Soybean is an essential crop to fight global food insecurity and is of great economic importance around the world. Along with genetic improvements aimed at boosting yield, soybean seed composition also changed. Since conditions during crop growth and development influences nutrient accumulation in soybean seeds, remote sensing offers a unique opportunity to estimate seed traits from the standing crops. Capturing phenological developments that influence seed composition requires frequent satellite observations at higher spatial and spectral resolutions. This study introduces a novel spectral fusion technique called multiheaded kernel-based spectral fusion (MKSF) that combines the higher spatial resolution of PlanetScope (PS) and spectral bands from Sentinel 2 (S2) satellites. The study also focuses on using the additional spectral bands and different statistical machine learning models to estimate seed traits, e.g., protein, oil, sucrose, starch, ash, fiber, and yield. The MKSF was trained using PS and S2 image pairs from different growth stages and predicted the potential VNIR1 (705 nm), VNIR2 (740 nm), VNIR3 (783 nm), SWIR1 (1610 nm), and SWIR2 (2190 nm) bands from the PS images. Our results indicate that VNIR3 prediction performance was the highest followed by VNIR2, VNIR1, SWIR1, and SWIR2. Among the seed traits, sucrose yielded the highest predictive performance with RFR model. Finally, the feature importance analysis revealed the importance of MKSF-generated vegetation indices from fused images.

BACKGROUND: A decrease in populations could affect healthcare access and systems, particularly in medically underserved areas (MUAs) where depopulation is becoming more prevalent. This study aimed to simulate the future population and land areas of MUAs in Japan.
METHODS: This study covered 380,948 1 km meshes, 87,942 clinics, and 8354 hospitals throughout Japan as of 2020. The areas outside a 4 km radius of medical institutions were considered as MUAs, based on the measure of areas in the current Japanese Medical Care Act. Based on the population estimate for a 1 km mesh, the population of mesh numbers of MUAs was predicted for every 10 years from 2020 to 2050 using geographic information system analysis. If the population within a 4 km radius from a medical institution fell below 1000, the institution was operationally assumed to be closed.
RESULTS: The number of MUAs was predicted to decrease from 964,310 (0.77% of the total Japanese population) in 2020 to 763,410 (0.75%) by 2050. By 2050, 48,105 meshes (13% of the total meshes in Japan) were predicted to be new MUAs, indicating a 31% increase in MUAs from 2020 to 2050. By 2050, 1601 medical institutions were tentatively estimated to be in close proximity.
CONCLUSIONS: In Japan, the population of MUAs will decrease, while the land area of MUAs will increase. Such changes may reform rural healthcare policy and systems.

Analysis of land use and land cover (LULC) change and its drivers and impacts in the biodiversity hotspot of Bale Mountain\'s socio-ecological system is crucial for formulating plausible policies and strategies that can enhance sustainable development. The study aimed to analyze spatio-temporal LULC changes and their trends, extents, drives, and impacts over the last 48 years in the Bale Mountain social-ecological system. Landsat imagery data from the years 1973, 1986, 1996, 2014, and 2021 together with qualitative data were used. LULC classification scheme employed a supervised classification method with the application of the maximum likelihood algorithm technique. In the period between 1973 and 2021, agriculture, bare land, and settlement showed areal increment by 153.13%, 295.57%, and 49.03% with the corresponding increased annual rate of 1.93%, 2.86%, and 0.83%, respectively. On the contrary, forest, wood land, bushland, grass land, and water body decreased by 29.97%, 1.36%, 28.16%, 8.63%, and 84.36% during the study period, respectively. During the period, major LULC change dynamics were also observed; the majority of woodland was converted to agriculture (757.8 km2) and grassland (531.3 km2); and forests were converted to other LULC classes, namely woodland (766.5 km2), agriculture (706.1 km2), grassland (34.6 km2), bushland (31.9 km2), settlement (20.5 km2), and bare land (14.3 km2). LULC changes were caused by the expansion of agriculture, settlement, overgrazing, infrastructure development, and fire that were driven by population growth and climate change, and supplemented by inadequate policy and institutional factors. Social and environmental importance and values of land uses and land covers in the study area necessitate further assessment of potential natural resources\' user groups and valuation of ecosystem services in the study area. Hence, we suggest the identification of potential natural resource-based user groups, and assessment of the influence of LULC changes on ecosystem services in Bale Mountains Eco Region (BMER) for the sustainable use and managements of land resources.

China has complex natural conditions and is rich in biodiversity. Based on the geographical distribution and species composition of terrestrial mammals, we explored the characteristics and geographic partitioning of mammal populations in different regions of China. We used a clustering algorithm, combined with the spatial distribution data and taxonomic characteristics of mammals, to geographically partition the terrestrial mammals in China. We found 10 zoogeographic regions of terrestrial mammals in China: Northeast region, North China region, Eastern grassland region, Western region, Northwest region, Qiangtang plateau region, Eastern Qinghai-Tibet Plateau region, Himalayan region, South China region, and Taiwan-Hainan region. We found a new geographical zoning pattern for terrestrial mammals in China, examined the variability and characteristics of species composition among different regions, and quantified the association between species distribution and environmental factors. We proposed a method of incorporating taxonomic information into cluster analysis, which provided a new idea for zoogeographic region studies, a new perspective for understanding species diversity, and a scientific basis for animal conservation and habitat planning.
中国自然条件复杂,生物多样性丰富。本研究基于中国陆栖哺乳动物的地理分布与物种构成特征,探讨中国不同地区哺乳动物种群的特点和地理分区;采用聚类算法,结合哺乳动物的空间分布数据和分类学特征,对中国陆栖哺乳动物进行地理分区。结果表明: 中国陆栖哺乳动物可分为东北区域、华北区域、东部草原区域、西部区域、西北区域、羌塘高原区域、青藏东部区域、喜马拉雅区域、华南区域、台湾-海南区域共10个动物地理区。研究结果揭示了中国陆栖哺乳动物的新地理分区模式,展现了不同区域间物种组成的差异性和特点,揭示了物种分布与环境因素之间的关联。本研究提出将分类信息纳入聚类分析的方法,为动物地理区域研究提供了新思路,为理解物种多样性提供了新视角,并为动物保护和栖息地规划提供了科学依据。.

Introduction Floods not only directly damage medical facilities but also hinder access to medical facilities, potentially disrupting local medical services. The scale of damage that medical facilities suffer from floods in Japan is unknown. In this study, we assessed the potential impact of floods on Japanese healthcare facilities by facility characteristics. Methods We conducted a cross-sectional study involving medical facilities registered in the Japan Medical Association Regional Medical Information System. Geographic data for the inundation area was obtained from open data of the Japanese government. Facilities that overlap with flooded areas were designated as affected facilities. The primary outcomes were the percentage of damaged facilities and beds. We calculated odds ratios (OR) and 95% confidence intervals (95%CI) using the Wald method to assess the impact of disaster base hospital designation on damage extent. Results We included 140,826 general clinics and 8,126 hospitals, which had 137,731 and 1,483,347 beds, respectively. The planned scale of flooding is estimated to affect 8.0% of general clinics and 10.8% of their beds. For hospitals, these figures were 8.8% and 7.8%, respectively. The maximum potential scale of flooding is estimated to affect 23.6% of general clinics and 23.9% of their beds. For hospitals, these figures were 22.5% and 20.6%, respectively. At the planned scale of flooding, there was no difference found in the rate of damaged facilities between disaster base hospitals and non-disaster base hospitals, and the rate of damaged beds was lower at non-disaster base hospitals (OR = 0.92, 95%CI = 0.71-1.18 for damaged facilities and OR = 0.79, 95%CI = 0.78-0.80 for damaged beds). At the maximum potential scale of flooding, there was no difference found in the expected damage between disaster base hospitals and non-disaster base hospitals (OR = 1.14, 95%CI = 0.95-1.38 for damaged facilities and OR = 0.99, 95%CI = 0.98-1.00 for damaged beds). Conclusion In Japan, floods can hinder nationwide medical functions, particularly in certain regions. Healthcare professionals should assess potential flood damage in advance and ensure that their workplace\'s business continuity plan includes appropriate countermeasures.

UNASSIGNED: Various factors, such as event location and response time, influence the outcomes of out-of-hospital cardiac arrest (OHCA). Very few studies have explored the delivery of basic life support (BLS) to patients having OHCA at health clinics or nursing homes-settings with professional BLS providers. Thus, in this study, we compared prognostic and survival outcomes between health clinics, nursing homes, and other public places (eg, workplaces and sports facilities/recreational areas) to offer insights for optimizing OHCA outcomes.
UNASSIGNED: This study included adults who had nontraumatic OHCA in Taoyuan City between January 2017 and December 2022.
UNASSIGNED: We collected data on patient characteristics, emergency medical service parameters, onsite patient management, automated external defibrillator (AED) locations, OHCA prognosis, and survival outcomes. Multivariate analyses were performed to predict survival to discharge (primary outcome) and neurological outcomes at discharge (secondary outcome).
UNASSIGNED: During the study period, the numbers of OHCA events at health clinics, nursing homes, and other public places were 158, 208, and 1986, respectively. The mean age of OHCA in health medical clinics, nursing home and other public places were 63.4, 81.5 and 64.7, respectively (P value<0.001). The proportion of witnessed events, rate of bystander resuscitation, and frequency of AED utilization were the highest for health clinics (53.2% (84/158), 83.4% (132/158), and 13.3% (21/158), respectively, P value<0.001). The average AED-scene distances and response times were the lowest for health clinics (388.8 m and 5.4 min, respectively). In initial shockable rhythm group, the probabilities of survival to discharge at discharge were the highest for health clinics (aOR=1.41, 95% CI=1.04-1.81, P value=0.041)) and lowest for nursing homes (aOR=0.84, 95% CI=0.76-0.93, P value=0.024).
UNASSIGNED: Our research shows that OHCA patients at medical health clinics have higher rates of witnessing and bystander CPR and AED usage than other public places. However, while survival rates for patients with shockable rhythms are slightly better at health clinics, the neurological outcomes are not significantly different. The AED-scene distances are too far to be used effectively.

To meet the 2050 decarbonization target of the global buildings and construction sector, more attention is needed to reduce carbon emissions from construction and demolition. However, current national carbon accounting studies for these activities remain limited in spatial granularity and localized applicability. This study developed a bottom-up spatiotemporal database of carbon emissions from building construction and demolition in Japan via integrating a geographic information system-based building stock model, statistical data, and survey information. Focusing on municipal-level emissions, the Logarithmic Mean Divisia Index approach was used to decompose spatiotemporal variations and identify the contributing factors. Results indicate that carbon emissions from Japan\'s construction and demolition activities fell by more than 50% between 2005 and 2020, largely due to declining new/demolished-to-stock ratio, suggesting a transition to a stock-based society. Central cities\' reliance on carbon-intensive buildings positively contributed to spatial variations in their construction emissions, underscoring the importance of sustainable materials and timber designs. Differences between prefectures in demolition emission intensity highlighted the strategic placement of recycling facilities in key regions to curb transportation-related emissions. Overall, these findings provided data reference for local governments to devise tailored policies for managing construction and demolition emissions.

The application of geospatial data often allows the tracing of people who are involved in activities of an illegal nature. In June 2021, we estimated the true magnitude of the spread of COVID-19 within the networks of escort-karaoke bars in Seoul, Republic of Korea, using geographic information system (GIS)-based contact tracing that was applied to our epidemiological investigation. Our joint rapid response team, composed of epidemic investigation officers and police personnel, identified 19 paper-traced cases and 158 GIS-traced cases from 5,692 confirmed cases in Seoul during the study period (June to July 2021). Our findings suggest that collaboration with law enforcement agencies and the use of overlaid satellite imagery in outbreak investigations enhances high vigilance and reduces the risk of potential breaches of human rights in the process.

In light of contemporary energy and environmental objectives, a pivotal transformation of the energy system, encompassing biomass energy, is imperative. A notable challenge in biomass energy facility layout planning is the trade-off between high-efficiency production and the associated investment costs. To harmonize energy efficiency with economy viability, a hybrid layout with the simultaneous construction of centralized and decentralized biomass energy facilities has emerged as a crucial strategic solution. However, the delineation methods for these two layouts lack explicit data support. This study established a population density threshold (PDT) suitable for selecting the distributed layout and employed population density as the criterion for delineating the two layouts. Taking Fuxin City as an example, hybrid layout planning schemes were generated under different PDTs, and a cost and energy benefit analysis framework was developed for these schemes. The results indicated that the scheme with a PDT of 145 person/km2 exhibited the highest energy and economic comprehensive benefits. Compared to a single layout, the planning strategy proposed in this study could achieve nearly the same energy surplus level while saving an investment cost ranging from 2403.9 million CNY to 25,000.23 million CNY. The findings are applicable to other regions with similar conditions, and the analysis framework proposed in this study can be utilized in formulating biomass development strategies for other countries and regions.

OBJECTIVE: This study aimed to investigate the risk factors for liver disease comorbidity among older adults in eastern, central, and western China, and explored binary, ternary and quaternary co-morbid co-causal patterns of liver disease within a health ecological model.
METHODS: Basic information from 9,763 older adults was analyzed using data from the China Health and Retirement Longitudinal Study (CHARLS). LASSO regression was employed to identify significant predictors in eastern, central, and western China. Patterns of liver disease comorbidity were studied using association rules, and spatial distribution was analyzed using a geographic information system. Furthermore, binary, ternary, and quaternary network diagrams were constructed to illustrate the relationships between liver disease comorbidity and co-causes.
RESULTS: Among the 9,763 elderly adults studied, 536 were found to have liver disease comorbidity, with binary or ternary comorbidity being the most prevalent. Provinces with a high prevalence of liver disease comorbidity were primarily concentrated in Inner Mongolia, Sichuan, and Henan. The most common comorbidity patterns identified were \"liver-heart-metabolic\", \"liver-kidney\", \"liver-lung\", and \"liver-stomach-arthritic\". In the eastern region, important combination patterns included \"liver disease-metabolic disease\", \"liver disease-stomach disease\", and \"liver disease-arthritis\", with the main influencing factors being sleep duration of less than 6 h, frequent drinking, female, and daily activity capability. In the central region, common combination patterns included \"liver disease-heart disease\", \"liver disease-metabolic disease\", and \"liver disease-kidney disease\", with the main influencing factors being an education level of primary school or below, marriage, having medical insurance, exercise, and no disabilities. In the western region, the main comorbidity patterns were \"liver disease-chronic lung disease\", \"liver disease-stomach disease\", \"liver disease-heart disease\", and \"liver disease-arthritis\", with the main influencing factors being general or poor health satisfaction, general or poor health condition, severe pain, and no disabilities.
CONCLUSIONS: The comorbidities associated with liver disease exhibit specific clustering patterns at both the overall and local levels. By analyzing the comorbidity patterns of liver diseases in different regions and establishing co-morbid co-causal patterns, this study offers a new perspective and scientific basis for the prevention and treatment of liver diseases.