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The lackluster societal response to the climate crisis is partially attributed to the abstractness of people's mental construals of climate change given its vast spatial and temporal dimensions, which fail to evoke urgency to act. Prior efforts to measure mental construal levels of climate change are inconsistent, insufficient, and labor-intensive. This study developed and implemented learning experiences for integrating engineering design and climate fiction writing to engage 48 high school students in concrete climate change thinking. A novel measure of cognitive abstractness overcomes previous methodological shortcomings by automatically quantifying the linguistic abstractness of participant-authored stories using natural language processing. Comparing participant stories written at the beginning and end of the intervention reveals a significant decrease in linguistic abstractness (Cohen's d = 1.01, p = 0.03). This study contributes to the nascent movement for greater use of narratives as data sources in environmental psychology research, which may uncover new insights into human behavior and decision making. • Created learning experience that reduced the cognitive abstractness of climate change. • Developed improved way to measure the cognitive abstractness of climate change. • Developed improved method for quantifying linguistic abstraction. [ABSTRACT FROM AUTHOR]

In an effort to reduce annotation costs in action recognition, unsupervised video domain adaptation methods have been proposed that aim to adapt a predictive model from a labelled dataset (i.e., source domain) to an unlabelled dataset (i.e., target domain). In this work we address a more realistic scenario, called open-set video domain adaptation (OUVDA), where the target dataset contains "unknown" semantic categories that are not shared with the source. The challenge lies in aligning the shared classes of the two domains while separating the shared classes from the unknown ones. In this work we propose to address OUVDA with an unified contrastive learning framework that learns discriminative and well-clustered features. We also propose a video-oriented temporal contrastive loss that enables our method to better cluster the feature space by exploiting the freely available temporal information in video data. We show that discriminative feature space facilitates better separation of the unknown classes, and thereby allows us to use a simple similarity based score to identify them. We conduct thorough experimental evaluation on multiple OUVDA benchmarks and show the effectiveness of our proposed method against the prior art. • The COLOSEO framework addressing open-set video domain adaptation with a contrastive learning approach. • A video-oriented temporal loss based on applying contrastive learning in order to model temporal consistency. • A thorough evaluation of the proposed framework on two benchmarks for open-set video domain adaptation. • Achievement of competitive or state-of-the-art results on all considered benchmarks. [ABSTRACT FROM AUTHOR]

Nanosized titanium dioxide (nTiO 2) is widely used in products, warranting its discharge from various sources into surface water bodies. However, nTiO 2 co-occurs in surface waters with other contaminants, such as metals. Studies with nTiO 2 and metals have indicated that the presence of natural organic matter (NOM) can mitigate their toxicity to aquatic organisms. In addition, "aging" of nTiO 2 can affect toxicity. However, it is a research challenge, particularly when addressing sublethal responses from dietary exposure over multiple generations. We, therefore exposed the alga Desmodesmus subspicatus to nTiO 2 (at concentrations of 0.0, 0.6 and 3.0 mg nTiO 2 /L) in nutrient medium aged for 0 or 3 days with copper (Cu) at concentrations of 0 and 116 µg Cu/L and with NOM at concentrations equivalent to 0 and 8 mg total organic carbon (TOC) per litre. Subsequently, the exposed alga was fed to Daphnia magna for 23 days over two generations and survival, reproduction and body length were assessed as endpoints of toxicity. In parallel, Cu accumulation and depuration from D. magna were measured. The results indicate that the reproduction of D. magna was the most sensitive parameter in this study, being reduced by 30% (at both parental (F 0) and filial (F 1) generations) and 50% (at F 0 but not F 1) due to the dietary Cu exposure in combination with nTiO 2 for 0 and 3 days aging, respectively. There was no relationship between the effects observed on reproduction and Cu body burden in D. magna. Moreover, D. magna from the F 1 generation showed an adaptive response to Cu in the treatment with 3.0 mg nTiO 2 /L aged for 3 days, potentially due to epigenetic inheritance. Unexpectedly, the presence of NOM hardly changed the observed effects, pointing towards the function of algal exopolymeric substances or intracellular organic matter, rendering the NOM irrelevant. Ultimately, the results indicate that the transferability of the impacts observed during the F 0 to the responses in the F 1 generation is challenging due to opposite effect directions. Additional mechanistic studies are needed to unravel this inconsistency in the responses between generations and to support the development of reliable effect models. • nTiO 2 aging controls dietary Cu effects on D. magna over two generations. • Impairments in reproduction were not explained by Cu body burden. • NOM did not substantially affect response variables. • Effect assessment over more than two generations is recommended. [ABSTRACT FROM AUTHOR]

Agricultural productivity is constantly being forced to maintain yield stability to feed the enormously growing world population. However, shrinking arable and nutrient-deprived soil and abiotic and biotic stressor (s) in different magnitudes put additional challenges to achieving global food security. Though well-defined, the concept of macro, micronutrients, and beneficial elements is from a plant nutritional perspective. Among various micronutrients, selenium (Se) is essential in small amounts for the life cycle of organisms, including crops. Selenium has the potential to improve soil health, leading to the improvement of productivity and crop quality. However, Se possesses an immense encouraging phenomenon when supplied within the threshold limit, also having wide variations. The supplementation of Se has exhibited promising outcomes in lessening biotic and abiotic stress in various crops. Besides, bulk form, nano-Se, and biogenic-Se also revealed some merits and limitations. Literature suggests that the possibilities of biogenic-Se in stress alleviation and fortifying foods are encouraging. In this article, apart from adopting a combination of a conventional extensive review of the literature and bibliometric analysis, the authors have assessed the journey of Se in the " soil to spoon " perspective in a diverse agroecosystem to highlight the research gap area. There is no doubt that the time has come to seriously consider the tag of beneficial elements associated with Se, especially in the drastic global climate change era. • Three types of selenium (Se) (bulk, nano and biogenic) have been considered in the review. • Selenium has exhibited a dual role in crops, based on dose, and species in agroecosystem. • The efficacy of Se in stress mitigation and biofortification has been discussed in the review. • Enrichment of plants with Se as a means of micronutrient can be useful for hidden hunger. • Machine-based Se analysis as a mean of useful tool has been highlighted in the study. [ABSTRACT FROM AUTHOR]

Convolutional neural networks (CNNs) have become deeper and wider over time. However due to low computational power, mobile devices or embedded systems cannot use very deep models. Filter pruning solves this by eliminating redundant filters. Pruning can be performed in a feature dependent or independent manner. Feature dependent methods require extensive time to determine the filter importance as these methods require generation and processing of feature maps for each example. Additionally, in iterative pruning, filter importance is computed several times based on the current state. This increases algorithm execution time further. However, existing feature independent methods are fast, but they perform poor as they compute importance using only current layer filter weights. However, our analysis suggests that both the current and succeeding layer filters are crucial to determine filter importance. We propose 'Filter Pruning by Successive Layers analysis' (FPSL), a novel feature independent algorithm, that considers the effect of pruning a filter on the generation of feature maps for the first time. Moreover, FPSL does not require layer-wise retraining, rigorous hyperparameter search for fine-tuning, or human intervention to set the pruning percentage per layer. These make FPSL extremely fast, efficient, and adaptive. Thus it follows iterative pruning and retraining. FPSL outperforms the state-of-the-art (SOTA) methods on extensive experiments with different datasets (CIFAR, ImageNet) and architectures (VGG, ResNet, MobileNet). It decreases the computational burden of VGG16 by half but improves CIFAR10 and CIFAR100 accuracy. Even for ImageNet, FPSL reduces 42.7% floating point operations (FLOPs) while maintaining top-1 accuracy for ResNet50. • We propose FPSL, a fast and efficient feature independent filter pruning algorithm. • Current and subsequent layer filter weights determine filter importance. • While pruning, contribution of a filter towards feature map generation is considered. • FPSL adaptively prunes different amount of filters from different layers. • Layer wise retraining is not required to recover the performance. [ABSTRACT FROM AUTHOR]

Bacterial cellulose (BC) is a natural polymer produced by the acetic acid producing bacterium and has gathered much interest over the last decade for its biomedical and biotechnological applications. Unlike the plant derived cellulose nanofibres, which require pretreatment to deconstruct the recalcitrant lignocellulosic network, BC are 100% pure, and are extruded by cells as nanofibrils. Moreover, these nanofibrils can be converted to macrofibers that possess excellent material properties, surpassing even the strength of steel, and can be used as substitutes for fossil fuel derived synthetic fibers. The focus of the review is to present the fundamental long-term research on the influence of environmental factors on the organism's BC production capabilities, the production methods that are available for scaling up/scaled-up processes, and its use as a bulk commodity or for biomedical applications. [ABSTRACT FROM AUTHOR]

Triclosan (TCS) is a biocide commonly used in household and personal care items to prevent the microbial growth and is currently considered as an emerging pollutant. It has a ubiquitous distribution which can substantially contribute towards antimicrobial resistance. The present study was designed to evaluate the effect of different concentrations of TCS exposure on the antibiotic sensitivity of aquatic bacteria. Aeromonas hydrophila ATCC® 49140™ and Edwardsiella tarda ATCC® 15947™ exposed to TCS for short (30 min) and long duration (serial passages). The agar-disc diffusion assay during the serial passages of TCS exposure and subsequent exposure withdrawal showed clinically insignificant changes in the zone of inhibition for six selected antibiotics in both bacterial strains at all exposure concentrations. Four folds concentration-dependent increase in the minimum inhibitory concentrations (MICs) of TCS was observed in both the strains following TCS exposure. Similarly, a concentration-dependent increase in the MICs of oxytetracycline (OTC) up to 4 folds in A. hydrophila , and up to 8 folds in E. tarda , was also documented during the TCS exposure. In all the cases, withdrawal of TCS exposure effectively reduced the MICs of TCS and OTC in blank passages suggesting a decline in acquired resistance. The frequencies of mutation during 30 min TCS exposure for E. tarda and A. hydrophila ranged between >10−6 and 10−7 levels. Nevertheless, the TCS exposure did not cause any detectable mutation on the fabV gene of A. hydrophila indicating that the TCS may elicit phenotypic adaptation or other resistance mechanism. Although the reduction in MICs due to exposure withdrawal did not restore the bacterial susceptibility up to the initial level, the study proved that the reduced TCS use could significantly help reduce the antimicrobial-resistance and cross-resistance in pathogenic bacteria. Image 1 • Triclosan mediated antimicrobial resistance was concentration dependent. • Triclosan induced resistance conferred cross-resistance to oxytetracycline. • Withdrawal of triclosan exposure reduced the acquired antimicrobial resistance. • Triclosan exposure dose did not induce mutation in fabV genes of A. hydrophila. [ABSTRACT FROM AUTHOR]

Rhizospheric and plant root associated microbes generally play a protective role against arsenic toxicity in rhizosphere. Rhizospheric microbial interaction influences arsenic (As) detoxification/mobilization into crop plants and its level of toxicity and burden. In the present investigation, we have reported a rhizospheric fungi Aspergillus flavus from an As contaminated rice field, which has capability to grow at high As concentration and convert soluble As into As particles. These As particles showed a reduced toxicity to soil dwelling bacteria, fungi, plant and slime mold. It does not disrupt membrane potential, inner/outer membrane integrity and survival of the free N 2 fixating bacteria. In arbuscular mycorrhiza like endophytic fungi Piriformospora indica , these As particles does not influence mycelial growth and plant beneficial parameters such as phosphate solubilizing enzyme rAPase secretion and plant root colonization. Similarly, it does not affect plant growth and chlorophyll content negatively in rice plant. However, these As particles showed a poor absorption and mobilization in plant. These As particle also does not affect attachment process and survival of amoeboid cells in slime mold, Dictyostelium discoideum. This study suggests that the process of conversion of physical and chemical properties of arsenic during transformation, decides the toxicity of arsenic particles in the rhizospheric environment. This phenomenon is of environmental significance, not only in reducing arsenic toxicity but also in the survival of healthy living organism in arsenic-contaminated rhizospheric environment. Image 1 • A rhizospheric fungus from rice has ability to bio-transform soluble arsenic into immobilized arsenic particle. • These arsenic particles are non-toxic for bacteria and fungi and does not influence their growth negatively. • Arsenic particles have reduced mobilization to plant and does not negatively impact beneficial plant-microbe interaction. • These particles does not influence adversely on the growth and attachment process of soil residing amoeba (slime mold). • Bio-transformed arsenic particles are more compatible to rhizospheric environment than soluble arsenic. [ABSTRACT FROM AUTHOR]

Abstract In the present work, quantitative structure-activity relationship (QSAR) models have been developed for ecotoxicity of pharmaceuticals on four different aquatic species namely Pseudokirchneriella subcapitata , Daphnia magna , Oncorhynchus mykiss and Pimephales promelas using genetic algorithm (GA) for feature selection followed by Partial Least Squares regression technique according to the Organization for Economic Co-operation and Development (OECD) guidelines. Double cross-validation methodology was employed for selecting suitable models. Only 2D descriptors were used for capturing chemical information and model building, whereas validation of the models was performed by considering various stringent internal and external validation metrics. Interestingly, models could be developed even without using any LogP terms in contrary to the usual dependence of toxicity on lipophilicity. However, the current manuscript proposes highly robust and more predictive models employing computed logP descriptors. The applicability domain study was performed in order to set a predefined chemical zone of applicability for the obtained QSAR models, and the test compounds falling outside the domain were not taken for further analysis while making a prioritized list. An additional comparison was made with ECOSAR, an online expert system for toxicity prediction of organic pollutants, in order to prove predictability of the obtained models. The obtained robust consensus models were utilized to predict the toxicity of a large dataset of approximately 9300 drug-like molecules in order to prioritize the existing drug-like substances in accordance to their acute predicted aquatic toxicities following a scaling technique. Finally, prioritized lists of 500 most toxic chemicals obtained by respective consensus models and those predicted from ECOSAR tool have been reported. Highlights • This work proposes robust QSAR models for aquatic toxicity of pharmaceuticals. • Consensus modeling improves predictive performance of models. • Comparison of predictive performance is made with the ECOSAR tool. • Ranking and prioritization of pharmaceuticals from DrugBank database are performed. [ABSTRACT FROM AUTHOR]

Abstract The contaminants of emerging concern (CEC) are universally detected in surface water and soil. They can affect the wild life, and their subsequent translocation through the food chain can affect human health, which is an issue of serious concern. Very few amounts of ecotoxicological data are available on the environmental behavior and ecotoxicity of CEC, thus modeling approaches are essential to bridge the existing gap in experimental data. In this present study, we have developed quantitative structure-toxicity relationship (QSTR) models using a data set of 75 compounds for the prediction of aquatic ecotoxicity of CECs on fresh water planarian (Dugesia japonica) by partial least squares (PLS) regression algorithm using simple molecular descriptors selected by genetic algorithm approach. We also explore the correlations between toxicity against D. japonica and those against daphnia (D. magna) and fish (P. promelas), and these were improved on addition of a few molecular descriptors (B08[C-O] and B09[N-O] in case of daphnia and C-006 and H-052 in case of fish) which allowed us to develop predictive interspecies quantitative structure toxicity-toxicity relationship (QSTTR) models, allowing to extrapolate data from one endpoint to another endpoint. The QSTR (Q2 LOO ranging from 0.630 to 0.720 and R2 pred ranging from 0.723 to 0.798) and QSTTR (Q2 LOO = 0.60 and 0.67, R2 pred = 0.88 and 0.84) models have desirable statistical qualities and acceptable internal and external validation measures, meeting rigorous criteria of different validation metrics and showing acceptability for regulatory purposes as proposed by Organization for Economic Cooperation and Development (OECD). Consensus predictions were also performed based on multiple models generated in this study by using the "Intelligent Consensus Predictor" (ICP) tool to enhance the prediction quality for external set compounds. Graphical abstract fx1 Highlights • New QSTR models are developed using computed 2D descriptors for the toxicity of CECs to D. japonica. • We quantitatively show that hydrophobicity and aromaticity increase the aquatic toxicity of CECs. • "Intelligent Consensus Predictor" was used to enhance the prediction quality for external set compounds. • An interspecies model for toxicity between P. promelas and D. japonica was established for the first time. [ABSTRACT FROM AUTHOR]

Abstract Background Variations in the management of pediatric patients at children's hospitals (CHs) and non-CHs (NCHs) have been well described, especially within the trauma literature. However, little is known about the outcomes and costs of common general surgical procedures at NCHs. The purpose of this study was to evaluate the effect of CH designation on the outcomes and costs of appendectomy and cholecystectomy. Methods The Kids' Inpatient Database (2003-2012) was queried for patients aged under 18 y who underwent appendectomy or cholecystectomy at CHs and NCHs. Outcomes analyzed included disease severity, complications, laparoscopy, length of stay (LOS), and cost. Results Most of appendectomies and cholecystectomies were performed at NCHs. Overall, CHs cared for younger children were more likely to be teaching hospitals, had higher costs, and longer LOS. On multivariate analysis for appendectomies, CHs were associated with higher rates of perforated appendicitis (OR = 1.53, 95% CI = 1.42-1.66, P < 0.001), less complications (OR = 0.68, 95% CI = 0.61-0.75, P < 0.001), increased laparoscopy (OR = 2.93, 95% CI = 2.36-3.64, P < 0.001), longer LOS (RR = 1.13, 95% CI = 1.09-1.17, P < 0.001), and higher costs (exponentiated log $ = 1.19, 95% CI = 1.13-1.24, P < 0.001). Multivariate analysis for cholecystectomies revealed that CHs were associated with less laparoscopy (OR = 0.58, 95% CI = 0.50-0.67, P < 0.001), longer LOS (RR = 1.26, 95% CI = 1.19-1.34, P < 0.001), and higher costs (exponentiated log $ = 1.29, 95% CI = 1.22-1.37, P < 0.001) with similar complications. Independent predictors of LOS and cost included CH designation, negative appendectomy, perforated appendicitis, complications, younger age, black patients, and public insurance. Conclusions Variations in surgical management, outcomes, and costs after appendectomy and cholecystectomy exist between CHs and NCHs. CHs excelled in treating complicated appendicitis. NCHs effectively performed cholecystectomies. These differences in outcomes require further investigation to identify modifiable factors to optimize care across all hospitals for these common surgical diseases. [ABSTRACT FROM AUTHOR]

The production of ethanol by yeast fermentation represents the largest of all global biotechnologies. Consequently, the yeast Saccharomyces cerevisiae is the world's premier industrial microorganism, which is responsible not only for the production of alcoholic beverages, including beer, wine, and distilled spirits, but also for the billions of liters of bioethanol produced annually for use as a renewable transportation fuel. Although humankind has exploited the fermentative activities of yeasts for millennia, many aspects of alcohol fermentation remain poorly understood. This chapter will review some of the key considerations in optimizing industrial alcohol fermentations with a particular emphasis on enhancement opportunities involving cell physiology and strain engineering of the major microbial ethanologen, the yeast S. cerevisiae. [ABSTRACT FROM AUTHOR]

Bacteriophages are more abundant than any other organism on our planet. The interaction of bacteriophages and bacteria and their coevolution is well known. In this chapter, we describe various aspects of modeling such systems and their dynamics. We explore their interaction in: (i) liquid media, which leads to well-mixed populations and (ii) solid media, where their interaction is spatially restricted. Such modeling, when used in conjunction with experiments would not only shed deep insight into the underlying dynamics but also provide useful clues toward potential therapeutic applications. [ABSTRACT FROM AUTHOR]

Background The study of regional variations in surgical outcomes and cost has been used to identify areas for improvement and savings. This study investigates potential regional differences in the outcomes and cost of adult appendicitis. We hypothesized that there would be no difference in rates of laparoscopy, perforation, morbidity, length of stay (LOS), and cost among different regions of the United States. Materials and methods Data were obtained from the California (CA), New York (NY), and Florida (FL) State Inpatient Databases from 2005-2011. Patients between the ages of 18-69 who underwent nonincidental appendectomy in the three different states were evaluated with hierarchical and multivariate negative binomial regression analyses. Primary outcomes included laparoscopy, perforation, negative appendectomy, morbidity, LOS, and cost. Results There were 371,354 appendectomies performed. Multivariate analysis revealed multiple regional differences. Patients in FL were most likely to get laparoscopy ( P < 0.01). CA had higher rates of perforation than NY ( P < 0.01) and FL ( P < 0.05). CA also had higher rates of negative appendectomy compared to both NY and FL ( P < 0.01). Morbidity was lower in NY compared to CA and FL ( P < 0.01). The LOS was shortest in CA ( P < 0.01), despite CA having the highest median per patient cost ( P < 0.01). Conclusions Significant regional variations do exist with CA having the highest rate of perforation and negative appendectomy. Patients in CA also incurred the highest overall costs. A better understanding of the factors that drive these variations will help improve outcomes and lower cost across all states. [ABSTRACT FROM AUTHOR]

In the current scenario of global warming and climate change, plants face many biotic stresses, which restrain growth, development and productivity. Nanotechnology is gaining precedence over other means to deal with biotic and abiotic constraints for sustainable agriculture. One of nature's most beneficial metalloids, silicon (Si) shows ameliorative effect against environmental challenges. Silicon/Silica nanoparticles (Si/SiO 2 NPs) have gained special attention due to their significant chemical and optoelectronic capabilities. Its mesoporous nature, easy availability and least biological toxicity has made it very attractive to researchers. Si/SiO 2 NPs can be synthesised by chemical, physical and biological methods and supplied to plants by foliar, soil, or seed priming. Upon uptake and translocation, Si/SiO 2 NPs reach their destined cells and cause optimum growth, development and tolerance against environmental stresses as well as pest attack and pathogen infection. Using Si/SiO 2 NPs as a supplement can be an eco-friendly and cost-effective option for sustainable agriculture as they facilitate the delivery of nutrients, assist plants to mitigate biotic stress and enhances plant resistance. This review aims to present an overview of the methods of formulation of Si/SiO 2 NPs, their application, uptake, translocation and emphasize the role of Si/SiO 2 NPs in boosting growth and development of plants as well as their conventional advantage as fertilizers with special consideration on their mitigating effects towards biotic stress. • SiNPs are mesoporous, easily available and show least biological toxicity. • SiNPs can be easily synthesised and made available to plants. • Application of SiNPs promote growth, development and tolerance against biotic stress. • Use of SiNPs against pest and pathogens, is an eco-friendly and cost-effective option. [ABSTRACT FROM AUTHOR]

The distribution of antibiotic resistance genes (ARGs) in water sources potentially threatens drinking water safety. However, the sources of antibiotic resistome in groundwater are still under-investigated. Here, we evaluated the profiles of antibiotic resistome in peri-urban groundwater and its associated water sources (river and mountain spring) to characterize the antibiotic resistome from natural water sources on groundwater resistome. A total of 261 antibiotic resistome were detected in groundwater, mountain spring, and river samples. The relative abundances of ARGs and mobile genetic elements (MGEs) were significantly higher in the river samples than in spring water and groundwater samples. The resistome profiles were similar between groundwater and spring water but differed from the river samples. According to source tracking results, the groundwater resistome was likely to be derived from springs (28.0%−50.0%) and rivers (28.6%−48.6%), which share the same trend for the source tracking of bacterial communities. Bacterial α-diversity, bacterial β-diversity, and MGEs directly or indirectly affected the ARGs in groundwater samples. Although the abundance of groundwater resistome was not elevated by river and spring water, groundwater resistomes were diverse and may be derived from both river and spring water. We highlight the importance of groundwater resistome and its association with potential water sources, providing a better understanding and basis for the effective control of the ARG proliferation and dissemination in groundwater from exogenous water bodies in the future. [Display omitted] • River samples have the highest relative abundance of antibiotic resistome. • Groundwater ARGs may be driven by mountain springs and rivers. • Microbial movement leads to the spread of antibiotic resistome in hyporheic zone. [ABSTRACT FROM AUTHOR]

A large amount of lignocellulosic waste is generated every day in the world, and their accumulation in the agroecosystems, integration in soil compositions, or incineration for energy production has severe environmental pollution effects. Using enzymes as biocatalysts for the biodegradation of lignocellulosic materials, especially in harsh processing conditions, is a practical step towards green energy and environmental biosafety. Hence, the current study focuses on enzyme computationally screened from camel rumen metagenomics data as specialized microbiota that have the capacity to degrade lignocellulosic-rich and recalcitrant materials. The novel hyperthermostable xylanase named PersiXyn10 with the performance at extreme conditions was proper activity within a broad temperature (30–100 ℃) and pH range (4.0–11.0) but showed the maximum xylanolytic activity in severe alkaline and temperature conditions, pH 8.0 and temperature 90 ℃. Also, the enzyme had highly resistant to metals, surfactants, and organic solvents in optimal conditions. The introduced xylanase had unique properties in terms of thermal stability by maintaining over 82% of its activity after 15 days of incubation at 90 ℃. Considering the crucial role of hyperthermostable xylanases in the paper industry, the PersiXyn10 was subjected to biodegradation of paper pulp. The proper performance of hyperthermostable PersiXyn10 on the paper pulp was confirmed by structural analysis (SEM and FTIR) and produced 31.64 g/L of reducing sugar after 144 h hydrolysis. These results proved the applicability of the hyperthermostable xylanase in biobleaching and saccharification of lignocellulosic biomass for declining the environmental hazards. [Display omitted] • Novel xylanase was mined from the metagenomic data by the in-silico screening. • PersiXyn10 showed remarkable tolerance at a wide range of temperatures and pH. • Strong thermostable properties were found for PersiXyn10 by biophysical experiments. • The hyperthermostable xylanase was effectively used for biobleaching of pulp paper. [ABSTRACT FROM AUTHOR]

In 2020, COVID-19 mitigation measures, including lockdowns and travel bans to curtail disease transmission, inadvertently led to an "Anthropause" – a unique global pause to anthropogenic activities. While there was a spike in ecological studies measuring Anthropause effects on environmental indicators, people's experiences of the Anthropause or its potential to inspire change were hardly considered. Hence, we aimed to measure people's appreciation of the environmental outcomes of the Anthropause, ecophilosophical contemplations about the pandemic, and experiences of lockdown-triggered biophilia (human's innate love for and draw towards nature) and test the hypothesis that these experiences would be consistently more prominent among the already environmentally inclined. To that end, we developed and tested three measures on a representative sample of 993 New Zealanders. Anthropause Appreciation received the highest overall mean ratings, followed by Lockdown-Biophilia and Eco-Contemplation. Pre-existing pro-environmental dispositions and behaviours did not consistently influence our three measures as expected. Demographic variables had little influence, while experiences of financial and mental health impacts due to COVID-19 had no influence. We interpreted the limited influence of explanatory variables as indicative of a degree of uniformity in people's experiences. High appreciation of Anthropause benefits suggests that the public may be supportive of policies and ways of living that can lead to similar outcomes post-pandemic – offering environmental policymakers and communicators a basis for action. Ecophilosophical contemplations and biophilic draw among the public suggest an awareness of the significance of the human-nature relationship – offering a symbolic global keystone for communicating and advocating conservation and the many values of pauses in life to connect with nature. Building women's environmental leadership capabilities and the ongoing greening of Christianity may be essential steps for global post-pandemic environmental behaviour transformations. • We measured COVID-19-related environmental experiences in a representative sample. • The ecological benefits of the Anthropause were highly valued by society. • There was moderate eco-contemplation and biophilia during the COVID-19 lockdown. • Environmental predisposition and demographics had limited influence. • These unique COVID-19-related environmental experiences offer a basis for change. [ABSTRACT FROM AUTHOR]

Mesh Deformation is an important element of any fluid–structure interaction simulation. In this article, a new methodology is presented for the deformation of volume meshes using incremental radial basis function (RBF) based interpolation. A greedy algorithm is used to select a small subset of the surface nodes iteratively. Two incremental approaches are introduced to solve the RBF system of equations: 1) block matrix inversion based approach and 2) modified LU decomposition approach. The use of incremental approach decreased the computational complexity of solving the system of equations within each greedy algorithm's iteration from O ( n 3 ) to O ( n 2 ) . Results are presented from an accuracy study using specified deformations on a 2D surface. Mesh deformations for bending and twisting of a 3D rectangular supercritical wing have been demonstrated. Outcomes showed the incremental approaches reduce the CPU time up to 67% as compared to a traditional RBF matrix solver. Finally, the proposed mesh deformation approach was integrated within a fluid–structure interaction solver for investigating a flow induced cantilever beam vibration. [ABSTRACT FROM AUTHOR]

Despite a plethora of literature on organizational climate for innovation and the persuasive arguments establishing its link to organizational performance, few studies hitherto have explored innovative work behavior of managers. Specifically, limited attention has been paid to explaining how organizations perceive the importance of stimulating innovative work environments. Drawing from organizational climate theory, this study investigates the mediating effects of innovative work behavior on the relationship between organizational climate for innovation and organizational performance. Our findings from a survey of 202 managers working in Malaysian companies demonstrate that innovative work behavior plays a mediating role in the relationship between organizational climate for innovation and organizational performance. Implications of these findings and avenues for future research are discussed. [ABSTRACT FROM AUTHOR]

We describe a project intended to improve the use of Electronic Medical Record (EMR) patient portal information by older adults with diverse numeracy and literacy abilities, so that portals can better support patient-centered care. Patient portals are intended to bridge patients and providers by ensuring patients have continuous access to their health information and services. However, they are underutilized, especially by older adults with low health literacy, because they often function more as information repositories than as tools to engage patients. We outline an interdisciplinary approach to designing and evaluating portal-based messages that convey clinical test results so as to support patient-centered care. We first describe a theory-based framework for designing effective messages for patients. This involves analyzing shortcomings of the standard portal message format (presenting numerical test results with little context to guide comprehension) and developing verbally, graphically, video- and computer agent-based formats that enhance context. The framework encompasses theories from cognitive and behavioral science (health literacy, fuzzy trace memory, behavior change) as well as computational/engineering approaches (e.g., image and speech processing models). We then describe an approach to evaluating whether the formats improve comprehension of and responses to the messages about test results, focusing on our methods. The approach combines quantitative (e.g., response accuracy, Likert scale responses) and qualitative (interview) measures, as well as experimental and individual difference methods in order to investigate which formats are more effective, and whether some formats benefit some types of patients more than others. We also report the results of two pilot studies conducted as part of developing the message formats. [ABSTRACT FROM AUTHOR]

The problem of image-base person identification/recognition is to provide an identity to the image of an individual based on learned models that describe his/her appearance. Most traditional person identification systems rely on learning a static model on tediously labeled training data. Though labeling manually is an indispensable part of a supervised framework, for a large scale identification system labeling huge amount of data is a significant overhead. For large multi-sensor data as typically encountered in camera networks, labeling a lot of samples does not always mean more information, as redundant images are labeled several times. In this work, we propose a convex optimization based iterative framework that progressively and judiciously chooses a sparse but informative set of samples for labeling, with minimal overlap with previously labeled images. We also use a structure preserving sparse reconstruction based classifier to reduce the training burden typically seen in discriminative classifiers. The two stage approach leads to a novel framework for online update of the classifiers involving only the incorporation of new labeled data rather than any expensive training phase. We demonstrate the effectiveness of our approach on multi-camera person re-identification datasets, to demonstrate the feasibility of learning online classification models in multi-camera big data applications. Using three benchmark datasets, we validate our approach and demonstrate that our framework achieves superior performance with significantly less amount of manual labeling. [ABSTRACT FROM AUTHOR]

We study anisotropic oscillator in the presence of a homogeneous magnetic field and other related systems in the noncommutative plane. Energy values as function of the noncommutative parameter θ and the magnetic field B have been obtained. Some features of the spectrum, for example, formation of energy bands etc. have been examined. The effect of anisotropy on the energy levels has also been discussed. [ABSTRACT FROM AUTHOR]

Semi Global Boundary Detection (SGBD) breaks the image into scan lines in multiple orientations, segments each one independently, and combines the results into a final probabilistic 2D boundary map. The reason we break the image into scan lines is that they are a mid-level image representation that captures more information than a local patch. Luckily, scan lines are 1D signals that can be optimally segmented using dynamic programming, and we make the assumption that the border pixels between segments are boundary pixels in the image. This leads to a simple and efficient algorithm for boundary detection. The entire algorithm requires little parameter tuning, works well across different data sets and modalities, and produces sharp boundaries. We report results on several benchmarks that include both color and depth. [ABSTRACT FROM AUTHOR]

In this study, differing metrics were utilized to measure effects of erythromycin (ER), trimethoprim (TR) and clindamycin (CL) on the structure and function of attached Wascana Creek, SK microbial communities. All three test antibiotics, especially ER, affected community structure and function of biofilms grown in rotating annular reactors. Biofilm thickness, bacterial biomass, and lectin binding biovolume (exopolymeric substances) were consistently less in ER treated biofilms when compared to the control. As well negative effects on protozoan numbers, and carbon utilization were detected. Finally, PCA analyses of DGGE results indicated that bacterial community diversity in ER exposed biofilms was always different from the control. ER exhibited toxic effects even at lower concentrations. Observations on TR and CL exposed biofilms indicated that bacterial biomass, lectin binding biovolume and carbon utilization were negatively affected as well. In terms of bacterial community diversity, however, CL exposed biofilms tended to group with the control while TR grouped with nutrient additions suggesting both nutritive and toxic effects. This study results represent an important step in understanding antibiotic effects, especially ER, on aquatic microbial communities. And because ER is so ubiquitous in receiving water bodies worldwide, the Wascana study results suggest the possibility of ecosystem disturbance elsewhere. Capsule abstract Erythromycin (ER) is ubiquitous in waterbodies receiving sewage effluent. Structure and function of microbial communities from an effluent dominated stream were negatively affected by ER, at realistic concentrations. [ABSTRACT FROM AUTHOR]

The depth and width of CNNs have increased over the years so as to learn a better representation of the input–output mapping of a dataset. However, a significant amount of redundancy exists among different convolutional kernels. Several methods on pruning suggest that trimming redundant parameters can produce compact structures with minor degradation in classification performance. Existing pruning methods reduce the number of filters at a uniform rate (i.e. pruning same percentage of filters from each layer) in every convolutional layer, which is suboptimal. In this paper, we conduct experiments to observe the sensitivity of each and every filter towards the final performance of the neural network. The essence of comparing filter importance on a global scale and subsequently pruning the neural network adaptively, is highlighted for the first time in this paper. Based on our observations, we propose a novel method named 'Global Filter Importance based Adaptive Pruning (GFI-AP)' that assigns importance scores to all filters based on how the network learns the input–output mapping of a dataset, which can then be compared across all the other convolutional filters. Our results show that non-uniform pruning achieves better compression as compared to uniform pruning. We demonstrate that GFI-AP significantly decreases the number of FLOPs (floating point operations) of VGG and ResNet networks in ImageNet and CIFAR datasets, without substantial drop in classification accuracy. GFI-AP reduces more number of FLOPs compared to existing pruning methods, for example, the ResNet50 variant of GFI-AP provides an additional 11% reduction in FLOPs over Taylor-FO-BN-72% while achieving higher accuracy. • A novel adaptive pruning method for CNN to produce compact architecture. • Determining filter importance using class-specific feature map activation. • Filter importances are globally comparable across the convolutional layers. • Trimming insignificant filters in a non-uniform manner from each convolutional layer. [ABSTRACT FROM AUTHOR]

Computer vision systems in outdoor environments are strongly affected by different atmospheric/weather conditions. Therefore, understanding the actual behavior of outdoor scenes is necessary for effective removal and improvement of the overall performance of computer vision systems. Although the classification of atmospheric/weather conditions has been well explored, reporting on the same in multiclass problem using Convolutional Neural Networks (CNNs) has received very little attention. In response to address this disparity, we propose a new CNN architecture named the "Adversarial Weather Degraded Multi-class scenes Classification Network (AWDMC-Net)" for outdoor scene classification degraded by different atmospheric/weather conditions. The proposed network is based on adopting different combinations of skip connections in building blocks of CNN there after adaptively pruning the least important convolutional kernels from the network. For effective pruning, we proposed a new pruning criterion named "Entropy Guided Mean- l 1 Norm" that can adaptively evaluate the importance of convolutional kernels by considering the filters and their corresponding output feature maps. The prediction performance of our proposed model was evaluated on our newly designed E-TUVD (Extended Tripura University Video Dataset) and on publicly available benchmark datasets. Our newly created video dataset, E-TUVD, consists of 147 video clips (approximately 793800 frames) that represent six atmospheric/weather conditions, namely, fog, dust, rain, haze, poor illumination, and clear day conditions. Our proposed model achieves an accuracy of 93.85%, a specificity of 93.79%, and a sensitivity of 94.18% on our dataset, which outperforms the prevailing standard CNN models and recent state-of-the-art methods for atmospheric/weather classification tasks. Furthermore, our network also reduces the time consumption for atmospheric/weather classification tasks, and therefore mostly meets the requirements of practical applications in real-world scenarios. • We proposed a network "AWDMC-Net" for atmospheric/weather classification tasks. • We proposed "Entropy Guided Mean- l 1 Norm" pruning criteria for filter pruning. • We conduct experiments on available benchmarks and our own created E-TUVD dataset. • Our AWDMC-Net is accurate and efficient as compared to the existing methods. • Our AWDMC-Net also reduces the time for atmospheric/weather classification tasks. [ABSTRACT FROM AUTHOR]

Salinity is one of the most common factors affecting alfalfa (Medicago sativa L.), and NaCl is one of the main factors of salinity stress which can cause heavy losses in agricultural production in the world. The application of exogenous melatonin (MT) plays a major role in numerous plants against various stress environments. The effects of exogenous MT on the NaCl tolerance of alfalfa treated with the control, 100 µmol L−1 MT, 150 mmol L−1 NaCl, or 150 mmol L−1 NaCl+ 100 µmol L−1 MT were investigated. The results showed that MT increased growth parameters, inhibited chlorophyll degradation and promoted photosynthetic gas exchange parameters (photosynthetic rate, conductance to H 2 O, and transpiration rate) and stomatal opening under NaCl stress. Osmotic regulation substances such as soluble sugar, proline and glycine betaine were the highest in the NaCl treatment and the second in the NaCl+MT treatment. Nitrogen, phosphorus, potassium, calcium and magnesium were reduced and sodium was increased by NaCl, whereas these levels were reversed by the NaCl+MT treatment. MT inhibited cell membrane imperfection, lipid peroxidation and reactive oxygen species (ROS) accumulation caused by NaCl stress. MT up-regulated the gene expression and activity of antioxidant enzymes and increased the content of antioxidant non-enzyme substances to scavenge excessive ROS in NaCl-treated plants. In addition, all indicators interacted with each other to a certain extent and could be grouped according to the relative values. All variables were divided into PC 1 (89.2 %) and PC 2 (4 %). They were clustered into two categories with opposite effects, and most of them were significant variables. Hence, these findings reveal that exogenous MT alleviates the inhibitory effects of NaCl stress on photosynthesis, stomata opening, osmotic adjustment, ion balance and redox homeostasis, enhancing tolerance and growth of alfalfa. Furthermore, it suggests that MT could be implemented to improve the NaCl tolerance of alfalfa. [Display omitted] • Exogenous MT improves photosynthetic capacity of alfalfa under salt stress. • Exogenous MT modulates osmotic stress caused by salt stress. • MT maintains ion homeostasis and promotes mineral nutrition in salt-treated alfalfa. • MT reduces ROS and lipid peroxidation by regulating gene and antioxidant system. • MT improves the salt tolerance of alfalfa by co-regulating multiple pathways. [ABSTRACT FROM AUTHOR]

Marine environment is the most abundant source of chitin. Several marine organisms possess chitin in their structural components. Hence, a huge amount of chitin wastes is deposited in marine environment when such organisms shed their outer skeleton and also after their demise. Waste chitins are potential nutrient source of certain microbes. These microbes produce chitinases that hydrolyze waste chitins. These organisms thus play an important role to remove the chitin wastes from marine environment. In connection with this, chitinases are found to be most important biocatalyst for the utilization of chitin wastes. Therefore, use of chitin for chitinase production is one of the useful tools for different types of bioprocesses. [ABSTRACT FROM AUTHOR]

Synthesis of novel nanoparticles should always be accompanied by a comprehensive assessment of risk to human health and to ecosystem. Application of in silico models is encouraged by regulatory authorities to fill the data gaps related to the properties of nanoparticles affecting the environment and human health. Interspecies toxicity correlations provide a tool for estimation of contaminant's sensitivity with known levels of uncertainty for a diverse pool of species. We propose here first interspecies cytotoxicity correlation models between Escherichia coli (prokaryotic system) and human keratinocyte cell line (HaCaT) (eukaryotic system) to assess the discriminatory features for cytotoxicity of metal oxide nanoparticles. The nano-QTTR models can be employed for extrapolating cytotoxicity to E. coli and human keratinocyte cell line (HaCaT) for metal nanoparticles when the data for the other species are available. Informative illustrations of the contributing mechanisms of toxic action of the metal oxide nanoparticles to the HaCaT cell line as well as to the E. coli are identified from the developed nano quantitative toxicity–toxicity relationship (nano-QTTR) models. [ABSTRACT FROM AUTHOR]

Learning human activity models from streaming videos should be a continuous process as new activities arrive over time. However, recent approaches for human activity recognition are usually batch methods, which assume that all the training instances are labeled and present in advance. Among such methods, the exploitation of the inter-relationship between the various objects in the scene (termed as context) has proved extremely promising. Many state-of-the-art approaches learn human activity models continuously but do not exploit the contextual information. In this paper, we propose a novel framework that continuously learns both of the appearance and the context models of complex human activities from streaming videos. We automatically construct a conditional random field (CRF) graphical model to encode the mutual contextual information among the activities and the related object attributes. In order to reduce the amount of manual labeling of the incoming instances, we exploit active learning to select the most informative training instances with respect to both of the appearance and the context models to incrementally update these models. Rigorous experiments on four challenging datasets demonstrate that our framework outperforms state-of-the-art approaches with significantly less amount of manually labeled data. [ABSTRACT FROM AUTHOR]

This study tested the habit discontinuity hypothesis, which states that behaviour change interventions are more effective when delivered in the context of life course changes. The assumption was that when habits are (temporarily) disturbed, people are more sensitive to new information and adopt a mind-set that is conducive to behaviour change. A field experiment was conducted among 800 participants, who received either an intervention promoting sustainable behaviours, or were in a no-intervention control condition. In both conditions half of the households had recently relocated, and were matched with households that had not relocated. Self-reported frequencies of twenty-five environment-related behaviours were assessed at baseline and eight weeks later. While controlling for past behaviour, habit strength, intentions, perceived control, biospheric values, personal norms, and personal involvement, the intervention was more effective among recently relocated participants. The results suggested that the duration of the ‘window of opportunity’ was three months after relocation. [ABSTRACT FROM AUTHOR]

Ground water is the principal source of drinking water in Assam. Ground water contamination of arsenic in drinking water is a great concern for human health and considered as a human carcinogen. The present cytogenetic biomonitoring study was undertaken to investigate the genotoxic effects associated with people of southern Assam consuming arsenic contaminated water and chewing tobacco. Employing the buccal cytome assay, exfoliated cells were analyzed in 138 individuals of age range 22–42 years and divided into four groups. Group I ( n =54) are participants residing in localities where ground water contains arsenic concentration below the permissible limit (<10 μg/l) and without any tobacco chewing history. Group II ( n =32) participants from the same area but they are tobacco chewers. Group III ( n =24) participants from localities where significantly high arsenic contamination in ground water were observed. Whereas the Group IV ( n =28) consists of participants from the arsenic contaminated area and also tobacco chewers. Body mass index (BMI) in all the groups are found to be nearly same and in normal range. Statistically significant ( P <0.001) increase in genotoxic, cell death parameters and cell proliferation biomarkers were observed in the Group IV compared to other groups. In the comet assay, percent of tail DNA gradually increases among the groups and has statistical significance. Spearman correlation revealed strong positive correlation between the arsenic exposed peoples and the binucleated cells ( r =0.4763; P <0.001). Amount of chewing tobacco had significant positive correlation with micronucleus frequency ( r =0.268; P <0.05) and karyolitic cells ( r =0.217; P <0.05) and also in the percentage of tail DNA ( r =0.5532, P <0.001). A statistically significant increase in glucose content and decrease in hemoglobin content as well as acetylcholine esterase in the blood of exposed individuals was observed. Our preliminary study indicate that population exposed to arsenic through drinking water may become more susceptible towards chewing tobacco induced nuclear damage as evaluated by buccal cytome assay and comet assay. [ABSTRACT FROM AUTHOR]

Considering the increasing uses of ionic liquids (ILs) in various industrial processes and chemical engineering operations, a complete assessment of their hazardous profile is essential. In the absence of adequate experimental data, in silico modeling might be helpful in filling data gaps for the toxicity of ILs towards various ecological indicator organisms. Using the rationale of taxonomic relatedness, the development of predictive quantitative structure–toxicity–toxicity relationship (QSTTR) models allows predicting the toxicity of ILs to a particular species using available experimental toxicity data towards a different species. Such studies may employ, along with the available experimental toxicity data to a species, molecular structure features and physicochemical properties of chemicals as independent variables for prediction of the toxicity profile against another closely related species. A few such interspecies toxicity correlation models have been reported in the literature for diverse chemicals in general, but this approach has been rarely applied to the class of ionic liquids. The present study involves the use of IL toxicity data towards the bacteria Vibrio fischeri along with molecular structure derived information or computational descriptors like extended topochemical atom (ETA) indices, quantum topological molecular similarity (QTMS) descriptors and computed lipophilicity measure (log k 0 ) for the interspecies exploration of the toxicity data towards green algae S. vacuolatus and crustacea Daphnia magna , separately. This modeling study has been performed in accordance with the OECD guidelines. Finally, predictions for a true external set have been performed to fill the data gap of toxicity towards daphnids and algae using the Vibrio toxicity data and molecular structure attributes. [ABSTRACT FROM AUTHOR]

In the present study, it was aimed to optimize the process of lactose hydrolysis using free and immobilized β-galactosidase to produce glucose and galactose. Response surface methodology (RSM) by central composite design (CCD) was employed to optimize the degree of hydrolysis by varying three parameters, temperature (15–45 °C), solution pH (5–9) and β-galactosidase enzyme concentration (2–8 mg/mL) for free mode of analysis and sodium alginate concentration (2–4%), calcium chloride concentration (3–6%) and enzyme concentration (2–8 mg/mL) for immobilized process. Based on plots and variance analysis, the optimum operational conditions for maximizing lactose hydrolysis were found to be temperature (35.5 °C), pH (6.7) and enzyme concentration (6.7 mg/mL) in free mode and sodium alginate concentration (3%), calcium chloride concentration (5.9%) and enzyme concentration (5.2 mg/mL) in immobilized mode. [ABSTRACT FROM AUTHOR]

This paper discusses the control of an ideal reactive distillation column (RDC) using model predictive control (MPC) based on a combination of deterministic generalized orthonormal basis filter (GOBF) and stochastic autoregressive moving average (ARMA) models. Reactive distillation (RD) integrates reaction and distillation in a single process resulting in process and energy integration promoting green chemistry principles. Improved selectivity of products, increased conversion, better utilization and control of reaction heat, scope for difficult separations and the avoidance of azeotropes are some of the advantages that reactive distillation offers over conventional technique of distillation column after reactor. The introduction of an in situ separation in the reaction zone leads to complex interactions between vapor–liquid equilibrium, mass transfer rates, diffusion and chemical kinetics. RD with its high order and nonlinear dynamics, and multiple steady states is a good candidate for testing and verification of new control schemes. Here a combination of GOBF-ARMA models is used to catch and represent the dynamics of the RDC. This GOBF-ARMA model is then used to design an MPC scheme for the control of product purity of RDC under different operating constraints and conditions. The performance of proposed modeling and control using GOBF-ARMA based MPC is simulated and analyzed. The proposed controller is found to perform satisfactorily for reference tracking and disturbance rejection in RDC. [ABSTRACT FROM AUTHOR]

The high-resolution absorption spectrum of trifluoromethyliodide (CF 3 I), an alternative gas to chlorofluorocarbons but with potential greenhouse effects, has been recorded at 0.001 cm − 1 resolution in the 200–350 cm − 1 region with the Bruker IFS125HR Fourier transform spectrometer at synchrotron SOLEIL. Due to the spectral congestion and the presence of numerous hot bands, the spectra have been recorded at the AILES Beamline facility at SOLEIL either at room temperature using a 150 m optical path length cell or at 163 K using the new LISA-SOLEIL cryogenic cell and at the Australian synchrotron using a flow cooling cell. This enables a detailed analysis of the v 3 band at 286.29712(3) cm − 1 of CF 3 I. The results of previous microwave measurements in the v 3 = 1 and v 6 = 1 vibrational states (Walters and Whiffen, 1983; Wahi, 1987) were combined with those of the present infrared analysis of the v 3 band to obtain an improved set of parameters for the v 3 = 1 (C–I stretching) and v 6 = 1 (I–C–F bending) interacting vibrational states accounting for the Coriolis resonance coupling the v 3 = 1 energy levels with those of the dark v 6 = 1 state (located at ∼261.5 or at ∼267.6 cm − 1 ). Finally, a first investigation of the 2 v 3 − v 3 hot band is also performed. [ABSTRACT FROM AUTHOR]

The continuous-fed activated sludge test (OECD TG 303A) was used to predict the removal of cationic surfactants from wastewater in activated sludge plants. However, a method to differentiate between adsorption and biodegradation is not provided in these guidelines. Assessment of removal by biodegradation was possible with analysis of the surfactant present in mixed liquid suspended solids in combination with a simple equation. This equation was derived from the mass balance of the activated sludge unit in steady state. The removal by biodegradation of decylamine, tetradecylamine, octadecylamine, dioctadecylmethylamine and dioctadecyldimethylammonium chloride that have different capacities to adsorb was >99.9%, >99.9%, 98.2%, 94.2%, and 69.0%, respectively. The total removal of all five cationic surfactants from the influent was ≥98.8%. The removal of octadecylamine spiked at different influent concentrations indicated first order kinetics. [ABSTRACT FROM AUTHOR]

In this paper we propose a framework for tracking multiple interacting targets in a wide-area camera network consisting of both overlapping and non-overlapping cameras. Our method is motivated from observations that both individuals and groups of targets interact with each other in natural scenes. We associate each raw target trajectory ( i.e. , a tracklet) with a group state, which indicates if the trajectory belongs to an individual or a group. Structural Support Vector Machine (SSVM) is applied to the group states to decide if merge or split events occur in the scene. Information fusion between multiple overlapping cameras is handled using a homography-based voting scheme. The problem of tracking multiple interacting targets is then converted to a network flow problem, for which the solution can be obtained by the K-shortest paths algorithm. We demonstrate the effectiveness of the proposed algorithm on the challenging VideoWeb dataset in which a large amount of multi-person interaction activities are present. Comparative analysis with state-of-the-art methods is also shown. [ABSTRACT FROM AUTHOR]

The recent exponential growth of genomic databases has resulted in the common task of sequence alignment becoming one of the major bottlenecks in the field of computational biology. It is typical for these large datasets and complex computations to require cost prohibitive High Performance Computing (HPC) to function. As such, parallelised solutions have been proposed but many exhibit scalability limitations and are incapable of effectively processing “Big Data” – the name attributed to datasets that are extremely large, complex and require rapid processing. The Hadoop framework, comprised of distributed storage and a parallelised programming framework known as MapReduce, is specifically designed to work with such datasets but it is not trivial to efficiently redesign and implement bioinformatics algorithms according to this paradigm. The parallelisation strategy of “divide and conquer” for alignment algorithms can be applied to both data sets and input query sequences. However, scalability is still an issue due to memory constraints or large databases, with very large database segmentation leading to additional performance decline. Herein, we present Hadoop Blast (HBlast), a parallelised BLAST algorithm that proposes a flexible method to partition both databases and input query sequences using “virtual partitioning”. HBlast presents improved scalability over existing solutions and well balanced computational work load while keeping database segmentation and recompilation to a minimum. Enhanced BLAST search performance on cheap memory constrained hardware has significant implications for in field clinical diagnostic testing; enabling faster and more accurate identification of pathogenic DNA in human blood or tissue samples. [ABSTRACT FROM AUTHOR]

Within this work we evaluated the cytotoxicity towards the Channel Catfish Ovary (CCO) cell line of some imidazolium-based ionic liquids containing different functionalized and unsaturated side chains. The toxic effects were measured by the reduction of the WST-1 dye after 72 h exposure resulting in dose- and structure-dependent toxicities. The obtained data on cytotoxic effects of 14 different imidazolium ionic liquids in CCO cells, expressed as EC50 values, were used in a preliminary quantitative structure–toxicity relationship (QSTR) study employing regression- and classification-based approaches. The toxicity of ILs towards CCO was chiefly related to the shape and hydrophobicity parameters of cations. A significant influence of the quantum topological molecular similarity descriptor ellipticity ( ε ) of the imine bond was also observed. [ABSTRACT FROM AUTHOR]

We present the polarimetric results and analysis of Comet C/2012 L2 (LINEAR) observed at 31°.1 phase angle before perihelion passage. The observations of the comet were carried out using ARIES Imaging Polarimeter (AIMPOL) mounted on the 1.04-m Sampurnanand telescope of ARIES, Nainital, India on 11 and 12 March, 2013 using R photometric band ( λ = 630 nm, Δ λ = 120 nm ) . The extended coma of the comet (∼65000 km) shows a significant variation in the intensity as well as polarization profile in all considered directions which suggest that the dust particles originate from the active areas of the nucleus. The elongation of the coma is prominent along the Sun–comet position angle. The polarization of Comet C/2012 L2 (LINEAR) do not show steep radial dependence on the aperture size during both the nights of observation. A jet extended in the antisolar direction is well observed in both intensity and polarization map. [ABSTRACT FROM AUTHOR]

We study ( 2 + 1 ) dimensional massless Dirac oscillator in the presence of perpendicular magnetic and transverse electric fields. Exact solutions are obtained and it is shown that there exists a critical magnetic field B c such that the spectrum is different in the two regions B > B c and B < B c . The situation is also analyzed for the case B = B c . [ABSTRACT FROM AUTHOR]

The copper redhorse, Moxostoma hubbsi , is an endangered species endemic to Quebec. The presence of contaminants, in particular endocrine disrupting chemicals (EDCs), in its habitat has been advanced as partly responsible for the reproductive difficulties encountered by the species. In the present study, immature copper redhorse were exposed to the estrogenic surfactant nonylphenol (NP; 1, 10 and 50 µg/l) and the synthetic estrogen 17α-ethinylestradiol (EE2; 10 ng/l) for 21 days in a flow-through system. The endpoints investigated included general health indicators (hepatosomatic index and hematocrit), thyroid hormones, sex steroids, brain aromatase activity, plasma and mucus vitellogenin (VTG), cytochrome P4501A protein expression and ethoxyresorufin-O-deethylase activity, heat shock protein 70 (HSP70) and muscle acetylcholinesterase. Exposure to 10 ng EE2/l significantly increased brain aromatase activity. Exposure to 50 µg NP/l resulted in a significant reduction of plasma testosterone concentrations and a significant induction of hepatic HSP70 protein expression. NP at 50 µg/l also induced plasma and mucus VTG. The presence of elevated VTG levels in the surface mucus of immature copper redhorse exposed to NP, and its correlation to plasma VTG, supports the use of mucus VTG as a non-invasive biomarker to evaluate copper redhorse exposure to EDCs in the environment and contribute to restoration efforts of the species. The results of the present study indicate that exposure to high environmentally relevant concentrations of NP and EE2 can affect molecular endpoints related to reproduction in the copper redhorse. [ABSTRACT FROM AUTHOR]

Nanotechnology has evolved as a frontrunner in the development of modern science. Current studies have established toxicity of some nanoparticles to human and environment. Lack of sufficient data and low adequacy of experimental protocols hinder comprehensive risk assessment of nanoparticles (NPs). In the present work, metal electronegativity (χ), the charge of the metal cation corresponding to a given oxide (χox), atomic number and valence electron number of the metal have been used as simple molecular descriptors to build up quantitative structure–toxicity relationship (QSTR) models for prediction of cytotoxicity of metal oxide NPs to bacteria Escherichia coli . These descriptors can be easily obtained from molecular formula and information acquired from periodic table in no time. It has been shown that a simple molecular descriptor χox can efficiently encode cytotoxicity of metal oxides leading to models with high statistical quality as well as interpretability. Based on this model and previously published experimental results, we have hypothesized the most probable mechanism of the cytotoxicity of metal oxide nanoparticles to E. coli . Moreover, the required information for descriptor calculation is independent of size range of NPs, nullifying a significant problem that various physical properties of NPs change for different size ranges. [ABSTRACT FROM AUTHOR]

Work constitutes a central component of a person's identity. Retirement, which is a significant change in life, also affects the way one's identity is established upon entering this new stage in life. Continuing to work after retirement enables individuals to maintain their professional identity alongside their retirement identity, thus facilitating the transition and entry into a new stage of life. The current study uses in-depth interviews to examine post-retirement working among Israeli doctors who have retired over the past few years but continue to work. The findings show that doctors have difficulty shedding their professional identity since the medical profession was, and still is, central to their overall identity. They thus experience retirement as a forced event rather than a desirable transition. However, by continuing to work, they preserve their status as doctors, which imparts a feeling of still being needed and thus enhances their self-image. Working beyond retirement allows doctors to put off the advent of old age and to avoid self-definition as retired persons, thus allowing them to preserve their professional status and hybrid identity. • Post-retirement work is a common phenomenon among doctors. • Post retirement work allows doctors to keep professional status and have a smoother transition to their new phase of life. • Working after retirement age contributes to one's satisfaction and wellbeing. • An integration of three theories provides a new outlook for the meaning of work after retirement. [ABSTRACT FROM AUTHOR]

Biodiversity nurturing may be a valuable pathway in controlling chemical stress on the ecosystem. In the present work, in silico studies have been performed to develop regression based quantitative structure toxicity relationship (QSTR) models using a data set containing 105 organic chemicals for the prediction of 48-h chemical toxicity towards Pseudokirchneriella subcapitata. Classification based linear discriminant analysis (LDA) was also performed to distinguish chemicals into toxic and nontoxic groups using the same data set. The developed models were found to possess good predictive quality in terms of internal, external and overall validation parameters. The regression based QSTR model suggests that second order molecular connectivity index (molecular size and lipophilicity), density (aromaticity), relative shape of molecules (cyclicity/aromaticity), and specific molecular fragments of the chemicals are important properties of chemicals to exert their toxicity on P. subcapitata. The classification based LDA QSTR model suggested that fused ring aromatic systems, secondary carbon atom fragments, second order valence molecular connectivity indices (molecular size and branching) and molecular weight are the distinguishing features to differentiate chemicals into toxic and nontoxic groups. [Copyright &y& Elsevier]

Abstract: The CD200:CD200R1 inhibitory signaling pathway has been implicated in playing a prominent role in limiting inflammation in a wide range of inflammatory diseases. CD200R1 signaling inhibits the expression of proinflammatory molecules including tumor necrosis factor, interferons, and inducible nitric oxide synthase in response to selected stimuli. Unsurprisingly, due to the regulatory role that CD200R1 plays in multiple inflammatory pathways, an increasing number of parasitic, bacterial, and viral pathogens exploit this pathway to suppress host defenses. A complete understanding of the pathways regulated by CD200R1 signaling and the diverse mechanisms that pathogens have evolved to manipulate the CD200:CD200R1 pathway can help identify clinical situations where targeting this interaction can be of therapeutic benefit. In this review, we compare CD200R1 to other pathogen-targeted inhibitory receptors and highlight how this signaling pathway is utilized by a diverse number of pathogens and, therefore, may represent a novel targeting strategy for the treatment of infectious diseases. [Copyright &y& Elsevier]