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AbstractThe Padang Beach Tourism Area is a popular destination in Padang City making it susceptible to contamination by microplastics. From April to June 2023, we sampled seawater and sediment for microplastics from eight stations having varying degrees of human influence, including densely populated areas, river estuaries, tourist areas, and sparsely populated areas. We analyzed the samples to determine abundance, shape, size, color, and composition. Five shapes (fibers, films, fragments, granules, and pellets), seven colors (black, blue, brown, red, transparent, green, and white), and eight compositons (polycarbonate, polypropylene, polyethylene, polysulfone, polyvinyl chloride, polyethylene terephthalate, polystyrene, and polytetrafluoroethylene) were identified and categorized into five size ranges (1-100 µm, 100-300 µm, 300-500 µm, 500-1000 µm, and 1-5 mm). Microplastics abundance in seawater was not significantly different across stations, ranging from 0.064 to 0.229 particles/m3. Microplastic abundance in sediment, was also not significantly different across stations, ranging from 0.151 to 0.387 particles/kg. However, there was a significant difference between the abundance of microplastics in seawater and sediment. The highest abundance of microplastics was in the form of fragments, and there was significant difference from fiber, fragment, pellet, and granule types. In contrast, thre was a significant difference between the abundance of film-type microplastics in seawater and sediment. Overall, microplastic abundance was similar across densely populated areas, river estuaries, and tourist areas and higher than in sparsely populated areas. [ABSTRACT FROM AUTHOR]

Background: Unlike in urban areas, community healthcare in medically underpopulated areas in Japan is constantly challenged because of the uncertainty in effectively using the limited resources. However, no study has focused on human resources or identified the actual state of pharmacists' support in the community. Therefore, our study identified the actual status and problems of pharmacists involved in home medical care in medically underpopulated areas and discussed the roles required of pharmacists and specific methods of support. Methods: The content of semi-structured interviews with care managers involved in home healthcare in Misugi town, Tsu City, between November 10, 2023 and March 13, 2024, was analyzed qualitatively using the grounded theory approach. Results: Five care managers participated in the study. Semi-structured interviews on the actual situation and challenges faced by pharmacists indicated that the following roles were required for pharmacists: as in other regions, it was observed that elderly people with dementia and those living alone managed their medicines, adjusted leftover medicines, collaborated with other professions, bridged with physicians, checked medication status through frequent visits, and adhered to internal medication regimens. Issues related to the characteristics of depopulated areas were identified including human resources, limitations of healthcare resources, economic burden, limits on the number of visits by pharmacists. As a characteristic of communities with no pharmacies and only in-hospital prescribing, pharmacists were expected by care managers to manage the problems caused by in-hospital prescribing. Conclusions: Our findings suggest that pharmacists should ensure the number of visits and collaborate with attending physicians, visiting nurses, and care managers to conduct drug management for patients with dementia and older adults living alone. Community healthcare specialists and those involved in the healthcare planning system can also utilize these findings while planning home healthcare to those who live in medically underpopulated areas in Japan. [ABSTRACT FROM AUTHOR]

Background: Cancer is still the leading cause of non-accidental death in childhood, although the majority of children diagnosed in high-income countries survive their illness. In accordance with international standards, equal and early access to palliative care should be available to children and adults. Yet communication and prognostic disclosure may influence the timing of involvement in palliative care. Purpose: To investigate whether parents perceived that their child received palliative care and to what extent that contrasted parents' perceptions of their child's care and symptoms in the last month of life. Methods: A nationwide population-based parental questionnaire study in Sweden, one to five years after their child's death (n=226). Descriptive statistics were used. Results: A majority of parents (70%) reported that they were aware that their child received palliative care and they were informed about the incurable disease (57%) within 3 months before the child died. The most common diagnosis among children receiving palliative care was a brain tumor (45%) with a disease related death (90%) and the care was often received at home (44%). Based on the reports of parents who felt that their child did not receive palliative care, 45% were informed within days or hours about the child's incurable disease, 45% of these children were diagnosed with leukemia, 60% died at the intensive care unit, and 49% died of treatment-related complications. It was most common for families who lived in urban areas (28%) to report their child received palliative care, in comparison to families living in sparsely populated areas (11%). A significant proportion of parents whose child received palliative care (96%) stated that the healthcare professionals were competent in caring for their child, for those who reported no palliative care it was slightly lower (74%). In both groups many children were affected by multiple symptoms the last month of life. Conclusions: The study findings highlight the role of understanding parental perceptions of pediatric palliative oncology care, the role of initiating palliative care early, the need of access to national equitable PC and professional competence across the lifespan, regardless of diagnosis and place of residence. [ABSTRACT FROM AUTHOR]

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Gridded data sets representing the distribution of the human population are increasingly available globally today. If most of the attention they draw is directed toward inhabited areas, in this article, the authors turns to very sparsely or unpopulated areas, which allow for a renewed exploration of their reality and a reflection on the essence of "unpopulatedness." To do so, the author reflects on the multiplication of gridded population data sets and the methods used to produce them, using unpopulated areas as a revealing factor of the limits of algorithms. In the second part, different geographical concepts related to uninhabited areas are explored to show that their reality is not clear-cut and more difficult to grasp than data sets based on population density indicate. Very sparsely populated or unpopulated areas include a vast array of regions and situations, from areas not permanently settled but heavily used and travelled to areas that are very infrequently visited. Their levels of transformation by human activities, frequentation, or accessibility differ wildly, so it is impossible to consider them as a unique or coherent category. In conclusion, the author calls for going beyond the "nobody lives there" vision, popular on the internet, by understanding better how population gridded data sets are constructed and by complementing them with new quantitative and qualitative data, which could help distinguish between several nuances of occupation in space and time. [ABSTRACT FROM AUTHOR]

Solar photovoltaics have emerged as an economic source of renewable electricity generation for regions with high solar irradiation. Still, the installation of utility-scale PV systems is often disrupted due to the unavailability of land. Sparsely populated areas with a hot, dry climate can mitigate the land-energy conflict as they experience higher solar irradiation. In arid areas, the PV systems incur more losses due to dust deposition on PV modules and reduced energy conversion efficiency at higher temperatures. The shortage of water makes the module cleaning procedures cost-prohibitive. Floating Solar photovoltaic (FSPV) systems resolve these problems due to their reduced land footprint, higher efficiency, and reduce evaporative water loss. This study estimates the energy generation of a 4.8 MW FSPV-based microgrid in a hot, semi-arid urban area. By utilizing 5% area of the waterbody, the FSPV system yields 8.876 GWh of electricity annually, to meet 41.7% electricity demand of the study area. The system generates 16.7% more power compared to the land-based PV system. The performance ratio of 82%, and a DC capacity utilization factor of 20.3% is achieved. The system saves 52,810.32 m3 of water per year, compensating for the water requirement of 786.99 m3. for cleaning and dust removal of PV modules. The weekly cleaning procedure limits the soiling loss to 2.79%, compared to 8.47% after a month without cleaning. The FSPV-based microgrid reduces annual CO2 emissions by 2.93 tonnes. This study shall enable engineers, urban planners, and policymakers to develop clean energy-based, sustainable microgrid solutions for urban areas. [ABSTRACT FROM AUTHOR]

In recent years, the problem of ecosystem degradation caused by human activities has become increasingly serious. Vegetation restoration is a key means to solve this problem, which has increased. To address the suitability and structural optimization of vegetation restoration in the Loess Plateau (China), the MaxEnt model was used to quantify the impacts of environmental and human activities on the planting suitability of vegetation restoration species at the raster scale. Three layers of trees, shrubs, and herbs with 12 common vegetation restoration species were selected. The factor index system was constructed by combining climatic, ecological, and socio-economic data, and the MaxEnt model predicted land suitability. It was found that human activities significantly increased the unsuitable planting area. This especially affected Robinia pseudoacacia in the tree layer and Amorpha fruticosa in the shrub layer. High and medium suitable areas were mainly sparsely populated areas with close water sources. Through maximum suitability optimization, it was identified that the overall spatial distribution of the three layers in the study area was relatively consistent, and the structural dominance of trees + shrubs + herbs and single herbs in the vertical structure was obvious; these were concentrated in the southwestern and northeastern parts of the study area, respectively. In addition, organic content (OC) and distance from the road to woodland (RW) were the dominant factors affecting land suitability, with a contribution rate of more than 50% and up to 80%. These results provide a scientific basis for optimizing planting structures. They are of significant theoretical and practical significance in guiding vegetation restoration work. [ABSTRACT FROM AUTHOR]

Low Earth orbit (LEO) communication satellite constellation provides network service to remote areas without terrestrialnetwork coverage. In sparsely populated areas, the deployment of ground stations is also scarce, due to geographic constraints and the lack of terrestrial backhaul. Due to the constant orbiting of the satellite constellation, location management in LEO satellite-assisted vehicular networks faces the challenges of the dual mobility of access points and users. In this paper, we propose a privacy-preserving location management scheme in an LEO satellite network with sparsely deployed ground stations. Specifically, the proposed scheme exploits the RSA-based accumulator and the Non-Interactive Proof-of-Knowledge of Exponent (NI - PoKE ) protocol to verify the linkages between satellites and vehicles. Meanwhile, our scheme combines the homomorphic Symmetric Homomorphic Encryption (SHE ) cryptosystem, the Secure Less than (SLESS ) protocol, and the KdTree structure, to identify the potential set of accessing satellites. Security analysis shows that the proposed scheme achieves privacy preservation and authentication. Performance evaluations show that ours achieve high computation and communication efficiency. [ABSTRACT FROM AUTHOR]

Demand-responsive transport (DRT) could be an alternative for extending the accessibility of high-speed rail (HSR) servicing cities in rural environments, where fixed public transport does not provide efficient services. This paper proposes a method to analyse the factors that influence the implementation of DRT systems for inter-urban mobility, connecting and integrating towns in rural areas. Methodologically, a vehicle routing problem analysis in a GIS-based environment is applied to a theoretical case study to evaluate the factors that influence DRT efficiency in different scenarios, considering the specific singularities of this kind of inter-urban long-distance mobility. The results suggest the optimal DRT solutions in these rural contexts to be those that, after adjusting the fleet to specific demands, use low-capacity vehicles, which are much better adapted to the geography of sparsely populated areas. Moreover, in adapting DRT systems to HSR travellers' needs, windows catering to these needs should incorporate the option of setting the pickup or arrival times. This paper demonstrates that DRT systems could reach significant levels of service in rural areas compared with fixed lines and even private vehicles, especially when evaluating key aspects of the system's efficiency for its implementation. [ABSTRACT FROM AUTHOR]

The article "People Enslaved at Fairfield and Auckland Plantations (1773-ca. 1792)" by Zoie Horecny explores the lives of enslaved individuals at these plantations through historical inventories. The dataset compiled from the Fairfield Plantation Book provides demographic information, familial relationships, and insights into the labor and daily lives of those enslaved. The research sheds light on the experiences of enslaved people in the South Carolina Lowcountry, highlighting the role of the Pinckney family in maintaining the institution of slavery. The dataset aims to connect genealogical information and descendant communities to deepen understanding of enslaved communities across multiple plantations. [Extracted from the article]

This study employs the aspirations‐capabilities framework to explore the intricate interplay between choices and constraints shaping migrants' settlement patterns, with a particular emphasis on the often‐overlooked aspect of educational attainment. Using Swedish register data containing information about migrants' educational level, this paper examines and typifies the initial residential sorting patterns of migrants arriving in Sweden in the period 2000–2014. Employing multinomial logistic regression to understand how migrant sorting takes place, the results show a clear distinction in settlement patterns, with higher educated migrants being more likely to settle in metropolitan areas, and lower educated migrants ending up in rural areas, even when controlling for region of origin and purpose of migration. Nordic and African migrants, resettled refugees, older migrants, and migrant families with younger children are most likely to live in sparsely populated areas. The paper concludes that these trends exacerbate existing patterns of spatial polarization. [ABSTRACT FROM AUTHOR]

The European Smart Specialisation Strategy (S3) with its underlying aim to support regional growth, cohesion, and innovation has by now been widely applied to European Sparsely Populated Areas (SPAs). Previous works have identified that intra-regional stakeholder networks are important for a successful S3 implementation, and that their establishment is related to the level of proximity between stakeholders; however, the nature of such networks in the context of developing S3 in SPAs deserves further investigation. This paper explores how different dimensions of proximity are associated with intra-regional networks aimed at implementing S3 in a Northern European SPA (Lapland, Finland). The results suggest that geographical and cognitive proximity are positively associated with both formal and informal networking, while institutional proximity is negatively related with informal networking, suggesting that effective policy interventions require multiple relationships to be activated through supporting greater diversity between SPAs stakeholders. [ABSTRACT FROM AUTHOR]

Background: The attractive targeted sugar bait (ATSB) is a novel malaria vector control tool designed to attract and kill mosquitoes using a sugar-based bait, laced with oral toxicant. Western Province, Zambia, was one of three countries selected for a series of phase III cluster randomized controlled trials of the Westham ATSB Sarabi version 1.2. The trial sites in Kenya, Mali, and Zambia were selected to represent a range of different ecologies and malaria transmission settings across sub-Saharan Africa. This case study describes the key characteristics of the ATSB Zambia trial site to allow for interpretation of the results relative to the Kenya and Mali sites. Methods: This study site characterization incorporates data from the trial baseline epidemiological and mosquito sugar feeding surveys conducted in 2021, as well as relevant literature on the study area. Results: Characterization of the trial site The trial site in Zambia was comprised of 70 trial-designed clusters in Kaoma, Nkeyema, and Luampa districts. Population settlements in the trial site were dispersed across a large geographic area with sparsely populated villages. The overall population density in the 70 study clusters was 65.7 people per square kilometre with a total site population of 122,023 people living in a geographic area that covered 1858 square kilometres. However, the study clusters were distributed over a total area of approximately 11,728 square kilometres. The region was tropical with intense and seasonal malaria transmission. An abundance of trees and other plants in the trial site were potential sources of sugar meals for malaria vectors. Fourteen Anopheles species were endemic in the site and Anopheles funestus was the dominant vector, likely accounting for around 95% of all Plasmodium falciparum malaria infections. Despite high coverage of indoor residual spraying and insecticide-treated nets, the baseline malaria prevalence during the peak malaria transmission season was 50% among people ages six months and older. Conclusion: Malaria transmission remains high in Western Province, Zambia, despite coverage with vector control tools. New strategies are needed to address the drivers of malaria transmission in this region and other malaria-endemic areas in sub-Saharan Africa. [ABSTRACT FROM AUTHOR]

This paper deals with public transport services in sparsely populated areas. The definition of the term transport services and possible approaches to its provision is given in the introduction. The term sparsely populated area is subsequently defined. The problems that arise during the organization of transport services in these areas are further defined. These problems lie primarily in the variations in the number of people in the thousands in the area in the off-tourist season and in the summer tourist season. This affects the organization of transport and the organization of transport services. This paper proposes the technological procedure and measures for improving transport services in sparsely populated areas outside and during the summer tourist season. The proposals are applied in a selected sparsely populated area in the territory of the National Park Šumava and the Šumava Protected Landscape Area in the Czech Republic. [ABSTRACT FROM AUTHOR]

Sparsely populated areas of developed countries are regions of great demographic diversity and dynamism. While they remain strategically and economically important, trends in urbanization and technology have increased their relative sparsity and isolation making centralized government, service delivery and planning a challenge. Populations of their sub-jurisdictions are small and often exhibit significant heterogeneity in key demographic characteristics, not least between their Indigenous first residents and non-Indigenous citizens. Development of projection models for these areas is challenged by significant input data paucity, biases and structural issues related to the data collection and estimation architectures in place to gather input data across diverse and small populations. While this is the case, the demand for and importance of projections is no less for sparsely populated areas than elsewhere. Variants of the cohort component model are important tools for population projections for SPAs, with their grounding in the demographic accounting equation and modest input requirements. Nevertheless, to attain fit-for-purpose input data requires demographers to consider and select from a growing number of methods for smoothing issues with input data for projections for these regions. In this article we analyze the contributions of recent advances in methods for estimating fertility, mortality, and migration rates for small and diverse populations such as those in SPAs, focusing on the very sparsely populated jurisdiction of the Northern Territory of Australia. In addition to the contributions of our method itself, results at the detailed level demonstrate how abnormal and challenging ‘doing’ projections for sparsely populated areas can be. [ABSTRACT FROM AUTHOR]

The necessary implementation of decentralized wastewater treatment systems in densely populated rural regions is a viable alternative to constructing a large centralized system. Therefore, this study aims to assess the conceptual feasibility of implementing a portable containerized and decentralized wastewater treatment system as a case study in Palestine that can help in treating wastewater in rural areas efficiently generated by up to 4,000 individuals. The conceptually proposed system is comprised of two stages. The initial stage includes a standalone primary sedimentation tank located outside the container. The subsequent stage consists of a container housing all the equipment utilized in the treatment process beginning with aeration, followed by secondary sedimentation, and ending with filtration and chlorination. Although the system is designed as a single container, in practice, it will consist of two containers with identical units. The second container will ensure continuous operation mode in case of maintenance in the first container. An initial cost evaluation was conducted, and the projected cost for one container is roughly $9,800, which is reasonable. Indeed, adopting this proposed system would result in a significant cost-saving of approximately 40 million dollars compared to the current west wastewater treatment plant in Nablus. Additional research can be undertaken to explore the running cost and the level of efficacy attained. [ABSTRACT FROM AUTHOR]

The landscapes and, implicitly, the surfaces of secondary grasslands in the mountain areas have been intensively modified and transformed by humans. In this context, this paper analyses the spatial and temporal changes of grassland surfaces following the impact of human population reduction. Thus, the study proposes the implementation of the Grassland Anthropic Impact Index (GAII) as a "measurement tool" to functionally link the two components, grassland surface and human population. The spatiotemporal analyses are based on Corine Land Cover data and demographic data, processed via Geographic Information Systems (GIS) methods and the Land Change Modeler (LCM) tool. The research shows that over a period of 28 years, the population, which was continuously decreasing, caused a series of transformations to the grasslands over an area of 33343 ha. The influence of the reduction in the number of inhabitants was also demonstrated by the direction of the changes produced in the grassland surfaces: in the better populated areas, the grasslands expanded over lands with other uses, and in the sparsely populated areas, they were abandoned. GAII values generally increase with the decrease of the population in the target area, meaning that for an inhabitant (potential user) a greater grassland surface is reported, resulting in a greater responsibility for the management of this resource on a space and time scale. Following the evaluation of the trend of the last 28 years, it was observed that the depopulation of mountain areas can be seen as a threat to grassland ecosystems, either through the transition to other categories of use, or through abandonment. The implications of these phenomena are much broader: they produce chain reactions and affect other components of the regional geosystem. [ABSTRACT FROM AUTHOR]

Due to the economic infeasibility of establishing comprehensive healthcare facilities in sparsely populated areas and the responsibility of governments to ensure equal healthcare access for citizens, different approaches have been sought in healthcare service delivery. The Republic of Turkiye's Ministry of Health provides mobile healthcare services (MHS) to 9 million people monthly through 3400 healthcare facilities and 7500 doctors. This study focuses on the Mobile Healthcare Service Routing and Scheduling Problem (MHS-RSP). The objective of MHS-RSP is to determine the daily routes of doctors on a monthly basis to minimize total distance traveled, taking into account constraints such as working hours, route time, minimum service time per visit, and dedicated doctor assignments to villages. A mixed-integer mathematical model is developed to address the problem, which is NP-hard and equivalent to the multi-depot time-constrained periodic vehicle routing problem. To solve medium- and large-sized problems efficiently, a hybrid metaheuristic algorithm named "GCH-RRT" is introduced, based on greedy constructive heuristic(GCH) and record-to-record travel(RRT) metaheuristic. The performance of the mathematical model and the GCH-RRT algorithm is compared with existing service plans in Ankara, resulting in a 15.6% improvement with the mathematical model and a 22.3% improvement with the GCH-RRT algorithm in total distance traveled. [ABSTRACT FROM AUTHOR]

Background: A lack of onsite clinical trials is the largest barrier to participation of cancer patients in trials. Development of an automated process for regional trial eligibility screening first requires identification of patient electronic health record data that allows effective trial screening, and evidence that searching for trials regionally has a positive impact compared with site‐specific searching. Methods: To assess a screening framework that would support an automated regional search tool, a set of patient clinical variables was analyzed for prescreening clinical trials. The variables were used to assess regional compared with site‐specific screening throughout the United States. Results: Eight core variables from patient electronic health records were identified that yielded likely matches in a prescreen process. Assessment of the screening framework was performed using these variables to search for trials locally and regionally for an 84‐patient cohort. The likelihood that a trial returned in this prescreen was a provisional trial match was 45.7%. Expanding the search radius to 20 miles led to a net 91% increase in matches across cancers within the tested cohort. In a U.S. regional analysis, for sparsely populated areas, searching a 100‐mile radius using the prescreening framework was needed, whereas for urban areas a 20‐mile radius was sufficient. Conclusion: A clinical trial screening framework was assessed that uses limited patient data to efficiently and effectively identify prescreen matches for clinical trials. This framework improves trial matching rates when searching regionally compared with locally, although the applicability of this framework may vary geographically depending on oncology practice density. Plain Language Summary: Clinical trials provide cancer patients the opportunity to participate in research and development of new drugs and treatment approaches. It can be difficult to find available clinical trials for which a patient is eligible.This article describes an approach to clinical trial matching using limited patient data to search for trials regionally, beyond just the patient's local care site.Feasibility testing shows that this process can lead to a net 91% increase in the number of potential clinical trial matches available within 20 miles of a patient.Based on these findings, a software tool based on this model is being developed that will automatically send limited, deidentified information from patient medical records to services that can identify possible clinical trials within a given region. To increase patient access to clinical trials, a prescreening framework was developed using deidentified data elements extracted from patient electronic health records to identify likely clinical trials in a regional manner. Feasibility testing shows that this framework effectively performs trial eligibility screening using limited patient data and improves trial matching rates because of regional search capability. [ABSTRACT FROM AUTHOR]

The state of sea trout in 1251 Norwegian watercourses was assessed based on a scoring system for human pressures, abundance data, and local knowledge.Over 16,000 km of rivers and lakes were available to sea trout in these watercourses, spanning from the temperate to Arctic regions.Sea trout were classified to be in a good or very good state in fewer than 25% of the watercourses and in a poor or very poor state in almost 40%. Twenty‐nine watercourses had lost their sea trout populations.Salmon lice from aquaculture salmon farms had by far the largest adverse effect on sea trout among the human impact factors, both in the number of watercourses (83%) and river area affected (60%), and the total effect on sea trout abundance.Agriculture and hydropower production also had strong adverse impacts (35% and 19% of watercourses), but substantially lower than that caused by salmon lice. Culverts related to road crossings and other habitat alterations also had impacts on sea trout in many watercourses (27%).Exploitation of sea trout has been reduced in Norway in recent years, both in the marine and freshwater fisheries. Yet, the exploitation pressure was moderate or high in almost 14% of the watercourses where the state of sea trout was poor or very poor, suggesting a high potential for overexploitation in these.The state of sea trout was best in the northern sparsely populated areas. However, distribution of watercourses with sea trout in a poor or very poor state was more linked to aquaculture, agriculture, and hydropower production than human population density.The developed approach for large‐scale mapping of state and pressures, which is vital for prioritizing management measures, may inspire other nations in their conservation effort for this important species. [ABSTRACT FROM AUTHOR]

Unpaved roads, usually found in rural and sparsely populated areas, are prone to dust, potholes, corrugations, rutting and loose gravel and deteriorate faster than paved roads. Thus, they require regular condition monitoring to keep them at the required level of service. However, the cost of condition assessment could be huge, considering how vast and far away they are from the cities. Currently, subjective visual surveys and manual methods for monitoring and assessing the condition of unpaved roads dominate, while data-driven objective methods are not commonly applied for maintenance planning and decision-making. The paper proposes a participatory data-driven approach for unpaved road condition monitoring based on the literature and an exploratory case study of road maintenance practices in Sweden and Zambia. Participatory data collection empowers regular unpaved road users to collect road condition data, for instance, by equipping their vehicles with the relevant data acquisition devices embedded with a global positioning system (GPS) as they drive on unpaved roads on a typical day. By integrating open data collection aligned with sustainable practices, regular unpaved road users (garbage collectors, postal service providers, and road owners) share the collected condition data with the road governing bodies and process it for Nowcasting and Forecasting the unpaved road condition, thus providing valuable information for condition monitoring of unpaved roads. Thus, road users can support long-term maintenance planning and decision-making, potentially improving unpaved road management and minimising the cost of collecting and evaluating unpaved road condition data. However, the participating road users require training in data acquisition, and the vehicles must be calibrated according to the sensor properties, vehicle vibration response and speed to ensure quality data collection. Based on the literature and the case study findings, participatory data collection for unpaved roads can provide an efficient and effective alternative for collecting road condition data, accomplishing broad coverage. [ABSTRACT FROM AUTHOR]

This article explores the historical background and legends surrounding the headless horseman in Washington Irving's "The Legend of Sleepy Hollow." It investigates the claims of Hessian presence in the Tarry Town area during the American Revolution and examines the possibility of a connection between the headless horseman and these troops. The article also discusses the military demographics of German Auxiliary deployment during the Revolution and provides information on the routes taken by captured German soldiers. The author suggests the use of advanced technology to scientifically study the energy field of the headless horseman. The text confirms certain factual aspects of Irving's legend, such as the existence of North Tarry Town (now Sleepy Hollow) and the Old Dutch graveyard, as well as the presence of a wooden bridge mentioned in the story. It also discusses the possible inspiration for the Headless Horseman character, including a reference to a decapitated Hessian in General Heath's Memoirs. The text mentions that some of the characters in the legend were based on real people from the area. The text explores various facts and legends surrounding the story of the Headless Horseman in Sleepy Hollow, including an incident in 1777 where homes were burned and militia officers were targeted. It also mentions the story of Elizabeth Van Tassel running back into her burning house to save her baby, and the alleged burial of a decapitated Hessian soldier by the Van Tassel family. The text discusses the connection between the Headless Horseman and the Hessian soldiers, [Extracted from the article]

The estimate of precipitation from satellite measurements is an indirect estimate if compared to rain gauges or disdrometer measurements, but it has the advantage of complete coverage over oceans, mountainous regions, and sparsely populated areas where other sources of precipitation data (e.g., weather radar) are unavailable or unreliable. Among the satellite-based precipitation estimates, geostationary (GEO) data ensure the highest spatial and temporal resolution. At the same time, the IR/VIS channels deployed on GEO satellites have lower capabilities than microwave (MW) channels in characterizing the cloud structure. Machine learning (ML) techniques can be considered a powerful tool to overcome the limitations related to the physical relationship between IR/VIS channels and precipitation estimation. This study describes the development of a convolutional neural network (U-Net) to retrieve the precipitation rate using IR measurements only from the Meteosat Second Generation (MSG) satellite. Its performances are evaluated through a comparison with H SAF and NASA operational products (e.g., H60B or H03B and IMERG-E, respectively), of which the algorithms are based on different principles. The results highlight a lower error in precipitation rate estimates for the U-Net with respect to the other products but also some issues in correctly estimating the more intense precipitation (>5 mmh−1). On the other hand, the precipitation detection capabilities of the U-Net outperform the H SAF products for lower precipitation rate, while IMERG-E shows the best performance regardless of the precipitation regime. Furthermore, the U-Net is able to account for and correct the parallax displacement that affects the measurement as the satellite viewing angle increases. [ABSTRACT FROM AUTHOR]

Monitoring of the water level and river discharge is an important task, necessary both for assessment of water supply in the current season and for forecasting water consumption and possible prevention of catastrophic events. A network of ground hydrometric stations is used to measure the water level and consumption in rivers. Rivers located in sparsely populated areas in developing countries of Central Asia have a very limited hydrometric network. In addition to the sparse network of stations, in some cases remote probing data (virtual hydrometric stations) are used, which can improve the reliability of water level and discharge estimates, especially for large mountain rivers with large volumes of suspended sediment load and significant channel instability. The aim of this study is to develop a machine learning model for remote monitoring of water levels in the large transboundary (Kazakhstan-People's Republic of China) Ili River. The optical data from the Sentinel-2 satellite are used as input data. The in situ (ground-based) data collected at the Ili-Dobyn gauging station are used as target values. Application of feature engineering and ensemble machine learning techniques has achieved good accuracy of water level estimation (Nash–Sutcliffe model efficiency coefficient (NSE) >0.8). The coefficient of determination of the model results obtained using cross-validation of random permutations is NSE = 0.89. The method demonstrates good stability under different variations of input data and ranges of water levels (NSE > 0.8). The average absolute error of the method ranges from 0.12 to 0.18 meters against the background of the maximum river water level spread of more than 4 meters. The obtained result is the best current result of water level prediction in the Ili River using the remote probing data and can be recommended for practical use for increasing the reliability of water level estimation and reverse engineering of data in the process of river discharge monitoring. [ABSTRACT FROM AUTHOR]

Wildfire ignition models can help in identifying risk factors and mapping high-risk areas, which addresses an urgent issue as wildfires become increasingly destructive. Despite advancements in data collection and data analysis, challenges persist as ignitions depend on numerous interconnected factors at a fine spatial resolution. Predicting wildfire ignitions from data is an imbalanced classification problem, given the vast number of non-ignition data compared to ignition data. To address this issue, this study proposes an ensemble-based model for binary classification of wildfire ignitions. The data are collected for a 24,867 km2 area in northern California from January 2014 to May 2022 and includes 76 predictors covering topographic, land cover, anthropogenic, and climatic data. Different base classifiers are evaluated and the random forest is found the most performant, yielding a recall of 0.67 and a specificity of 0.87. Feature importance analysis shows that the Topographic Wetness Index is the most important climatic predictor, while population density and land cover development are also highly rated. Comparison of yearly average of computed daily probabilities with ignition data shows that the model accurately captures the spatial pattern of ignitions, which can reveal high-risk areas. The model is then used to assess how climatic and anthropogenic factors impact wildfire ignition frequency. The projected scenarios show that the number and spread of ignitions would significantly increase with an increase in population in sparsely populated areas, while climatic factors have secondary effects in isolation but in combination may compound the risk. As current land development and climate change trends are expected to increase the frequency and severity of wildfires, data-based models can provide insights to inform policy and mitigate risk. [ABSTRACT FROM AUTHOR]

The aim of the paper is to assess the impact of socio-economic and socio-demographic factors on the risk of poverty or social exclusion. The paper focuses on the analysis of the probability of social exclusion of the Slovak population from 4 perspectives, from being at risk of poverty or social exclusion, at risk of poverty, severely materially deprived, and living in a (quasi-)jobless household. The least-square means analysis and contrast analysis linked to logit models were used to identify risk groups, and to estimate the social exclusion probabilities. Based on the EU-SILC 2020 database, unemployed persons with low education and persons from single-parent and multi-child households had the greatest risk of social exclusion in Slovakia. Under ceteris paribus conditions, the risk decreased with increasing age and improving health status. The riskiest marital status was divorced. Analyses revealed regional disparities from the point of view of all 4 perspectives, with people living in South-Center and Eastern Slovakia and people living in sparsely and moderately populated areas having the greatest risk. Since economic activity status, household type, and educational attainment level showed as the most relevant factors, the article pays special attention to the assessment of the mutual influence of these factors. Although the pattern of the risk of social exclusion of persons broken down by household type and education for the unemployed and employed is similar, the riskiness of the most vulnerable groups of people is more pronounced for employed persons. [ABSTRACT FROM AUTHOR]

If a local government receives unconditional funding to design and implement a local development policy, what does it do? This quasi-experimental situation occurred in 2018 when the Swedish government started to allocate 70 million SEK per year to 39 municipalities in the most sparsely populated rural north of the country. The funds' purpose was to support local development initiatives, but they were unconditional and came without specific requirements. Against this backdrop, we analyse how local governments define and address problems related to local economic development, the solutions they develop to address these problems, and the analytical and normative frameworks that guide their decisions. We contrast the identified frameworks with the contemporary literature on place-based policy and planning to determine whether, and to what extent, local economic development policy in rural Sweden reflects the idea that policy and planning should take place-based conditions into account. [ABSTRACT FROM AUTHOR]

Cabo Ortegal, in Spain, was declared a UNESCO Global Geopark in 2023. An ultramafic complex makes it a geologically exciting unit, where many research works have been carried out. Serpentinites, formed by the weathering of peridotites, dunites, and other ultramafic rocks, have been described in detail in previous works. Their role as a construction material has been elucidated, although due to their complexity and heterogeneity, the results of using these materials for construction are not always successful. Talcose rocks, related to serpentinites, can also be found in the complex, although it is difficult to distinguish them. Talcose rocks may be a resource to be explored and exploited in an unpopulated area. The use of talc in pharmaceuticals, cosmetics, and handicrafts makes it a material of growing importance. However, the asbestos and heavy metal content should be severely limited to prevent health issues. The goal of this work is to start the characterization of these talcose rocks before promoting their potential use in different contexts to support the economy of an underpopulated area of Spain. [ABSTRACT FROM AUTHOR]

Current seismic design codes define safety levels based on the seismic risk of individual structures, such as specifying a maximum probability of collapse in 50 years. The design remains the same whether the structure is located within a sparsely populated area or within a densely populated area provided that both areas have the same seismic hazard. A novel seismic design approach, referred to as regional‐risk‐targeted seismic design is proposed in which the design level is based on a target seismic risk at the regional scale, as opposed to at the individual structure level. The proposed approach, which is aimed at new constructions, allows local governments to define acceptable levels of regional seismic risk and modify the seismic design criteria contained in national standards to satisfy them. As the possible consequences of a seismic event increase at the regional level, the design level becomes more stringent to control the regional seismic risk to acceptable limits. A series of simplifications are considered to facilitate its application. We illustrate the application of the proposed regional‐risk‐targeted seismic design with three examples in the city of San Francisco, California. In these examples, we iteratively compute the modifications to the maximum seismic risk on individual structures required to comply with specific target levels of regional seismic risk. In the proposed approach, the maximum tolerable seismic risk in individual structures depends not only on the seismic hazard at the site, but also on the number of structures and density in the region of interest. It is concluded that the proposed seismic design approach provides a more rational tool for local government officials to set and calibrate seismic design criteria to comply with their locally‐defined acceptable levels of regional seismic risks within a probabilistic risk management framework. [ABSTRACT FROM AUTHOR]