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30 results for “Economic factors”
Figure 5 in Seasonal Abundance of Economically Important Fruit Flies (Diptera: Tephritidae: Dacinae) in Bangladesh, in Relation to Abiotic Factors and Host Plants
Figure 5. Distribution and mean monthly trap captures of Dacus longicornis, in relation with abiotic factors and host fruit availability.
Figure 4 in Seasonal Abundance of Economically Important Fruit Flies (Diptera: Tephritidae: Dacinae) in Bangladesh, in Relation to Abiotic Factors and Host Plants
Figure 4. Distribution and mean monthly trap captures of Zeugodacus cucurbitae (A) and Z. tau (B), in relation with abiotic factors and host fruit availability.
Figure 3 in Seasonal Abundance of Economically Important Fruit Flies (Diptera: Tephritidae: Dacinae) in Bangladesh, in Relation to Abiotic Factors and Host Plants
Figure 3. Distribution and mean monthly trap captures of Bactrocera rubigina (A) and B. correcta (B), in relation with abiotic factors.
Figure 2 in Seasonal Abundance of Economically Important Fruit Flies (Diptera: Tephritidae: Dacinae) in Bangladesh, in Relation to Abiotic Factors and Host Plants
Figure 2. Distribution and mean monthly trap captures of Bactrocera dorsalis (A) and B. zonata (B), in relation with abiotic factors and host fruit availability.
Figure 1. A in Seasonal Abundance of Economically Important Fruit Flies (Diptera: Tephritidae: Dacinae) in Bangladesh, in Relation to Abiotic Factors and Host Plants
Figure 1. A: Fruit fly trapping sites maintained at the Atomic Energy Research Establishment compound in Bangladesh in 2016–2017 (sites 1 to 10) and 2017–2018 (sites 1, 8, 9). B: Mean monthly rainfall and minimum and maximum temperature recorded in Dhaka, Bangladesh, during the study period.
Economic Factors Influencing the Empowerment of Peruvian Women
<p><strong><span>Objective:</span></strong><span> To determine whether economic factors are crucial in empowering women, guiding them towards growth and development opportunities, achieving empowerment, and contributing to two sustainable development goals of the 2030 development agenda: ending poverty and achieving gender equality.</span></p> <p><strong><span>Methodology:</span></strong><span> The research was foundational, with a phenomenological and hermeneutic design. The applied technique was in-depth interviews with 12 women who had started a business within the last five years in a region of Peru.</span></p> <p><strong><span>Results:</span></strong><span> It is evident that economic factors are decisive in business experiences and decisions, highlighting the necessity of having contingency funds to prevent operational impacts. Through entrepreneurship, women achieved economic independence, enabling them to support their families and impacting their empowerment. It concludes that to promote economic opportunity equality, addressing financing needs, encouraging economic independence, strengthening family empowerment, improving customer management, and facilitating access to government funds are essential.</span></p> <p><strong><span>Conclusions:</span></strong><span> The narrative of the participants provides a solid foundation for designing specific policies and support programs that boost the economic empowerment of women entrepreneurs and encourage their active participation in the business sphere</span><span>.</span></p> <p><strong><span>Palabras clave:</span></strong><span> Women's Empowerment; Financial Capacity; Legal Framework; Economic Independence; Potential Customers; Access to Financing.</span></p>
Data from: Factoring economic costs into conservation planning may not improve agreement over priorities for protection
Conservation organizations must redouble efforts to protect habitat given continuing biodiversity declines. Prioritization of future areas for protection is hampered by disagreements over what the ecological targets of conservation should be. Here we test the claim that such disagreements will become less important as conservation moves away from prioritizing areas for protection based only on ecological considerations and accounts for varying costs of protection using return-on-investment (ROI) methods. We combine a simulation approach with a case study of forests in the eastern United States, paying particular attention to how covariation between ecological benefits and economic costs influences agreement levels. For many conservation goals, agreement over spatial priorities improves with ROI methods. However, we also show that a reliance on ROI-based prioritization can sometimes exacerbate disagreements over priorities. As such, accounting for costs in conservation planning does not enable society to sidestep careful consideration of the ecological goals of conservation.
Figure 2 in Socio-economic factors threatening the survival of Ganges River Dolphin Platanista gangetica gangetica in the upper Ganges River, India
Figure 2. Perception of fishermen about dolphin distribution in the Upper Ganges River.
Figure 1 in Socio-economic factors threatening the survival of Ganges River Dolphin Platanista gangetica gangetica in the upper Ganges River, India
Figure 1. The location of the study area in Uttar Pradesh, India. Source: WWF-India
Data from: Factoring economic costs into conservation planning may not improve agreement over priorities for protection
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Variations in leaf economics spectrum traits for an evergreen coniferous species: Tree size dominates over environment factors
<ol> <li>Many leaf traits strongly vary with tree size and environmental factors, but the importance of these factors to intraspecific variations of leaf traits in forest trees have rarely been <a><span>simultaneously</span></a> evaluated.</li> <li>We measured needle longevity and specific leaf area (SLA) and nitrogen (N) content of every needle age (0 to 4 year old) for 65 individuals with 0.3-100 cm diameter at breast height (DBH) for an evergreen coniferous species, <i>Pinus koraiensis</i> Sieb. et Zucc., in Northeast China. We <a><span>simultaneously</span></a> evaluated effects of tree size (DBH or tree height) and environment factors (light intensity, soil N content and water availability) on the needle longevity, SLA, foliage N content as well as the slopes of regressions of SLA and foliage N content against needle age.</li> <li>All of the studied leaf traits and slopes of regressions of SLA and foliage N content against needle age were significantly related to tree size. Tree height had a greater impact on SLA and area-based leaf N content (N<sub>area</sub>), whereas DBH was more important for needle longevity and mass-based leaf N content (N<sub>mass</sub>). The environment variables, light intensity, soil N content and water availability, were rather minor factors for trait variations compared with tree size. Significant influences of light intensity were found only on needle longevity, and soil N and water availability had no effects on the leaf traits.</li> <li>Our study clearly showed that tree size is an important driver of intraspecific variations in the key leaf traits of <i>Pinus koraiensis</i> in a natural forest. We also emphasize the importance of DBH or tree height varies depending on leaf traits, suggesting various mechanisms of size effects on the intraspecific variations in leaf traits. We suggest that ecological significance of leaf trait variations needs reconsideration incorporating tree size effect.</li> </ol>
Dataset with determinants or factors influencing graduate economics student preparation and success in an online environment
<p>The data relates to the paper that analyses the determinants or factors that best explain student research skills and success in the honours research report module during the COVID-19 pandemic in 2021. The data used have been gathered through an online survey created on the Qualtrics software package. The research questions were developed from demographic factors and subject knowledge including assignments to supervisor influence and other factors in terms of experience or belonging that played a role (see anonymous link at <a href="https://unisa.qualtrics.com/jfe/form/SV_86OZZOdyA5sBurY">https://unisa.qualtrics.com/jfe/form/SV_86OZZOdyA5sBurY</a>. An SMS was sent to all students of the 2021 module group to make them aware of the survey. They were under no obligation to complete it and all information was regarded as anonymous. We received 39 responses. The raw data from the survey was processed through the SPSS statistical, software package. The data file contains the demographics, frequencies, descriptives, and open questions processed. </p> <p>The study reported in this paper employed the mixed methods approach comprising a quantitative and qualitative analysis. The quantitative and econometric analysis of the dependent variable, namely, the final marks for the research report and the independent variables that explain it. The results show significance in terms of the assignments and existing knowledge marks in terms of their bachelor's average mark. We extended the analysis to a qualitative and quantitative survey, which indicated that the mean statistical feedback was above average and therefore strongly agreed/agreed except for library use by the student. Students, therefore, need more guidance in terms of library use and the open questions showed a need for a research methods course in the future. Furthermore, supervision tends to be a significant determinant in all cases. It is also here where supervisors can use social media instruments such as WhatsApp and Facebook to inform students further. This study contributes as the first to investigate the preparation and research skills of students for master's and doctoral studies during the COVID-19 pandemic in an online environment.</p>
Factor Endowments, Economic Integration, Sanctions, and Offshores: Evidence from Inward FDI in Russia
<p>These files reproduce figures and empirical results found in Cieślik, A., Gurshev, O. Factor Endowments, Economic Integration, Sanctions, and Offshores: Evidence from Inward FDI in Russia. <em>Comparative Economic Studies</em> (2022). https://doi.org/10.1057/s41294-022-00202-6 . If you use these files for your own work, please cite the abovementioned article. </p> <p>It includes data, graphs, and econometric analysis performed in the paper. We thank Peter Egger, Ariel Reshef, Matheu Parenti, Anne-Célia Disdier, Richard Frensch, Stefano Bolatto, Sarhad Hamza, one anonymous referee and participants of the graduate workshop hosted by Paris School of Economics for helpful comments on the earlier versions of the paper. Gurshev acknowledges financial assistance from University of Warsaw and host assistance of University of Bologna.</p>
Socio-Economic Factors Influencing Biogas Technology Uptake among Rural Households in Kuresoi South Sub-County, Nakuru County
<p>Biogas technology presents an alternative sustainable energy source that offers an opportunity to transform energy security, environmental sustainability, and reduction in greenhouse gas emissions. The research study explores the socioeconomic factors affecting biogas technology uptake among rural households in Kuresoi South Sub-County, Nakuru County. This is a descriptive study design based on the use of both primary and secondary data sources. The data collection covered 155 respondents through the use of questionnaires, focus group discussions, key informant interviews and observations. Selection of the respondents was done by using systematic random sampling, while data analysis was done using descriptive statistics, chi-square tests, and cross-tabulation supported by SPSS version 26. Results indicated that despite high levels of awareness, the adoption of biogas technology was low, with firewood remaining the primary source of energy in 68% of the households. Fixed dome and tubular were the biogas digester types in use, since they are relatively cheaper and more durable; however, economic factors, mainly household income, were the main determinant of uptake. The chi-square results indicated that there was a significant relationship between household income and uptake of biogas, χ² = 9.531, p = 0.048, implying that the poorer a household is, the greater the financial barrier to the technology. Level of education, too had a say in energy adoption; education and energy choice had a strong association-since χ² = 12.814, p = 0.002-which depicted that more educated households were more likely to adopt the technology. The gender factor is insignificant in influencing energy choices, underlining a proof from the fact that χ² = 2.119, p = 0.346, where broader socio-economic factors played a much greater role in decisions. This study also revealed out that radio was the effective channel for knowledge sharing and information dissemination related to biogas technology. On the other hand, partial understanding of the technical aspects has acted as a big barrier to the better diffusion of this technology. In conclusion, income levels and education are two main factors affecting the uptake of biogas technology. Enhanced education, targeted financial support and better outreach strategies go toward increasing adoption rates and supporting transitions to sustainable energy in rural areas.</p>
Socio-economic, Meteorological and Environmental Factors Associated With the Incidence of COVID-19
ClinicalTrials.gov study NCT05379621. IPD Sharing: Not stated. Countries: 1. Publications: 1.
A Trial Investigating the Effect of Specialised Palliative Care on Symptoms, Survival, Economical Factors and Satisfaction
ClinicalTrials.gov study NCT01348048. IPD Sharing: Not stated. Countries: 1. Publications: 5.
Variations in leaf economics spectrum traits for an evergreen coniferous species: Tree size dominates over environment factors
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Dataset with determinants or factors influencing graduate economics student preparation and success in an online environment
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Data from: Pet problems: biological and economic factors that influence the release of alien reptiles and amphibians by pet owners
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Influence of socio-economic, demographic and climate factors on the regional distribution of dengue in the United States and Mexico
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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)
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DANDI Archive for NWB datasets
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International Brain Laboratory public data
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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.