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670 results for “Influence factors”
Hierarchy of the factors influencing the broad-scale waterbirds functional diversity gradients in temperate China
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Data from: Landscape-level factors influencing bog turtle persistence and distribution in southeastern New York State
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Data from: Factors influencing detection of eDNA from a stream-dwelling amphibian
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Data from: Influence of mortality factors and host resistance on the population dynamics of emerald ash borer (Coleoptera: Buprestidae) in urban forests
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Data from: Environmental factors influence both abundance and genetic diversity in a widespread bird species
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Abiotic factors influence species co‐occurrence patterns of lake fishes
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Raw data used in A unified framework for herbivore-to-producer biomass ratio reveals the relative influence of four ecological factor
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Data from: Palaeoepidemiology in extinct vertebrate populations: factors influencing skeletal health in Jurassic marine reptiles
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Assessing the influence of organizational factors on knowledge sharing in inter-firm collaborations
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Factors influencing nature interactions vary between cities and types of nature interactions
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Combined influence of intrinsic and environmental factors in shaping productivity in a small pelagic gull, the black-legged kittiwake Rissa tridactyla
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What factors influence the extent of midstorey development in Mountain Ash forests?
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Figure 3 from: Souza Silva M, Iniesta LFM, Ferreira RL (2020) Invertebrates diversity in mountain Neotropical quartzite caves: which factors can influence the composition, richness, and distribution of the cave communities? Subterranean Biology 33: 23-43. https://doi.org/10.3897/subtbiol.33.46444
Figure 3 Obligate cave species found in the Ibitipoca Estadual Park, Brazil. AHypogastruridaeBBlattodeaCBrasilomma enigmatica (Prodidomidae) DProjapygidaeEEukoenenia ibitipoca (Palpigradi).
Figure 2 from: Souza Silva M, Iniesta LFM, Ferreira RL (2020) Invertebrates diversity in mountain Neotropical quartzite caves: which factors can influence the composition, richness, and distribution of the cave communities? Subterranean Biology 33: 23-43. https://doi.org/10.3897/subtbiol.33.46444
Figure 2 Higher taxa invertebrate abundance, taxonomic diversity (richness) (A) and average taxonomic distinctness (Δ+) (B) in all 20 quartzite caves placed above 1200 m high in Minas Gerais (Brazil).
Figure 5 from: Souza Silva M, Iniesta LFM, Ferreira RL (2020) Invertebrates diversity in mountain Neotropical quartzite caves: which factors can influence the composition, richness, and distribution of the cave communities? Subterranean Biology 33: 23-43. https://doi.org/10.3897/subtbiol.33.46444
Figure 5 Metric multidimensional scaling (MDS) ordination plot of the 20 quartzite caves with and without a stream using bootstrap regions for group means around their centroids (triangles). Average (Av).
Figure 1 from: Souza Silva M, Iniesta LFM, Ferreira RL (2020) Invertebrates diversity in mountain Neotropical quartzite caves: which factors can influence the composition, richness, and distribution of the cave communities? Subterranean Biology 33: 23-43. https://doi.org/10.3897/subtbiol.33.46444
Figure 1 Borders of the Ibitipoca Estadual Park (A), sampled caves (white dots) and altitudinal layers (red lines 1610–1780, blue lines 1460–1600, yellow lines 1310–1450, green lines 1124–1450, black lines 950–1100 meters). Vegetation types vary from slope forest (B) to grasslands (D and C) on the top of the hills.
Figure 4 from: Souza Silva M, Iniesta LFM, Ferreira RL (2020) Invertebrates diversity in mountain Neotropical quartzite caves: which factors can influence the composition, richness, and distribution of the cave communities? Subterranean Biology 33: 23-43. https://doi.org/10.3897/subtbiol.33.46444
Figure 4 Distance-based redundancy analysis (dbRDA) showing the influences of the environmental factors on cave fauna composition in the 20 studied caves. The two axes explained nearly 55% of the variability in the fitted model and nearly 17% of the total variation in the data cloud. The first overlay shows how the first dbRDA axis is strongly related to cave sampled extension.
Data from: Socio-cultural factors influencing knowledge, attitudes and menstrual hygiene practices among Junior High School adolescent girls in the Kpando District of Ghana: A mixed method study
<p><b>Background: </b>Menstruation is scarcely discussed openly in Ghana due to social and religious beliefs concerning it. This has limited transfer of knowledge on menstruation to adolescents. In this study we examined socio-cultural factors affecting knowledge, attitudes and menstrual hygiene practices of Junior High School adolescent girls in the Kpando Municipality of Ghana.</p> <p><b>Materials and Methods:</b> A mixed method approach was employed with 480 respondents. A survey was conducted among 390 adolescent girls using interviewer administered questionnaires whilst Focus Group Discussions using a discussion guide were conducted among 90 respondents in groups of 9 members. Descriptive, inferential statistics and content analysis were used to summarize quantitative and qualitative data respectively.</p> <p><b>Results: </b>Fifty nine percent of the respondents had good knowledge of menstruation. Most (84.6%) of the students practiced good menstrual hygiene. Attending a private (AOR=0.19, 95% CI=0.09-0.40) and rural (AOR= 0.42, 95% CI=0.22-0.83, p=0.012) schools were significantly associated with reduced odds of practicing good menstrual hygiene. Good knowledge on menstruation was associated with increased odds of good hygiene practices (AOR=2.61, 95% CI=1.46-4.67, p=0.001). Qualitative results showed respondents were not given in-depth information on menstruation at menarche. Social and religious beliefs concerning menstruation were prominent and they influenced attitudes and practices such as isolation of menstruating girls and perception that menstruation was dirty and evil.</p> <p><b>Conclusion:</b> Although, good menstrual hygiene practice was high, religious and social beliefs regarding menstruation were common. Most of these beliefs lead to menstrual related restrictions which limit desire to seek crucial menstrual information. It is necessary to expand the scope of menstrual health awareness beyond the school environment in both rural and urban areas to eradicate menstrual misconceptions and restrictions.</p>
Comparison of health literacy profile of patients with end stage kidney disease on dialysis versus non-dialysis chronic kidney disease and the influencing factors: a cross-sectional study
<p><strong>Objectives</strong>: Lower health literacy (HL) is associated with poor outcomes in patients with kidney disease. Since HL matches the patient's competencies with the complexities of the care package, the level of HL sufficient in earlier stages of chronic kidney disease (CKD) may be inadequate for end-stage kidney disease (ESKD) patients on dialysis. We aimed to analyse the HL profile of ESKD and non-dialysis CKD patients and examine if there were significant associations with covariates which could be targeted to address HL deficits, thereby improving patient outcomes.</p> <p><strong>Design and setting</strong>: Cross-sectional study of CKD and ESKD patients from a single Australian health district.</p> <p><strong>Methods</strong>: We assessed the HL profile of 114 CKD and 109 ESKD patients using a 44-item multi-domain HL Questionnaire (HLQ) and examined its association with demographic factors (age, gender, race), smoking, income, education, comorbidities, carer status, cognitive function and depression. Using multi-variable logistic regression models, HL profiles of CKD and ESKD patients were evaluated after adjusting for covariates.</p> <p><strong>Results</strong>: Patients with ESKD had similar demographics and educational levels compared to CKD patients. ESKD had significantly higher frequency of vascular disease, cognitive impairment and depression. ESKD patients had better HL scores for the social support domain (37.1% vs 19.5% in higher HLQ4 tertile, p=0.004), whereas all other HL domains including engagement with healthcare providers were comparable to CKD. Depression was independently associated with nearly all of the HL domains (HLQ1: OR 2.6, p=0.030, HLQ2: OR 7.9, p=<0.001, HLQ3: OR 7.6, p<0.001, HLQ4: OR 3.5, p=0.010, HLQ5: OR 8.9, p=0.001, HLQ6: OR 3.9, p=0.002, HLQ7: OR 4.8, p=0.001, HLQ8: OR 5.3, p=0.001) and education with HL domains relevant to processing health related information (HLQ8: OR 2.6, p=0.008, HLQ9: OR 2.5, p=0.006).</p> <p><strong>Conclusions</strong>: Despite very frequent interactions with health systems, ESKD patients on dialysis did not have higher HL in engagement with health providers and most other HL domains, compared to CKD patients. Strategies promoting patient-provider engagement and managing depression which strongly associates with lower HL may address the impact of HL deficits and favourably modify clinical outcomes in renal patients. </p>
Data from: Regional response of grassland productivity to changing environment conditions influenced by limiting factors
<p>Regional differences and regulatory mechanisms of vegetation productivity response to changing environmental conditions constitute a core issue in macroecological researches. To verify the main limiting factors of different macrosystems [temperature-limited Tibetan Plateau (TP), precipitation-limited Mongolian Plateau (MP), and nutrient-limited Loess Plateau (LP)], we conducted a comparative survey of the east-west grassland transects on the three plateaus and explored the factors limiting regional productivity and their underlying mechanisms. The results showed that aboveground net primary productivity (ANPP) of LP (109.10 ± 16.76 g m<sup>−2</sup> yr<sup>−1</sup>) was significantly higher than that of MP (66.71 ± 11.11 g m<sup>−2</sup> yr<sup>−1</sup>) and TP (57.02 ± 10.59 g m<sup>−2</sup> yr<sup>−1</sup>). The response rate of ANPP with environmental changes was different among different plateaus, being closely related to the main limiting factors. On MP, this was precipitation, on LP it was temperature and nutrients, and on TP, it was non-specific, reflecting restriction by the extremely low temperature. After autocorrelation screening of environmental factors, different regions exhibited different productivity response mechanisms. MP was mainly influenced by temperature and precipitation, LP was influenced by temperature and nutrient, and TP was influenced by nutrient, reflecting the modifying effect of the main limiting factors. The effect of each regional environment on ANPP was 72.56% on average and only 27.18% after simple regional integration. The regional model could optimize the simulation error of the integrated model, and the relative deviations in MP, LP, and TP were reduced by 31.76%, 17.22%, and 2.23%, respectively. These findings indicate that the grasslands on the three plateaus may have different or even the opposite mechanisms to control productivity.</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.