki/Fslutils Save the weighted mean code below into a text file named “weighted_mean.sh”. Make sure the file permissions for this program are set to executable by running this line after saving. chmod 770 weighted_mean.sh Note that the code in ’weighted_mean.sh” assumes: A base directory where all folder are located with data: ${baseDir} A text file with the structures you want to run. Here again the naming is defined by what the name of the file is, and that it is located in the main directory, in a folder called STRUCTURES: ${baseDir}/STRUCTURES/${region} A text file with the scalars you want to run. The naming here is defined by how your scalar files are appended. E.g. “subj_fa.nii.gz”; in this case “fa” is the identifier of the scalar file: ${scalar_dir}/*${sub}*${scalar}.nii* The location of all the scalar files in the scalar directory : ${scalar_dir} A list of subject prefixes that you want to run. Weighted mean code: #!/bin/bash # 2013-2018 # Dan Grupe & Do Tromp if [ $# -lt 3 ] then echo echo ERROR, not enough input variables echo echo Create weighted mean for multiple subjects, for multiple structures, for multiple scalars; echo Usage: echo sh weighted_mean.sh {process_dir} {structures_text_file} {scalars_text_file} {scalar_dir} {subjects} echo eg: echo echo weighted_mean.sh /Volumes/Vol/processed_DTI/ structures_all.txt scalars_all.txt /Volumes/etc S01 S02 echo else baseDir=$1 echo "Output directory "$baseDir structures=`cat $2` echo "Structures to be run "$structures scalars=`cat $3` echo "Scalars to be run "$scalars scalar_dir=$4 echo "Directory with scalars "$scalar_dir cd ${baseDir} mkdir -p -v ${baseDir}/weighted_scalars finalLoc=${baseDir}/weighted_scalars shift 4 subject=$* echo echo ~~~Create Weighted Mean~~~; for sub in ${subject}; do cd ${baseDir}; for region in ${structures}; do img=${baseDir}/STRUCTURES/${region}; final_img=${finalLoc}/${region}_weighted; for scalar in ${scalars}; do #if [ ! -f ${final_img}_${sub}_${scalar}.nii.gz ]; #then scalar_image=${scalar_dir}/*${sub}*${scalar}.nii* #~~Calculate voxelwise weighting factor (number of tracks passing through voxel)/(total number of tracks passing through all voxels)~~ #~~First calculate total number of tracks - roundabout method because there is no 'sum' feature in fslstats~~ echo echo ~Subject: ${sub}, Region: ${region}, Scalar: ${scalar}~ totalVolume=`fslstats ${img} -V | awk '{ print $1 }'`; echo avgDensity=`fslstats ${img} -M`; avgDensity=`fslstats ${img} -M`; echo totalTracksFloat=`echo "$totalVolume * $avgDensity" | bc`; totalTracksFloat=`echo "$totalVolume * $avgDensity" | bc`; echo totalTracks=${totalTracksFloat/.*}; totalTracks=${totalTracksFloat/.*}; #~~Then divide number of tracks passing through each voxel by total number of tracks to get voxelwise weighting factor~~ echo fslmaths ${img} -div ${totalTracks} ${final_img}; fslmaths ${img} -div ${totalTracks} ${final_img}; #~~Multiply weighting factor by scalar of each voxel to get the weighted scalar value of each voxel~~ echo fslmaths ${final_img} -mul ${scalar_image} -mul 10000 ${final_img}_${sub}_${scalar}; fslmaths ${final_img} -mul ${scalar_image} -mul 10000 ${final_img}_${sub}_${scalar}; #else # echo "${region} already completed for subject ${sub}"; #fi; #~~Sum together these weighted scalar values for each voxel in the region~~ #~~Again, roundabout method because no 'sum' feature~~ echo totalVolume=`fslstats ${img} -V | awk '{ print $1 }'`; totalVolume=`fslstats ${img} -V | awk '{ print $1 }'`; echo avgWeightedScalar=`fslstats ${final_img}_${sub}_${scalar} -M`; avgWeightedScalar=`fslstats ${final_img}_${sub}_${scalar} -M`; value=`echo "${totalVolume} * ${avgWeightedScalar}"|bc`; echo ${sub}, ${region}, ${scalar}, ${value} >> ${final_img}_output.txt; echo ${sub}, ${region}, ${scalar}, ${value}; #~~ Remember to divide final output by 10000 ~~ #~~ and tr also by 3 ~~ rm -f ${final_img}_${sub}_${scalar}*.nii.gz done; done; done; fi Once the weighted mean program is saved in a file you can start running code to run groups of subjects. See for example the script below. Run Weighted Mean for group of subjects: #Calculate weighted means: echo fa tr ad rd > scalars_all.txt echo CING_L CING_R UNC_L UNC_R > structures_all.txt sh /Volumes/Vol/processed_DTI/SCRIPTS/weighted_mean.sh /Volumes/Vol/processed_DTI/ structures_all.txt scalars_all.txt /Volumes/Vol/processed_DTI/scalars S01 S02 S03 S04; Once that finishes running you can organize the output data, and divide the output values by 10000. This is necessary because to make sure the output values in the weighted mean code have sufficient number of decimals they are multiplied by 10000. Furthermore, this code will also divide trace (TR) values by 3 to get the appropriate value of mean diffusivity (MD = TR/3). Organize output data: cd /Volumes/Vol/processed_DTI/weighted_scalars for scalar in fa tr ad rd; do for structure in CING_L CING_R UNC_L UNC_R; do rm -f ${structure}_${scalar}_merge.txt; echo "Subject">>subject${scalar}${structure}.txt; echo ${structure}_${scalar} >> ${structure}_${scalar}_merge.txt; for subject in S01 S02 S03 S04; do echo ${subject}>>subject${scalar}${structure}.txt; if [ "${scalar}" == "tr" ] then var=`cat *_weighted_output.txt | grep ${subject}|grep ${structure}|grep ${scalar}|awk 'BEGIN{FS=" "}{print $4}'`; value=`bc <<<"scale=8; $var / 30000"`;echo $value >> ${structure}_${scalar}_merge.txt; else var=`cat *_weighted_output.txt | grep ${subject}|grep ${structure}|grep ${scalar}|awk 'BEGIN{FS=" "}{print $4}'`; value=`bc <<<"scale=8; $var / 10000"`;echo $value >> ${structure}_${scalar}_merge.txt; fi done mv subject${scalar}${structure}.txt subject.txt; cat ${structure}_${scalar}_merge.txt; done done #Print data to text file and screen rm all_weighted_output_organized.txt paste subject.txt *_merge.txt > all_weighted_output_organized.txt cat all_weighted_output_organized.txt This should provide you with a text file with columns for each structure & scalar combination, with rows for each subject. You can then export this to your favorite statistical processing software. Finally as promised. Code to extract significant cluster from whole brain voxel-wise statistics, in this case from FSL’s Randomise output:Extract binary files for each significant clusters: #Extract Cluster values for all significant maps dir=/Volumes/Vol/processed_DTI/ cd $dir; rm modality_index.txt; for study in DTI/STUDY_randomise_out DTI/STUDY_randomise_out2; do prefix=`echo $study|awk 'BEGIN{FS="randomise_"}{print $2}'`; cluster -i ${study}_tfce_corrp_tstat1 -t 0.95 -c ${study}_tstat1 --oindex=${study}_cluster_index1; cluster -i ${study}_tfce_corrp_tstat2 -t 0.95 -c ${study}_tstat2 --oindex=${study}_cluster_index2; num1=`fslstats ${study}_cluster_index1.nii.gz -R|awk 'BEGIN{FS=" "}{print $2}'|awk 'BEGIN{FS="."}{print $1}'`; num2=`fslstats ${study}_cluster_index2.nii.gz -R|awk 'BEGIN{FS=" "}{print $2}'|awk 'BEGIN{FS="."}{print $1}'`;  echo $prefix"," $num1 "," $num2; echo $prefix"," $num1 "," $num2>>modality_index.txt; #loop through significant clusters count=1 while [ $count -le $num1 ]; do fslmaths ${study}_cluster_index1.nii.gz -thr $count -uthr $count -bin /Volumes/Vol/processed_DTI/STRUCTURES/${prefix}_${count}_neg.nii.gz; let count=count+1 done count=1 while [ $count -le $num2 ]; do fslmaths ${study}_cluster_index2.nii.gz -thr $count -uthr $count -bin /Volumes/Vol/processed_DTI/STRUCTURES/${prefix}_${count}_pos.nii.gz; let count=count+1 done done Extract cluster means: #Extract TFCE cluster means rm -f *_weighted.nii.gz rm -f *_weighted_output.txt; rm -f *_merge.txt; cd /Volumes/Vol/processed_DTI; for i in DTI/STUDY_randomise_out DTI/STUDY_randomise_out2; do prefix=`echo ${i}|awk 'BEGIN{FS="/"}{print $1}'`; suffix=`echo ${i}|awk 'BEGIN{FS="/"}{print $2}'`; rm structures_all.txt; cd /Volumes/Vol/processed_DTI/STRUCTURES; for j in `ls ${prefix}_${suffix}*`; do pre=`echo ${j}|awk 'BEGIN{FS=".nii"}{print $1}'`; echo $pre >> /Volumes/Vol/processed_DTI/structures_all.txt; done cd /Volumes/Vol5/processed_DTI/NOMOM2/TEMPLATE/normalize_2017; rm scalars_all.txt; echo $suffix > scalars_all.txt; sh ./weighted_mean.sh /Volumes/Vol/processed_DTI/ structures_all.txt scalars_all.txt /Volumes/Vol/processed_DTI/${prefix}/${suffix} S01 S02 S03 S04; done Finally, run the previous code to organize the output data. This code has now helped you extract weighted mean values for your selected pathways and clusters. You can now import these files into CSV files and run statistics in your favorite statistical package (e.g. python on R). 
What changes emerge when translating feminist literature from English into Polish?  ...
Monika Andrzejewska

Monika Andrzejewska

February 01, 2018
Abstract The aim of this essay is to investigate to what extent gender matters in translation. The discussion centres on the translation of English feminist writings into Polish: „A Room of One’s Own”, „Orlando” and „Written on the Body”. Unlike English, Polish is a highly inflected language, which requires gendered choices in the language used to describe characters. Thus, there is a risk that the translation may distort the original meaning of the whole text. I will begin by introducing some concepts of feminist theory of translation, which draw attention to gender issues. Then, I will analyse the Polish translations of books in question. The main argument of this essay is that because translating sexual ambiguity into Polish is impossible, feminist translators may take it to their advantage to transfer their own attitudes. This ultimately may shape the overall perception of the book and the author by a given readership.
THE TRUTH IS IN THE SOUL OF BEHOLDER - Silence
Igor Korosec

Igor Korosec

February 01, 2018
A document by Igor Korosec, written on Authorea.
Why we should use balances and machine learning to diagnose ionomes
Serge-Étienne Parent

Serge-Étienne Parent

January 24, 2018
The performance of a plant can be predicted from its ionome (concentration of elements in a living tissue) at a specific growth stage. Diagnoses have yet been based on simple statistical tools by relating a Boolean index to a vector of nutrient concentrations or to unstructured sets of nutrient ratios. We are now aware that compositional data such as nutrient concentrations should be carefully preprocessed before statistical modeling. Projecting concentrations to isometric log-ratios confer a Euclidean space to compositional data, similar to geographic coordinates. By comparing projected nutrient profiles to a geographical map, this perspective paper shows why univariate ranges and ellipsoids are less accurate to assess the nutrient status of a plant from its ionome compared to machine learning models. I propose an imbalance index defined as the Aitchison distance between an imbalanced specimen to the closest balanced point or region in a reference data set. I also propose and raise some limitations of a recommendation system where the ionome of a specimen is translated to its closest point or region where high plant performance is reported. The approach is applied to a data set comprising macro- and oligo-elements measured in blueberry leaves from Québec, Canada.
From the bench to a grander vision
Adriana Bankston

Adriana Bankston

January 20, 2018
As a kid, I was always very diligent in school and took it very seriously. As I was also curious and enjoyed a challenge, science was a good field for me to pursue. Plus, I grew up in a family of scientists, with both my parents and grandparents doing it. But that didn’t necessarily mean I knew how academia worked.  I moved to the U.S. after high school, graduated from college (with a B.S. from Clemson University), and attended graduate school at Emory University. While I had good grades and test scores, I still had a lot to learn about doing research in spite of having worked in a lab for one year prior to graduate school. But I knew that I enjoyed the bench work enough to pursue a graduate education, and I wanted to learn the scientific way of thinking. I had a really excellent graduate mentor (also female) who taught me everything I know about science. She taught me how to design experiments and interpret data, and pointed out when I was doing things wrong. She always pushed me to do better in multiple aspects of being a scientist, and taught me to speak up when I had a question or a thought, no matter how small it might have been. This ultimately allowed me to become more confident in my abilities as a scientist. She also managed work-life balance extremely well, which was really inspiring to see and proved to be very useful for me later. Overall, she was an amazing mentor and role model. Graduate school was pretty comfortable. I wasn't eligible to apply for many fellowships (at least not until I obtained my U.S. citizenship), but luckily the lab was well funded during my time there, which alleviated some pressure. I didn’t seek additional mentors because I felt that her guidance could point me in the right direction, which, at the time, was still an academic career. I also didn't really consider other career options during this time - if I did, I probably would have approached my scientific training differently. During my postdoctoral training, I started exploring other careers, although academia was still on the table. Many changes took place in my life during this time, which allowed me to mature in several ways. I still carried with me the confidence I had gained during graduate school, which materialized into wanting to become a leader in my field of choice. But while examining potential careers, I also kept an open mind. I attended my first national meeting related to postdoctoral issues (but unrelated to my bench research), which peaked my interest in this area. Together with another postdoc at the university, I subsequently established a career seminar series as a resource for postdocs to hear from professionals in non-academic careers. While I didn’t realize this at the time, the seminar had the potential to change the local academic culture. Trainees came up to me and thanked me for creating this resource, which made me feel good in so many ways. At some point I noticed that some of them were regularly attending the events, and also seemed to be asking more questions and interact more frequently with some of the speakers following their talks. This was a great experience. After that, I organized regional symposia to connect trainees to each other, and got involved with national organizations focused on training and policy for graduate students and postdocs. During this time, I began to network with experts in these areas, and to speak up about certain issues in academia. As I participated in more of these activities on the side of my postdoctoral work, I eventually decided to follow these strong interests that I was developing instead of trying to stay in academia. So, I quit my postdoc and continued to explore what I was really interested in doing, but now with a slightly more clear direction. As luck would have it, I obtained a travel award to attend a science advocacy meeting in Boston (organized by Future of Research and other groups), which interestingly took place during my last month as a postdoc. That meeting got me hooked on studying academia and advocating for scientists, although my interests were fairly broad at that point. But these topics seemed to fit me like a glove, and I knew that I had to get more involved with the group.The rest is history. At the Future of Research, I was fortunate enough to be involved early on with a project on tracking postdoc salaries nationally, which isn't something I ever imagined myself doing but I loved it. This experience also opened me up to the idea of trying new things and going with the flow, instead of planning my next move in detail as I had always done. Overtime, this project gave me a sense of purpose and direction while still figuring out my path. And no matter what else I did during this time, I always came back to that feeling of passion that I had developed for trying to create evidence-based change in academia, while advocating for transparency in the system. I was a bit surprised to see how naturally these ideas came to me, as I never knew that you could study something like this; nevertheless, I found it extremely fascinating. I later reflected upon why it was so easy for me to engage in this area, and realized that it essentially blended multiple aspects of my personality: 1) an interest in doing research with a purpose; 2) the feeling that I am making a difference with my work; 3) speaking up for a particular cause and backing it up with data; and 4) I had always been a bit of rebel, which worked well for wanting to challenge the status quo.  I finally felt that my life had a purpose and direction that I was happy to pursue. Without going into details about my contributions (see more on my website), volunteering for a cause I believe in (and knowing what that is) has been a very powerful motivator for engaging in this type of work. In this context, taking ownership of science policy projects and leading them has been a very fulfilling experience. I am now on the Future of Research Board of Directors, which I feel is the ideal leadership position for me. In some ways, this is the opportunity I had been waiting for all this time, I just didn't know it, and obviously couldn’t have predicted it.I’m very grateful to this group for making my opinion feel valued and my voice count during a time when I wasn’t quite sure where I was going. I now know the direction I want my life to take, which is quite amazing in itself. I also know that just having a job isn’t sufficient for me without contributing to a grander vision and the potential to make the world a better place. And while I am still looking for a position in this area, I am now aware of the fact that I am much more motivated by a mission (than by money). I wouldn't have realized that if it weren't for my experience with Future of Research. Some of the lessons I’ve learned along the way are: 1) Don’t let anyone tell you how to live your life; 2) Volunteering can pay off if you are truly invested in it; and 3) Gratitude is a good way to live your life in general. As I try to keep these lessons in mind moving forward, perhaps the biggest one is still that taking some time to discover what is truly important to me will be a worthwhile long-term investment in my future.
Medical Students Fail Blood Pressure Measurement Challenge: Implications for Measurem...
Kenneth Royal, PhD

Kenneth Royal, PhD

January 19, 2018
Rakotz and colleagues (2017) recently published a paper describing a blood pressure (BP) challenge presented to 159 medical students representing 37 states at the American Medical Association’s House of Delegates Meeting in June 2015. The challenge consisted of correctly performing all 11 elements involved in a BP assessment using simulated patients. Alarmingly, only 1 of the 159 (0.63 %) medical students correctly performed all 11 elements. According to professional guidelines (Bickley & Szilagyi, 2013; and Pickering et al, 2005), the 11 steps involved in a proper BP assessment include: 1) allowing the patient to rest for 5 minutes before taking the measurement; 2) ensuring patient’s legs are uncrossed; 3) ensuring the patient’s feet are flat on the floor; 4) ensuring the patient’s arm is supported; 5) ensuring the sphygmomanometer’s cuff size is correct; 6) properly positing cuff over bare arm; 7) no talking; 8) ensuring the patient does not use his/her cell phone during the reading; 9) taking BP measurements in both arms; 10) identifying the arm with the higher reading as being clinically more important; and 11) identifying the correct arm to use when performing future BP assessment (the one with the higher measurement). All medical students involved in the study had confirmed that they had previously received training during medical school for measuring blood pressure. Further, because additional skills are necessary when using a manual sphygmomanometer, the authors of the study elected to provide all students with an automated device in order to remove students’ ability to use the auscultatory method correctly from the testing process. The authors of the study reported the average number of elements correctly performed was 4.1 (no SD was reported). While the results from this study likely will raise concern among the general public, scholars and practitioners of measurement may also find these results particularly troubling. There currently exists an enormous literature regarding blood pressure measurements. In fact, there are even academic journals devoted entirely to the study of blood pressure measurements (e.g., Blood Pressure Monitoring), and numerous medical journals devoted to the study of blood pressure (e.g., Blood Pressure, Hypertension, Integrated Blood Pressure Control, Kidney & Blood Pressure Research, High Blood Pressure & Cardiovascular Prevention, etc.) Further, a considerable body of literature also discusses the many BP instruments and methods available for collecting readings, and various statistical algorithms used to improve the precision of BP measurements. Yet, despite all the technological advances and sophisticated instruments available, these tools likely are of only limited utility until health care professionals utilize them correctly. Inappropriate inferences about BP readings could result in unintended consequences that jeopardize a patient’s health. In fact, research (Chobanian et al, 2003) indicates most human errors when measuring BP result in higher readings. Therefore, these costly errors may result in misclassifying prehypertension as stage 1 hypertension and beginning a treatment program that may be both unnecessary and harmful to a patient. This problem is further exacerbated when physicians put a patient on high blood pressure medication, as most physicians are extremely reluctant to take a patient off the medication, as the risks associated with stopping are extremely high. Further, continued usage of poor BP measurement techniques could result in patients whose blood pressure is under control to appear uncontrolled, thus escalating therapy that could further harm a patient. Until physicians can obtain accurate BP measurements, it is unlikely they can accurately differentiate those individuals who may need treatment from those that do not. So, I wish to ask the measurement community how we might assist healthcare professionals (and those responsible for their training) to correctly practice proper blood pressure measurement techniques? What lessons from psychometrics can parlay into the everyday practice of healthcare providers? Contributing practical solutions to this problem could go a long way in directly improving patient health and outcomes. References Pickering T, Hall JE, Appel LJ, et al. Recommendations for blood pressure measurement in humans and experimental animals part 1: blood pressure measurement in humans – a statement for professionals from the Subcommittee of Professional and Public Education of the American Heart Association Council on High Blood Pressure Research. Hypertension. 2005;45:142‐161. Bickley LS, Szilagyi PG. Beginning the physical examination: general survey, vital signs and pain. In: Bickley LS, Szilagyi PG, eds. Bates’ Guide to Physical Examination and History Taking, 11th ed. Philadelphia, PA: Wolters Kluwer Health/ Lippincott Williams and Wilkins; 2013:119‐134. Chobanian AV, Bakris GL, Black HR, et al. Seventh report of the Joint National Committee on prevention, detection, evaluation and treatment of high blood pressure. Hypertension. 2003;42:1206‐1252. Rakotz MK, Townsend RR, Yang J, et al. Medical students and measuring blood pressure: Results from the American Medical Association Blood Pressure Check Challenge. Journal of Clinical Hypertension. 2017;19:614–619.
Trust Asymmetry
Percy Venegas

Percy Venegas

January 18, 2018
In the traditional financial sector, players profited from information asymmetries. In the blockchain financial system, they profit from trust asymmetries. Transactions are a flow, trust is a stock. Even if the information asymmetries across the medium of exchange are close to zero (as it is expected in a decentralized financial system), there exists a “trust imbalance” in the perimeter. This fluid dynamic follows Hayek's concept of monetary policy: “What we find is rather a continuum in which objects of various degrees of liquidity, or with values which can fluctuate independently of each other, shade into each other in the degree to which they function as money”. Trust-enabling structures are derived using Evolutionary Computing and Topological Data Analysis; trust dynamics are rendered using Fields Finance and the modeling of mass and information flows of Forrester's System Dynamics methodology. Since the levels of trust are computed from the rates of information flows (attention and transactions), trust asymmetries might be viewed as a particular case of information asymmetries -- albeit one in which hidden information can be accessed, of the sort that neither price nor on-chain data can provide. The key discovery is the existence of a “belief consensus” with trust metrics as the possible fundamental source of intrinsic value in digital assets. This research is relevant to policymakers, investors, and businesses operating in the real economy, who are looking to understand the structure and dynamics of digital asset-based financial systems. Its contributions are also applicable to any socio-technical system of value-based attention flows.
Integritas Panitia Tarung Bebas
Saortua Marbun

Saortua Marbun

January 18, 2018
Integritas Panitia Tarung Bebas Saortua Marbun\citep{marbun2018}saortuam@gmail.com | http://orcid.org/0000-0003-1521-7694  DOI: 10.22541/au.151624089.92438669 ©2018 Saortua Marbun 
Menabur Benih Politik Berkeadaban
Saortua Marbun

Saortua Marbun

January 18, 2018
Menabur Benih Politik Berkeadaban Saortua Marbun\citep{Marbun2018} Sekolah Tinggi Ilmu Ekonomi Triatma Mulyasaortuam@gmail.com | http://orcid.org/0000-0003-1521-7694  DOI: 10.22541/au.151623662.20184822 ©2018 Saortua Marbun  "Tampaknya Bawaslu dan Satgas Anti Money Politic, anti SARA, anti hoaks - kali ini tidak main-main. Jangan sampai dirimu tertangkap tangan kawan. Jika tidak takut dilihat oleh TUHAN, setidaknya takutlah pada kamera CCTV, hidden cameras, "mata-mata", kamera media massa." Begitulah isi salah satu cuitan yang diposting di media sosial.\citep{marbun2018a} Menurut Amartya Sen (2009) di dalam \citet{rido2017} , hakikat demokrasi adalah terdorongnya fungsi pembangun dalam pembentukan nilai-nilai dan pentingnya hakikat kehidupan manusia (kesejahteraan). Akan tetapi realitanya belum demikian. \citet{wattimena2018}, menulis bahwa "politik telah tercabut" dari keutamaan, tercabut dari spiritualitas, tercabut dari ilmu pengetahuan dan tercabut dari budaya. Oleh sebab itu Negara harus menunjukkan "taringnya" - agar hajatan politik - tahun ini dan seterusnya - kembali ke jati diri politik luhur, hakikat demokrasi. Politik tercabut dari keutamaan dan filsafat yang mendasarinya, sehingga ia berubah menjadi transaksi kekuasaan yang mengorbankan kepentingan rakyat luas. Politik yang sejatinya sebuah profesi luhur untuk mewujudkan konsensus demi kebaikan bersama melalui kebijakan cerdas dan keteladanan. Keluhuran profesi ini bagai "lenyap" ditelan oleh “syahwat” kekuasaan. Politik bermetamorfosa menjadi musuh-musuh kebaikan. Sikap dan perilaku berpolitik masa kini telah memisahkan diri dari narasi kesantunan. Internalisasi nilai dan kultur demokrasi berkeadaban pada level massa - terpinggirkan. Politik sudah tercabut dari ilmu pengetahuan. Beragam kebijakan politik diproduksi tanpa dasar rasionalitas, tanpa dukungan penelitian ilmiah yang bermutu. Berulangkali publik dibuat tidak berdaya oleh kebijakan politik yang dibuat atas dasar persekongkolan dengan pemilik modal yang korup, ujungnya merugikan kepentingan publik. Beragam kebijakan yang ada justru tidak masuk akal sehat, terkadang memperburuk persoalan yang sudah ada. Politik sudah tercabut dari spiritualitas atau cara hidup yang mengedepankan aspek-aspek kemanusiaan universal di dalam segala keputusan dan perilaku. Politik masa kini telah menghimpit spiritualitas menjadi sebatas agama yang dijadikan kendaraan dan menjadi topeng untuk menutupi aroma amis dari kebusukan. Sadar atau tidak, kampanye politik yang menunggangi agama menjadi salah satu indikasi bahwa aktor dan dalang di balik layar itu korup.   Politik sudah tercabut dari budaya, ia menjadi korban dari nilai-nilai yang diimport dari nilai-nilai Barat dan Timur Tengah. Alhasil, nilai-nilai luhur budaya setempat terkikis, lenyap. Politik yang tercabut dari budaya justru menciptakan keterasingan dan melahirkan kemiskinan dan kebodohan yang semakin parah di tengah masyarakat. Demokrasi masa kini telah menciptakan "permusuhan" antar pendukung - para pihak memandang yang lain sebagai musuh politik, mereka saling berhadap-hadapan pada pemilihan kepala desa, bupati, walikota, gubernur, legislatif hingga pemilihan presiden. Ketegangan elektoral tahun 2013 yang lalu rasanya masih segar, kini 2018 publik berharap demokrasi berlangsung dalam suasana teduh. Rasanya tepat membaca kembali tulisan \citet{thohari2014}, "Pada masa lalu perebutan kekuasaan dan takhta dilakukan dengan peperangan yang sarat dengan kekerasan dan pertumpahan darah. Politik demokrasi memberikan mekanisme "perebutan takhta" secara adil, sehat, dan berkeadaban melalui pemilihan umum. Maka, sangat ironis jika pemilihan umum yang mestinya berkeadaban itu kembali diperlakukan menjadi laksana peperangan perebutan takhta yang keras, kasar, dan brutal seperti masa pramodern dulu." Oleh sebab itu, keseriusan penyelenggara bersama seluruh pemangku kepentingan tentu sangat diperlukan dalam upaya menyemai benih politik yang sehat seraya memutus akar-akar politik yang bermasalah. Masa depan, keutuhan dan kesejahteraan bangsa menjadi taruhannya - bila upaya ini gagal maka politik akan menjadi mesin penghancur yang membawa petaka kemiskinan, penderitaan, kehancuran moral. Firman Allah berkata, "Bangsa yang tidak mendapat bimbingan dari TUHAN menjadi bangsa yang penuh kekacauan. Berbahagialah orang yang taat kepada hukum TUHAN." (Amsal 29:18, BIS) \cite{sabda}.  
Backstory of  "Molcas 8: New capabilities for multiconfigurational quantum chemical c...
roland.lindh
Josh Nicholson

Roland Lindh

and 1 more

January 15, 2018
The subject paper\cite{Aquilante_2015} is the 5th paper in a series of papers\cite{Aquilante_2012,Roos_1990,Roos_1991,Veryazov_2004,Aquilante_2010} on the development of the MOLCAS program package.  In this short back story I will try to put the MOLCAS quantum chemistry program package into a brief historical context, shortly describe its development, and finally argue the case why papers like the subject paper is needed. The Molcas project started in 1989 by the theoretical chemistry group of  the late Prof. Björn Roos (see Figure 1) at Lund University, Sweden. The Swedish government struck a deal with the banks -- no increase of tax if they supported research. As a consequence of this the Molcas project materialised as a collaboration between IBM and the research group in Lund. Swedish theoretical chemistry had made a serious impart on the ab inition field at the time with contributions from researchers as Jan Almlöf, Per. E. M. Siegbahn, and Björn Roos - the former two the first Ph.D. students of the latter at Stockholm University. During this time the three of them had developed specialized software. Jan Almöf developed the Molecule\cite{Taylor_2017} program (computation of two-electron integrals), Per E. M. Siegbahn the MRCI code\cite{Siegbahn_1992,Roos_1977} (multi reference configuration interaction), and Björn O. Roos developed the CASSCF program\cite{Roos_1980} (complete active space self-consistent field). The goal of the Molcas project was to bring these pieces of software together in a single package designed for the IBM 3090 machine. Version 1.0 was distributed to the public in the late 1989.  Subsequent versions were released 1991, 1993, 1997, 2000, 2003, 2007, and 2014, covering version 2-8. All versions have been commercial versions.Today the package support multiple options and methods, and several hardware and software platforms. In 2005 the project started the "Molcas users' workshops" with the most recent workshop, the 8th, taking place in Uppsala November 2017.  Over the time and under the leadership of Björn Roos the project have had several success stories which have been seminal to the field. Let us mention two here, the complete active space 2nd order perturbation theory model\cite{Andersson_1993} and the complete active space state interaction\cite{Malmqvist_1989} method. From the formation of the project until about 2010 the project was mainly a project which was heavenly dominated by the Lund group, especially with respect to the leadership and strategic decisions,  however, with significant programming contributions from international collaborators. During 2009 Björn Roos retired from the project due to poor health\cite{Siegbahn_2011}, the baton was passed on to the long time Molcas co-developer Roland Lindh. Starting in Zürich 2013 the first "Molcas developers' workshop" took place. This has been followed by annual workshops at Alcalá (Spain), Siena (Italy), Vienna (Austria), Jerusalem (Israel) and this year at Leuven (Belgium). During the same time the project have developed from a national Swedish project -- dominated by a single Swedish research group -- to an international project with 30-40 active developers from some 10 different universities and institutes. The authors list of the subject paper is a testament to this development. In 2017 the project went open-source having the most significant part being released under the "Lesser GLP" license and is now distributed free of charge under the name of OpenMolcas.The subject paper was written on the request of the developers after one of our developers' workshops. People argued that a single paper, including the most recent developments, would be needed to make new developments and implementations known to the computational chemistry community. Additionally, the issue of lack of recognition and credits for software development was mentioned as one of the most important reasons for the need of a paper like the subject paper -- in many aspects a mini-review paper with no novel contributions. Normally hard-working software developers seldom get proper credits for their work, although it can and is fundamental to the ability to perform accurate quantum chemical simulations. In particular if this development is not associated with new wave-function models. Some of us, like me, contribute with significant software and methods, which are completely instrumental for the calculations, but hardly ever get any credit for this contribution. Let me give an example, I'll use my own contribution, two-electron integrals \cite{Lindh_1991} (since long also a part of MOLPRO), which without no calculations with the package would be possible,  as an example. Since its publication in 1991 this paper, on the computation of two-electron integrals, has, according to Google Scholar, attracted 258 citations. In the same time the two packages have attracted 7249 citation -- the use of the two-electron code was surely significant to the research the citations corresponds to but they handed credit to the developer in less than 3.6% of the time. If I would have designed the basis set, however, I would have been assured the full 7249 citations -- we always cited the basis sets but hardly ever how we efficiently compute the matrix elements they generate. There are several other developments and features in a quantum chemistry package which are not considered worthy citations but are still as essential to calculations. Here comes the paper, as the subject paper, in as an equalizer and makes sure that all developers of a package gets the credit and respect they deserve. With these type of papers around we kill two flies with one stone -- we reduce the number of references to theoretical papers and at the same time make sure that all developers get the recognition they all deserve and need.
Animals that eat animals could help people that grow food
Sam Williams

Sam Williams

January 13, 2018
Animals that eat animals could help people that grow foodPeople that grow food don't get along well with animals that eat other animals. We used things that take pictures by themselves to find out if there are more animals that eat other animals in places where people grow food, in places that people live, or in places where there are lots of trees. We found out that the highest animals that eat other animals live where people grow food. We also found these animals that eat other animals eat lots of small animals. Animals that eat other animals could help people that grow food, by eating small animals that would eat the food they grow.This is part of the #upgoerfive challenge, explaining the findings of \citet{Williams_2017}.
Menata Impresi dengan Angka Kemiskinan
Saortua Marbun

Saortua Marbun

January 09, 2018
Menata Impresi dengan Angka Kemiskinan Saortua Marbun \cite{marbun2018}25 Januari 2018Rasul Yohanes menulis pada pasal 12 ayat 3-8. Maria, saudari Lazarus, "mengambil setengah kati minyak narwastu murni yang mahal harganya, lalu meminyaki kaki Yesus dan menyekanya dengan rambutnya; dan bau minyak semerbak di seluruh rumah itu. Tetapi Yudas Iskariot, berkata: "Mengapa minyak narwastu ini tidak dijual tiga ratus dinar dan uangnya diberikan kepada orang-orang miskin?" Hal itu dikatakannya bukan karena ia memperhatikan nasib orang-orang miskin, melainkan karena ia adalah seorang pencuri; ia sering mengambil uang yang disimpan dalam kas yang dipegangnya. Maka kata Yesus: "Biarkanlah dia melakukan hal ini mengingat hari penguburan-Ku. Karena orang-orang miskin selalu ada pada kamu, tetapi Aku tidak akan selalu ada pada kamu." "Tindakan Maria ini merupakan suatu pengorbanan besar, karena minyak narwastu murni itu sangat mahal harganya. Maria sadar bahwa kesempatan untuk mengungkapkan pengabdian kepada Yesus segera akan berakhir, karena itu dia memanfaatkan kesempatan yang tersedia. Iman dan pengabdiannya kepada Tuhan merupakan teladan tertinggi dari apa yang diinginkan Allah dari orang percaya."\cite{sabda}  Undang-Undang Dasar 1945 menyebutkan bahwa “Fakir miskin dan anak-anak terlantar dipelihara oleh negara.”\cite{subekan2014} Itu betul. Wajar pula bila ada oknum selaku "negarawan" menaruh peduli pada "angka kemiskinan". Namun demikian, perhatian tersebut dapat dimaknai "terbalik" apabila dilontarkan dalam konteks "kontestasi politik" misalnya menjelang pilkada dan pilpres. Kata kunci "miskin, petani, nelayan" kerap muncul sebagai "lipstick" atau bedak penghias paras. Mengulas angka kemiskinan dengan segudang kepentingan. Mengelola impresi sembari memanfaatkan sorotan kamera. Sadar bahwa "komentar" tersebut disaksikan banyak orang. Tidakkah hal itu mirip dengan kemunafikan Yudas Iskariot? Tentu saja, "si miskin, si fakir, si anak terlantar" - tidak berdaya menolak sekali pun "kata kunci" itu dikapitalisasi, dipolitisir. Oknum memperkuat argumennya dengan data kemiskinan yang dirilis Badan Pusat Statistik. Katanya Maret 2017 penduduk miskin ada 27,77 juta jiwa, sekitar 17,10 juta jiwa di antaranya berada di desa. \cite{bps2017} Data itu, lalu dibandingkan dengan angka periode sebelumnya, katanya semakin parah. Ujung-ujungnya pemerintah "katanya" belum berhasil. Timpang di sana-sini, "katanya". Sekilas memberi kesan menarik dan meyakinkan. Namun, bila dicermati secara kritis "impresi" itu mirip dengan kemunafikan Yudas Iskariot. Ucapan dan niatnya tidak selaras. Wacana kepedulian terhadap si miskin ibarat peribahasa yang berkata, "telunjuk lurus, kelingking berkait." Tampaknya baik, tetapi hatinya diragukan. Di pihak lain, ada "oknum" yang secara sukarela, melaksanakan pengobatan gratis, memberi bantuan secara swadaya. Mereka tidak melibatkan media, tidak bersuara, tentu saja informasinya tidak meluas diketahui publik. Kontras dengan oknum yang lihai melipat kelingking seraya meluruskan telunjuk - menuding dengan "maksud" yang dapat dipahami pemirsa. Perempuan bernama Maria meminyaki kaki Kristus di Kota Betania. Sebuah kota di mana Lazarus pernah dibangkitkan oleh Yesus dari kematian. Mujizat yang terjadi di sana membuat tempat itu menjadi masyhur. Ketika Yesus tiba di Betania, diadakan perjamuan sebagai sambutan untuk Dia. Maria pun menunjukkan rasa hormat dan rasa syukur karena kematian dan kebangkitan kakak lelakinya, Lazarus. Minyak setengah kati (setengah liter) seharga 300 Dinar dipersembahkan kepada Yesus, sebagai persembahan yang terbaik. Persembahan yang termahal, karena harganya setara dengan upah seorang pekerja selama 300 hari. Yesus Kristus tidak keberatan atas perbuatan Maria. Akan tetapi, Yudas Iskariot tampaknya gagal memahami makna tertinggi dari perbuatan Maria. Yudas melontarkan kritik seraya berkata, "Mengapa minyak narwastu ini tidak dijual tiga ratus dinar dan uangnya diberikan kepada orang-orang miskin?" Bagi Yudas, perbuatan Maria itu adalah suatu "pemborosan" - dan ia tidak bisa mengerti, "Mengapa Yesus membiarkan hal itu?" "Apakah Yesus tidak lagi memperhatikan orang-orang miskin?" Menurut Matthew Henry, "Yudas, seorang dari murid-murid Yesus bersungut-sungut atas tindakan Maria. Memang tidak aneh bila orang-orang yang paling jahat menyamar di balik pengakuan iman mereka yang terbaik. Banyak orang berpura-pura mengaku mengenal Kristus, padahal mereka sama sekali tidak mengasihi-Nya. Yudas adalah seorang rasul, seorang pengkhotbah Injil, tetapi ia malah berkeberatan dan mencela perbuatan yang menunjukkan kasih sayang dan pengabdian yang tulus seperti yang dilakukan Maria tadi. Perhatikan, menyedihkan sekali jika kehidupan agama dan semangat yang kudus malah dicerca dan ditolak oleh orang-orang yang justru seharusnya mendorong dan menyokong semuanya itu."\cite{sabdaa}"kasih yang telah mendingin terhadap Kristus dan kebencian tersembunyi terhadap kesalehan yang tulus, bila muncul dalam diri penganut agama, maka ini menjadi pertanda buruk akan terjadinya kemurtadan. Orang-orang munafik yang biasanya tidak mudah tergelincir karena godaan-godaan duniawi, justru lebih mudah jatuh oleh karena godaan-godaan yang lebih besar daripada itu." "rasa amal terhadap orang miskin dijadikan alasan untuk menentang kesalehan yang ditujukan kepada Kristus dan dijadikan kedok untuk menyembunyikan ketamakan." "Keberatan Yudas itu tidak didasari oleh kepeduliannya untuk beramal: Bukan karena ia memperhatikan nasib orang-orang miskin. Dia tidak memiliki belas kasihan terhadap mereka, sama sekali tidak peduli kepada mereka: baginya, orang-orang miskin hanyalah sekedar alat untuk mendapatkan keinginannya, dengan cara berpura-pura memperhatikan mereka." "Keberatan Yudas itu justru muncul karena ketamakannya. Kenyataannya adalah, dia lebih menginginkan minyak narwastu yang dipersembahkan untuk Guru-nya itu supaya dijual saja, lalu uangnya dapat dimasukkan ke dalam kas yang ia pegang, dan setelah itu ia tahu apa yang akan dilakukannya."\cite{sabdaa} Maria tidak berhenti, karena ia melakukannya sebagai tanda kasih. Perbuatan Yesus Kristus yang telah membangkitkan Lazarus tidak dapat dapat dibalas dengan apa pun. Sebagai umat yang beriman, tentu kita pun patut berterima kasih atas kasih dan pengorbanan Kristus bagi kita. Kiranya kita menjadi peniru teladan ketulusan hati Maria. Semoga pula, impresi ala Yudas Iskariot dijauhkan dari anda dan saya.(*)
Comments on "An empirical test of the temperature dependence of carrying capacity"
Kristina Riemer
Hao Ye

Kristina Riemer

and 1 more

January 06, 2018
This is a preprint review of An empirical test of the temperature dependence of carrying capacity by Joey Bernhardt, Jennifer M. Sunday, and Mary I. O'Connor. The preprint was originally posted on bioRxiv on October 28, 2017 (DOI: https://doi.org/10.1101/210690).
Long- and short-lists of key performance indicators in industry and for industrial sy...
Ivan Kantor

Ivan Kantor

and 9 more

January 05, 2018
en INTRODUCTION A key performance indicator (KPI) is a measurable value that demonstrates how effectively an organisation, process or project is achieving a key objective. For instance, the internal rate of return can be used to measure the effectiveness of a project from an economic perspective, where the objective is profitability. Another example is the CO₂ emissions of an industrial process, which can be calculated to quantify the environmental performance with the objective of mitigating climate change. Industrial symbiosis (IS) can be defined as the integration of industrial processes from different companies or sectors. The most common example is when industries exchange by-products or waste, including energy. Other examples include the sharing of infrastructure or services by two or more companies. IS can have several benefits for the companies involved, but also for the local community, and even society as a whole. These include aspects of legal, economic, spatial, technical social (LESTS) and environmental benefits. The realisation of those benefits through the implementation of IS needs to be quantified with appropriate KPIs. The goal of the EPOS project is to implement a decision support toolbox for cross-sectorial IS, providing a wide range of technological and organisational options for making businesses and operations more efficient, more cost-effective, more competitive and more sustainable across various process sectors. The definition of KPIs is a crucial step in the project, as they will allow decision makers to evaluate and compare the solutions proposed by the tool from the different perspectives mentioned. The first step of the KPIs definition was reported in an EPOS deliverable (D1.4) and consisted of constructing a long list of both sectoral and cross-sectoral KPIs. The sectoral KPIs were provided by the four sector industries of the EPOS project, while the cross-sectoral KPIs were suggested by the universities and Quantis as a result of literature review and experience. The next step was to refine that long list by identifying the most useful KPIs to include in the EPOS toolbox. Since the goal of EPOS is to have a generic framework that can apply to multiple industrial sectors, including those outside of the consortium, care was taken to remove KPIs that were sector specific, and only leave in the ones that all industries could relate to and that actually evaluated the IS solutions (i.e. cross-sectoral KPIs). This document presents the long-list of KPIs which were considered and the preliminary short list of KPIs agreed upon by the EPOS consortium, and some discussion of the refinement method applied to achieve it. INDUSTRIAL KPIS Typical KPIs used in the steel industry As the World’s leading Steel and Mining Company, ArcelorMittal’s success is built on its core values of sustainability, quality and leadership. In order to cement this leading position over the years, ArcelorMittal is continuously making decisions and acting through a well-defined strategy and taking the right balance sheet to reach the targets identified. As do many companies to support their strategy, ArcelorMittal follows a large amount of metrics (plant operation, security, production, etc.) thus allowing the performance monitoring of its facilities worldwide. These indicators differ depending on the actor following them and that acts accordingly, going from the management committees to the detailed process follow ups. [tab:steelKPI] gathers a selection of metrics considered as relevant to the EPOS project framework. They are divided into different categories: 1. Safety, health, quality of working life (for ArcelorMittal collaborators). 2. Use of resources and recycling rates: progress in terms of resource use efficiency. 3. Use of air, land and water: environmental impact assessment. 4. Use of energy: as an energy intensive company due to its process routes and requirements, ArcelorMittal is a responsible energy user that helps create a lower carbon future. 5. Process operation: tracking of influential parameters to make process improvements. For more information about ArcelorMittal’s metrics, the ArcelorMittal Corporate website can be consulted . METRIC UNIT ---------------------------------------------- ---------------------------------------------- -------------------------------- Productivity tCrude\ Steel / year [13]*Safety, health, quality of working life Number of employees Number Number of contractors Number Lost Time Injury Frequency Rate (LTIFR) Number per million hours Absenteeism rate % Employee turnover rate % Employee training h / employee / year Female collaborators % [13]*Use of resources and recycling rates tIron\ Ore / year tCoal / year tDRI / year tSteel\ Scrap\ Recycled / year tCO₂\ Steel\ Recycled / year % tBF\ Slag / year [14]*Use of air, land and water Environmental and energy capital expenditure €/ year Specific dust emissions t / tSteel Specific NOx emissions t / tSteel Specific SOx emissions t / tSteel Specific CO₂ emissions t / tSteel Production residues to landfill / waste % Specific net water consumption Nm³ / tSteel Use of energy GJ / tSteel\ Coils [28]*Process operation Operating time h / year Final product output tFinal\ Product / year Mean Time Between Failures (MTBF) h Mean Time To Repair (MTTR) h Average daily production tFinal\ Product / day Specific material inlet stream rate t / tFinal\ Product Specific material outlet stream rate t / tFinal\ Product Nm³ / tFinal\ Product or GJ / tFinal\ Product Nm³ / tFinal\ Product or GJ / tFinal\ Product Nm³ / tFinal\ Product or GJ / tFinal\ Product Nm³ / tFinal\ Product or GJ / tFinal\ Product Specific water inlet stream rate Nm³ / tFinal\ Product Specific water outlet stream rate Nm³ / tFinal\ Product Specific electricity consumption MWh / tFinal\ Product : List of KPIs used in the steel industry Typical KPIs used in the cement industry As is the case with other industrial sectors, the cement industry utilizes a series of metrics which are industry-standard and are used to objectively measure and then track the performance of a manufacturing facility in terms of energy consumption, throughput and environmental impact among others. For cement plants which manufacture the intermediate product: clinker, the main energy vectors are typically comprised of: coal, fossil fuels, solid and liquid alternative fuels and electricity. The performance for these facilities is usually measured based on specific energy consumptions, specific environmental impacts (mainly air emissions) or specific costs of products. It is important to mention, that the cement industry is very energy intensive and also generates an environmental impact in terms of direct and indirect air emissions. These emissions mainly originate in the cement kiln. The main key performance indicators used in this industry are listed in Table [tab:cemKPI]. METRIC UNIT ---------------------------- --------------------------------------------------- ------------------------------- [10]*Economic / Efficiency €/tclinker €/tcement kcal/kgclinker or MJ/tclinker €/MWh kWh/tclinker kWh/tcement Percentage of AF substitution % Clinker factor % [2]*Operational % % Clinker specific net CO₂ emissions tCO₂/tclinker “Cementitious product” specific net CO₂ emissions tCO₂/tcementitious Kiln emissions tpollutant/ Nm³gas : List of KPIs used in the cement industry Typical KPIs used in the petrochemical industry By being monitored regularly, they keep track of the value of important parameters or ratios related to the global system performances. The number of KPIs should not be too high and their definition not too complex. As a representative industry in the chemical and petrochemical sector, INEOS defined a list of typical KPIs used in the petrochemical industry and especially on INEOS sites. METRIC UNIT ------------------------------ ------------------------------------------------------------------------- -------------------------- [24]*Resource and energy use t % GJ or GJp/t % % - GJ or GJp % tcat.\ loss/tproduct tflare\ loss/tflare\ gas - - [12]*Finance Earnings Before Interest, Taxes, Depreciation and Amortisation (EBITDA) k€ Site Average Margin (SAM) $/bbl Energy prices (natural gas and electricity) Various CO₂ prices €/tCO₂ Variable cost € Payback time (PBT) yr. [9]*Environment Various Various Various twastes/tproduct twastes/tproduct [9]*Safety & Operability On Stream Availability (OSA) % Recordable Incident (RI) - LOC10 - High Potential Incident (HiPO) - HRO+ days - Quality - : List of KPIs used in the chemical industry Table [tab:chemKPI] gives a non-exhaustive list of typical KPIs used to assess INEOS sites’ performances. Subsection 3.3.2 describes in detail all the KPIs aforementioned.   Typical KPIs used in the mineral industry In the minerals industry, key performance indicators are used to assess the performance of the industry based on throughput, impact on environment and energy intensity of products. A non-exhaustive list of specific KPIs used by Omya are shown in Table [tab:minKPI]. NAME OF KEY PERFORMANCE INDICATOR UNITS ------------------ ----------------------------------- -------------------------- [22]*Electricity MWhelec / tproduct % €/ MWhelec €/ tproduct kgCO2eq. / MWhelec % MWhrenewable MWhnon-renewable % % [12]*Gas Gas intensity MWhgas / tproduct Power Load Factor (gas) % Gas cost €/ MWhgas Specific gas cost €/ tproduct CO2 emissions (gas) kgCO2 / MWhgas\ consumed Drying Plant process efficiency % [8]*Production % t m³ ppm or kg / tproduct : List of KPIs used in the industrial minerals industry PROPOSED LIST OF ECONOMIC AND SUSTAINABILITY KPIS Legal KPIs ----------------------------------------------------------------------------- ------------------------ -------------------- KPI NAME UNIT SOURCE Environmental regulatory non-compliances resulting in fines or prosecutions number Environmental licence limit exceedances & other non-compliances number Certifications List of certifications Number of certifications gained by cooperation number Number of certifications maintained by cooperation number Number of certifications lost by cooperation number Level of cooperation LESTS score ----------------------------------------------------------------------------- ------------------------ -------------------- : List of Legal KPIs Environmental regulatory non-compliances resulting in fines or prosecutions This legal indicator relates to the performance of an industry on legal issues originating from non-compliance to environmental regulations. This KPI serves two purposes: one, as a performance indicator for the industrial symbiosis projects which may have contributed to this non-compliance; and two, as an indicator to help prioritise improvements/industrial symbiosis projects for an industry. Environmental license limit exceedances and other non-compliances This indicator exhibits the environmental performance of an industry or the project that may have led to these non-compliances. ISO certifications ISO certifications provide a sustainability level for an industry. For EPOS, the most relevant ISO standards are ISO 9001, ISO 14001, ISO 50001 and OHSAH 18001. Economic KPIs KPI NAME UNIT SOURCE --------------------------------------- ------------- --------------------- Generate local business opportunities yes / no Sales € Profit € Wages paid € Tangible environmental costs € Transport costs € Return on Investment % Internal rate of return % Payback period years Discounted payback period years Net present value € Return on invested capital % Capital expenditure € Operating expenditure € Level of economic cooperation LESTS score : List of common economic KPIs Generate local business opportunities This indicator is listed in as a publicised indicator for economic impacts of industrial symbiosis projects. Some industrial symbioses can generate local business opportunities. For example, this can be in the form of work offered by an industry to a local business which operates & maintains the infrastructure enabling the industrial symbiosis. This indicator is unique in its binary nature, if local business opportunities are not generated or foreseen to be generated, the indicator is 0 or ‘no’; however, in the opposite case, this KPI should be 1 or ‘yes’. Sales This indicator is listed in as a publicised indicator for economic impacts of industrial symbiosis projects. Sales are the revenues resulting from a company’s product sales to customers over a period of time (typically a year). This also includes the revenues from the rendering of services to customers. Care should be taken to delimit the perimeter of the entity for which the sales are considered. As an industrial symbiosis study is focused on a specific site, only the sales emanating from that site (and not the whole company) should be considered. Moreover, it should also be clarified prior to the study which products or services are included in the sales. For example, in the case of an incinerator, waste usually has a negative economic value. A business that operates an incinerator will therefore be paid in exchange of receiving waste to eliminate it. Although waste utilisation is not considered as a ‘product’ per se, it can be viewed as a ‘service’ and therefore included in the sales revenue calculation. Additionally, co-products or services which are not linked to the core business of the company should also be taken into account (e.g. slag from steel industry, or electricity produced by an incinerator). Profit This indicator is listed in as a publicised indicator for economic impacts of industrial symbiosis projects. Profit, also referred to as ‘net income’, is equal to a company’s total revenues minus total expenses over a period of time (typically a year). This value should be reported in the company’s income statement. Total revenues include the amount of any assets (usually cash or accounts receivable) received from customers on the sale of goods or services. Total expenses (or expenditures) are all the outflow of assets from the company to any other entity. Similarly to sales, the perimeter for which the profit is considered should be limited to the site considered for the industrial symbiosis study, rather than the whole company. Therefore, earnings collected at the company scale (e.g. dividends) rather than at the site level should not be considered. Wages paid This indicator is listed in as a publicised indicator for economic impacts of industrial symbiosis projects. Wages paid, or “wage expense”, are the costs incurred for employee’s gross wages over a period of time (typically a year), which includes amounts withheld from those wages for payment to government or other entities (e.g. health insurance) on the employee’s behalf. Again, the cost perimeter should be clearly identified on a case by case basis, especially when dealing with wages of employees that work in or provide support services common to several sites, or also external contractors whose wages are not directly paid by the company. Tangible environmental costs This indicator is listed in as a publicised indicator for economic impacts of industrial symbiosis projects. Tangible costs, as opposed to intangible costs, are costs related to an identifiable source or asset and are therefore easily measurable. In the case of environmental tangible costs, this could correspond to a fine that the company would have to pay if the emissions of a given pollutant are higher than the regulatory threshold. The intangible cost associated could be the loss incurred by the reduced health of employees and thus taking more ‘illness’ days off. A list of tangible environmental costs needs to be defined, including things such as fines for not respecting regulations, environmental taxes, emissions trading schemes, investments made to reduce environmental impact, campaigns to promote eco-friendly behaviour, etc. Transport costs This indicator is listed in as a publicised indicator for economic impacts of industrial symbiosis projects. Transport costs are associated with the transportation of raw materials or goods provided to/by the industrial site from/ to another entity. The transport costs considered need to be clearly defined. First of all, it should be clarified if the investment cost of the transportation medium (e.g. railcar) should impact the transport cost, or only the costs related to the transport itself (e.g. fuel and operator wages). Secondly, the origin/destination of the product should be wisely chosen. For example, an input raw material could have first been transported from a mine (belonging to a mining company) to a storage warehouse (belonging to a distributor), and then further transported to the industrial site considered. In that case, it must be well-defined whether the transport cost should be from the distributor warehouse or from the mine. Return on investment Return on investment (ROI) is a performance measure to evaluate the efficiency of an investment. It measures the amount of financial return on an investment relative to the investment’s cost. The formula is: ROI={Cost\,of\,investment} The gain from investment could also be associated with the savings incurred from buying infrastructure enabling industrial symbiosis actions. For example, the investment could be a pipe which allows sending excess steam from one company to another, which would have otherwise been lost. The gain (for the overall system consisting of both companies) would be the total fuel savings compensated by the exchanged steam. More information c anc an be found in . Net present value Net Present Value (NPV) is the difference between the present value of cash inflows and the present value of cash outflows over a period of time. The cash flows are discounted back to their present value using a discount rate in order to take into account the time value of money. NPV is used to analyse the profitability of a projected investment or project in the current time. The following formula is used for calculating the NPV: NPV=^{N_t} {(1+r)^t}-C_0 -------- ---- ----------------------------------------------------------- Where: Ct is the net cash inflow (revenue-expenses) during period t C₀ is the total initial investment cost r is the discount rate t is the time period Nt is the number of time periods -------- ---- ----------------------------------------------------------- A positive NPV indicates the projected earnings generated by a project or investment (in present currency) exceeds the anticipated costs (also in present currency). Generally, an investment with a positive NPV will be a profitable one and one with a negative NPV will result in a net loss. More information can be found in . Internal rate of return Internal rate of return (IRR) is the discount rate that makes the NPV from a particular project equal to zero over a given period of time. The higher a project’s internal rate of return, the more desirable it is to undertake the project. IRR is uniform for investments of varying types and, as such, it can be used to rank multiple prospective projects on a relatively even basis. Assuming the investment costs of various projects are equal, the project with the highest IRR would probably be considered the best from an economic point of view. More information can be found in . Payback period The payback period (PBP) is the length of time required to recover the cost of an investment. It is calculated by dividing the initial investment by the yearly cash inflow. The payback period is an important determinant of whether to undertake the project or investment, as longer payback periods are less desirable. The payback period ignores the time value of money, unlike other methods of capital budgeting such as net present value or internal rate of return. More information can be found in . Discounted payback period The discounted payback period gives the number of years it takes to break even from undertaking the initial expenditure, by discounting future cash flows and recognising the time value of money. In other words, it is the number of time periods from which the net present value becomes positive for a given discount rate. This indicator is adapted from PBP to account for the time value of money which is often considered to be a weakness in non-discounted PBP calculations, especially over longer time horizons. More information can be found in . Return on invested capital Return On Invested Capital (ROIC) is a measure used to assess a company’s efficiency at allocating the capital under its control to profitable investments. ROIC gives a sense of how well a company is using its money to generate returns. One way to calculate it is: ROI={Invested\,capital} More information can be found in . Capital expenditure Capital expenditure (capex) are the funds required to acquire or upgrade physical assets such as property, industrial buildings or equipment. This is an important consideration for projects as companies will have limited funds that they can mobilise, ruling out certain projects regardless of their profitability. If there is a strong interest in a project that exceeds the company’s funding capabilities, funding from external sources will have to be sought. More information can be found in . Spatial KPIs KPI NAME UNIT SOURCE ---------------------------------------------------------------------------------- ---------------------------- -------- Efficient use of land number of activities / km² Distance between the partner industries km Availability of major connections (routes / channels) between partner industries List of modalities Economic intensity €/km² Level of economic cooperation LESTS ranking : List of Spatial KPIs Efficient use of land Multiple land use is an objective of efficient land use. This indicator will be affected significantly by the number of activities being performed in the area. Distance between dispatching and receiving nodes This indicator is specifically defined for industrial symbiosis projects. Distance between two or more industries is a crucial parameter which defines the economic suitability of an industrial symbiosis. The distance between the industries shows the distance covered via a transport route connecting the industries. Availability of major connection routes / channels between partner industries Effective connection routes between partner industries within an industrial symbiosis is a crucial indicator, especially if the industries are not located in immediate proximity to one another. Economic intensity This metric represents the profit generated per land area used for the industrial activities. The higher the value, the less impact economic activities will have on land usage, which is in line with the general idea of going towards a more densified society, leaving more space for natural habitats. Technical KPIs A list of technical KPIs defined in literature were identified and are listed in Table [tab:technical]. Each of these is then described in more detail in the following subsections. KPI NAME SHORT DESCRIPTION UNIT SOURCE --------------------------------- -------------------------------------------------------------------------------- ------------- --------------------- Domestic Material Input DMI Domestic extraction (DE) + imports t Total Material Requirement TMR Direct material input + indirect flows + unused DE t DMIw (t/worker) DMI/number of workers t/worker TWGw (t/worker) TWG/number of workers t/worker Worker Productivity WP Total production/number of workers t/worker Total Water Input TWI Total water consumption t Total WasteWater Generated TWWG Total amount of waste water produced t Total Water Input /worker TWI/number of workers t/worker Total Energy Input Total energy consumption GJ Total Energy Input per worker TEI/number of workers GJ/worker Energy Intensity E-In TEI/total production GJ/t Energy efficiency energy in products/total energy in % Exergy efficiency product exergy/ input exergy % Material efficiency mass of (products out /raw materials in) % Level of technical cooperation 0 – no technical feasible cooperation to 5, principles of circular economy met LESTS score : List of Technical KPIs Domestic Material Input (DMI) The DMI is an indicator derived from material flow analysis (MFA) and is the measure of material flows to be used in the system. The materials used in the system can be domestic (i.e. from own sources) and/or imported. Hence DMI is the sum of domestic extraction and imports. It is used to indicate the material requirement of a system as well as to reflect co-product exchange between sub-systems . The DMI of a system can be improved by increasing exchange between the subsystems while the DMI of the subsystems will remain the same. As DMI is directly linked to the size of the system, for comparing two or more systems, normalization with another parameter which is linked to the system size is required. This leads to another indicator, the DMIw, which is DMI divided by the number of workers. Worker Productivity (WP) The WP is a measure to assess the efficiency of a group of workers. It is calculated by dividing the amount of output (product) to the number of workers producing that output. The output can be considered as product (material) itself or the revenue it brings. In the EPOS project, when using this KPI, the focus will be on the material itself. Total Water Input (TWI) Total water consumption of a system can be represented with TWI. Water usage can be from domestic sources or imported from outside sources such as city water networks, lakes and rivers. It is important to note that natural water sources such as lakes and rivers do not fall in the category of domestic sources as they generally cross the system boundaries and are shared with other systems . Domestic sources, therefore, include only water coming from rain or use of water from a surface source on-site or reclaimed at the site. The TWI is a sum from all sources. Similar to other KPIs identified from MFA, this parameter can be normalized by dividing it by the number of workers, which results in total water input per worker (TWIw). Total Wastewater Generated (TWWG) As explained in Section 4.6, the total waste generation indicator (TWG) does not include wastewater. Hence a separate measure is used for wastewater generation. The TWWG is the total waste water that is generated by the processes in the system. Commonly TWI and TWWG of companies are similar: the more the TWI the more the TWWG . For systems with dissipative usage of water, such as evaporation processes, TWI is higher than TWWG. Total Energy Input (TEI) Total net energy required by the system is called as total energy input. As the energy flows are measured at the entrance of the system, their efficiencies are accounted within the TEI indicator . Therefore, the definition of the system and its boundaries is important when determining this KPI. The normalisation of this parameter is completed, as with several indicators, by dividing TEI by the number of workers to obtain the total energy input per worker, TEIw. Energy Intensity (E-In) As the TEI is directly linked to the production rate of a system, it is difficult to use as a comparative indicator between systems with differing products. The E-In, therefore, is used to indicate the specific energy required for a unit of product. It is calculated by dividing the TEI by production to obtain the result in units of GJ/tonne. Energy Efficiency Energy efficiency is, in general, referred to as the ratio of output energy to input energy. It can be defined for a process, equipment, cycle etc. Therefore, when calculating energy efficiency, the choice of system boundaries is important as the inputs and outputs are determined based on them. Energy efficiency can also be referred to as ‘thermal efficiency’ or ‘first law efficiency’ and can also be estimated using losses when the output energy is not measured or more difficult to obtain accurately. \eta_E=}{E_{in}} = 1-}{E_{in}} -------- ------- -------------------------- Where: ηE is the energy efficiency Eout is the energy output Ein is the energy input Eloss is the energy lost -------- ------- -------------------------- Exergy efficiency Exergy is defined as the maximum work that can be achieved by a material by reversible exchanges with the environment . Exergy efficiency is the ratio of output exergy from a system to input exergy to the system. It can be referred to as ‘second law efficiency’ as well. This is expressed similarly to energy efficiency, where B represents exergy: \eta_B=}{B_{in}} = 1-}{B_{in}} Material Efficiency Material efficiency has multiple definitions. It can be referred to as the ratio of material flows that are used in the processes to the total material flow to the system. Alternatively, it may be referred to as the ratio of product flows to raw material flows. The choice for which definition to use in the EPOS project will be considered during the selection of cross-sectorial KPIs. Social KPIs KPI NAME UNIT SOURCE ---------------------------------------------------------------------------------------------------------------- --------------------------------- --------------------- Fatalities (employees only) # Lost Time Injury (employees only) # Near misses # First aid injuries # Medical treatment injuries # Restricted work injuries # Occupational illness # A sketch of all the supply chain actors y/n Ratio of supply chain actors showing their commitment to CSR (Corporate Social Responsibility) criteria % Taxation revenue € Membership in an initiative that promotes social responsibility along the supply chain (number of enterprises) # Skill level number Leadership positions held by women % Ratio of salary of female employee wages to male employee wages % Ratio of female employees % Ratio of employees with a foreign origin % Job security - Percentage of workers with a long-term contract % Evidence of violations of laws and employment regulation # Mechanism for registering grievances of community y/n Aesthetic and visual acceptability number of complaints Noise decibels + number of complaints Dust number of complaints Odour number of complaints Workforce employed locally % Social level of cooperation LESTS score : Social KPIs Health and Safety KPIs Fatalities (employees only) This is the number of employees who have experienced a fatal event. Lost Time Injury (employees only) A lost time injury is the time (days) that could not be worked by the worker due to an occupational accident or disease resulting from a non-fatal injury arising out of or in the course of work. Near misses A near miss is an unplanned event that did not result in injury, illness, or damage – but had the potential to do so. It is typically tracked as part of plant safety records.It is First aid injuries Injuries which could be treated onsite, resulting in no further medical treatment. Medical treatment injuries Injuries requiring intervention of medical personnel, directly after the incident or some time after the incident occurred. No further work absence required after treatment. Restricted work injuries Injuries resulting in absence of work longer than required for the treatment. Occupational illness Illness resulting from the nature of the work carried out during prolonged time or exposure to hazards. Skill level This is accounted for as the average number of hours of training per employee, i.e. the total number of training hours divided by the total number of employees. Social Responsibility in supply chain A sketch of all the supply chain actors An overview of all actors directly involved within the supply chain and their interactions. Ratio of supply chain actors showing their commitment to CSR (Corporate Social Responsibility) criteria Number of supply chain actors practicing CSR. CSR policy is usually regarded as a self-regulatory mechanism whereby a business monitors, and ensures its active compliance with the legal framework, common ethical standards and internationally agreed norms. Arguably, a firm’s implementation of CSR goes beyond mere adhering to the existing legal framework and involves “actions that appear to further some social good, beyond the interests of the firm and that which is required by law”. Taxation revenue This indicator is listed in as a publicised indicator for economic impacts of industrial symbiosis projects. Taxation revenue represents the taxes paid by the company. One should only consider the taxes emanating from the site under study. Membership in an initiative that promotes social responsibility along the supply chain (number of enterprises) Number of participations in social responsibility programmes Non-discrimination Leadership positions held by women Ratio of women in leadership positions to total number of leadership positions Ratio of salary of women wages to men Salary balance between male and female employees Ratio of female employees Female employees compared to total employees. Ratio of employees with a foreign origin Employees of foreign origin to total employees. Job security - Percentage of workers with a limited duration contract Ratio of employees with a contract of limited duration. Evidence of violations of laws and employment regulation Number of complaints/convictions regarding employees contracts. Workforce employed locally Number of employees from the local region / total population within the hiring age range (18 – 65). Social responsibility towards the community Mechanism for registering grievances of community Indicating if a system for registering and treatment of community complaints is in place. Aesthetic and visual acceptability Number of complaints about visual pollution. Noise Average noise measured outside the plant / number of reasonable complaints. Dust Number of complaints about dust emissions. Odour Number of complaints about odour. Environmental KPIs p6cm c p4cm & UNIT & SOURCE & M t & Raw materials used & M t & Materials for packaging purposes & M t & Total on-site energy consumption from renewable sources & % & CO₂e emissions from power generation & k t & NOx emissions & k t & SOx emissions & k t & Total particulate emissions & k t & Water withdrawal from marine water sources & M m³ & Water withdrawal from freshwater sources & M m³ & Water withdrawal from municipal water sources & M m³ & Water discharged- cooling water to marine water sources & M m³ & Water discharged- treated wastewater to marine water sources & M m³ & Water discharged- treated wastewater to freshwater sources & M m³ & Water discharged- waste water to sewerage & M m³ & Water discharged- waste water to other destinations & M m³ & hazardous waste produced & t (solid) or m³ (liquids) & hazardous waste recycled & t (solid) or m³ (liquids) & Non-hazardous waste produced & t (solid) or m³ (liquids) & Non-hazardous waste recycled & t (solid) or m³ (liquids) & Direct GHG emissions & M t CO₂eq or kg CO₂eq/ tproduct & Total waste sent to landfill & k t & Carcinogens & kg C₂H₃Cl eq & Non-carcinogens & kg C₂H₃Cl eq & Respiratory inorganics & kg PM2.5 eq & Ionising radiation & Bq & Ozone layer depletion & kg CFC-11 eq & Respiratory organics & kg C₂H₄ eq & Aquatic ecotoxicity & kg TEG water & Terrestrial ecotoxicity & kg TEG soil & Terrestrial acidification/nutrification & kg SO₂ eq & Land occupation & m²org arable & Aquatic acidification & kg SO₂ eq & Aquatic eutrophication & kg PO₄3- (P-limiting) & Global warming & kg CO₂ eq & Non-renewable energy & MJ primary & Mineral extraction & MJ surplus & Land occupation, biodiversity & ha.yr arable & Fossil energy use & MJ deprived & Mineral resources use & kg deprived & Water use & m³ deprived & Aquatic eutrophication & kg PO₄3- (P-limiting) & marine eutrophication & kg N eq & Aquatic ecotoxicity, short-term & CTUe & Aquatic ecotoxicity, long-term & CTUe & Respiratory organics & kg NMVOC eq & Carcinogens, short-term & CTUh & Carcinogens, long-term & CTUh & Carcinogens, indoor & CTUh & Carcinogens, pesticides residues & CTUh & Non-carcinogens, short-term & CTUh & Non-carcinogens, long-term & CTUh & Non-carcinogens, indoor & CTUh & Non-carcinogens, pesticides residues & CTUh & Human health & DALY & Ecosystem quality & PDF m² yr & Climate change & kg CO₂ eq & Resources & MJ primary & Total material requirement per worker & t/worker & Total Waste Generated & t & Eco-Efficiency & none & Eco-Intensity & none & Material Inefficiency & none & Life-cycle assessment-based methodologies Life-cycle assessment (LCA) is one of the most systematic methods currently available and standardized by the ISO to address environmental impacts from a product or process. The details of the methodology will not be included here; rather, the categories used in two popular impact assessment methodologies are presented as being potential KPIs for use in the EPOS project. One important distinction must be made between midpoint and endpoint categories. Midpoint categories are typically the first level of aggregation following the life-cycle inventory data which are the real data from the production process. These categories are meaningful on their own to some audiences but individually cannot address the entire impact on meaningful sectors of people or plant. Endpoint categories are an aggregated set of midpoints with the intention of providing more meaningful and generalizable results for the user. Both levels of impact category are relevant and thus both are presented here. The categories used are taken from the IMPACT 2002+ method developed at EPFL in Switzerland and IMPACT World+ which was developed as an international collaboration to address regional specificities for different impact categories. Endpoint impact categories will be presented first, followed by the contributing midpoint categories. Human Health Human Health is an endpoint impact category used in both IMPACT 2002+ and IMPACT World+ though the dependencies differ between the two methods. In IMPACT 2002+, this category accounts for Human Toxicity, Respiratory Effects, Ionizing Radiation and portions of Ozone Layer Depletion and Photochemical Oxidation. In IMPACT World+, the contributing midpoint indicators are Human Toxicity, Photochemical Oxidation, Ozone Layer Depletion,Depletion, Global Warming and Water Use. In both characterization methodologies, however, the units used for measurement of the endpoint category are Disability Adjusted Life Years (DALY) which refer to the years of life which are degraded or lost as a result of the activity studied, averaged over a population. Thus, for the population affected, the DALY will be averaged over that population. Ecosystem Quality The Ecosystem Quality endpoint indicator is common between the IMPACT 2002+ and IMPACT World+ methods discussed here but as with the Human Health category, the midpoint indicators that contribute are slightly different. In the IMPACT 2002+ method, this endpoint category includes Aquatic Ecotoxicity, Terrestrial Ecotoxicity, Aquatic acidification and eutrophication, Land occupation, Terrestrial acidification and elements of Ozone Layer Depletion and Photochemical oxidation. Resource Use, Land Use, Water Use, Eutrophication, Acidification, Ecotoxicity, Global Warming and Ozone Layer depletion are all included in this endpoint impact category. The units of measurement considered for Ecosystem Quality are PDFm2yr which is the potentially disappeared fraction of species (PDF) in an area of 1m2 in one year as defined by Jolliet . Climate Change Climate Change is used as an endpoint impact category in IMPACT 2002+ and is measured in kg CO₂ eq, as is the contributing midpoint category of Global Warming. Climate change is often referred to as being the most pressing concern for sustainability and is often referred to in literature as a reason to reduce fossil fuel consumption. Climate Change is not used as an Endpoint category by IMPACT World+ _per se_ but instead spans all impact categories in the methodology or it can be treated separately if its contributions to the other categories are not double-counted (i.e. If Climate Change is considered as a separate endpoint category, its impacts cannot be included in the Ecosystem Quality endpoint impact category) Resources (and Ecosystem Services) Resources is an endpoint category in IMPACT 2002+ which encompasses the midpoint categories of Mineral Extraction and Non-renewable Energy Consumption. It represents a measure of damage caused by depleting the resources of the planet, specifically the energy/fuel resources. The units of measure are in MJ primary energy eq as are the two contributing midpoint categories. The IMPACT World+ system defines this endpoint category as Resources and Ecosystem Services with contributions from the midpoint categories of Water Use, Land Use and Resource Use. Carcinogens The Carcinogen indicator relates to the amount of cancer-inducing chemicals which are emitted by an activity. The measurement is made in equivalencies of vinyl chloride (C2H3Cl), also commonly referred to as VC or VCM for vinyl chloride monomer. Carcinogens are a midpoint indicator in the IMPACT 2002+ method and contribute to the endpoint indicator of Human Toxicity. This category should be considered in any cases where highly carcinogenic products, co-products or wastes are used or produced. In the IMPACT World+ methodology, carcinogens are split into short-term, long-term, indoor and pesticide residues and are measured in comparative toxic units for humans (CTUh), following the definition of the USETox system for chemicals toxic to humans. Non-Carcinogens This midpoint category from IMPACT 2002+ refers to non-carcinogenic chemical compounds which have other effects on human health. The equivalency unit used is the same as for carcinogens, chloroethene (C2H3Cl), but refers to chemical compounds which are not carcinogenic for humans but lead to decreased life expectancy or quality of life on the same basis. The combination of Carcinogens and non-carcinogens make up the midpoint indicator of Human Toxicity which then contributes to the endpoint indicator of Human Health Impacts. Similarly to carcinogens, the IMPACT World+ represents non-carcinogens in a variety of settingstemporal scales, namely: short-term, long-term, indoor and pesticide residues. The unit of measure is also the same as for carcinogens, CTUh. Respiratory Inorganics This midpoint indicator for Eco-indicator 99 , adopted into IMPACT 2002+ and IMPACT World+, reflects upon damage caused by small particulate matter. The reference unit for this category is kg PM2.5 eq which is to say, particles of diameter less than 2.5 microns. This category covers all small particulate matter and the respiratory issues induced in humans from such small particulates. As such, this midpoint category is carried further into the endpoint category of Human Health Impacts. Ionizing Radiation Ionizing radiation is the type of radiation specifically problematic for health impacts in humans. Ionizing radiation is a midpoint category in IMPACT 2002+ and IMPACT World+ to account for the radiation exposure for a product or process, measured in Bq ¹⁴C eq emitted to air as the base unit for this category. This midpoint category is included in the Human Health Impact endpoint category. Ozone Layer Depletion Depletion of the Ozone layer is adopted from the Eco-indicator 99 methodology and treated as a midpoint category within the IMPACT 2002+ and adopted verbatim within the IMPACT World+ framework. The units used for this category are kg CFC-11 eq, relating the impact of a product or process to the same impact on ozone layer depletion by CFC-11 which is one of the problematic refrigerants identified as being the cause of massive ozone depletion. This midpoint category is factored into the endpoint categories of Human Health Impacts and Ecosystem Quality. Respiratory Organics (Photochemical Oxidation) Both IMPACT 2002+ and IMPACT World+ have have a midpoint indicator for Respiratory Organics, sometimes referred to as Photochemical Oxidation for the reason that the main danger for humans is the photochemical synthesis of smog. The IMPACT 2002+ midpoint category has units of kg ethene (C₂H₄) eq whereas the IMPACT World+ method refers to non-methane volatile organic compounds which are the reagents for the formation of photochemical smog. In both methods, this midpoint category has an impact on the endpoint categories of Human Health and Ecosystem Quality. Aquatic Ecotoxicity The midpoint indicator for aquatic ecotoxicity is used in IMPACT 2002+ as a midpoint category based on the equivalent level of triethylene glycol (TEG) which is emitted to air, water and land but refer to the impacts on fresh surface water. As this midpoint indicator is directly linked to the impact of activity on the natural system, it is included in the endpoint category of Ecosystem Quality according to IMPACT 2002+. The IMPACT World+ Method dichotomizes this category into Aquatic ecotoxicity in the short- and long-term to create the distinction between acute and chronic effects in aquatic ecosystems. The unit of measure also differs for IMPACT World+, being recorded in comparative toxic units (CTU) which is then specifically adapted to the aquatic ecotoxicity impact category and used as CTUe following the definitions of USETox . Terrestrial Ecotoxicity This is similar to Aquatic ecotoxicity and is based on the same metrics but refers specifically to emissions to soils. Indeed, the reference unit of kg TEG emitted to soil is also used for this midpoint indicator. As with aquatic ecotoxicity, terrestrial ecotoxicity contributes to the endpoint impact category of Ecosystem Quality. Terrestrial Acidification/Nutrification Contrary to the case in aquatic systems, terrestrial acidification and eutrophication are grouped into one midpoint impact category in IMPACT 2002+ and IMPACT World+ . The basis units are kg SO₂ eq emitted to air which are then assumed to cause terrestrial acidification. The nutrification portion of this category must also be converted into the same equivalent units though the methodology for this conversion is unclear in the literature. Land Occupation The land occupation impact category builds on work from Eco-indicator 99 and uses m² organic arable land eq required or affectedaffected by the product or process in question. This midpoint indicator speaks to the use of land that could otherwise exist in its natural statestatestatestate and thus contributes to the endpoint indicator of Ecosystem Quality. Aquatic Acidification This midpoint impactimpact category relates to the acidification (pH depression) of water systems. The measurement units for this category are kg SO₂ eq emitted to air. The units of SO₂ eq emitted to air are specifically used for this purpose as atmospheric SO₂ will eventually converted to dilute Sulfuric acid by reaction with atmospheric water vapour. As such, the acidification potential of any of acidifying substance must be converted to the acidification potential of SO₂. The aquatic acidification midpoint impact category is factored into the endpoint category of Ecosystem Quality. Aquatic Eutrophication Eutrophication is increased nutrient availability or concentration in water which causes excessive growth of plant species. Such activities disrupt natural ecosystems and thus this IMPACT 2002+ midpoint indicator is included in the calculation of the endpoint category of Ecosystem quality. The midpoint indicator units are kg PO₄3- eq into water by default. In regions where nitrogen is the limiting factor in plant growth, the midpoint basis unit is a nitrogenic species but for simplicity in this document, the basis units are defined as kg PO₄3- eq into water. IMPACT World+ uses Aquatic Eutrophication as a midpoint impact category in the same way but also has an additional midpoint impact category of Marine Eutrophication which relates to other bodies of water such as seas and oceans (as opposed to fresh surface water). Global Warming The Global Warming midpoint impact category indicates the contribution of the subject of study to the increase in global warming associated with the greenhouse effect. The units of measurement are kg CO₂ equivalent and is one of the major foci on many policies and studies with regard to sustainability and future policy on industrial production. Using the IMPACT 2002+ methodology, this midpoint indicator contributes to the endpoint impact category of Climate Change and is indeed its only contributor. The IMPACT World+ method treats the Global Warming midpoint indicator slightly differently, as a contribution both to Ecosystem Quality and Human Health. Non-renewable Energy The IMPACT 2002+ impact category of Non-renewable Energy specifically refers to the specific primary energy demand of the product or process. The midpoint units are MJ primary energy extracted and use the higher heating value for combustible fuels. This midpoint category further contributes to the Resource endpoint impact category. Mineral Extraction The mineral extraction midpoint category in IMPACT 2002+ contributes together with Non-renewable Energy to provide the endpoint Resource impact category. The calculations for this indicator are expressed in units of specific MJ of surplus energy as from Eco-indicator 99 . This calculation represents an extrapolation of the energy demand of the mineral product over an unknown lifetime of the mining activity based on cumulative demand in a given period. Land Occupation, Biodiversity This indicator is a midpoint impact category of Impact World+ and represents similar information to the Land Occupation category in Impact 2002+ but is expressed in units of ha yr arable land, expressing the land use and biodiversity impact as a loss of arable land and habitat for animals. Fossil Energy Use This midpoint impact category of IMPACT World+ bears a resemblance to the Non-renewable Energy category used in IMPACT 2002+ but is expressed specifically for the use of fossil energy. The units of measure are MJ primary energy deprived, meaning that this energy is no longer available for other uses. This midpoint impact contributes to the midpoint category of resource use and thus the endpoint categories of Ecosystem Quality and Resources and ecosystem Services. Mineral Resources Use Mineral Resources Use, like Fossil Energy Use, bears a resemblance to the IMPACT 2002+ midpoint impact category of Mineral extraction but is instead measured in kg deprived. This refers to the deprivation of future potential users of this resource. This midpoint impact contributes to the midpoint category of resource use and thus the endpoint categories of Ecosystem Quality and Resources and ecosystem Services. Water Use This midpoint impact category of IMPACT World+ indicates the volume of water that is used which is therefore no longer available for use by other processes. As such, the reference unit for the category is m³ deprived, meaning that that water is unusable by other processes. This midpoint impact category further contributes to the endpoint of Resources and Ecosystem Services. Global Reporting Initiative Indicators The global reporting initiative (GRI) is an independent organization with the mission to standardize industrial reporting on sustainability. Selected indicators from are suggested here for use in EPOS. Raw Materials Used This indicator is based on the G4 Sustainability Reporting Guidelines (G4SRG) and is simply the total mass of material used to produce (and package) the main products and service of an industry. The guideline also suggests reporting in the two sub-categories of renewable and non-renewable materials used. The units suggested for this indicator are Mtonnes. Materials for Packaging Purposes Similar to the indicator of Raw Materials Used, this indicator is simply a report of the mass of material which is used for packaging the main products or services of a company. As with the parent category, the units suggested for this indicator are Mtonnes. On-site Energy Consumption from Renewable Sources This indicator from the G4SRG is an indication of percentage of site energy demand that is met by renewable sources. It is calculated by dividing the amount of renewable energy utilized by the total site energy demand. If the company exports energy products, this is accounted for by subtracting the exports from the imports in the denominator of the calculation. Direct CO₂eq emissions This indicator (based on G4-EN15 ) reflects the equivalent CO₂ emissions from site operations. This refers to the direct emissions from processes on the site and does not include the indirect effects from importing materials or energy from outside of the site boundary. As stated in the guide: “GHG emissions in metric tons of CO₂ equivalent, independent of any GHG trades, such as purchases, sales, or transfers of offsets or allowances.” NOx Emissions This indicator is a subset of G4-EN21 of the G4SRG specifically focusing on NOx emissions as being one of the most relevant emissions to air that can be measured on sites. NOx are of particular importance as they are limiting reagent in photochemical smog formation in some jurisdictions but can also contribute to acidification and nutrification generally. This indicator is intended to showcase the total amount of NOx emissions from an industry. SOx Emissions Similar to the emissions of NOx, SOx emissions are a subset of the G4-EN21 reporting and are specifically referred to as a significant emission. As mentioned for the indicators based on LCA, SOx contribute to terrestrial and aquatic acidification and are thus the focus of a specific indicator. Total Particulate Emissions The total emissions of particulate matter from a process is another airborne emission indicator based on G4-EN21 . This indicator refers to the total direct emissions of particulate matter (diameter less than 100 microns) to the air. Such emissions have health impact for nearby populations and workers and should be kept as low as possible. Of particular concern are particulates of diameter less than 2.5 microns which have greater health consequences than larger particles. Thus, the diameter used for this indicator could be modified according to the most relevant particle size. Water Withdrawal Three indicators are suggested for addressing water withdrawal based on G4-EN8 . These indicators cover withdrawal from marine sources, freshwater sources and municipal sources. The indicator for each source should be reported as a separate quantity according to G4-EN8 and measured in Mm³. For adaption to industrial symbiosis situations, an additional category of water from other industries could also be measured. Reporting could also be done using system of percentages though the absolute values can be useful for representing the scale of industries as well. Water Discharge Water discharge is suggested by G4-EN22 to be recorded by the final disposition including treatment. As such, the suggestion here is to include five measurements, or a relevant subset thereof, of: cooling water to marine destination, treated wastewater to marine water sources, treated wastewater to freshwater sources, wastewater to sewerage and wastewater to other destinations. As with water withdrawal, the recommended unit of measure for water discharge is Mm³. Additional destinations could be included, such as wastewater sent to a non-treatment industry which may be especially relevant for IS scenarios. Hazardous Waste Following G4-EN23 , hazardous waste should be classified as such by local legislation for each site and measures in tonnes for solids and m³ for liquids. The fate of the waste should be accounted for by noting the total hazardous waste production as well as the amount that is recycled. The definition of recycling could be extended to include the reuse of such hazardous waste by neighbouring industries. Non-hazardous Waste The suggestion for non-hazardous waste is similar as that for Hazardous Waste but of course is separated by local legislation which specifies materials as being hazardous or not. The units should also be similar, measured in tonnes for solids and m³ for liquids. As with hazardous waste, the category could be split into the total production and also allow for a specification of the amount recycled where the definition could be extended to symbiosis efforts. Total Waste sent to Landfill This indicator is a sub-calculation of the non-hazardous waste destination but specifically addresses the burden on landfill facilities caused by a site. Landfill usage can also have additional impacts on the health and safety of neighbouring residents in addition to local ecosystems which warrants its inclusion as a separate indicator and should be reported in ktonnes. GHG Emissions As Greenhouse Gas (GHG) emissions are a major concern and are one focal point of expected legislative changes, two indicators are suggested for accounting. Both indicators are following G4-EN15 and address both the total emissions and the specific emissions for a product. The first indicator is a measurement of the absolute measurement of the GHG emissions in Mtonnes CO₂ eq, while the second is this absolute emission divided by the mass of product resulting from these emissions, expressed as kg CO₂ eq / kgproduct. The two methods account for both the total emissions burden and the specific emissions related to the production of the plant. The latter also relates to the GHG intensity of a product which allows for simple comparison of GHG emissions across all sectors. Material flow analysis environmental indicators Material flow analysis is a methodology which is specifically refined for attributing products to its constituent flows. Sendra et al. Suggested an adaptation to the commonly-practiced methodology for specific use in industrial settings . A subset of the indicators proposed by Sendra are suggested as potential indicators for EPOS. Total waste generation (TWG) The TWG indicator exhibits the burden on the environment to treat waste generated by site operations. This indicator specifically refers to the waste generated which is not emitted to air or in wastewater and thus those flows should be accounted for separately. The theory for this indicator is derived from material flow analysis (MFA) and accounts only for the outputs to nature, not including product exports, material recycled or emissions to air or wastewater. Total Material Requirement The total material requirement is defined by Sendra et al. according to MFA as the direct material input plus unused domestic extraction and indirect flows stemming from imports. This can be viewed as being one step beyond the site boundary, accounting for some indirect consequences of material use. One method of normalising TMR is to view it with respect to the number of workers on a site instead of per mass of production. Normalising in this way leads to another indicator, known as TMRw, which is the total material requirement divided by the number of workers. The use of TMR can also lead to the definition of Eco-Efficiency and Eco-Intensity. Eco-Efficiency The Eco-Efficiency indicator stems from MFA and is simply a ratio of the annual plant production to the TMR. The mass of product exported is simply divided by the TMR to obtain this ratio and speaks to the mass efficiency of converting feedstock to products. Eco-Intensity The Eco-Intensity indicator is the inverse of Eco-Efficiency but can be more meaningful in some cases as it is the expression of how much material must be used to produce a reference unit of product. The colloquial analogue can be found in vehicle fuel efficiency where ’miles/gallonfuel’ and ’Lfuel/100km’ are both meaningful quantities but importance placed either on the fuel consumption or the distance travelled as the reference unit. Material Inefficiency This indicator is a combination of many flows represented in the methodology of MFA presented by Sendra et al. . This indicator is calculated by adding the emissions to air and wastewater to the TWG to find the total output to nature and then dividing the sum by the TMR: M_{Inef}=_{emissions}^{air} +\sum _{emissions}^{wastewater}}{TMR} The result is fractional, complementary to Eco-Efficiency. Summary Thus, it can be seen that many KPIs can be found in literature and in many cases overlap with those proposed and used by industry while there are also sector-specific KPIs which are not addressed. Gathering sufficient data and calculating all KPIs for industrial sites is often not practical and thus the list of KPIs must be refined for the context in which they will be used. In context of the EPOS project, focused on industrial symbiosis, the list of KPIs will be reduced to a shorter list which is more pragmatic and practical for assessing symbiosis options across sectors. REFINEMENT METHOD The long list of KPIs that above are refined with multiple steps using different methods in each step. The details of the methods employed are explained in the following sections. The first step for refining the list was a coarse reduction of the longlist of KPIs by the universities, assessing the inputs from each sector as well as the available literature. This step included analysing the sector-specific and cross-sectoral KPIs to find the commonalities between industries and also between literature sources and industries. Then the KPIs were sorted with respect to the number of sectors using them. The importance of this step is to eliminate the KPIs that are not of importance to any of the EPOS sectors so that more detailed analysis can be carried out using those remaining. SPQR Method for Non-Technical KPIs For the evaluation and selection of non-technical KPIs, the SPQR method was developed and used by EPFL. This method is similar to the RACER method which has been used in other EU projects . With the RACER method, evaluation is done considering 5 aspects, namely Relevant, Accepted, Credible, Easy and Robust. Since the focus in the EPOS project is on industrial symbiosis, it was necessary to focus on KPIs which adhere to slightly different criteria. With the SPQR method, the KPIs are evaluated considering 4 independent aspects: Simple: if it is simple to assess and understand Predictable: if it is possible to roughly estimate the changes in the KPI, especially how symbiosis will affect it Quantifiable: if it is possible to express the corresponding KPI in numbers Relevant: if it is directly or indirectly related to industrial symbiosis and hence EPOS The following grades are used in the evaluation: 2 : yes 1 : somewhat 0 : no If ‘Land Use’ of an industrial unit is considered as an example: S: 2, as it is simple to assess regardless of the position of the person, whether they work on the unit or not P: 2, as it is predictable for a size of equipment required to implement a synergy Q: 2, as it is quantifiable (actual surface area of land) R: 2, as it is relevant to industrial symbiosis, since considering a potential symbiosis with the unit depends on availability and usage of land for new units or transportation processes The SPQR evaluation of all the non-technical KPIs can be seen in Table [tab:SPQR]. KPI S P Q R ----------------------------------------------------------------------------- --- --- --- --- 2 1 2 2 Environmental regulatory non-compliances resulting in fines or prosecutions 2 1 2 1 0 1 2 1 Fatalities (employees only) 2 0 2 2 2 0 2 2 Average hours of training per year per employee per category 1 1 2 1 2 0 2 0 ISO certifications (140001 etc) 2 0 2 0 2 2 2 2 Job security 1 0 0 1 0 0 1 1 Health and well-being 1 0 1 1 0 0 0 0 Education standards 1 0 2 0 1 2 0 2 Crime rates 2 0 2 0 2 0 1 1 Noise 2 1 2 1 2 1 2 1 Odour 2 1 1 1 : SPQR evaluation of non-technical KPIs Consultation Method The consultation method was to simply refine the long list of KPIs with respect to the feedback from the project partners. In a technical meeting of project partners, the long list of KPIs was shortened after open discussion with the participation of all partners in the project consortium. The KPIs in the shortened list were refined by the partners who have expertise in the corresponding field; feedback was received from Quantis on environmental KPIs and UGent on non-technical KPIs. All the EPOS industries gave feedback on the refined list of KPIs to EPFL as well to make sure that the list includes everything of their interest. Then the final approval was given by discussion between universities and Quantis. The workflow described in this section is summarized in Figure [fig:consult]. The reduction in the number of KPIs after each step is also visualised. [Workflow for KPI list refinement]
Backstory of: Climate-related range shifts – a global multidimensional synthesis and...
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Backstories

Jonathan Lenoir

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January 04, 2018
This is the backstory behind the scientific article entitled "Climate-related range shifts – a global multidimensional synthesis and new research directions" published in Ecography \citep*{Lenoir2015}.
How the lignin-first biorefinery strategy unfolded ...
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Sander Van den Bosch

Bert Sels

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January 04, 2018
This article is the backstory behind: S. Van den Bosch, W. Schutyser, B.F. Sels, et al., Reductive lignocellulose fractionation into soluble lignin-derived phenolic monomers and dimers and processable carbohydrate pulps \cite{Bosch2015}. 
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