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Susceptibility Assessment of Human–Wildlife Conflict in Hirpora Wildlife Sanctuary Western Himalayas, Kashmir Using Geospatial Techniques
Get PDFManaging human-wildlife conflict requires a spatial understanding, but this is hindered by a lack of spatially explicit data. The present research was conducted in the Hirpora Wildlife Sanctuary (HWS) in Kashmir, India, with the aim of investigating possible geospatial connections between animal attacks on humans between 2019 and 2021. The patterns and drivers of human-wildlife conflicts around HWS were investigated using spatially-implicit data collected from 2019–2021. There were significant differences in attack patterns across the months, and majority of the attacks occurred outside the park. Most of the attacks occurred within 1 km of the buffer zone forests and croplands. A maximum of one victim per 1 km2 was observed for all attacking animals, indicating a strong positive correlation. A combination of kernel density and land use groups was used to calculate magnitude per unit area at risk of wildlife attack. Finally, it was found that the most dangerous sites were those near the forest that were covered by agricultural land and inhabited by humans. Our findings can help any local spatial decision-making process improve the coexistence of natural protection in the park and the safety of human communities living nearby
A Study on the 2016 and 2022 MS and OH Populations: How Obesity is Related to the Co-mingling of Median Household Income, Limited Access to Healthy Foods and Limited Access to Exercise Opportunities
Get PDFBackground: Obesity has plagued the United States for decades, and while the implications of obesity have drastically changed over time (from a sign of wealth to a possible implication of mal/low nutrition), its impacts on the country’s population are abrasive and costly. Objective: The aim is to address and investigate how factors such as Median Household Income (MHI), Limited Access to Healthy Food and Limited Access to Exercise interplay with and correlate to obesity. Methods: Data acquired from the County Health Rankings was analyzed using several analysis strategies (paired and unpaired T-tests, and regression plots, etc.). Only Mississippi and Ohio adults were included in the data. Results: Mississippi had a statistically significant lower MHI than Ohio in both 2016 (p \u3c .001) and 2022 (p \u3c .001). Mississippi also had statistically significant higher rates of obesity than Ohio in both 2016 (p \u3c .001) and 2022 (p \u3c .001). A Spearman Correlation revealed that in Ohio, as the MHI increased, the percentage of obesity in adults decreased; this was a weak but significant correlation (r = -.430, p \u3c .001). The same test revealed that in Mississippi, as the percentage of adults experiencing obesity decreased, MHI increased; this time there was a strong and significant correlation (r = -.753, p \u3c .001). A Stepwise Linear Regression on Ohio’s data stated that the best fitting model was statistically significant (p \u3c .001) and is responsible for 32.1% of the variance in the percent of obese adults; MHI was the most contributory to the results. Mississippi’s data resulted statistical significance (p \u3c .001) and is responsible for 67.9% of the variance in the percent obesity, again, most correlated to MHI. An Enter Method Linear Regression for Mississippi suggested the best fitting model was statistically significant (p \u3c .001) and is responsible for 59.4% of the variance in obesity. MHI is the largest and sole most important contributor to the model. Surprisingly, the percentage of people with Exercise Opportunities and with Limited Access to Healthy Foods did not have a statistically significant contribution to the model. Ohio yielded the same results (p \u3c .001); however, Ohio’s data was responsible for 32.3% of the variance in obesity. Conclusion: Obesity prevalence within a state is most readily predicted by looking at the Median Household Income. Despite limited healthy food access and exercise opportunities being reasonable assumed correlates, they are not significant indicators of obesity. This paper later discusses future directions of research and discusses how other understudied factors could lead to more fruitful connections to obesity prevalence
The Relationship Between Being Uninsured and Having Poor Health Outcomes and Experiences in Eastern Kentucky
Get PDFObjective: To examine health insurance and health outcome disparities in Eastern Kentucky since Kentucky’s implementation of the Affordable Care Act. Methods: Using data from County Health Rankings and Roadmap, rates of uninsurance will be compared before and a decade after implementation of the ACA in Kentucky (2013 and 2023). In addition, prevalence of certain health outcomes in Eastern Kentucky will be compared from 2013 and 2023 and correlation established between uninsured rates and particular health outcomes for 2023. Results: Since 2013, the percentage of those uninsured in Eastern Kentucky has seen a significant decline. While there is no correlation between the percent uninsured and health outcomes such as obesity, smoking, diabetes prevalence, poor or fair health, and poor mental health days in 2023, each of these outcomes saw significant changes from 2013 to 2023. Rates of smoking, diabetes, and poor or fair health all saw dramatic reductions while rates of obesity and poor mental health days significantly increased in Eastern Kentucky during this time
Estimation of Bovine Tuberculosis Prevalence, Associated Risk Factors, and Public Health Significance in District Dera Ismail Khan
Get PDFBovine tuberculosis (bTB) is zoonotic disease of global concern, affecting both animal and human populations. To estimate the prevalence of bovine TB in District Dera Ismail Khan and identify associated risk factors. A total of 138 cattle from different herds were included in the survey, and diagnostic tests, including the tuberculin skin test and Ziehl Neelsen stain, were employed. The results revealed a high prevalence of bovine TB, with an estimated prevalence of 10.87 % in the study area. Prevalence analysis based on tehsils revealed varying rates: 6.66 % in Dera Ismail Khan, 11.11 % in Kulachi, and 14.81 % in Daraban and Paroa. Paharpur had a prevalence of 7.40 %. The overall district prevalence was 10.87 %. Age-wise prevalence showed no significant difference, with 10 % in calves (\u3c1 year) and 9.33 % in 1-3-year-olds. Prevalence in cattle over 3 years was 13.95 %. Sex-wise prevalence showed no significant difference between male (10 %) and female (12.38 %) cows (p \u3e 0.05). Seasonal prevalence indicated 10 % in spring, 6.06 % in summer, 11.11 % in autumn, and 27.27 % in winter (highest prevalence) (p \u3c 0.05). Overcrowding of animals and inadequate biosecurity measures were significantly associated with higher prevalence rates (p \u3c 0.05). Herd size and presence of co-infections showed no significant correlation with bovine TB prevalence (p \u3e 0.05). This study found a high prevalence of bTB in District Dera Ismail Khan and identified overcrowding of animals and inadequate biosecurity measures as significant risk factors for disease transmission
Evaluation of Cotton Advanced Lines/Varieties for Genetic Diversity and Correlation Studies of Cotton Leaf Curl Virus Disease with Yield Contributing Traits in Cotton
Get PDFPlant genetic diversity aids in the creation of new varieties that are more resistant to pests and unfavorable climatic conditions. In order to discover varied parents and assess their cross-performance, the current study was carried out. The findings showed a substantial positive connection (0.81) between green bolls, plant height (0.57), and open bolls, as well as a significant positive correlation (0.52) between open bolls. On the other hand, a highly significant negative connection was discovered between the number of open bolls (-0.59), number of green bolls (-0.72), plant height (-0.78), and major stem nodes (-0.70) for the cotton leaf curl viral disease. Principal component analysis (PCA) showed that PC-I and PC-II accounted for 66.6% of the total variance. Plant height and green bolls were found to be positively correlated by PCA biplot analysis, but main stem nodes and open bolls showed a negative link, particularly with cotton leaf curl virus diseases. Based on cluster analysis, genotypes were divided into four clusters. Of these, Cluster-IV stood out because to its strong resistance to the cotton leaf curl virus disease and high yield, making it a good candidate for further breeding efforts. Other clusters include Mac-07, MNH-875, CRP-257, Super Okra, MNH-Super Gold, and GT/Bt Okra. The research emphasizes how crucial it is to use a variety of statistical methods to evaluate genetic diversity and support improved breeding practices. The knowledge that is derived will be useful in creating hybrids for upcoming breeding programs
The Foreigner in Our Midst: Jewish Rights Debates in Revolutionary France
Get PDFThe debates surrounding Jewish rights during the French Revolution concerned many of the same subjects that divide the Western world today. The fear of the other, immigration as a political tool, and the disagreements over assimilation are all subjects which feature prominently today. In this essay Evans sets out to explore these debates while fairly assessing the historical informants
The Guardian the Month of October 2024
Get PDFNews articles from The Guardian for the Month of October 2024. The Guardian is the official student-run newspaper for Wright State University. It has been published regularly since March of 1965.https://corescholar.libraries.wright.edu/guardian/3669/thumbnail.jp
Exploring Antibiotic Resistance and Exopolysaccharide Production in Bacillus Paramycoides from Wastewater
Get PDFAntibiotics have been found extensively in the environment, particularly in groundwater, sediments, and surface water. The purpose of this study was to isolate and identify antibiotic-resistant bacteria from wastewater collected from sewage (Sher Shah Colony, Raiwind) and an industrial area (Hudiara Drain Gajju Matta) in Lahore. Ten bacterial strains (Z1, Z2, Z3, Z4, Z5, Z6, Z7, Z8, Z9, and Z10) were isolated from the samples. All of these strains were gram-positive. Antibiotic resistance profiling showed that strain Z1 was most resistant to ampicillin (1500 μg/ml) among all of the antibiotics (tetracycline, penicillin, erythromycin, and chloramphenicol) that were tested. A growth curve study revealed that these strains showed constitutive enzyme activity. Exopolysaccharide (EPS) production of strains Z1 and Z3 was 1.34±0.010 g/L and 1.35±0.011 g/L, respectively, under non stress conditions, while in the presence of ampicillin stress, strain Z1 produced higher EPS (1.61±0.017 g/L) than strain Z3 (0.85±0.012 g/L). Thin layer chromatography (TLC) analysis of the extracted EPS of strain Z1 showed that it contained carbohydrates and amino acids. Fourier transform Infrared (FTIR) study of EPS produced by strain Z1 showed that it is made up of many different functional groups, including alkenes, alkynes, and carboxylic acids. Scanning Electron Microscopy (SEM) revealed that EPS became firmly connected to the cells in the presence of stress. The 16S rRNA gene sequence of strain Z1 (OR177988) showed 100% homology with the Bacillus paramycoides (MCCC1A04098). The findings contribute to the understanding of the microbial ecology of wastewater systems and highlight the need for further research on biofouling, bacterial adaptability, and the potential implications for public health and the environment
An Analysis of Moth Diversity in Garbhanga Reserve Forest, Basistha, Assam, India
Get PDFThe Garbhanga Reserve Forest, located on the south-western side of Guwahati City, covers an area of about 117 km2 and borders the foothills of Meghalaya (26°05´36˝N and 91°44´57˝E). Despite the constant threat of exploitation due to its proximity to the rapidly developing city, this area hosts a diverse ecosystem of moths and butterflies. In a study conducted over one year from January 2022 to December 2022, a total of 140 moth species were documented, with the majority belonging to the Erebidae family (46 species) and 1090 individuals, followed by the Crambidae family (31 species) and 704 individuals. The dominance of these families at 33 % and 22 %, respectively, highlights their significance in this ecosystem. The findings emphasize the importance of studying the population dynamics, distribution, and abundance of moth species in the urban disturbed Garbhanga Reserve Forest providing valuable insights into the ecosystem\u27s health and biodiversity
Data Mining and SME Growth: Exploring Evidence from Ghana
No full textIn developing economies, Small and Medium Enterprises (SMEs) have emerged as central pillars of growth and innovation, propelled by evolving market dynamics. Among these innovations, data analytics has distinguished itself as a pivotal force driving SME development, enabling these businesses to boost operational efficiency. This exploration delves into the application of data mining within the context of SMEs, specifically examining the catalysts for the adoption of Data Mining Systems (DMS) and assessing their impact on the advancement of SMEs. This research aims to unravel the intricate motivations behind SMEs\u27 incorporation of DMS into their operational frameworks, spotlighting both the opportunities unleashed and the challenges encountered. It accentuates the transformative role of data analytics in demystifying complex business landscapes, converting extensive datasets into actionable intelligence. Moreover, the study emphasizes the need for proficient data analysts who can shepherd SMEs through the digital transition, ensuring the effectiveness of these technological solutions (Venkatesh et al., 2003). Leveraging data from a fashion enterprise based in Ghana, this qualitative inquiry solicited insights from employees interacting with the firm\u27s DMS. The investigation centered on three pivotal questions regarding the adoption, duration, and motivations behind integrating DMS. Through an interpretive methodology, leveraging the Unified Theory of Acceptance and Use of Technology (UTAUT) as a theoretical lens, the study analyzed interview data to unearth established and emergent factors influencing the use of DMS (Walsham, 2006). A thematic analysis of the responses highlighted key attributes affecting DMS adoption. Initial findings reveal the profound advantages DMS proffers to SMEs in decision-making. However, the study also uncovers impediments, such as lack of awareness regarding data mining technologies among SME personnel and the acute necessity for qualified data analysts to lead DMS adoption efforts effectively. By synthesizing insights from existing literature with empirical observations, this research offers a nuanced perspective on the dynamics steering DMS adoption within SMEs, enriching the broader dialogue on leveraging data analytics to spur business growth in the developing world (Venkatesh et al., 2016)