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While the primary sequences of human proteins have been cataloged for over a decade, determining how these are organized into a dynamic collection of multiprotein assemblies, with structures and functions spanning biological scales, is an ongoing venture. Systematic and data-driven analyses of these higher-order structures are emerging, facilitating the discovery and understanding of cellular phenotypes. At present, knowledge of protein localization and function has been primarily derived from manual annotation and curation in resources such as the Gene Ontology, which are biased toward richly annotated genes in the literature. Here, we envision a future powered by data-driven mapping of protein assemblies. These maps can capture and decode cellular functions through the integration of protein expression, localization, and interaction data across length scales and timescales. In this review, we focus on progress toward constructing integrated cell maps that accelerate the life sciences and translational research.

A large body of literature has examined specificity and transfer of perceptual learning, suggesting a complex picture. Here, we distinguish between transfer over variations in a task-relevant feature (e.g., transfer of a learned orientation task to a different reference orientation) and transfer over a task-irrelevant feature (e.g., transfer of a learned orientation task to a different retinal location or different spatial frequency), and we focus on the mechanism for the latter. Experimentally, we assessed whether learning a judgment of one feature (such as orientation) using one value of an irrelevant feature (e.g., spatial frequency) transfers to another value of the irrelevant feature. Experiment 1 examined whether learning in eight-alternative orientation identification with one or multiple spatial frequencies transfers to stimuli at five different spatial frequencies. Experiment 2 paralleled Experiment 1, examining whether learning in eight-alternative spatial-frequency identification at one or multiple orientations transfers to stimuli with five different orientations. Training the orientation task with a single spatial frequency transferred widely to all other spatial frequencies, with a tendency to specificity when training with the highest spatial frequency. Training the spatial frequency task fully transferred across all orientations. Computationally, we extended the identification integrated reweighting theory (I-IRT) to account for the transfer data (Dosher, Liu, & Lu, 2023; Liu, Dosher, & Lu, 2023). Just as location-invariant representations in the original IRT explain transfer over retinal locations, incorporating feature-invariant representations effectively accounted for the observed transfer. Taken together, we suggest that feature-invariant representations can account for transfer of learning over a task-irrelevant feature.

Despite numerous studies in the field of dementia and Alzheimer's disease (AD), a comprehensive understanding of this devastating disease remains elusive. Bulk transcriptomics have provided insights into the underlying genetic factors at a high level. Subsequent technological advancements have focused on single-cell omics, encompassing techniques such as single-cell RNA sequencing and epigenomics, enabling the capture of RNA transcripts and chromatin states at a single cell or nucleus resolution. Furthermore, the emergence of spatial omics has allowed the study of gene responses in the vicinity of amyloid beta plaques or across various brain regions. With the vast amount of data generated, utilizing gene regulatory networks to comprehensively study this disease has become essential. This review delves into some techniques employed in the field of AD, explores the discoveries made using these techniques, and provides insights into the future of the field.

ABSTRACT Wolf spiders can learn simple spatial navigation tasks. Previous studies have shown that the wolf spider Tigrosa helluo can use environmental edge features (reference frame landmarks) to learn the location of a dry target in flooded T‐mazes; however, the relative importance of different types or numbers of landmark cues to spatial learning remains unknown. We used a modified open arena water maze and recorded the ability of adult female T. helluo to find a target reward (a dark and dry cup) among cups that were identical to the target but flooded. We measured variation in spatial learning by measuring time to target with no landmark (control), with a beacon (a landmark that is part of the target), with an associative cue (a landmark associated with a specific navigational action), and with both a beacon and an associative cue (N = 92 subjects, n = 23 per landmark cue treatment). For each treatment, we tested females for five trials each on four consecutive days, with the last trial on the fourth day having an altered target location, totaling 19 training trials and one reversal trial (1840 trials). We found that spiders took significantly less time to find the target over subsequent trials within a day and learned more quickly when landmark cues were present, but we found no difference in the type or number of landmark features in the meantime to target entrance. After learning a target location, moving the landmark significantly increased the mean time to target entrance in the combined beacon and associative cue treatment relative to other treatments. Our results indicate that wolf spiders use visual beacons and associative cue landmarks alone or in combination and that performance improves across trials when landmarks are present and deteriorates more when multiple landmarks are moved. [ABSTRACT FROM AUTHOR]

Tumor-infiltrating B cells play a significant role in tumor development, progression, and prognosis, yet a comprehensive classification system is lacking. To address this gap, we present a pan-cancer single-cell RNA sequencing (scRNA-seq) atlas of tumor-infiltrating B and plasma cells across a large sample cohort. We identify key B cell subset signatures, revealing distinct subpopulations and highlighting the heterogeneity and functional diversity of these cells in the tumor microenvironment. We explore associations between B cell subsets and checkpoint inhibitor therapy responses, finding subset-specific effects on overall response. Additionally, we examine B and T cell crosstalk, identifying unique ligand-receptor pairs for specific B cell subsets, spatially validated. This comprehensive dataset serves as a valuable resource, providing a detailed atlas that enhances the understanding of B cell complexity in tumors and opens new avenues for research and therapeutic strategies. [Display omitted] • A scRNA-seq atlas identifies ten clusters of intratumoral B and plasma cells • Specific B cell subsets are associated with checkpoint inhibitor therapy responses • Atlas-derived B cell gene signatures validated in spatial analyses • Publicly available Shiny tool enables users to interactively explore the atlas Fitzsimons et al. present a comprehensive pan-cancer single-cell RNA-seq atlas of intratumoral B cells, identifying ten distinct B and plasma cell clusters. They uncover associations with checkpoint inhibitor therapy response, explore B-T cell crosstalk, validate findings with spatial data, and offer an interactive tool for further research. [ABSTRACT FROM AUTHOR]

Background: Peste des petits ruminant (PPR) is a contagious disease caused by the peste des petits ruminants virus (PPRV). The disease poses a significant economic threat to small ruminant production in Ethiopia, particularly to the striving pastoral production system. A cross-sectional study was conducted to estimate the seroprevalence and associated risk factors of PPR in the small ruminants of the Borena Zone. A total of 384 serum samples were collected randomly from sheep and goats and examined for the presence of PPRV antibodies using competition enzyme-linked immune sorbent assay (c-ELISA). Additionally, a retrospective analysis of five years of outbreak data was performed to provide insight into the spatial and temporal distribution of the disease. Results: The seroprevalence of PPRV antibodies in nonvaccinated, vaccinated, and unknown vaccination status of small ruminants in this study was found to be 32.1%, 68.8%, and 45.5%, respectively. Multivariable logistic analysis revealed a statistically significant association between PPRV seropositivity and several factors, including age, animal origin, flock size, and veterinary services status. A retrospective analysis revealed 53 PPR outbreaks in the Borena Zone from 2018 to 2022, exacerbated by low vaccination coverage relative to the at-risk animal population. Conclusion: The study revealed significant gaps in current vaccination efforts, with herd immunity levels falling below the FAO-WOAH recommended threshold of 80%. Despite Ethiopia's ambitious goal to eradicate PPR by 2027, the frequent outbreaks and insufficient herd immunity highlight the inadequacy of the existing strategies. To effectively move toward eradication, Ethiopia must align its approach with the global PPR eradication framework, which emphasizes a comprehensive strategy that includes diagnostics, surveillance, prevention, and the establishment of a robust veterinary regulatory system, rather than relying solely on vaccination. Overcoming logistical challenges, improving vaccination coverage, and optimizing the timing of vaccination campaigns, especially in hard-to-reach areas, will be crucial for reducing outbreaks and making progress toward eradication. [ABSTRACT FROM AUTHOR]

The article "Spatial clustering of dengue cases during the 2024 epidemic in Brazil" published in the Journal of Travel Medicine explores the spatial distribution of dengue cases in Brazil during the severe 2024 epidemic. The study reveals significant spatial heterogeneity in dengue incidence rates, with clusters primarily in the South and Southeast regions. Lower coverage rates of primary healthcare and family health teams were associated with higher dengue incidence, highlighting the importance of robust healthcare systems in controlling vector-borne diseases. The findings emphasize the need for targeted public health interventions, including enhanced vector control, infrastructure improvements, community health education, and strategic vaccine distribution, to reduce the burden of dengue in Brazil. [Extracted from the article]

We examine the relationship between economic participation rates and rates of assaults, vandalisms, and drug offenses in neighborhoods in Forsyth County, N.C. We use a unique dataset containing assault, vandalism, and drug offense rates at the neighborhood level from 2013 to 2020. We estimate a two-way fixed effects spatial Durbin regression model relating crime rates to economic participation rates for the three types of crime. The results show that neighborhoods, proxied with census tracts, with higher economic participation rates among its residents have significantly lower crime rates. The relationship exists even after controlling for unobserved heterogeneity and spatial autocorrelation. Workforce programs that recruit individuals from neighborhoods with low economic participation rates may have the additional benefit of reducing crime. [ABSTRACT FROM AUTHOR]

Prepositions are among the most difficult parts of speech for ESL learners owing to their polysemous nature and how they behave in different languages. The present study aims to determine how English prepositions are represented in English Language textbooks designed by the National Council of Educational Research and Training (NCERT) for Classes I and II in India. For a comparison of the frequency of prepositions in English, we have selected the British National Corpus. The study revealed that though the choice of prepositions in the textbooks is as par with their occurrences in the standard English corpus, their senses are not always primary, i.e., spatial. We found instances of temporal and metaphorical senses as well. One significant finding of this study is the relatively very low frequency of temporal use of prepositions as compared to the proto-typical spatial sense in these textbooks. The metaphorical uses of some common prepositions, which are more abstract and complex, are higher in frequency, especially in the exercises for giving instructions. [ABSTRACT FROM AUTHOR]

Agricultural nutrients nitrogen and phosphorus can subsequently be transported to waterways and are often managed through the adoption of best management practices (BMPs). However, we have a poor understanding of how the use of BMPs varies spatially and how BMP adoption might be related to nutrient yields in surface waters. To address this, we performed a survey of agricultural landowners across New York State and compared this with estimates of annual incremental nitrogen and phosphorus yields of agricultural origin from the Spatially Referenced Regressions On Watershed attributes (SPARROW) model. Using these socio-behavioral data and SPARROW predictions, we perform colocation analysis to identify areas where watersheds with high nutrient yield from agriculture are collocated with non-use of agricultural BMPs. This colocation analysis offers a novel methodology for identifying areas where monitoring of waterways and promotion of best management practices could be targeted to achieve the greatest benefits. [ABSTRACT FROM AUTHOR]

Avian influenza (AI) is a viral infection that profoundly affects global poultry production. This study aimed to identify the spatial and temporal factors associated with AI in Thailand, using a geographic information system (GIS)–based multi‐criteria decision analysis (MCDA) approach. We discovered that high‐risk areas for AI were primarily concentrated in the central and lower northern regions of the country, with fewer occurrences in the northeastern and southern regions. Model validation using historical outbreak data showed moderate agreement (AUC = 0.60, 95% CI = 0.58–0.61). This study provides valuable insights for planning national AI surveillance programs and aiding in disease prevention and control efforts. The efficiency and effectiveness of disease surveillance at the national level can be improved using this GIS‐based MCDA, in conjunction with temporal risk factor analysis. [ABSTRACT FROM AUTHOR]

AbstractBuilding upon prior work, we propose an alternative way to look at the pattern of spatial crime concentration and temporal stability of it. We first identify a high-crime cluster using the sample block groups in New York City by employing a k-means clustering method. We then examine the temporal stability of the high-crime cluster over time. We also longitudinally assess how our high-crime cluster classification is associated with the actual amount of crime while accounting for the measures of social and physical environments. We observed that about 6–12% of total areas are identified to be in the high-crime cluster. We also found that block groups identified to be high-crime cluster in one year are more likely to be that way in the next year. We hope future research may consider using data-driven approaches to expand understanding of spatial and temporal crime patterns. [ABSTRACT FROM AUTHOR]

Dengue, a zoonotic viral disease transmitted by Aedes mosquitoes, poses a significant public health concern throughout the Lao People's Democratic Republic (Lao PDR). This study aimed to describe spatial–temporal patterns and quantify the effects of environmental and climate variables on dengue transmission at the district level. The dengue data from 2015 to 2020 across 148 districts of Lao PDR were obtained from the Lao PDR National Center for Laboratory and Epidemiology (NCLE). The association between monthly dengue occurrences and environmental and climate variations was investigated using a multivariable Zero-inflated Poisson regression model developed in a Bayesian framework. The study analyzed a total of 72,471 dengue cases with an incidence rate of 174 per 100,000 population. Each year, incidence peaked from June to September and a large spike was observed in 2019. The Bayesian spatio-temporal model revealed a 9.1% decrease (95% credible interval [CrI] 8.9%, 9.2%) in dengue incidence for a 0.1 unit increase in monthly normalized difference vegetation index at a 1-month lag and a 5.7% decrease (95% CrI 5.3%, 6.2%) for a 1 cm increase in monthly precipitation at a 6-month lag. Conversely, dengue incidence increased by 43% (95% CrI 41%, 45%) for a 1 °C increase in monthly mean temperature at a 3-month lag. After accounting for covariates, the most significant high-risk spatial clusters were detected in the southern regions of Lao PDR. Probability analysis highlighted elevated trends in 45 districts, emphasizing the importance of targeted control strategies in high-risk areas. This research underscores the impact of climate and environmental factors on dengue transmission, emphasizing the need for proactive public health interventions tailored to specific contexts in Lao PDR. [ABSTRACT FROM AUTHOR]

A field study was conducted on the course of the Shatt al-Arab for the period from September 2021 to August 2022. to track the space-time changes in the quality of moving water in the course of the Shatt al-Arab under the influence of the movement of tidal cycles and their interference with fresh water coming from the Tigris River. through four study stations located in the areas of Al-Sada Al-Nour, the paper factory, Al-Ashar, and Sehan. and the study aimed to find out the extent of variation in the values of salinity. the concentration of dissolved solids and concentrations of some Cations and anions spatially and temporally and the extent to which they are affected by the movement of tides. Aquatic samples were collected from the study stations according to the four seasons of the study period and from three depths and three repeats from each depth. The results of the statistical analysis showed significant differences in the values of all studied vocabulary, namely EC, pH, Ca+2, Mg+2, TH, Na+1, HCO3-1, Cl-1, SO4-2 based on the stations and seasons studied, and the values of the studied vocabulary showed a spatial and temporal variation, as the salinity values increased as we headed south towards the mouth of the river and the ranges of values reached 1.92-8.45 dS-1 .The pH values tended to be light basal and ranged between 7.79 – 8.06, and the concentrations of cations and anions varied spatially and temporally as they were affected by the movement of the tides and the values of the concentrations ranged between 116.43 - 661.67, 35.16 -147.62, 167.67 - 1118.91, 221.43-2337.53 and 344.88 - 1073.68 mg L-1 for ions Ca+2, Mg+2, Na+1, Cl-1, SO4-2 respectively. [ABSTRACT FROM AUTHOR]

In this study, we ran a meta-analysis of neuroimaging studies to pinpoint the neural regions that are commonly activated across space, time, and numerosity, and we tested the existence of gradient transitions among these magnitude representations in the brain. Following PRISMA guidelines, we included in the meta-analysis 112 experiments (for space domain), 114 experiments (time domain), and 115 experiments (numerosity domain), and we used the activation likelihood estimation method. We found a system of brain regions that was commonly recruited in all the three magnitudes, which included bilateral insula, the supplementary motor area (SMA), the right inferior frontal gyrus, and bilateral intraparietal sulci. Gradiental transitions between different magnitudes were found along all these regions but insulae, with space and numbers leading to gradients mainly over parietal regions (and SMA) whereas time and numbers mainly over frontal regions. These findings provide evidence for the GradiATOM theory (Gradient Theory of Magnitude), suggesting that spatial proximity given by overlapping activations and gradients is a key aspect for efficient interactions and integrations among magnitudes. [ABSTRACT FROM AUTHOR]

Seaweed has the potential to become a significant fisheries commodity in the coastal areas of Bone Regency. This study aimed to analyze the socioeconomic aspects of seaweed cultivation in Bone Regency as part of a strategy for its sustainable management. The research was conducted in three villages known for their seaweed production: Palette Village, Mallari Village, and Waetuwo Village. Data were collected using purposive sampling techniques, including observation and interviews with 90 seaweed farmers. Socioeconomic data were analyzed using percentage and SWOT analysis, while spatial analysis was used to examine the distribution of respondents and cultivation locations. The results showed that seaweed management strategies in Bone Regency fall within quadrant 1 of the SO (Strengths-Opportunities) strategy. This strategy focuses on increasing community involvement in government programs that support the development of seaweed as a key commodity, leveraging local knowledge and experience. The recommendations include developing training and education programs to improve cultivation skills, enhance productivity, and raise the quality of seaweed products to meet growing demand. Additionally, optimizing local and national marketing networks, implementing digital marketing strategies, and expanding access to international markets are essential. Finally, encouraging younger farmers to utilize land more effectively, in line with RZWP3K (spatial planning regulations), could increase the area available for seaweed cultivation. [ABSTRACT FROM AUTHOR]

Flashiness refers to the rapidity and frequency of fluctuations in river flow. It can provide insights into flooding, by capturing dramatic increases in river flow, as well as contaminant transport, relating to concentrations of diffuse pollution. Despite a very well gauged river system, there is limited research in Great Britain targeting this component of river flow. This study addresses that gap in knowledge, with a detailed spatio-temporal analysis of river flashiness in Great Britain. Using 513 gauging stations, with historical records of at least 30 years, the average Richards–Baker flashiness index ( R B I ¯ ) was calculated for 1990–2020, showing an overall west- (0.6–0.8) to east-coast (0.1–0.2) gradient, being higher in the west (with the exception of some gauges in the south-east). Employing random forest models, the main predictor for flashiness was found to be soil composition, with some additional region-specific predictors. These include flood attenuation by reservoirs and catchment areas, affecting flashiness in the north and west of Great Britain. Additionally, using a subset of 208 gauging stations with data recorded from 1970 to 2020, a temporal analysis examined significant breakpoints and/or trends in yearly flashiness, using the Pettitt test and Mann–Kendall trend test, respectively. Increases in flashiness were found mainly in the north-east and south-west of Great Britain, with implications in flooding and river health. On a seasonal scale, and using a monthly R B I ¯ , the timing of flashy events was found to oscillate between autumn and spring over the 50 years, gravitating around winter. [ABSTRACT FROM AUTHOR]

Many ecosystems are defined and shaped by one or a few common, foundation species. Even though such species hold a key role in the restoration of these ecosystems, the demographic processes involved in their re‐establishment have rarely been studied. Foundation species' population dynamics, re‐establishment history, and the abiotic and biotic factors that affect individual establishment at restored sites can be studied by addressing population spatial patterns and age structure. Such an approach to studying population dynamics is particularly relevant for long‐lived species with low mortality, such as shrubs in alpine areas. We studied a population of the foundation species Empetrum nigrum ssp. hermaphroditum at an alpine spoil heap site and found evidence of population re‐establishment starting within a decade after construction. High Empetrum densities close to the spoil heap edges indicated that short distances to seed sources in the surroundings had a strong positive effect on establishment of individuals. Empetrum individuals were significantly clustered, which indicated intraspecific facilitation. As revealed by spatial analyses of recruits and older, established individuals, clustering developed gradually over time, which indicated a shift from no interaction to increased facilitation. We conclude that intraspecific facilitation promotes Empetrum reestablishment at the studied alpine spoil heap. Synthesis: We show that population spatial patterns and age structure can be successfully used to unveil the re‐establishment history of a foundation species in a restoration context. Efficient seed dispersal and intraspecific facilitation seem to be important factors behind Empetrum's successful re‐establishment at alpine spoil heaps. Identification of abiotic and biotic factors determining foundation species' establishment success at restored sites can support planning and improve success of restoration. [ABSTRACT FROM AUTHOR]

Stock market indices are volatile by nature, and sudden shocks are known to affect volatility patterns. The autoregressive conditional heteroskedasticity (ARCH) and generalized ARCH (GARCH) models neglect structural breaks triggered by sudden shocks that may lead to an overestimation of persistence, causing an upward bias in the estimates. Different regime‐switching models that have abrupt regime‐switching governed by a Markov chain were developed to model volatility in financial time series data. Volatility modelling was also extended to spatially interconnected time series, resulting in spatial variants of ARCH models. This inspired us to propose a Markov switching framework of the spatio‐temporal log‐ARCH model. In this article, we discuss the Markov‐switching extension of the model, the estimation procedure and the smooth inferences of the regimes. The Monte Carlo simulation studies show that the maximum likelihood estimation method for our proposed model has good finite sample properties. The proposed model was applied to 28 stock indices' data that were presumably affected by the 2015–2016 Chinese stock market crash. The results showed that our model is a better fit compared to that of the one‐regime counterpart. Furthermore, the smoothed inference of the data indicated the approximate periods where structural breaks occurred. This model can capture structural breaks that simultaneously occur in nearby locations. [ABSTRACT FROM AUTHOR]

Small area estimation (SAE) has become an important tool in official statistics, used to construct estimates of population quantities for domains with small sample sizes. Typical area-level models function as a type of heteroscedastic regression, where the variance for each domain is assumed to be known and plugged in following a design-based estimate. Recent work has considered hierarchical models for the variance, where the design-based estimates are used as an additional data point to model the latent true variance in each domain. These hierarchical models may incorporate covariate information but can be difficult to sample from in high-dimensional settings. Utilizing recent distribution theory, we explore a class of Bayesian hierarchical models for SAE that smooth both the design-based estimate of the mean and the variance. In addition, we develop a class of unit-level models for heteroscedastic Gaussian response data. Importantly, we incorporate both covariate information as well as spatial dependence, while retaining a conjugate model structure that allows for efficient sampling. We illustrate our methodology through an empirical simulation study as well as an application using data from the American Community Survey. [ABSTRACT FROM AUTHOR]

Children with Attention Deficit Hyperactivity Disorder (ADHD) demonstrate a heterogeneous sensorimotor, emotional, and cognitive profile. Comorbid sensorimotor imbalance, anxiety, and spatial disorientation are particularly prevalent among their non-core symptoms. Studies in other populations presented these three comorbid dysfunctions in the context of vestibular hypofunction. To test whether there is a subgroup of children with ADHD who have vestibular hypofunction presenting with concomitant imbalance, anxiety, and spatial disorientation. Children with ADHD-only (n = 28), ADHD + Developmental Coordination Disorder (ADHD + DCD; n = 38), and Typical Development (TD; n = 19) were evaluated for vestibular function by the Dynamic Visual Acuity test (DVA-t), balance by the Bruininks-Oseretsky Test of motor proficiency (BOT-2), panic anxiety by the Screen for Child Anxiety Related Emotional Disorders questionnaire-Child version (SCARED-C), and spatial navigation by the Triangular Completion test (TC-t). Children with ADHD vs. TD presented with a high rate of vestibular hypofunction (65 vs. 0 %), imbalance (42 vs. 0 %), panic anxiety (27 vs. 11 %), and spatial disorientation (30 vs. 5 %). Children with ADHD + DCD contributed more frequent and severe vestibular hypofunction and imbalance than children with ADHD-only (74 vs. 54 %; 58 vs. 21 %, respectively). A concomitant presence of imbalance, anxiety, and spatial disorientation was observed in 33 % of children with ADHD, all sharing vestibular hypofunction. Vestibular hypofunction may be the common pathophysiology of imbalance, anxiety, and spatial disorientation in children. These comorbidities are preferentially present in children with ADHD + DCD rather than ADHD-only, thus likely related to DCD rather than to ADHD disorder. Children with this profile may benefit from a vestibular rehabilitation intervention. • A subgroup of children with ADHD, mainly with ADHD + DCD, demonstrated vestibular hypofunction. • The subgroup with vestibular hypofunction presented with concomitant imbalance, anxiety, and spatial disorientation. • Identification of this subgroup in the clinical milieu may redirect the treatment to the vestibular system. [ABSTRACT FROM AUTHOR]

With the rise of forced displacement, attention has turned to the economic impact of refugees. However, few studies investigate long-term impacts. We use data for Tanzania for the period 1985–2015 to examine the effect of camps on urbanisation and local development, exploiting a unique satellite-derived dataset of high spatial resolution and temporal frequency. We show a modest but significant effect of refugee camps on built-up area up to a 100 km distance. We then match camp locations to regional gross domestic product, local consumption spending and employment patterns. Output in areas with camps grew at a faster rate during camp operation, but closure of camps was associated with change in economic activity. Activity induced by camps is largely in non-tradeable goods and services rather than inducing longer run structural transformation. [ABSTRACT FROM AUTHOR]

Remote sensing is essential in construction management by providing valuable information and insights throughout the project lifecycle. Due to the rapid advancement of remote sensing technologies, their use has been increasingly adopted in the architecture, engineering, and construction industries. This review paper aims to advance the understanding, knowledge base, and practical implementation of remote sensing technologies in the construction industry. It may help support the development of robust methodologies, address challenges, and pave the way for the effective integration of remote sensing into construction management processes. This paper presents the results of a comprehensive literature review, focusing on the challenges faced in using remote sensing technologies in construction management. One hundred and seventeen papers were collected from eight relevant journals, indexed in Web of Science, and then categorized by challenge type. The results of 44 exemplary studies were reported in the three types of remote sensing platforms (satellite, airborne, and ground-based remote sensing). The paper provides construction professionals with a deeper understanding of remote sensing technologies and their applications in construction management. The challenges of using remote sensing in construction were collected and classified into eleven challenges. According to the number of collected documents, the critical challenges were shadow, spatial, and temporal resolution issues. The findings emphasize the use of unmanned airborne systems (UASs) and satellite remote sensing, which have become increasingly common and valuable for tasks such as preconstruction planning, progress tracking, safety monitoring, and environmental management. This knowledge allows for informed decision-making regarding integrating remote sensing into construction projects, leading to more efficient and practical project planning, design, and execution. [ABSTRACT FROM AUTHOR]

Occupancy models are commonly used in statistical ecology to model binary detection/non-detection data. These hierarchical models make a distinction between detection/non-detection and presence/absence by treating true occupancy as a latent process. In this paper, we propose a multi-species, multi-season occupancy model to jointly model detection/non-detection data on multiple species. Existing literature has shown that models that account for various sources of dependence in the latent occupancy process improve estimation, especially in the single-survey setting. However, the detection process in the model has not received much attention, even though detectability of a species is expected to relate to the detectability of other species and to detectability in previous time periods. In this work, we propose a model to capture this phenomenon by incorporating a multivariate temporal random effect in the detection process. We perform a simulation study to show that the proposed model yields more accurate inference than models that only use covariates to quantify detection. We apply our model to detection/non-detection data on three species—Thomson's gazelle, zebra, and wildebeest—in Serengeti National Park of Tanzania, Africa. [ABSTRACT FROM AUTHOR]

The fragile environment of the Himalayan region is prone to natural hazards, which are intensified by climate change, leading to food and livelihood insecurity for inhabitants. Therefore, building resilience in the most dominant livelihood sector, i.e., the agricultural sector, has become a priority in development and planning. To assess the perils induced by climate change on the agriculture sector in the ecologically fragile region of Kashmir Valley, a study has been conducted to evaluate the risk using the Intergovernmental Panel on Climate Change (IPCC) framework. The risk index has been derived based on socioeconomic and ecological indicators for risk determinants, i.e., vulnerability, hazard, and exposure. Furthermore, the study also evaluated the future risk to the agriculture sector under changing climatic conditions using Shared Socioeconomic Pathways (SSPs) for SSP2-4.5 and SSP5-8.5 at mid- and late-century timescales. It was observed that districts such as Bandipora (0.59), Kulgam (0.56), Ganderbal (0.56), and Kupwara (0.54) are most vulnerable due to drivers like low per capita income, yield variability, and areas with >30% slope. Shopian and Srinagar were found to be the least vulnerable due to adaptive capacity factors like livelihood diversification, crop diversification, percentage of tree crops, and percentage of agriculture labor. In terms of the Risk index, the districts found to be at high risk are Baramulla (0.19), Pulwama (0.16), Kupwara (0.15), and Budgam (0.13). In addition, the findings suggested that the region would experience a higher risk of natural hazards by the mid- (MC) and end-century (EC) due to the projected increase in temperature with decreasing precipitation, which would have an impact on crop yields and the livelihoods of farmers in the region. [ABSTRACT FROM AUTHOR]

High-quality geospatial data are required to examine how the places in which we reside, work and play determine health outcomes; however, seldom is the quality of nationwide geospatial data reported. We examined the quality of geospatial data of public drinking water distribution zones (WDZ) across all territorial authorities in Aotearoa New Zealand to investigate structural inequities in data quality. In our national dataset of WDZ, we identified several differences in the quality of geospatial information that are associated with the population, area-level deprivation, ethnicity and most of all urban/rural classification. Our research highlights structural data inequity, which may undermine efforts to reduce health inequity. [ABSTRACT FROM AUTHOR]

Abstract Introduction Cambodia is a low-income country with limited access to family planning (FP) in terms of modern contraceptive utilization. Despite several FP programs designed to make contraceptives accessible, adoption of contraceptives has been difficult in Cambodia, which has high rates of fertility and maternal mortality. This gap in essential care can put women and adolescent girls at greater risk of adverse outcomes such as stillbirth, spontaneous abortion, unwanted pregnancy, or even maternal death. One of the goals set by the government to decrease both maternal and child mortality and morbidity was increasing the modern contraceptives utilization. So, the main objective of this study was to evaluate spatial variations in modern contraceptives utilization and its contributing factors among women. Methods Data from the Cambodia 2021–22 Demographic and Health Survey datasets were used for secondary data analysis. A total of 19,496 women of reproductive age participated in the study. A spatial and multilevel mixed effects analysis was done on the factors affecting modern contraceptives utilization among Cambodian women. Finally, the percentage, odd ratio, together with their 95% confidence intervals and the results of the spatial analysis were provided. Result The prevalence of modern contraceptive use was 31.2% in Cambodia. Living in an urban area [AOR = 1.224; 95% CI = (1.126.1.330); P = 0.0001]; being married [AOR = 34.131; 95% CI= (12.673, 91.921); P = 0.0001]; and having a history of terminated pregnancy [AOR = 1.137; 95% CI= (1.055, 1.225); P = 0.0001] were found to be positively associated with modern contraceptive utilization. In contrast to this, being between the age range of 46–49 [AOR = 0.421; 95% CI = (0.364, 0.487); P = 0.0001]; being a female-headed household [AOR = 0.784; 95% CI = (0.723, 0.850); P = 0.0001]; and current breast feeding [AOR = 0.84; 95% CI = (0.75, 0.93); P = 0.010] were found to be negatively associated with modern contraceptive utilization. Additionally, the spatial analysis of modern contraceptive utilization showed that a higher proportion was utilized in the southern and southwest regions of Cambodia. Conclusion In this study, living in urban area, being married and having history of terminated pregnancy were found positively associated with modern contraceptive utilization. In contrast to this, being old age, being female headed household and being currently breast-feeding women were found negatively associated with modern contraceptive utilization. In addition to this, there were geographic (spatial) variations in modern contraceptive utilization among Cambodian’s women across the country.

Abstract Background Peste des petits ruminant (PPR) is a contagious disease caused by the peste des petits ruminants virus (PPRV). The disease poses a significant economic threat to small ruminant production in Ethiopia, particularly to the striving pastoral production system. A cross-sectional study was conducted to estimate the seroprevalence and associated risk factors of PPR in the small ruminants of the Borena Zone. A total of 384 serum samples were collected randomly from sheep and goats and examined for the presence of PPRV antibodies using competition enzyme-linked immune sorbent assay (c-ELISA). Additionally, a retrospective analysis of five years of outbreak data was performed to provide insight into the spatial and temporal distribution of the disease. Results The seroprevalence of PPRV antibodies in nonvaccinated, vaccinated, and unknown vaccination status of small ruminants in this study was found to be 32.1%, 68.8%, and 45.5%, respectively. Multivariable logistic analysis revealed a statistically significant association between PPRV seropositivity and several factors, including age, animal origin, flock size, and veterinary services status. A retrospective analysis revealed 53 PPR outbreaks in the Borena Zone from 2018 to 2022, exacerbated by low vaccination coverage relative to the at-risk animal population. Conclusion The study revealed significant gaps in current vaccination efforts, with herd immunity levels falling below the FAO-WOAH recommended threshold of 80%. Despite Ethiopia’s ambitious goal to eradicate PPR by 2027, the frequent outbreaks and insufficient herd immunity highlight the inadequacy of the existing strategies. To effectively move toward eradication, Ethiopia must align its approach with the global PPR eradication framework, which emphasizes a comprehensive strategy that includes diagnostics, surveillance, prevention, and the establishment of a robust veterinary regulatory system, rather than relying solely on vaccination. Overcoming logistical challenges, improving vaccination coverage, and optimizing the timing of vaccination campaigns, especially in hard-to-reach areas, will be crucial for reducing outbreaks and making progress toward eradication.

A coastal rice field is generally characterized by salt-affected soil and low soil quality for rice cultivation. Identifying soil chemical properties in these areas is necessary to determine soil management options for rice production. Therefore, soil samples were collected from 33 sampling points in the Wedung Sub-district of Demak Regency in the late dry season of 2021 to evaluate the variation among soil chemical characteristics in a coastline rice field. Soil samples were obtained beneath the topsoil (0-20 cm soil depth) and observed for electrical conductivity, exchangeable potassium, sodium, calcium, magnesium, and cation exchange capacity. Soils in the research field were categorized as slightly salty (0.75-2 dS m-1) to lightly salty (2.0-4.0 dS m-1) with very high sodium (>2 cmol(+) kg-1). Exchangeable potassium was dominated by moderate (0.3-0.7 cmol(+) kg-1) and low categories (0.2-0.3 cmol(+) kg-1). Based on soil calcium-to-magnesium ratios, around 6% of all samples were classified as calcium-deficient. The range of soil cation exchange capacity was 22-30 cmol(+) kg-1 and classified as high soil cation exchange capacity. Rice productivity in the salt-affected soil was around 4 t ha-1. Strategies for soil and controlling plants, such as soil amelioration and salt-tolerant rice cultivars, should be pursued to support plant growth and enhance rice productivity in the salt-affected soil, particularly in the coastal area.

Abstract Dengue, a zoonotic viral disease transmitted by Aedes mosquitoes, poses a significant public health concern throughout the Lao People’s Democratic Republic (Lao PDR). This study aimed to describe spatial–temporal patterns and quantify the effects of environmental and climate variables on dengue transmission at the district level. The dengue data from 2015 to 2020 across 148 districts of Lao PDR were obtained from the Lao PDR National Center for Laboratory and Epidemiology (NCLE). The association between monthly dengue occurrences and environmental and climate variations was investigated using a multivariable Zero-inflated Poisson regression model developed in a Bayesian framework. The study analyzed a total of 72,471 dengue cases with an incidence rate of 174 per 100,000 population. Each year, incidence peaked from June to September and a large spike was observed in 2019. The Bayesian spatio-temporal model revealed a 9.1% decrease (95% credible interval [CrI] 8.9%, 9.2%) in dengue incidence for a 0.1 unit increase in monthly normalized difference vegetation index at a 1-month lag and a 5.7% decrease (95% CrI 5.3%, 6.2%) for a 1 cm increase in monthly precipitation at a 6-month lag. Conversely, dengue incidence increased by 43% (95% CrI 41%, 45%) for a 1 °C increase in monthly mean temperature at a 3-month lag. After accounting for covariates, the most significant high-risk spatial clusters were detected in the southern regions of Lao PDR. Probability analysis highlighted elevated trends in 45 districts, emphasizing the importance of targeted control strategies in high-risk areas. This research underscores the impact of climate and environmental factors on dengue transmission, emphasizing the need for proactive public health interventions tailored to specific contexts in Lao PDR.

Background: This study adds to the current literature by using a novel device-based method to explore where preschool children are physically active outside of home and childcare settings. This study combined accelerometry with geospatial data to explore the influence of the environment on preschool children's physical activity by objectively identifying the locations where preschool children engage in moderate to vigorous physical activity (MVPA) within and outside of their neighborhood. Methods: Accelerometry, Global Positioning System, and Geographic Information Systems data from 168 preschool children aged 2–5 years were processed in ArcGIS Pro to identify locations (per 25 × 25-m fishnet cell) with high MVPA counts. Locations with high MVPA counts were defined as those with the top 20% of MVPA counts per fishnet cell. The land use for high MVPA count location was determined for 3 domains: <500 m from home, 500 to 1600 m from home, and >1600 m from home. Results: Locations with high MVPA counts <500 m from home were playgrounds (66.6%), schools (16.7%), and parks (16.7%). Locations with high MVPA counts 500 to 1600 m from home included playgrounds (33.3%), nonhome residential (29.6%), childcare centers (11.1%), and parks (3.7%). Locations with high MVPA counts >1600 m from home included nonhome residential (54.7%), sports and recreation centers (11.1%), playgrounds (6.8%), and parks (5.3%). Conclusions: Our findings highlight that local parks and playgrounds provide physical activity opportunities for preschool children, yet beyond the local neighborhood, the homes of others are important locations for preschool children to accumulate MVPA. These findings can be used to inform the design of current and future neighborhood places to better accommodate preschool children's MVPA. [ABSTRACT FROM AUTHOR]

Traumatic brain injury (TBI) is a leading cause of death and disability, primarily caused by falls and motor vehicle collisions (MVC). However, understanding the spatial distribution of TBI risk and their correlation with area-based deprivation remains limited. This study addresses this gap by employing a Bayesian spatial modeling approach to analyze the spatial patterns of fall and MVC-related TBI and their associations with area-based deprivation. Data on TBI cases from 2003 to 2019 in the Halifax Regional Municipality were sourced from the Nova Scotia Trauma Registry. Patients' residential postal codes were geocoded to dissemination areas (DAs), and area-based deprivation status from the national census data was linked to DAs. Bayesian spatial models were utilized to analyze TBI incidence rates resulting from falls and MVCs across DAs. The analysis revealed a substantial spatial disparity in TBI risk, illustrated through maps showing both the relative risk and posterior exceedance probability. Furthermore, area-based deprivation emerged as a significant factor associated with TBI risk. Specifically, areas within the most economically deprived quintile increased the risk of fall related TBI nearly threefold (RR = 2.7, 95%CI 1.98–3.66) compared to those in the least deprived quintile. The most residentially unstable quintile had a 35% greater risk of fall-related TBI than the least deprived quintile (RR = 1.35, 95%CI = 1.01–1.80). The risk of MVC-related TBI increased by 71% among areas in the second most deprived quintile (RR = 1.71; 95% CI 1.18–2.49), highlighting situational vulnerability as a significant risk factor. Deprivation was mapped within a social determinants of health framework to understand the downstream effects of residential instability, economic dependency, and situational vulnerability. This study reveals the unique spatial risk patterns of TBI resulting from falls and MVCs and demonstrates the impact of areal-level deprivation on injury risk. By identifying high-risk areas and understanding the pathways through which deprivation acts on the physical environment and community behavior, public health interventions can be developed to mitigate injury risk. [ABSTRACT FROM AUTHOR]

Abstract Osteosarcomas are intricate cellular ecosystems, where heterotypic interactions significantly influence disease progression and therapeutic outcomes. Despite their importance, a detailed understanding of their cellular composition and organizational structure remains elusive. In this study, we provide a comprehensive single-cell and spatially resolved transcriptomics analysis of human osteosarcomas. We construct a cellular meta-map to dissect spatial transcriptomic data, unveiling a detailed atlas of osteosarcoma compositional subgroups. We meticulously characterize the unique gene signatures and functional states of each subgroup and investigate the impact of chemotherapy on these cellular subpopulations. Additionally, our spatial transcriptomics analysis identifies a distinct spatial niche, located at the forefront of tumor necrotic zones, potentially associated with chemotherapy resistance. We also delve into the crosstalk between different cellular subgroups. This study furnishes a comprehensive transcriptional atlas of osteosarcoma's cellular architecture, enriching our comprehension of its complexity and laying the groundwork for more targeted therapeutic approaches.

Abstract High childhood disease prevalence and under-five mortality rates have been consistently reported in Nigeria. Vaccination is a cost-effective preventive strategy against childhood diseases. Therefore, this study aimed to identify the determinants of Incomplete Vaccination (IV) among children aged 12–23 months in Nigeria. This cross-sectional design study utilized the 2018 Nigeria Demographic and Health Survey (NDHS) dataset. A two-stage cluster sampling technique was used to select women of reproductive age who have children (n = 5475) aged 12–23 months. The outcome variable was IV of children against childhood diseases. Data were analyzed using Integrated Nested Laplace Approximation and Bayesian binary regression models (α0.05). Visualization of incomplete vaccination was produced using the ArcGIS software. Children’s mean age was 15.1 ± 3.2 months and the median number of vaccines received was four. Northern regions contributed largely to the IV. The likelihood of IV was lower among women aged 25–34 years (aOR = 0.67, 95% CI = 0.54–0.82, p

Introduction: Mycobacterium tuberculosis bacteria can cause tuberculosis disease. In 2022, East Java Province reported 8,398 cases of child tuberculosis with a discovery coverage of 105.6%. This study aims to describe the distribution of child tuberculosis incidence in East Java Province by mapping and analyzing the correlation between livable houses, BCG immunization coverage, and population density with the incidence of child tuberculosis in 38 districts/cities in East Java Province from 2020 to 2022. Methods: This was a descriptive approach with a population correlation study design using the Spearman correlation statistical test. Secondary records from the East Java Health Profile 2020, 2021, and 2022 were used in this study. Thirty-eight districts/cities in the province of East Java comprised the study's population. Results and Discussion: This study showed that there has been a positive correlation between BCG immunization coverage in 2020 (r=0.043); 2021 (r=0.140); 2022 (r=0.214) and population density 2020 (r=0.082); 2021 (r=0.102); and 2022 (r=0.174) with the incidence of child tuberculosis. Meanwhile, the correlation between livable houses and the incidence of child tuberculosis is negative in 2020 (r=-0.990) and 2022 (r=-0.047) but positive in 2021 (r=0.078). Conclusion: The increase in BCG immunization coverage and population density aligns with the increase in child tuberculosis cases. Meanwhile, an increase in the percentage of access to livable houses is followed by a decrease in the incidence of child tuberculosis.

As the value ranges presented in the literature with tables and graphs that feature soil index properties related to the soil swelling potential are intertwined, their interpretation may pose certain challenges. In this study, the spatial distribution maps of soil swelling potential were created using soil index data obtained from this research, and those values of ranges from the swelling potential of the study area were assessed by combining all maps, resulting in a single comprehensive map and new limit ranges in the high plasticity cohesive soils. Soils in the study area were evaluated according to the newly determined limit value ranges. The findings show that the high plasticity cohesive soils in the region should have swelling potential in all parameters of the new limit value ranges to show swelling potential. The limit values for high plasticity cohesive soils to demonstrate a high swelling potential are: % natural water content 90, liquid limit >65, plasticity index >21, swelling pressure >240 kPa, and % swelling percentage >6.

Abstract Introduction The United Nations established the Sustainable Development Goals (SDGs) in 2015 to enhance global development. In this study, we examine an SDG indicator: the percentage of women aged 15–49 whose family planning needs are met by modern contraception (mDFPS). We evaluate both the factors influencing its coverage and its progress since 2015. Methods We used nationally representative surveys data (Demographic and Health Surveys (DHS) and Performance Monitoring for Action (PMA)) from Ethiopia, Kenya, and Nigeria. We assessed predictors of mDFPS. We also computed mDFPS coverage across countries and subnational areas, assessing coverage changes from the SDGs onset to the most recent period, using a Bayesian model-based geostatistical approach. We assessed whether the subnational areas exceeded the minimum recommended WHO mDFPS coverage of 75%. Results Varied individual and community-level determinants emerged, highlighting the countries’ uniqueness. Factors such as being part of a female-headed household, and low household wealth, lowered the odds of mDFPS, while rural-residence had low odds only in Ethiopia and Nigeria. The results indicate mDFPS stagnation in most administrative areas across the three countries. Geographic disparities persisted over time, favouring affluent regions. The predicted posterior proportion of mDFPS and exceedance probability (EP) for WHO target for Ethiopia was 39.85% (95% CI: [4.51, 83.01], EP = 0.08) in 2016 and 46.28% (95% CI: [7.15, 85.99], EP = 0.13) in 2019. In Kenya, the adjusted predicted proportion for 2014 was 30.19% (95% CI: [2.59, 80.24], EP = 0.06) and 44.16% (95%CI: [9.35, 80.24], EP = 0.13) in 2022. In Nigeria, the predicted posterior proportion of mDFPS was 17.91% (95% CI: [1.24, 61.29], EP = 0.00) in 2013, and it was 23.08% (95% CI: [1.80, 56.24], EP = 0.00) in 2018. None of the sub-national areas in Ethiopia and Nigeria exceeded the WHO target. While 9 out of 47 counties in Kenya in 2022 exceeded the WHO mDFPS target. Conclusion The study unveils demographic, geographic, and socioeconomic mDFPS disparities, signalling progress and stagnation across administrative areas. The findings offer policymakers and governments insights into targeting interventions for enhanced mDFPS coverage. Context-specific strategies can address local needs, aiding SDG attainment.

Abstract Under-five children’s diarrhea is a significant public health threat and the World Health Organization (WHO) reported it as the second leading cause of children’s death worldwide. In this study area, little is known about the spatiotemporal distribution of under-5 diarrhea incidence. This study was therefore, conducted among all districts in the Central Gondar zone to assess the spatial, temporal, and spatiotemporal variation in diarrhea incidence among under-five children in the Central Gondar zone. The data for children under 5 years of age with diarrhea was obtained from Central Gondar Zone Health Department diarrhea reports from January 2019 to December 2022. All districts were included and geo-coded. The spatial data were created in ArcGIS 10.8.1. Global and local spatial autocorrelation were used to detect hot spots and cold spots. The Poisson model was generated by applying the Kulldorff method in SaTScan™9.6 to analyse the the purely temporal, spatial, and space-time clusters. The study revealed spatial variation of under-5 diarrhea where Gondar City, Gondar Zuria, East Dembia, and Lay Armacho districts were the high-rate spatial clusters during the study period. A year search window for temporal scan statistic identified 01 January 2020-30 December 2021 as risk periods across all districts. Spatiotemporal scan statistics detected high-rate clusters at Gondar City, Gondar Zuria, East Dembia, Lay Armacho, and Alefa between 2019 and 2022. In conclusion, there has been a spatial, temporal, and spatiotemporal variability of under-5 children’s diarrhea in the Central Gondar Zone. Interventional and preventive strategies should be developed and given priority to the areas that has been detected as a hotspot in this study to reduce the mortality and morbidity of under 5 children.

Tens of thousands of plant species globally are harvested to varying extents as non-timber forest products (NTFPs). Local populations of many NTFPs face significant pressures from harvesters, often leading to calls for harvesting guidelines to promote sustainable offtakes. However, most studies to determine sustainable harvest levels implicitly assume that the entire population is available to harvesters. Yet, certain areas or portions of particular NTFP populations outside of protected areas may not be open to harvesting because they are in some sort of cultural or spatial refuge. Using a mixed-methods approach we assessed the prevalence and efficacy of refugia for 70 NTFP plant species at seven communal land sites in south-eastern South Africa. Based on reports from local harvesters, approximately 10 % of the 70 species had part of their population in a refuge. For most of these, populations within a refuge showed lower levels of harvesting and were in a better condition than adjacent populations not in a refuge. These results demonstrate that studies assessing the sustainability of harvesting of NTFP populations should account for whether refugia are present.

Spatial regression, particularly the Spatial Error Model (SERM), was utilized in prior studies to analyze Human Development Index (HDI) modeling. However, the studies were unable to determine which dimension among the three defined by the UN and BPS had the significant impact on HDI, as they constructed models based on the indicators used for the interpretation of the dimensions. Therefore, a comprehensive analysis combining spatial regression and Structural Equation Modeling (SEM), known as spatial SEM, was deemed necessary. This is the reason the current study aimed to develop SERM-SEM modeling holistically. The model parameters were estimated using the Generalized Method of Moments (GMM). To assess spatial dependency, the Lagrange Multiplier (LM) method was employed, with a distinct model error distribution compared to the error distribution of the traditional spatial model. The result of the LM test development showed that, under the null hypothesis, the LM test statistics followed a distribution. The results of the SERM-SEM model development were applied to HDI modeling using data in 2022 with three latent variables, namely a Long and Healthy Life (LHL), Knowledge (Know_L), and a Decent Standard of Living (DLS) (based on UN standards). The assessment of the outer model in SEM was based on the loading factor values that exceed 0.5 and their significance. This evaluation aimed to identify indicators that effectively explained or measured latent variables, so it got the revised model in SEM. These indicators are LHL2 and LHL 4 to form LHL. DLS1 and DLS3 are indicators to make up DLS, and for Know_L, they are K2 and K3. The revised SEM model was analyzed using spatial. The results of the spatial dependency test showed that the HDI model significantly led to the SERM-SEM model. Knowledge and a decent standard of living variables significantly influence HDI.

Osteosarcomas are intricate cellular ecosystems, where heterotypic interactions significantly influence disease progression and therapeutic outcomes. Despite their importance, a detailed understanding of their cellular composition and organizational structure remains elusive. In this study, we provide a comprehensive single-cell and spatially resolved transcriptomics analysis of human osteosarcomas. We construct a cellular meta-map to dissect spatial transcriptomic data, unveiling a detailed atlas of osteosarcoma compositional subgroups. We meticulously characterize the unique gene signatures and functional states of each subgroup and investigate the impact of chemotherapy on these cellular subpopulations. Additionally, our spatial transcriptomics analysis identifies a distinct spatial niche, located at the forefront of tumor necrotic zones, potentially associated with chemotherapy resistance. We also delve into the crosstalk between different cellular subgroups. This study furnishes a comprehensive transcriptional atlas of osteosarcoma's cellular architecture, enriching our comprehension of its complexity and laying the groundwork for more targeted therapeutic approaches. [ABSTRACT FROM AUTHOR]

High childhood disease prevalence and under-five mortality rates have been consistently reported in Nigeria. Vaccination is a cost-effective preventive strategy against childhood diseases. Therefore, this study aimed to identify the determinants of Incomplete Vaccination (IV) among children aged 12–23 months in Nigeria. This cross-sectional design study utilized the 2018 Nigeria Demographic and Health Survey (NDHS) dataset. A two-stage cluster sampling technique was used to select women of reproductive age who have children (n = 5475) aged 12–23 months. The outcome variable was IV of children against childhood diseases. Data were analyzed using Integrated Nested Laplace Approximation and Bayesian binary regression models (α0.05). Visualization of incomplete vaccination was produced using the ArcGIS software. Children’s mean age was 15.1 ± 3.2 months and the median number of vaccines received was four. Northern regions contributed largely to the IV. The likelihood of IV was lower among women aged 25–34 years (aOR = 0.67, 95% CI = 0.54–0.82, p < 0.05) and 35–49 years (aOR = 0.59, 95%CI = 0.46–0.77, p < 0.05) compared to younger women in the age group 15–24 years. An increasing level of education reduces the risk of odds of IV. Other predictors of IV were delivery at the health facility (aOR = 0.64, 95% CI = 053–0.76, p < 0.05), and media exposure (aOR = 0.63, 95%CI = 0.54–0.79, p < 0.05). Mothers’ characteristics explained most of the variability in the IV, relatively to smaller overall contributions from the community and state-level factors (p < 0.05). The level of IV against childhood diseases was high in Nigeria. However, disparities exist across the regions and other socioeconomic segments of the population. More efforts are required to improve vaccination sensitization programs and campaigns in Nigeria. [ABSTRACT FROM AUTHOR]

The conversion of agricultural land into built-up land is one of the factors causing the decline in rice production in Majalengka Regency and West Java Province. The agricultural sector still plays a vital role in local economic development, as evidenced by the GRDP of the agriculture, forestry, and fisheries sector being the second highest after the processing industry. Regional Regulation No. 11 of 2011 regarding the Spatial Planning of Majalengka Regency 2011-2031 stipulates a minimum of 39,190 ha of sustainable agricultural land. However, this amount has decreased to 30,966 ha with the issuance of Majalengka Regent Decree No. 520/KEP.1279- DKP3/2021 on the Designation of Sustainable Agricultural Land. To mitigate the negative impact of the reduction in land area, policy formulations supporting the preservation of agricultural land and implementing sustainable farming practices by local governments and related stakeholders are necessary. These efforts aim to maintain the area of food agricultural land within the framework of achieving food self-sufficiency in the Majalengka Regency. The study shows that to meet food (rice) needs until 2045, according to the direction of the RPJPN Development, a protected rice field area of 48,235 ha is required, with a surplus of 4,037 tons of rice. [ABSTRACT FROM AUTHOR]

Everyone learns differently, but individual performance is often ignored in favour of a group-level analysis. Using data from four different experiments, we show that generalised linear mixed models (GLMMs) and extensions can be used to examine individual learning patterns. Producing ellipsoids and cluster analyses based on predicted random effects, individual learning patterns can be identified, clustered and used for comparisons across various experimental conditions or groups. This analysis can handle a range of datasets including discrete, continuous, censored and non-censored, as well as different experimental conditions, sample sizes and trial numbers. Using this approach, we show that learning a face-named paired associative task produced individuals that can learn quickly, with the performance of some remaining high, but with a drop-off in others, whereas other individuals show poor performance throughout the learning period. We see this more clearly in a virtual navigation spatial learning task (NavWell). Two prominent clusters of learning emerged, one showing individuals who produced a rapid learning and another showing a slow and gradual learning pattern. Using data from another spatial learning task (Sea Hero Quest), we show that individuals' performance generally reflects their age category, but not always. Overall, using this analytical approach may help practitioners in education and medicine to identify those individuals who might need extra help and attention. In addition, identifying learning patterns may enable further investigation of the underlying neural, biological, environmental and other factors associated with these individuals. [ABSTRACT FROM AUTHOR]

Rainfall is a crucial climate variable, shows irregular spatial and temporal variations. Significant spatial variability and persistent changes in land use intensify the complexity of urban weather systems. Therefore, climatological rainfall variables deserve attention from both a scientific and technological perspective. The rapid urban expansion of Hyderabad city, coupled with extreme weather variations, has led to increased environmental vulnerability. The present study aims to assess the spatiotemporal trends of annual rainfall and rainfall extremes in Hyderabad city from 1990 to 2020. This study employed the RClimDex model and daily gridded rainfall data to analyze annual rainfall and rainfall extreme indices, focusing on Consecutive Dry Days (CDD), Consecutive Wet Days (CWD), Total Precipitation (PRCPTOT), Rainfall Events Exceeding 10 mm (R10MM), 20 mm (R20MM), Total Precipitation from Very Wet Days (R95PTOT), Maximum 1-Day Precipitation (RX1DAY), and Maximum 5-Day Precipitation (RX5DAY). The trends in annual rainfall and rainfall extremes were assessed using the Mann-Kendall (MK) test, and spatial distribution variations for the identified trends were evaluated with the Inverse Distance Weighting (IDW) interpolation technique. The results of the study showed that no significant annual rainfall trends from 1990 to 2020, indicating natural variability rather than consistent long-term changes. However, extreme Consecutive Dry Days and Maximum Wet Spell trends show increasing trends. The PRCPTOT pattern remains almost stable, and R10MM rainfall events exhibit an increasing trend at a few locations, suggesting potential shifts in precipitation patterns. Conversely, a decreasing trend for rainfall extremes R20MM, R95PTOT, RX1DAY, and RX5DAY indicate a general reduction in extreme rainfall events and very wet days in GHMC suggesting localized reductions in extreme events and varied impacts of prolonged rainfall reductions at annual scale. The study reveals Hyderabad's high spatial variability in annual rainfall distribution and rainfall extremes, emphasizing the importance of analyzing high resolution gridded rainfall data for effective decision-making and efficient water resource management. [ABSTRACT FROM AUTHOR]

Objective To analyze the epidemiological characteristics of dengue fever in Guangzhou and provide a scientific basis for dengue fever prevention and control. Methods The data of dengue cases in Guangzhou, Guangdong Province reported between 2019 and 2023, were retrieved from the China Disease Prevention and Control Information System. Cross-sectional analysis was used to describe the temporal, spatial, and demographic distribution, and analyze the epidemiological characteristics. Results A total of 3 518 cases of dengue fever were reported in Guangzhou from 2019 to 2023, including 3 101 local cases (88.15%) and 417 imported cases (11.85%). The annual average incidence rate ranged from 0.09 to 17.59 per 100 000 population. Imported dengue fever cases were reported in all months, with the peak reported from May to November (374 cases, 89.69%). Local cases were first reported in May and the last in December, with the highest incidence from August to November (2 960 cases, 95.45%). The cases were reported in all 11 administrative districts; the top three were Baiyun District, Yuexiu District, and Liwan District. Male and female cases accounted for 53.52% and 46.48%, respectively; the age group mainly concentrated between 20-<60 years (2 547 cases, 72.40%). The top three occupations were business services (784 cases), housework and unemployment (738 cases), and retirees (596 cases). The average time from onset to diagnosis for local cases was 4.06 days, and 4.60 days for imported cases. The overseas imported cases mainly came from Southeast Asia 88.10%(311/353), with the most being imported from Cambodia. Cases imported from other provinces mainly came from Yunnan Province, and cases imported from other cities within the province mainly came from Foshan City. Conclusions In recent years, the incidence of dengue fever in Guangzhou has remained at a high level, with obvious imported and seasonal characteristics. Relevant departments should pay attention to key populations and take effective measures to reduce the density of mosquito vectors, and strictly prevent the spread of dengue fever. [ABSTRACT FROM AUTHOR]

This paper reports a comparison of different spatial and statistical models to predict the concentrations of the particulate matter (PM10), measured by the environmental stations of the Community of Madrid (Spain). Three methods were compared: Inverse Distance Weighting (IDW), Ordinary Kriging (OK) and Empirical Bayesian Kriging (EBK). The most accurate spatial interpolation method was the EBK. An interpolation map obtained by applying the EBK geostatistical method is presented to identify the areas with the highest pollution of PM10.] [ABSTRACT FROM AUTHOR]

This study aimed to determine the effect of spatial and climatic factors on the productivity of chestnut honey and chestnut propolis produced in chestnut forests and to reveal the potential contribution of their production to the economy. The study area included the provinces of Artvin, Trabzon, Ordu and Samsun in the Eastern and Central Black Sea Region, and covered the beekeepers producing chestnut honey and chestnut propolis in chestnut forests. The primary data of the study were obtained from the yield measurements of chestnut honey and chestnut propolis obtained from the hives, whereas the secondary data were obtained from the surveys conducted with beekeepers. Analysis of variance, independent sample t-test and correlation analysis were used to analyze the statistical difference between the chestnut honey and chestnut propolis yields of the beehives in different provinces. It was determined that there was a negative relationship between the yield of chestnut honey and chestnut propolis, relative humidity and wind speed, and a positive relationship between yield and altitude, temperature and precipitation. The potential contribution of chestnut honey and propolis production was US $ 51.10 million to the Eastern and Central Black Sea Region economy. [ABSTRACT FROM AUTHOR]

Background: Generalized Joint Hyper-mobility (GJH) can aid in the diagnosis of Ehlers-Danlos Syndrome (EDS), a complex genetic connective tissue disorder with clinical features that can mimic other disease processes. Our study focuses on developing a unique image-based goniometry system, the HybridPoseNet, which utilizes a hybrid deep learning model. Objective: The proposed model is designed to provide the most accurate joint angle measurements in EDS appraisals. Using a hybrid of CNNs and HyperLSTMs in the pose estimation module of HybridPoseNet offers superior generalization and time consistency properties, setting it apart from existing complex libraries. Methodology: HybridPoseNet integrates the spatial pattern recognition prowess of MobileNet-V2 with the sequential data processing capability of HyperLSTM units. The system captures the dynamic nature of joint motion by creating a model that learns from individual frames and the sequence of movements. The CNN module of HybridPoseNet was trained on a large and diverse data set before the fine-tuning of video data involving 50 individuals visiting the EDS clinic, focusing on joints that can hyperextend. HyperLSTMs have been incorporated in video frames to avoid any time breakage in joint angle estimation in consecutive frames. The model performance was evaluated using Spearman's coefficient correlation versus manual goniometry measurements, as well as by the human labeling of joint position, the second validation step. Outcome: Preliminary findings demonstrate HybridPoseNet achieving a remarkable correlation with manual Goniometric measurements: thumb (rho = 0.847), elbows (rho = 0.822), knees (rho = 0.839), and fifth fingers (rho = 0.896), indicating that the newest model is considerably better. The model manifested a consistent performance in all joint assessments, hence not requiring selecting a variety of pose-measuring libraries for every joint. The presentation of HybridPoseNet contributes to achieving a combined and normalized approach to reviewing the mobility of joints, which has an overall enhancement of approximately 20% in accuracy compared to the regular pose estimation libraries. This innovation is very valuable to the field of medical diagnostics of connective tissue diseases and a vast improvement to its understanding. [ABSTRACT FROM AUTHOR]