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Forensic entomology requires knowledge of the developmental rates of the species that colonize a body after death to estimate the postmortem interval (PMI). These developmental rates may vary depending not only on the species but also on the geographic location due to population differences. Therefore, the objectives of this work were to determine the developmental duration of the forensically important fly Chrysomya megacephala under constant controlled and field condition temperatures and to compare these results, through a meta-analysis, with data reported by other authors on populations from different localities. For this, C. megacephala colonies were established in the laboratory, and the duration of the life cycle was studied at two controlled temperatures (25 °C and 27 °C) and field conditions (27.5 ± 3.2 °C). Analysis of variance was performed to determine differences in developmental time and larval length between constant laboratory temperatures and field conditions. A generalized linear model was performed with predictor variables extracted from the literature (diet, relative humidity, latitude, longitude) to evaluate the effect of population variation on developmental times. The results showed significant differences in developmental times between 25 and 27 °C. As expected, the complete life cycle of C. megacephala was shorter at 27 °C. Finally, the meta-analysis suggested differences between the developmental times of different populations, based on temperature and geographic location. The results of this study provide fundamental developmental data to use C. megacephala in PMI estimations. Finally, we suggest that, when making expert reports, information from local populations should be used to determine a more accurate and reliable PMI.

To meet the national development goals in India on poverty alleviation and to trail the Sustainable Development Goals (SDG), policy makers need to have adequate information on poverty in the country. To this end the aim of this paper is to analyse the trends in multidimensional poverty at the all-India level, across geographic locations, castes and religious groups. We have used Alkire–Foster methodology to measure multidimensional poverty index (MPI) and utilized National Family Health Survey unit level data of the latest three rounds 2005–06, 2015–16 and 2019–21. To the best of our understanding this is the first paper that utilizes the latest data sets to analyse the trends of MPI in India. We have also made a comparative assessment of trends of poverty in India measured by Global MPI approach and India’s MPI approach. Over the period 2005–2006 to 2019–2021 the absolute decline in MPI was larger in rural areas of India. However, the contribution to MPI in rural areas is relatively high and that increased over time. There was no evidence of reduction of inter-caste and inter-religious based disparities. There are larger doses of decline in MPI in the sub period 2015–2016 to 2019–2021 but the decline across the states of India continues to be non-regressive. The states which were worst performing in 2005–2006 continue to be the same in 2019–2021. The paper concludes that by exploring the MPI over time one can decipher the urgencies in policy development to move towards the SDGs.

Intestinal microbiota plays an important role in promoting digestion, metabolism, and immunity. Intestinal microbiota and fatty acids are important indicators to evaluate the health and nutritional composition of Procambarus clarkii . They have been shown to be strongly influence by environmental and genetic factors. However, it is not clear whether environmental factors have a greater impact on the intestinal microbiota and fatty acid composition of crayfish. The link between the intestinal microbial communities and fatty acid (FA) compositions of red swamp crayfish from different geographical has not yet been studied. Thus, the current paper focuses on the influence of different environments on the fatty acids in muscles of crayfish and the possible existence between gut microbiota and fatty acids. Therefore, in this study, we compared the fatty acid compositions and intestinal microbiota of five crayfish populations from different geographical locations. The results were further analyzed to determine whether there is a relationship between geographical location, fatty acid compositions and intestinal microbiota. The gut microbial communities of the crayfish populations were characterized using 16S rRNA high-throughput gene sequencing. The results showed that there were significant differences in FA compositions of crayfish populations from different geographical locations. A similar trend was observed in the gut microbiome, which also varied significantly according to geographic location. Interestingly, the analysis revealed that there was a relationship between fatty acid compositions and intestinal microbes, revealed by alpha diversity analysis and cluster analysis. However, further studies of the interactions between the P. clarkii gut microbiota and biochemical composition are needed, which will ultimately reveal the complexity of microbial ecosystems with potential applications in aquaculture and species conservation.

Introduction: The problem this research the childrens have low motor skills. This study aims to: (1) assess the motor abilities of children in highland areas, (2) assess the motor skills of children in lowland areas, (3) assess the motor skills of children in coastal areas, and (4) analyze the differences in motor skills among elementary school students based on geographical location (highlands, lowlands, coastal areas). Objective: to state the objective and scope of the research or hypotheses. Methodology: The quantitative research method used in this study involved a survey of  State Elementary School 26 Singgalang Tanah Datar, Padang City Experimental State Elementary School, and State Elementary School 01 Pariaman City. The study's population comprised 188 students, from which a sample of 115 students was selected using the purposive sampling technique. The research instrument such as the standing broad jump, ball passing to the wall, 4-second dash and basketball throw. The instrument has a validity score of 0.64 and a reliability score of 0.92. Results: The results indicate that geographical factors ( highland, lowland, coastal areas) significantly affect children's motor skills. Discussion: Effect of different geographical locations on levels of motor skills. Conclusions:  (1) children from the highland region showed good motor skill levels; (2) children from the lowland region displayed sufficient motor skills; (3) children in the highlands engaged in more motor skill activities compared to those in lowland and coastal areas; and (4) there were notable differences in motor skills between children in coastal areas  and lowland areas.

Background Host associated gut microbiota are important in understanding the coevolution of host-microbe, and how they may help wildlife populations to adapt to rapid environmental changes. Mammalian gut microbiota composition and diversity may be affected by a variety of factors including geographic variation, seasonal variation in diet, habitat disturbance, environmental conditions, age, and sex. However, there have been few studies that examined how ecological and environmental factors influence gut microbiota composition in animals' natural environments. In this study, we explore how host habitat, geographical location and environmental factors affect the fecal microbiota of Cynomys ludovicianus at a small spatial scale. We collected fecal samples from five geographically distinct locations in the Texas Panhandle classified as urban and rural areas and analyzed them using high throughput 16S rRNA gene amplicon sequencing. Results The results showed that microbiota of these fecal samples was largely dominated by the phylum Bacteroidetes . Fecal microbiome diversity and composition differed significantly across sampling sites and habitats. Prairie dogs inhabiting urban areas showed reduced fecal diversity due to more homogenous environment and, likely, anthropogenic disturbance. Urban prairie dog colonies displayed greater phylogenetic variation among replicates than those in rural habitats. Differentially abundant analysis revealed that bacterial species pathogenic to humans and animals were highly abundant in urban areas which indicates that host health and fitness might be negatively affected. Random forest models identified Alistipes shahii as the important species driving the changes in fecal microbiome composition. Despite the effects of habitat and geographic location of host, we found a strong correlation with environmental factors and that- average maximum temperature was the best predictor of prairie dog fecal microbial diversity. Conclusions Our findings suggest that reduction in alpha diversity in conjunction with greater dispersion in beta diversity could be indicative of declining host health in urban areas; this information may, in turn, help determine future conservation efforts. Moreover, several bacterial species pathogenic to humans and other animals were enriched in prairie dog colonies near urban areas, which may in turn adversely affect host phenotype and fitness.

The Location based advertising (LBA) is a new and commercial scheme for advertisers to get the information via personalized texts which is sent openly to mobile phones by their geographic location. Because of the enhanced interaction with the marketer and the user, there is an increasing challenge about privacy among the concerns of mobile users and personalization. This paper presents a deep learning based bidirectional hybrid optimized model for LBA. Initially, the location data is attained by the Geographical Information System (GIS) for receiving the accurate information about the location. The input collected location information is send to the word embedding approach. This generates a vector associated with each word and it creates a matrix. Afterwards, the features are extracted using deep sparse auto encoder (DSAE) approach. Finally, Bidirectional optimized hybrid model i.e. Bidirectional Long-Short Term Memory-Deep Neural Network and Adaptive Sunflower Optimization Algorithm (BLSTM-DNN-ASOA) is used for the better classification. In order to effectively provide the location based services, a hybrid model named BLSTM-DNN is utilized and the optimal solution is obtained by the proposed ASOA algorithm. The proposed LBA with GIS is simulated in JAVA platform. The performance of the proposed algorithm is assessed depends on the metrics named as Accuracy (98.97%), Precision (99.7%), F-measure (99.48%), computational time (99.8 ms), Area under the curve (AUC) (82.23%) and Recall (99.52%) in terms of different number of documents. The simulation result of the proposed algorithm provides better performance in LBA than the existing approaches.

Cropland abandonment has been a widespread phenomenon in mountainous areas due to the increasing number of natural disasters and the massive migration of rural labor in the process of rapid urbanization. Land transfer is a crucial prerequisite for ensuring food security and fostering rural revitalization. How to promote land transfer in mountainous areas remains a challenging but important task. Nevertheless, there is a dearth of research examining land transfers among farm households that specifically address mountainous regions, and the influence of grassroots governance and geographic location has not been thoroughly elucidated within this particular context. Based on 895 household samples collected in Dabie Mountainous Area in China, this study employs binary and ordinal logistic regression models to provide a more comprehensive analysis on land transfers among rural households and the determinants, including the decision to transfer land, the existence of land transfer rents, the channel of land transfer, the duration of the transfer, the pre-transfer cultivation situation, and the level of satisfaction with the land transfer rent. The findings reveal that grassroots governance, geographic location, livelihood capital, and demographic factors significantly influence land transfers among rural households. Specifically, villagers’ public participation positively affects land transfer participation ( β =0.235, p <0.05), while the operation of village rules and regulations negatively impacts it ( β =−0.296, p <0.05). Village cadre satisfaction positively influences both land transfer rent ( β =0.274, p <0.05) and rent satisfaction ( β =0.303, p <0.05). Improved civil relations in the village correlate with lower land transfer rent ( β =−0.511, p <0.05), while a better social atmosphere is associated with higher satisfaction with transfer rent ( β =0.575, p <0.01). Households at higher elevations tend to prefer government-mediated land transfers with longer durations. The distances to the township and county centers have contrasting effects on land transfer rent, but their impacts on participation in land transfer, choice of transfer channel, and duration are consistent. The study also found that different types of livelihood capital, as well as the demographic characteristics of households, significantly affect various aspects of land transfer. These empirical findings can inform policymaking to promote more efficient land transfers in mountainous region.

Both ammonia-oxidizing bacteria (AOB) and archaea (AOA) can play important roles in ammonia biotransformation in ecosystems. However, the factors regulating the distribution of these microorganisms in lacustrine ecosystems remain essentially unclear. The present study investigated the effects of geographic location on the distribution of sediment AOA and AOB in 13 freshwater lakes on the Yunnan Plateau (China). The spatial dissimilarity in the abundance and structure of sediment AOA and AOB communities was observed in these plateau lakes. AOA abundance was usually less than AOB abundance, and the AOA/AOB ratio was positively correlated with water depth. Nitrososphaera-like AOA occurred in most of the studied lakes and were dominant in two lakes. Nitrosospira was the dominant AOB species in most of the lakes, while Nitrosomonas showed high abundance only in three lakes. In addition, geographic location was found to affect lake sediment AOB community structure.

Background Rhizosphere soil physicochemical, endophytic fungi have an important role in plant growth. A large number of endophytic fungi play an indispensable role in promoting plant growth and development, and they can provide protection for host plants by producing a variety of secondary metabolites to resist and inhibit plant pathogens. Due to the terrain of Gansu province is north–south and longitudinal, different climatic conditions, altitude, terrain and growth environment will affect the growth of Codonopsis pilosula , and the changes in these environmental factors directly affect the quality and yield of C. pilosula in different production areas. However, In C. pilosula , the connection between soil nutrients, spatiotemporal variation and the community structure of endophytic fungi isolated from C. pilosula roots has not been well studied. Results Seven hundred six strains of endophytic fungi were obtained using tissue isolation and the hyphaend-purification method from C. pilosula roots that picked at all seasons and six districts (Huichuan, HC; Longxi, LX; Zhangxian, ZX; Minxian, MX; Weiyuan, WY; and Lintao, LT) in Gansu Province, China. Fusarium sp . (205 strains, 29.04%), Aspergillus sp . (196 strains, 27.76%), Alternaria sp . (73 strains, 10.34%), Penicillium sp . (58 strains, 8.22%) and Plectosphaerella sp . (56 strains, 7.93%) were the dominant genus. The species composition differed from temporal and spatial distribution (Autumn and Winter were higher than Spring and Summer, MX and LT had the highest similarity, HC and LT had the lowest). physical and chemical of soil like Electroconductibility (EC), Total nitrogen (TN), Catalase (CAT), Urease (URE) and Sucrase (SUC) had significant effects on agronomic traits of C. pilosula ( P  < 0.05). AK (Spring and Summer), TN (Autumn) and altitude (Winter) are the main driving factors for the change of endophytic fungal community. Moreover, geographic location (such as altitude, latitude and longitude) also has effects on the diversity of endophytic fungi. Conclusions These results suggested that soil nutrients and enzyme, seasonal variation and geographical locations have an impact on shaping the community structure of culturable endophytic fungi in the roots of C. pilosula and its root traits. This suggests that climatic conditions may play a driving role in the growth and development of C. pilosula .

The geographic pattern of cropland is an important risk factor for invasion and saturation by crop-specific pathogens and arthropods. Understanding cropland networks supports smart pest sampling and mitigation strategies. We evaluate global networks of cropland connectivity for key vegetatively propagated crops (banana and plantain, cassava, potato, sweet potato, and yam) important for food security in the tropics. For each crop, potential movement between geographic location pairs was evaluated using a gravity model, with associated uncertainty quantification. The highly linked hub and bridge locations in cropland connectivity risk maps are likely priorities for surveillance and management, and for tracing intraregion movement of pathogens and pests. Important locations are identified beyond those locations that simply have high crop density. Cropland connectivity risk maps provide a new risk component for integration with other factors—such as climatic suitability, genetic resistance, and global trade routes—to inform pest risk assessment and mitigation.