Usage of statistical modeling of lightning leader advancement process in the last stroke phase for determination of lightning protection system parameters

In the paper, the experimental data on the electrical physical characteristics of long spark gaps and lightning are used to create a lightning leader development model in the last stroke phase. The model is verified by comparison of the calculated probabilities of lightning attachments to air terminals and protected objects with normalized level. In order to determine the influence of ground system resistance on protection ability for lightning air terminals, lightning attachments with different ground system resistances have been modeled. The proposed method has been implemented for the calculation of lightning strokes probability to objects of an extended facility with oil storage tanks

Cover Crops and Returning Residue Impact on Soil Organic Carbon, Bulk Density, Penetration Resistance, Water Retention, Infiltration, and Soybean Yield

Residue management with cover crops (CC) can conserve soil moisture and thus has a potential to increase crop yield, but its effectiveness varies significantly by region and cropping system management. A study was conducted at Brookings, SD, on finesilty, mixed, superactive, frigid, Calcic/Pachic Hapludolls soils to understand the impact of CC and crop residue on soil properties and soil-water dynamics for soybean (Glycine max L.) crop grown after corn (Zea mays L.). The site had two crop residue treatments (residue returned [RR] and residue not returned [RNR]) under a no-till corn–soybean rotation. Each residue returned treatment was later subdivided to include CC and no CC (NCC) treatments. Results from this 3 yr (2014, 2015, and 2016) study showed that RR (1.30 Mg m–3) had 7% lower bulk density (BD) compared to the RNR (1.40 Mg m–3). Soil organic carbon (SOC) was 22% higher under RR (26.2 g kg–1) compared to RNR (21.5 g kg–1). Soil water infiltration was 66% higher under RR (108 mm h–1) compared to RNR (64.8 mm h–1). Similarly, soil water infiltration in CC treatment (111 mm h–1) was 80% higher compared to NCC (61.7 mm h–1). The RR with CC treatment increased soil volumetric water content and soil water storage. Overall, the CC increased soybean yield by 14% compared to NCC. Data from this study suggest that the use of CC with RR are beneficial for improving soil properties, conserving soil moisture and enhancing crop yield

Low Levels of Fruit Nitrogen as Drivers for the Evolution of Madagascar's Primate Communities

The uneven representation of frugivorous mammals and birds across tropical regions - high in the New World, low in Madagascar and intermediate in Africa and Asia - represents a long-standing enigma in ecology. Several hypotheses have been proposed to explain these differences but the ultimate drivers remain unclear. Here, we tested the hypothesis that fruits in Madagascar contain insufficient nitrogen to meet primate metabolic requirements, thus constraining the evolution of frugivory. We performed a global analysis of nitrogen in fruits consumed by primates, as collated from 79 studies. Our results showed that average frugivory among lemur communities was lower compared to New World and Asian-African primate communities. Fruits in Madagascar contain lower average nitrogen than those in the New World and Old World. Nitrogen content in the overall diets of primate species did not differ significantly between major taxonomic radiations. There is no relationship between fruit protein and the degree of frugivory among primates either globally or within regions, with the exception of Madagascar. This suggests that low protein availability in fruits influences current lemur communities to select for protein from other sources, whereas in the New World and Old World other factors are more significant in shaping primate communities

Complex patterns of human antisera reactivity to novel 2009 H1N1 and historical H1N1 influenza strains

Background: During the 2009 influenza pandemic, individuals over the age of 60 had the lowest incidence of infection with approximately 25% of these people having pre-existing, cross-reactive antibodies to novel 2009 H1N1 influenza isolates. It was proposed that older people had pre-existing antibodies induced by previous 1918-like virus infection(s) that cross-reacted to novel H1N1 strains. Methodology/Principal Findings: Using antisera collected from a cohort of individuals collected before the second wave of novel H1N1 infections, only a minority of individuals with 1918 influenza specific antibodies also demonstrated hemagglutination-inhibition activity against the novel H1N1 influenza. In this study, we examined human antisera collected from individuals that ranged between the ages of 1 month and 90 years to determine the profile of seropositive influenza immunity to viruses representing H1N1 antigenic eras over the past 100 years. Even though HAI titers to novel 2009 H1N1 and the 1918 H1N1 influenza viruses were positively associated, the association was far from perfect, particularly for the older and younger age groups. Conclusions/Significance: Therefore, there may be a complex set of immune responses that are retained in people infected with seasonal H1N1 that can contribute to the reduced rates of H1N1 influenza infection in older populations. © 2012 Carter et al

Soil erosion modelling: A global review and statistical analysis

To gain a better understanding of the global application of soil erosion prediction models, we comprehensivelyreviewed relevant peer-reviewed research literature on soil-erosion modelling published between 1994 and2017. We aimed to identify (i) the processes and models most frequently addressed in the literature, (ii) the re-gions within which models are primarily applied, (iii) the regions which remain unaddressed and why, and (iv)how frequently studies are conducted to validate/evaluate model outcomes relative to measured data. To per-form this task, we combined the collective knowledge of 67 soil-erosion scientists from 25 countries. Theresulting database, named‘Global Applications of Soil Erosion Modelling Tracker (GASEMT)’, includes 3030 indi-vidual modelling records from 126 countries, encompassing all continents (except Antarctica). Out of the 8471articles identified as potentially relevant, we reviewed 1697 appropriate articles and systematically evaluatedand transferred 42 relevant attributes into the database. This GASEMT database provides comprehensive insightsinto the state-of-the-art of soil- erosion models and model applications worldwide. This database intends to sup-port the upcoming country-based United Nations global soil-erosion assessment in addition to helping to informsoil erosion research priorities by building a foundation for future targeted, in-depth analyses. GASEMT is anopen-source database available to the entire user-community to develop research, rectify errors, andmakefutureexpansion

Soil erosion modelling: A bibliometric analysis

Soil erosion can present a major threat to agriculture due to loss of soil, nutrients, and organic carbon. Therefore, soil erosion modelling is one of the steps used to plan suitable soil protection measures and detect erosion hotspots. A bibliometric analysis of this topic can reveal research patterns and soil erosion modelling characteristics that can help identify steps needed to enhance the research conducted in this field. Therefore, a detailed bibliometric analysis, including investigation of collaboration networks and citation patterns, should be conducted. The updated version of the Global Applications of Soil Erosion Modelling Tracker (GASEMT) database contains information about citation characteristics and publication type. Here, we investigated the impact of the number of authors, the publication type and the selected journal on the number of citations. Generalized boosted regression tree (BRT) modelling was used to evaluate the most relevant variables related to soil erosion modelling. Additionally, bibliometric networks were analysed and visualized. This study revealed that the selection of the soil erosion model has the largest impact on the number of publication citations, followed by the modelling scale and the publication\u27s CiteScore. Some of the other GASEMT database attributes such as model calibration and validation have negligible influence on the number of citations according to the BRT model. Although it is true that studies that conduct calibration, on average, received around 30% more citations, than studies where calibration was not performed. Moreover, the bibliographic coupling and citation networks show a clear continental pattern, although the co-authorship network does not show the same characteristics. Therefore, soil erosion modellers should conduct even more comprehensive review of past studies and focus not just on the research conducted in the same country or continent. Moreover, when evaluating soil erosion models, an additional focus should be given to field measurements, model calibration, performance assessment and uncertainty of modelling results. The results of this study indicate that these GASEMT database attributes had smaller impact on the number of citations, according to the BRT model, than anticipated, which could suggest that these attributes should be given additional attention by the soil erosion modelling community. This study provides a kind of bibliographic benchmark for soil erosion modelling research papers as modellers can estimate the influence of their paper

Genetic Association Studies of Copy-Number Variation: Should Assignment of Copy Number States Precede Testing?

Recently, structural variation in the genome has been implicated in many complex diseases. Using genomewide single nucleotide polymorphism (SNP) arrays, researchers are able to investigate the impact not only of SNP variation, but also of copy-number variants (CNVs) on the phenotype. The most common analytic approach involves estimating, at the level of the individual genome, the underlying number of copies present at each location. Once this is completed, tests are performed to determine the association between copy number state and phenotype. An alternative approach is to carry out association testing first, between phenotype and raw intensities from the SNP array at the level of the individual marker, and then aggregate neighboring test results to identify CNVs associated with the phenotype. Here, we explore the strengths and weaknesses of these two approaches using both simulations and real data from a pharmacogenomic study of the chemotherapeutic agent gemcitabine. Our results indicate that pooled marker-level testing is capable of offering a dramatic increase in power (-fold) over CNV-level testing, particularly for small CNVs. However, CNV-level testing is superior when CNVs are large and rare; understanding these tradeoffs is an important consideration in conducting association studies of structural variation

Predicting attitudinal and behavioral responses to COVID-19 pandemic using machine learning

At the beginning of 2020, COVID-19 became a global problem. Despite all the efforts to emphasize the relevance of preventive measures, not everyone adhered to them. Thus, learning more about the characteristics determining attitudinal and behavioral responses to the pandemic is crucial to improving future interventions. In this study, we applied machine learning on the multi-national data collected by the International Collaboration on the Social and Moral Psychology of COVID-19 (N = 51,404) to test the predictive efficacy of constructs from social, moral, cognitive, and personality psychology, as well as socio-demographic factors, in the attitudinal and behavioral responses to the pandemic. The results point to several valuable insights. Internalized moral identity provided the most consistent predictive contribution—individuals perceiving moral traits as central to their self-concept reported higher adherence to preventive measures. Similar was found for morality as cooperation, symbolized moral identity, self-control, open-mindedness, collective narcissism, while the inverse relationship was evident for the endorsement of conspiracy theories. However, we also found a non-negligible variability in the explained variance and predictive contributions with respect to macro-level factors such as the pandemic stage or cultural region. Overall, the results underscore the importance of morality-related and contextual factors in understanding adherence to public health recommendations during the pandemic

Social and moral psychology of COVID-19 across 69 countries

The COVID-19 pandemic has affected all domains of human life, including the economic and social fabric of societies. One of the central strategies for managing public health throughout the pandemic has been through persuasive messaging and collective behaviour change. To help scholars better understand the social and moral psychology behind public health behaviour, we present a dataset comprising of 51,404 individuals from 69 countries. This dataset was collected for the International Collaboration on Social & Moral Psychology of COVID-19 project (ICSMP COVID-19). This social science survey invited participants around the world to complete a series of moral and psychological measures and public health attitudes about COVID-19 during an early phase of the COVID-19 pandemic (between April and June 2020). The survey included seven broad categories of questions: COVID-19 beliefs and compliance behaviours; identity and social attitudes; ideology; health and well-being; moral beliefs and motivation; personality traits; and demographic variables. We report both raw and cleaned data, along with all survey materials, data visualisations, and psychometric evaluations of key variables