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670 results for “Influence factors”
Opinion dynamics in social network under competition: the role of influencing factors in consensus reaching
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What factors influence the rediscovery of lost tetrapod species? Appendix G: Variables tested for their influence on rediscovery
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Code and data for: Habitat and local factors influence fish biomass recovery in marine protected areas
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What factors influence the rediscovery of lost tetrapod species? Appendix E: Lost and rediscovered species
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Asymmetrical hybridization and environmental factors influence the spatial genetic structure of a killifish hybrid zone
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Plant‐eating carnivores: Multispecies analysis on factors influencing the frequency of plant occurrence in obligate carnivores
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Sun exposure as a key factor influencing saproxylic beetle communities
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Exploring the influence of core-self evaluations, situational factors, and coping on nurse burnout: A cross-sectional survey study
<p>Stress has become an inherent aspect of the nursing profession. Chronically experienced work stress can lead to burnout. Although situational stressors show a significant influence on burnout, their power to predict the complete syndrome is rather limited. After all, stressors only exist “in the eye of the beholder”. This study aimed to explore how individual vulnerability factors such as core-self evaluations and coping, contribute to burnout in relation to situational stressors within a population of hospital nurses.</p> <p>Cross-sectional data was collected in 2014, using five validated self-report instruments: Dutch Core Self Evaluations Scale, Nursing Work Index Revised, Utrecht Coping List, Ruminative Response Scale, and Utrecht Burnout Scale. 219 of the 250 questionnaires were returned. This database is available here.</p> <p>Core-self evaluations, situational factors and coping each contributed significantly to the predictive capacity of the models of the separate burnout dimensions. Core-self evaluations was significantly related to emotional exhaustion. It was suggested that Core-self evaluations might be placed at the initiation of the loss cycle. However, further research is warranted.</p>
Data from: A meta-analysis of factors influencing the strength of mate choice copying in animals
Davies et al., (2020) All data and R code <p>Mate-choice copying is a form of social learning in which an individual's choice of mate is influenced by the apparent choices of other individuals of the same sex, and has been observed in more than 20 species across a broad taxonomic range. Though fitness benefits of copying have proven difficult to measure, theory suggests that copying should not be beneficial for all species or contexts. However, the factors influencing the evolution and expression of copying have proven difficult to resolve. We systematically searched the literature for studies of mate-choice copying in non-human animals, and then performed a phylogenetically-controlled meta-analysis to explore which factors influence the expression of copying across species. Across 58 published studies in 23 species, we find strong evidence that animals copy the mate choice of others. The strength of copying was significantly influenced by taxonomic group, however sample size limitations mean it is difficult to draw firm conclusions regarding copying in mammals and arthropods. The strength of copying was also influenced by experimental design: copying was stronger when choosers were tested before and after witnessing a conspecific's mate choice, compared to when choosers with social information were compared to choosers without. Importantly, we did not detect any difference in the strength of copying between males and females, or in relation to the rate of multiple mating. Our search also highlights that more empirical work is needed to investigate copying in a broader range of species, especially those with differing mating systems and levels of reproductive investment.</p>
Data from: Stopover refueling, movement, and departure decisions in the White-throated Sparrow: the influence of intrinsic and extrinsic factors during spring migration
<p>1. Differential migration timing between sex or age classes are examples of how migratory movement strategies can differ among sub-groups within a population. However, in songbirds, evidence for intrinsic differences in en route migratory behavior is often mixed, suggesting that the local environmental context may play a role in accentuating or diminishing patterns. 2. We evaluated how multiple intrinsic and extrinsic variables influenced refueling rates, local movement behavior, and departure decisions in the White-throated Sparrow (Zonotrichia albicollis) during spring migration. This species exhibits a unique genetically-based plumage dimorphism, providing a unique class of individual in which to evaluate patterns and processes of differential migration, in addition to sex, age, and migration distance. 3. At a migratory stopover site, plasma metabolite analysis was used to quantify individual variation in stopover refueling rate. In after second year adults, automated and manual radio telemetry was used to quantify daily activity timing, daily movement distances, stopover duration, and departure time. Arrival timing to the stopover site was determined using capture data. Non-breeding and previous breeding/natal latitude were determined using analysis of hydrogen isotopes in claws and feathers. 4. Males arrived at the stopover site 11 days on average before females, but no difference in migration timing was observed between plumage morph or age classes. After second year adults with more southern previous breeding latitudes arrived at stopover earlier whereas second year birds making their first return migration arrived at stopover in an inverse relationship to non-breeding latitude. Stopover refueling rate did not differ between ages, sexes, or plumage morphs, and daily departure probability of adults was higher under warmer temperatures and favorable tailwinds. White-striped morphs moved greater distances during stopover, initiated daily activity earlier in the morning, and departed for migration earlier in the evening than tan-striped morphs. 5. Our results show that while individual phenotype can influence some aspects of local stopover-scale movement behavior, evidence for differential stopover behavior was weak. Differential migration timing is unlikely to result from intrinsic differences in en route refueling rate and departure decisions, especially because the latter is strongly influenced by meteorological conditions. </p>
Influence of polymorphisms in the vascular endothelial growth factor gene on allograft rejection after kidney transplantation: a meta-analysis
<p><span><b><i>Purpose</i></b><i> </i>Reported associations of allograft rejection in kidney transplant patients with <i>VEGF</i> single nucleotide polymorphisms (SNPs) have been inconsistent between studies, which prompted a meta-analysis to obtain more precise estimates.</span></p> <p><span><b><i>Methods</i></b><i> </i>Using the PICO elements, kidney transplant patients (P) were compared by genotype data between rejectors (I) and non-rejectors (C) in order to determine the risk of allograft rejection (O) attributed to the <i>VEGF</i> SNPs. Literature search of four databases yielded seven articles. To calculate risks for allograft rejection, four SNPs were examined. Meta-analysis treatments included outlier and subgroup analyses, the latter was based on ethnicity (Indians/Caucasians) and rejection type (acute/chronic). Multiple comparisons were corrected with the Bonferroni test. </span></p> <p><span><span><b><i>Results</i></b> Five highly significant outcomes (P<sup>a</sup> < 0.01) survived Bonferroni correction, one of which showed reduced risk for the <i>var</i> allele (OR 0.61, 95% CI 0.45-0.82). The remaining four indicated increased risk for the <i>wt</i> allele where the chronic rejection (OR 2.10, 95% CI 1.36-3.24) and Indian (OR 1.44, 95% CI 1.13-1.84) subgroups were accorded susceptibility status. </span></span></p> <p><span><b><i>Conclusions</i></b> Risk associations for renal allograft rejection were increased and reduced on account of the <i>wt</i> and <i>var</i> alleles, respectively. These findings could render the <i>VEGF</i> polymorphisms useful in the clinical genetics of kidney transplantation. </span></p>
Data from: Factors influencing herpetofauna abundance and diversity in a tropical agricultural landscape mosaic
<p>Agricultural intensification and the associated factors, including land transformation, are among the major global threats affecting biodiversity especially herpetofauna. However, little information is available about how different factors shape herpetofauna species assemblages in agricultural landscape at different spatial scales from patch (125 – 250m) to the landscape (500 – 1000m).</p> <p>We assessed the diversity of amphibians and reptiles in areas under low and high degrees of agricultural intensification and explored different factors regulating diversity at different spatial scales using four sampling methods.</p> <p>Diversity and abundance of amphibians varied significantly between the two zones, but not for reptiles. Agricultural intensification Index (AII), calculated based on agrochemical use and area under agriculture at 250m scale, seemed to affect amphibians both at patch as well as at 500m and 1000m landscape scales. The AII influenced reptilian diversity only at patch and 500m scales. Vicinity of natural forest had a stronger influence on reptilian abundance. Semi-natural vegetation impacted herpetofauna diversities at larger spatial scales. The extent of water bodies influenced the reptilian abundance at 250m patch scale and amphibian abundance both at 250m and 1000m scale. Fallow lands affected only reptilian diversity at all spatial scales. Plantation affected amphibian at all scales but reptiles only at the landscape scale. Habitat heterogeneity regulated only amphibian diversity.</p> <p>These results highlight the fact that different patch and landscape-scale factors regulate the diversity of reptiles and amphibians differentially. Such scale specific information will crucially inform future conservation action for the herpetofauna in the agricultural landscape.</p>
Data from: Assessing the influence of biotic, abiotic, and social factors on the physiological stress of a large Neotropical primate in Atlantic Forest fragments
Wildlife physiological responses to environmental and human-related stressors provide useful clues on animal welfare. Non-invasive biomarkers, such as fecal glucocorticoid metabolites (fGCM), allow researchers to assess whether variations in habitat quality, behavior, and climate influence the animals' physiological stress. We examined the role of fragment size, ambient temperature, ripe fruit availability and consumption, percentage of records moving, sex, female reproductive state, and group composition as predictors of the level of fGCM in adult brown howler monkeys (Alouatta guariba clamitans) inhabiting three small (<10 ha) and three large (>90 ha) Atlantic Forest fragments in southern Brazil. We collected bimonthly behavioral data and fecal samples from adult individuals over three years, and used a multimodel inference framework to identify the main predictors of fGCM. We found that the mean (±SD) fGCM in the study groups ranged from 57 ± 49 ng/g to 93 ± 58 ng/g, which were within the known range for howler monkeys. We found 10 best models including five of the 17 tested variables. Sex and reproductive state were the only variables included in all these models. We found that fGCM was higher in nursing females (mean ± SD = 104 ± 73 ng/g) than in non-nursing females (64 ± 55 ng/g) and males (53 ± 40 ng/g, P < 0.05) and that it decreased with increasing ripe fruit consumption and minimum temperature. However, fragment size did not predict fGCM concentration (groups in small fragments = 71 ± 58 ng/g vs. groups in large fragments = 63 ± 54 ng/g, P > 0.05). We conclude that factors related to the energetic balance of individuals play major roles in modulating the physiological stress of brown howler monkeys. Future studies should investigate the consequences of higher levels of stress hormones on howler monkey health and demography.
Data from: Ecological factors influence balancing selection on leaf chemical profiles of a wildflower
<div> <div> <div> <div> <p>Balancing selection is frequently invoked as a mechanism to maintain variation within and across populations. However, rigorous tests demonstrating balancing selection operating in nature are scarce, particularly on complex traits, which frequently display high levels of variation. Leveraging a focal polymorphism, leaf chemical profile in a perennial wildflower (<em>Boechera stricta</em>, Brassicaceae), we investigated the ecological and genetic mechanisms that may influence the maintenance of variation in this trait. A suite of common garden and greenhouse experiments showed that the alleles underlying variation in chemical profile have contrasting fitness effects across environments, implicating two ecological drivers of selection on chemical profile: herbivory and drought. Phenotype-environment associations and molecular genetic analyses revealed additional evidence of past selection by these drivers. Together, these data are consistent with balancing selection on chemical profile, likely caused by pleiotropic effects of genes that influence secondary chemical biosynthesis on herbivore defense and drought response.</p> </div> </div> </div> </div>
Exploring Sleep Patterns and Influencing Factors in Elite Female Football Athletes
<p>This dataset contains a novel collection of data from 21 elite female footballers who were continuously monitored for 17 days. The dataset includes measures of actigraphy, well-being, caffeine consumption, screen time and daily hand strength tests. The main objective is to gain a deeper understanding of the interactions between lifestyle, sleep and athletic performance.</p> <p>Sleep is essential for physical and mental recovery, memory performance and brain development. Athletes' sleep quality can be significantly affected by various factors, such as rigorous training schedules, stress, light exposure and caffeine consumption. By closely examining these factors, this dataset supports the creation of personalised training models that take into account the individual sleep patterns and recovery needs of each athlete. Such personalised approaches aim to optimise training and recovery strategies to ultimately improve the overall performance and well-being of athletes.</p>
Factors influencing space-use and kill distribution of sympatric lion prides in a semi-arid savanna landscape
<p>In this study, Global Positioning System collar data and logistic regression were used to investigate space-use and kill distribution among three lion prides at Malilangwe Wildlife Reserve, Zimbabwe. The R statistical platform was used to perform logistic regression analysis to determine the effects of the environmental variables on the outcome of each pride's ranging behaviour. <i>Presence/Kill probability </i>(presence or absence) was used as a response variable while<i> distance to water, shrub canopy volume</i>, <i>soil depth</i> and <i>clay content</i> were treated as fixed effects.</p>
Landslide Influencing Factors for Landslide Susceptibility Mapping in Lombardy, Italy
<p>A selection of Landslide Influencing Factors used for Landslide susceptibility mapping through machine learning models covering the Lombardy region in Italy.</p> <p>A list of the factors:</p> <ul> <li>Averaged Hourly Precipitation for the year of 2020. Source: Precipitation data from ARPA Lombardia.</li> <li>Digital Elevation Model [meters], 5m/pix. Source: GeoPortale Lombardia.</li> <li>Eastness [unitless], 5m/pix. Source: DTM derived.</li> <li>Faults buffer (50, 100, 200, 500, >500), [meters], 1:10 000. Source: GeoPortale Lombardia, derived.</li> <li>Land Use Land Cover Map. Source: GeoPortale Lombardia.</li> <li>Lithology, 5m/pix. Source: GeoPortale Lombardia.</li> <li>Normalized Difference Vegetation Index, [unitless], 10m/pix. Source: Sentinel-2 derived for the year 2020.</li> <li>Northness [unitless], 5m/pix. Source: DTM derived.</li> <li>Orientation of the slope faces [degrees], 5m/pix. Source: DTM derived.</li> <li>Plan Curvature [unitless], 5m/pix. Source: DTM derived.</li> <li>Profile Curvature [unitless], 5m/pix. Source: DTM derived.</li> <li>River buffer (50, 100, 200, 500, >500), [meters], 1:10 000. Source: GeoPortale Lombardia, derived.</li> <li>Road buffer (50, 100, 200, 500, >500), [meters], 1:10 000. Source: GeoPortale Lombardia, derived.</li> <li>The 90<sup>th</sup> percentile of hourly precipitation for the year of 2020. Source: Precipitation data from ARPA Lombardia.</li> <li>Topographic Wetness Index, 5m/pix . Source: DTM derived</li> </ul> <p>The maps are in WGS 84/ UTM zone 32N (EPSG:32632).</p> <p>The map production process details are discussed in Xu et al. 2024. If you use the dataset, please, cite also the paper:</p> <p><em>Qiongjie Xu, Vasil Yordanov, Lorenzo Amici & Maria Antonia Brovelli (2024) Landslide susceptibility mapping using ensemble machine learning methods: a case</em><br><em>study in Lombardy, Northern Italy, International Journal of Digital Earth, 17:1, 2346263, DOI:10.1080/17538947.2024.2346263</em></p> <p>The maps are produced as part of the "Geoinformatics and Earth Observation for Landslide Monitoring" Italy-Vietnam.</p> <p>The work is partially funded by the Italian Ministry of Foreign Affairs and International Cooperation within the project “Geoinformatics and Earth Observation for Landslide Monitoring” CUP D19C21000480001.</p> <p> </p>
Factors influencing the residual air saturation during consecutive imbibition processes in an air-water two-phase fine sandy medium
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The Influence of cultural and psychological factors on mental health status during COVID-19 in Saudi Arabia
<p>The data supporting the findings of the article is available here to be published in the open psychology journal.</p> <p> </p> <p>the data set is excel file generated from google form</p>
Influence of past and current factors on the beta diversity of coastal lagoon fish communities in South America
<p><strong>Aim: </strong>We aimed to assess the relative influence of past (Quaternary paleodrainage characteristics) and current factors on the beta diversity of freshwater fishes in coastal lagoons and explore the main processes involved.</p> <p><strong>Location:</strong> Atlantic coast of South America. Taxon: Fishes (173 species)</p> <p><strong>Methods:</strong> We built a dataset of species occurrence in 129 lagoons across eight freshwater ecoregions of the world (FEOWs) located between latitudes 0° and 36° and calculated beta diversity (βjac) and its turnover (βjtu) and nestedness (βjne) components. We used a partial Mantel test and multiple regressions on distance matrices to evaluate the importance of past and current factors, and of geographical distance in determining beta diversity. Past variables were those representing the historical freshwater habitat during the last glacial maximum (LGM), and contemporary variables were those related to current habitat.</p> <p><strong>Results:</strong> We found high values of βjac within the FEOWs, with βjtu prevailing over βjne. Both past (paleodrainage) and current (drainage area, salinity, and lagoon area) factors affected species dissimilarity (βjac = 46%) and its components (βjtu = 44% and βjne =20%), although explanation was, in part, shared with geographical distance. Individually, the influence of past factors was prevalent in beta diversity and its components.</p> <p><strong>Main Conclusions:</strong> The results suggest that major changes in the availability of freshwater habitats and connectivity since the Pleistocene must have affected the colonization, extinction and recolonization processes of fishes along the eastern coast of South America. We suggest that the high beta diversity values may result from limited dispersal after extinctions in the LGM and that the dissimilar freshwater fish communities currently seen were formed mainly by heterogeneous subsets of the regional species pool that persisted in landscape refuges during past sea level increases and then recolonized coastal lagoons.</p>
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Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.