Phosphorus (P) is one of the essential mineral nutrients for plants. Nevertheless, large amounts of accumulated P easily wither whole plants, and this phenomenon is termed as P toxicity. For improving P-use efficiency, to overcome P toxicity is necessary for plant growth. However, the detailed mechanisms underlying P toxicity in plants have not yet been elucidated. In this study, we aimed to investigate the molecular mechanism of P toxicity in rice. We found that, under excessive inorganic-P (Pi) application conditions, Rubisco activation decreased and photosynthesis was inhibited, leading to lipid-peroxidation. Although the defense systems against reactive oxygen species accumulation were activated under excessive Pi application conditions, the Cu/Zn-type superoxide dismutase activity was inhibited. A metabolic analysis revealed that excess Pi application led to an increase in the cytosolic sugar-phosphate content, and activation of phytic acid synthesis. These conditions induced mRNA expressions of the genes that are activated under metal-deficiency conditions, although metals were rather accumulated. These results suggested that P toxicity is triggered by the attenuation of both photosynthesis, and metal availability within cells mediated by phytic acid accumulation. Here, we discuss the whole phenomenon of P toxicity, beginning from the accumulation of Pi within cells to death in plants.
Experimental studies on the speciation of berkelium in carbonate media have shown that complexation of berkelium(III) by carbonate results in spontaneous oxidation to berkelium(IV) and that multiple species can be present in solution. We studied two proposed structures present in solution based on theoretical comparisons with spectroscopic data previously reported for Bk(IV) carbonate solutions. The multiconfigurational character of the ground and low-lying excited states in both complexes is demonstrated to result from the strong spin-orbit coupling. Although bonding in berkelium(IV) carbonate and carbonate-hydroxide complexes is dominated by strong Coulombic forces, the presence of the non-negligible covalent character is supported by ligand-field theory, natural localized orbitals and topological studies of the electron density. Bond orders based in natural localized molecular orbitals (NLMOs) show that Bk–OH bonds possess enhanced orbital overlap that is reflected in the bond strength.
This paper presents a simplified design method (SDM) to analyze and design the flat plates with irregular column layouts. Theses flat plates having the irregular panels are subdivided into triangular panels. Flexural design formulas for largest triangular slab panel are derived based on the theoretical principles of plate and yield line theories and using the ultimate-strength design method USD under the provisions of ACI building code of design (ACI 318-14). Six different flat slabs with irregular column layouts (FS-1 to FS-6) are selected in this study to be analyzed and designed using the simplified design method approach. Numerical examples for two of the slabs (FS-3 and FS-6) are also presented to illustrate the method capability of designing the flat slabs having irregular column layouts. The selected slab sections (FS-1 to FS-6) are also analyzed and designed using the computer software (SAFE) and the results obtained are compared with the numerical solutions. The percentage difference of simplified design method with the finite element software (SAFE) ranges within 4% to 20% indicates that the SDM is a good and quick approach to design a flat slab having arbitrary/irregular column layout.
The Lazy learning associative classification (LLAC) is one of the associative classification methods, in which it delays the processing of training data until receives a test query, whereas, in eager learning, the system starts processing the training data before receiving queries. In this paper, the Lazy Learning Associative Classification with Weighted kNN (LLAC_WkNN) and Dual Weighted kNN (LLAC_DWkNN) are proposed. Where LLAC is applied on the dataset, that gives a subset of rules. Then weighted kNN (WkNN) algorithm is applied on this generated subset to predict the class label of the unseen test instance. This yields the improved accuracy of the classifier. The WkNN gives more weightage to outlier also. This limitation of WkNN is overcome by applying Dual Distance weighted kNN to LLAC. LLAC_DWkNN checks only k nearest neighbours, not all the large no of subsets for the subset evaluation and also gives less weight, which improves the accuracy of the classifier, further. The comparison results are shown in this paper of proposed algorithms with the existing associative classification methods and traditional methods in terms of classification accuracy.
Applications of transfer function to derivation of a high precision model of tracer flow in a commercial measurement system is presented. A transfer function concept makes easier development of models of complex systems and consequently allows for obtaining a model that matches in the best way a physical system. The method has an additional profit viz. the same numerical algorithm i.e. inverse Laplace transform can be employed to solve the model both on the stage of precise model development (boundary value problem) and to find real model parameters (inverse boundary value problem). As a result of concept application, a very precise model of commercial measurement instrument was developed and, next, it was employed to determination of axial dispersion coefficients for empty tube and packed bed. Presented method is precise in wide range of operating conditions and faster comparing to other methods previously described in literature. The paper shows that mathematical modelling can be exploited to enhance measurements for a commercial measurement instrument i.e unlock the full potential of the commercial measurement system with no equipment design changes. The method is also a fast alternative to computational fluid dynamics for high precision calculations.
Precipitation is an important phenomenon which contributes in the constant supply of water over entire earth. Atmospheric water accounts for less than 0.001% of total water yet it is responsible for the constant supply throughout the globe. It is important to know the distribution of precipitation along with space to know the pattern of precipitation spatially. In order to know this spatial pattern five different geospatial interpolation techniques totaling to 20 different models are applied for 30 years (1988 - 2018) of monthly average precipitation. These models are compared to know which one of these gives the best resemblance of the phenomena. Six performance measures, MAE, MBE, MSE, RMSE, ME and R2 are used to compare the different models. The model for which error is minimum (close to zero) and efficiency is maximum (close to unity) are preferable. After application of various models, it was found that IDW technique with weight parameter of 3 gives the best result with MBE of -0.1397, MAE of 2.9372, MSE of 13.0708, RMSE of 3.6154, ME of 0.7842 and R2 of 0.7744. Other models that performed well were Universal kriging and RBF. After evaluating the best model, error in the estimation of data by that model was also carried out to know the locations where error is intense. It is seen that where the precipitation is intense the errors associated increases. Temporal variation of rainfall is equally important to know have a clearer picture about the pattern of precipitation spatially as well as with seasonally. Therefore, after figuring out the best model, temporal variation of precipitation was also determined showing monthly variation of rainfall. So, after plotting spatial and temporal variation of precipitation it becomes easier for us to determine the precipitation at places which are not gauged.
The field of landscape genetics has been rapidly evolving, adopting and adapting analytical frameworks to address research questions. As landscape genetic analyses have shifted away from Mantel-based analytical frameworks, studies are increasingly using regression-based frameworks to understand the individual contributions of landscape and habitat variables on genetic differentiation. This paper outlines appropriate and inappropriate uses of multiple regression for these purposes. Of concern is the prevalence of studies seeking to explain genetic differences by fitting regression models with effective distance variables calculated independently on separate landscape resistance surfaces. When moving across the landscape, organisms cannot respond independently and uniquely to habitat and landscape features. Therefore, independent resistance surfaces and their effective distance measures have no mechanistic meaning or relevant statistical interpretation. There are also tremendous challenges to fitting and interpreting regression models that include ‘independent’ effective distance measures as predictors, including statistical suppression. As such, regression analyses seeking to understand how landscape resistance affects gene flow should be univariate models, with the creation of a single resistance surface being a necessary precursor to the regression analysis. There are, however, important statistical advances underway that explicitly model the covariance of allele frequencies or genetic distances as functions of spatial landscape variables. The growth and evolution of landscape genetics as a field has been rapid and exciting. It is the goal of this opinion paper to highlight past missteps and to ensure that future use of regression models will appropriately consider the process being modeled, which will provide clarity to model interpretation.
Long-Term Evolution (LTE), which is a standard for wireless communication, has incorporated Discontinuous Reception (DRX), a power-saving strategy having the primary purpose of enhancing energy-saving at the user equipment (UE). Nevertheless, for the networks that have varying channel quality, it is not possible all the time for fixed DRX parameters to obtain the desired improvement. This research introduces a new model based on CQI (Channel Quality Indicator) that will reduce energy consumption by eliminating unnecessary wakeups of UE’s and also achieve reduced latency. As the DRX mechanism saves UE’s energy usually by increasing latency, a tradeoff is necessary between these two performance factors. LTE networks can optimize DRX model parameters for minimizing power consumption based on CQI reporting by UEs and MCS (Modulation and Coding Scheme) assignments by eNodeB as network channel quality is not equal. In this research, an adaptive DRX model is developed, namely CQI DRX, that maintains a balance between power saving and latency. The simulation process is carried out using ns3, a discrete event network simulator. This research shows that energy consumption can be decreased by approximately 13%, and latency can be diminished by around 7% compared with static DRX.
For two processes of large importance, catalysis and biocatalysis, were reported zones without reactants, so called dead zone (DZ). They results from diffusional transport limitations, when apparent reaction order is between (-1..1). Formation of DZ reduces effectiveness of catalyst and influence packed bed reactor productivity. For simple reaction kinetic model, a DZ width inside a pellet can be calculated analytically solving appropriate differential mass balance model. However, generally the analytical solution is unknown and only with using numerical method the position of DZ can be established. The problem with DZ appearance belongs to problems with moving boundaries. Its solution requires application of special numerical procedure and relatively long CPU time. In this work it was proposed a simple, very fast numerical method for calculation of DZ position inside pellet. The method proposed combined with orthogonal collocation on finite elements can be applied for analysis of work of packed bed reactor.
A review of investigations on the effect of drag-reducing agents in curved pipe flows is presented in this work. Proposed mechanisms of drag reduction, as well as factors that influence their effectiveness also received attention. In addition, this review outlined proposed friction factor and fluid flux models for flow of drag-reducing agents in curved pipes. It was shown in this report that significant drag reduction in curved pipes can be achieved using drag-reducing agents. Drag reduction by additives in curved pipes are generally lower than the corresponding drag reduction in straight pipes. It decreases with increase in curvature ratio and is more pronounced in the transition and turbulent flow regimes. Drag reduction depends strongly on the concentration of polymers and surfactants as well as the bubble fraction of micro-bubbles. It is also reported that drag reduction in curved pipes depends on other factors such as temperature and presence of dissolved salts. Maximum drag reduction asymptote differed between straight and curved pipes and between polymer and surfactant. Due to the limited studies in the area of drag reduction for gas-liquid flow in curved pipes no definite conclusion could be drawn on the effect of drag-reducing agents on such flows. A number of questions remain such as the mechanism of drag reduction in curved pipes and how drag-reducing agents interact with secondary flows. Hence, some research gaps have been identified with recommendations for areas of future researches.
Information security is considered both an evolving field and a key concern in the modern mobile society. This research explores the vulnerabilities of public, free Wi-Fi hotspots, how their security can be compromised, and the perceptions of end-users, network administrators/owners and information security experts on cyber-security. Primary data was gathered through interviews with these three groups of stakeholders. An experimental test was also set up in a controlled environment to perform penetration testing. The goal of the experimental test was two-fold: to verify whether it is indeed practically possible to exploit the vulnerabilities of public Wi-Fi networks and to assess the level of difficulty for achieving this. The gathered insights were critically evaluated against the literature towards exploring the state of cyber-security in Cyprus. The findings from the thematic analysis of the interviews reaffirm what the literature suggests with regards to users’ and owners’ lack of awareness and technical skills. Additionally, convenience and cost were cited as major factors explaining why strict security measures are not deployed by small businesses. Coupled with these findings, the experimental test revealed the ease and speed with which public Wi-Fi networks can be compromised.
In this letter, we investigate the rebound dynamics of two equally sized droplets simultaneously impacting a superhydrophobic surface via lattice Boltzmann method (LBM) simulations. We discover three rebound regimes depending on the droplet distance: a complete-coalescence-rebound (CCR) regime, a partial-coalescence-rebound (PCR) regime, and a no-coalescence-rebound (NCR) regime. We demonstrate that the rebound regime is closely associated with dynamic behaviors of the formed liquid ridge or bridge between two droplets. We also present the contact time in the three regimes. Intriguingly, although partial coalescence takes places, the contact time is still dramatically shortened in the PCR regime, which is even smaller than that of a single droplet impact. These findings provide new insights into the contact time of multiple droplets impact, and thereby offering useful guidance for some application such as anti-icing, self-cleaning, and so forth.
Aim: We aim to document the extent to which climate oscillation and rat infestation on islands affect the distribution of seabirds at sea. Location: The Chagos Archipelago, British Indian Ocean Territory, Central Indian Ocean Methods: At sea observations of seabirds (n = 425) were collected from 2012 to 2017 during the breeding season. We used generalized additive models to identify relationships between dominant seabird families (Laridae, Sulidae, and Procellariidae), geomorphology, oceanographic variability, and climate oscillation. We built boosted regression trees to quantify the effects of proximity to both rat-free and rat-infested islands on seabird distribution, identifying breaking point thresholds in distribution. Results: We identified oceanic hotspots and common geomorphic and oceanographic drivers for all seabird families. We documented positive relationships between Sulidae and Procellariidae abundance and the Indian Ocean Dipole, as represented by the Dipole Mode Index. The abundance of Laridae and Sulidae declined abruptly with greater distance to island. Both families aggregated more densely (1.08 and 1.25 times higher respectively) and in greater proximity (distribution thresholds at 16 and 44 km closer to islands, respectively) next to rat-free island compared with to rat-infested islands. In contrast, Procellariidae increased in abundance with greater distance to islands, plateauing at 83 km and were not significantly influenced by rat presence on nearby islands. We identified areas of increased abundance at sea under a scenario where rats are eradicated from infested islands with subsequent seabird recolonization. Main conclusions: Climate oscillations may cause shifts in seabird distribution, possibly through changes in regional productivity and prey distribution. Invasive species eradications and subsequent island recolonization can lead to predictable distribution gains and increased competition. Our analysis predicting range extension after successful eradications enables anticipatory threat-mitigation in these areas, minimising competition between colonies and thereby maximising the risk of success and the conservation impact of eradication programmes.
As essential source for human consumption, plants of wheat, rice and soybean are highly sensitive to ozone (O3), resulting in significant agricultural losses under O3 pollution. However, little is known about the effects of elevated O3 on their metabolite profiling. In this study, three model cultivars were used for the metabolome analysis under elevated O3 and charcoal filtered air. Our study revealed that wheat and rice differed significantly from soybean in metabolic number and certain pathways. Metabolites response to elevated O3 were less in soybean, whilst those in wheat and rice were considerably larger. Under O3 stress, tricarboxylic acid cycle (TCA) was impaired in three crop plants. Methylerythritol 4-phosphate pathway and glycerol phosphate pathway were altered in wheat and rice with reduced terpene accumulation and high level of phospholipids. However, these pathways were not affected in soybean. Meanwhile, O3 suppressed the generation of flavonoid via benzoic acid pathway in three crop plants. Accordingly, the expressional level of genes coding key enzymes which catalyzed the synthesis or degradation of these metabolites. These findings provide valuable information for understanding of ozone’s effects on the metabolite profiling of crop plants, exploring the metabolite differences of three crop plants under elevated O3.
Through the correlation study between the abrasive resistance, compressive strength and pore characteristics indexes of coal-based activated coke (AC) for desulfurization and denitration, the effect of pore structure on mechanical strength of AC was clarified. The results show that the open pore is the main pore type that reduces the compressive strength. The open pore with diameter between 2 and 500 nm have the most serious damage to the compressive strength. The opening and closing state of the pore has no obvious effect on the abrasive resistance. The pores with diameter between 0 and 2 nm have the most serious damage to the abrasive resistance. With the increase of the number of recycling times, the AC pore structure further developed, and the compressive strength and abrasion resistance both decreases correspondingly. After recycled in the flue gas purification facility, AC average compressive strength reduces from 499 N to 340 N, while the abrasion resistance increases from 97.18% to 98.88% because its surface is smoothed during recycling.
Aerospace components and its coatings are required to possess excellent surface properties namely: fatigue, wear and corrosion resistance over a wide temperature range. Stainless steels, titanium, nickel superalloy and more recently high entropy alloys have been used to improve the exterior properties of these components. In this study, AlCoCrFeNiCu and AlTiCrFeCoNi High Entropy Alloys were successfully fabricated using laser additive manufacturing to produce coatings on a mild steel base plate. The influence of the laser parameters (laser power and scan speed) on the microstructure, hardness and coat geometry (height, width and depth) were also investigated. The results revealed that coatings homogeneously adhered to substrate. The optimum processing parameters for both alloys with defect free structures at a preheat temperature of 400 °C, were at 1200-1600 W at 8-12 mm/s with the layers composed of both FCC and BCC phases. The laser parameters affected the geometry, quality and hardness. The results showed that optimizing the laser parameters achieved by preheating temperature invariably improved the performance of the alloys with potential coatings and aerospace structural applications.
In this paper, a novel tree-like antenna is presented, the antenna is composed of tree-like radiating patch and four resonant links on the ground plane, and fed with CPW and microstrip line. The antenna has been fabricated and measured, the simulated and measured radiation patterns and impedance bandwidth have been obtained. The physical dimensions of the proposed antenna is 61.18×29.7×1.52, The measured impedance bandwidth(-10dB) is 106.8%(1.62GHz-5.33GHz), and the peak gain is 4.13dBi. The ultimate goal of this paper is to develop a stable gain, wide impedance bandwidth, low-profile, and low-cost antenna for wireless communication.
Most digesters in industrial-scale operate in deficient level and almost nominal due to inefficient process. Optimization of the process may rectify the issue but required a valid method that does not just improve the process yet able to unravel the eventuality of the intricate process if the adjustment needed. A proper tool is required. The central composite design (CCD) was implemented in this study to investigate the suitability of this tool for optimization of anaerobic digestion (AD) process. The main effect of pH and HRT studied in CCD acquired from the screening process show the importance of having neutral pH value and long retention period for a better biogas yield. The process with pH 7.0 and HRT 15.7 days, IP 33%, TS 4% and FR 4% found to be the optimum setting for the process. The new setting successfully improved the production output up to 60% compared with baseline (existing setting), while allowing 50% more sludge to be processed. The X2 goodness-of-fit test indicates that the mathematical model applied in this study is valid at 95% of confidence level with R2 of 0.9. The results presented in the paper demonstrate the reliability of CCD as optimization tools for AD process in the industrial scale sewage treatment plant (STP).