Lessons learnt from measures taken to prevent rabies introduction and spread into a long rabies free territory (case study of the Irkutsk Oblast) by I. V. Meltsov, A. M. Ablov, E. N. Shkolnikova, M. E. Koplik, P. A. Minchenko, T. V. Desyatova, I. D. Zarva, A. D. Botvinkin, A. Ye. Metlin

“…The paper demonstrates cartograms of fox and wolf population density along with designation of sites, where oral vaccination of wild carnivores was performed.…”
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Assessment of vulnerability to fluvial floods: Case of municipalities of the Gidra River Basin, Slovakia by Matej Vojtek, Soheyl Moradi

“…Material and methods: Three indicators (number of buildings within a 100 m radius from the watercourse; length of roads within a 100 m radius from the watercourse; and number of bridges over a watercourse) representing the economic vulnerability, and seven indicators of social vulnerability (population density of municipalities; share of residents aged 65+ in the total number of residents; share of unemployed residents in the total number of economically active residents; share of households with six and more persons in the total number of households; share of incomplete households in the total number of households; share of residents without education and with primary education in the the total number of residents; and share of residents with disabilities in the total number of residents) were used to determine the respective economic flood vulnerability sub-index (EFVsI) and social flood vulnerability sub-index (SFVsI). …”
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Chlamydia cases in women of reproductive age, 2006–2020: an analysis of surveillance data from Southern China by Peizhen Zhao, Peng Liang, Jinshen Wang, Wenqian Xu, Shujie Huang, Cheng Wang

“…City-level factors (population density, net migration rate, and male-to-female sex ratio) were derived from the Guangdong Statistical Yearbook and the Guangdong Health and Family Planning Statistical Yearbook. …”
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Environmental sustainability of urban expansion: Implications for transport emissions, air pollution, and city growth by Susana Lopez-Aparicio, Henrik Grythe, Arkadiusz Drabicki, Konrad Chwastek, Kamila Toboła, Lidia Górska-Niemas, Urszula Kierpiec, Miha Markelj, Joanna Strużewska, Bartosz Kud, Gabriela Sousa Santos

“…Results indicate that a compact future scenario reduces transport CO2 emissions and urban NO2 levels, though increases in population density raise exposure to air pollution. A sprawl future scenario increases CO2 and NOx emissions due to longer commutes and congestion, and NO2 levels increase up to 25% in parts of the city. …”
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Characteristics, location, and usage patterns of resting burrows in Chinese pangolins: Insights from radio-telemetry tracking by Nick Ching-Min Sun, Jing-Shiun Lin, Kurtis Jai‑Chyi Pei

“…To conclude the findings:1) burrow count, while useful for identifying pangolin presence, is not a suitable quantitative indicator of population density. 2) Most resting burrows had compacted soil at the entrance, which could be mistaken for old or inactive burrows in other studies. 3) Resting burrows function as permanent structures that are reused across seasons instead of seasonal adaptations. 4) Preserving low-disturbance habitats will be critical for ensuring sufficient resting burrow sites, thereby supporting the long-term viability of pangolin populations. …”
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Investigating Escherichia Coli (E. Coli) Contamination of Street Foods in Manjari Kabale District. by Unasi, Daniel

“…To cater for the high population density in kabale municipality, native people maneuvered to attain sustainability and among food supply was most important to maintain life in these urban areas. …”
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Environmental microbial communications in gram-positive and gram-negative bacteria by P. Srikanth, D. Sivakumar, J. Nouri

“…The concentration of these signalling substances rises above a critical level when the population density does, causing particular gene expression patterns in the microorganisms. …”
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Geospatial Data and Deep Learning Expose ESG Risks to Critical Raw Materials Supply: The Case of Lithium by Christopher J. M. Lawley, Marcus Haynes, Bijal Chudasama, Kathryn Goodenough, Toni Eerola, Artem Golev, Steven E. Zhang, Junhyeok Park, Eleonore Lèbre

“…The high AUC of the deep learning model demonstrates that public geospatial data can accurately predict natural resources conflicts, but we show that machine learning results are biased by proxies for population density and likely underestimate the potential for conflict in remote areas. …”
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Trend analysis of precipitation and temperature in Lahaul-Spiti district, Himachal Pradesh, India by Pankaj Kumar, Dhanjit Deka, Md. Arif Husain, Manish Kumar, Pandurang Choudhari, Shipra Singh, Azka Kamil, Abhishek Banerjee

“…The district has the lowest population density of 2 persons/km2 because of the harsh climate and rough topography that act as barriers to population growth. …”
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Cross-Sectional Survey to Assess Tobacco and Nicotine Product Use since the Introduction of Heated Tobacco Products in Japan: Wave 2 by Prasad Krishna, Shetty Mandara, Edward Lauren, Kanitscheider Claudia, Marczykowski Felix

“…A 3-stage probability sampling method was applied that was geographically stratified by street blocks proportionate to population density. Respondents self-reported patterns of product use and reasons for HTP use. …”
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Hotspots in peril: Misalignment of conservation efforts and ecological values in a shallow coastal sea by Kasper J. Meijer, Oscar Franken, Sterre Witte, Sander J. Holthuijsen, Tjisse van der Heide, Laura L. Govers, Han Olff

“…Such conflicts are especially found in coastal areas with high human population density and high natural productivity. Here, we aim to provide a framework to quantitatively and qualitatively assess conservation conformity using multiple indicators to identify hotspots of ecological quality. …”
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Assessment of ecological environment quality and their drivers in urban agglomeration based on a novel remote sensing ecological index by Fangyuan Lu, Chen Zhang, Haoyu Cao, Xibin Wang, Tong Zheng, Zhenfang Huang

“…However, notable regional disparities exist, with a spatial pattern characterized by “low EEQ in the northwest and high in the southeast.” (2) An analysis of NRSEI variations over this period indicates that the YRDUA’s EEQ has remained largely stable, although ecological degradation is concentrated in densely populated, low-lying areas near lakes, rivers, and plains. (3) Topographic complexity, economic development, and population density are the primary factors driving spatial differences in EEQ, with interactive effects among these factors exerting a more significant influence than individual factors alone.…”
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Interspecific Competition Between <i>Eotetranychus sexmaculatus</i> Riley and <i>Oligonychus biharensis</i> Hirst (Acari: Tetranychidae) by Lijiu Zheng, Yong Zhang, Xia Shi, Wei Gan, Fangping Zhang, Yueguan Fu, Ya Liu, Junyu Chen, Zhengpei Ye

“…Five initial population densities of <i>E. sexmaculatus</i> and <i>O. biharensis</i> were evaluated in mixed populations: 0:30, 10:20, 15:15, 20:10, and 30:0. …”
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Actual and optimal abundance of the main ungulate species in forestry and hunting districts of Ukraine by Ihor Sheihas, Ihor Gulyk

“…Calculations of the allowable population density and the optimal abundance of ungulates depending on the quality score of the grounds were made: from the least suitable to the best. …”
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Within-species variation in the gut microbiome of medaka (Oryzias latipes) is driven by the interaction of light intensity and genetic background by Evangelista, Charlotte, Kamenova, Stefaniya, Diaz Pauli, Beatriz, Sandkjenn, Joakim, Vøllestad, Leif Asbjørn, Edeline, Eric, Trosvik, Pål, de Muinck, Eric Jacques

“…In pond mesocosms, the two lineages were subjected to contrasting population density and light intensity (used as proxies of resource availability). …”
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Analysis of epidemiological trends and risk factors in high-risk areas for pulmonary tuberculosis: an observational longitudinal study in Xinjiang, China by Liping Zhang, Di Wu, Yanling Zheng, Yaoqin Lu, Salawati Haritebieke, Guangchao Liu

“…Objective To explore the spatial and temporal variations in the long-term risk of developing tuberculosis (TB) and the factors influencing it in order to contribute to the goal of eradicating TB.Design Observational longitudinal study.Setting Xinjiang, China, 2005–2019.Primary and secondary outcome measures Comparison of TB incidence across age, period, cohort and space using socioeconomic (including gross domestic product per capita, population density, public budget revenue and total retail sales of consumer goods), public health (including the number of hospital beds, health technicians and basic medical insurance for urban residents) and environmental variables (PM2.5, mean air temperature, mean wind speed, mean relative humidity and precipitation). …”
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The preference of migratory waterbirds to winter at a key location on the East Asian-Australasian flyway and its implications for habitat conservation by Shuangliang Dai, Yanyan Zhou, Jingsi Gao, Guowei Cheng, Linlin Wang, Haiyan Bai, Xiaoyu Lei, Hualin Xu, Xian-zhong Mao

“…However, when the human population density and relative nighttime light intensity in the Shenzhen Bay area exceeded certain thresholds, the effectiveness of protected areas declined. …”
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Spatial co-distribution of tuberculosis prevalence and low BCG vaccination coverage in Ethiopia by Haileab Fekadu Wolde, Archie C. A. Clements, Beth Gilmour, Kefyalew Addis Alene

“…While travel time to cities (Mean = 0.28, 95% BCI: 0.15, 0.41) and distance to health facilities (Mean = 0.43, 95% CI 0.22, 0.63), were positively associated, population density (Mean = −0.04, 95% BCI −0.05, −0.02) was negatively associated, with the proportion of unvaccinated children for BCG indicating areas near health facilities and cities have better BCG coverage. …”
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Historical and projected forest cover changes in the Mount Kenya Ecosystem: Implications for sustainable forest management by Brian Rotich, Abdalrahman Ahmed, Benjamin Kinyili, Harison Kipkulei

“…Explanatory factors of LULC change (slope, aspect, population density, proximity to rivers, roads, and towns) were used to project LULC for 2035 using Cellular Automata and Markov Chain Analysis (CA-MCA).Six LULC types (open forest, closed forest, cropland, bareland, built-up, shrubland and grassland) were successfully classified with accuracies exceeding 82.5% and Kappa coefficients above 0.77. …”
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Effect of Kind and Dosage of Enrichment Materials on the Nutritional Quality of Rotifers Especially n3-HUFA by Muhammad Agus Suprayudi

“…In addition Nannochloropsis oculata as an enrichment material showed the highest population density of rotifers during enrichment periods.  …”
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