Search Results (30)

In remote sensing building detection tasks, data acquisition remains a critical bottleneck that limits both model performance and large-scale deployment. Due to the high cost of manual annotation, limited geographic coverage, and constraints of image acquisition conditions, obtaining large-scale, high-quality labeled datasets remains a significant challenge. To address this issue, this study proposes an automatic semantic labeling framework for remote sensing imagery. The framework leverages geospatial vector data provided by OpenStreetMap, precisely aligns it with high-resolution satellite imagery from Bing Maps through projection transformation, and incorporates a quality-aware sample filtering strategy to automatically generate accurate annotations for building detection. The resulting dataset comprises 36,647 samples, covering buildings in both urban and suburban areas across multiple cities. To evaluate its effectiveness, we selected three publicly available datasets—WHU, INRIA, and DZU—and conducted three types of experiments using the following four representative object detection models: SSD, Faster R-CNN, DETR, and YOLOv11s. The experiments include benchmark performance evaluation, input perturbation robustness testing, and cross-dataset generalization analysis. Results show that our dataset achieved a mAP at 0.5 intersection over union of up to 93.2%, with a precision of 89.4% and a recall of 90.6%, outperforming the open-source benchmarks across all four models. Furthermore, when simulating real-world noise in satellite image acquisition—such as motion blur and brightness variation—our dataset maintained a mean average precision of 90.4% under the most severe perturbation, indicating strong robustness. In addition, it demonstrated superior cross-dataset stability compared to the benchmarks. Finally, comparative experiments conducted on public test areas further validated the effectiveness and reliability of the proposed annotation framework. Full article

Accurate and detailed spatial data on wind energy infrastructure is essential for renewable energy planning, grid integration, and system analysis. However, publicly available datasets often suffer from limited spatial accuracy, missing attributes, and inconsistent metadata. To address these challenges, this study presents a harmonized and spatially refined dataset of wind turbines in South Africa, combining OpenStreetMap (OSM) data with high-resolution satellite imagery, deep learning-based coordinate correction, and manual curation. The dataset includes 1487 turbines across 42 wind farms, representing over 3.9 GW of installed capacity as of 2025. Of this, more than 3.6 GW is currently operational. The Geo-Coordinates were validated and corrected using a RetinaNet-based object detection model applied to both Google and Bing satellite imagery. Instead of relying solely on spatial precision, the curation process emphasized attribute completeness and consistency. Through systematic verification and cross-referencing with multiple public sources, the final dataset achieves a high level of attribute completeness and internal consistency across all turbines, including turbine type, rated capacity, and commissioning year. The resulting dataset is the most accurate and comprehensive publicly available dataset on wind turbines in South Africa to date. It provides a robust foundation for spatial analysis, energy modeling, and policy assessment related to wind energy development. The dataset is publicly available. Full article

Introduction: Autism and ADHD shape behaviours related to food, exercise, and body image, potentially influencing obesity treatment outcomes, as seen in eating disorder research. Resultantly, autistic and ADHD patients with obesity may have distinct experiences and differences compared to non-autistic and non-ADHD patients. This review maps existing literature on autism and ADHD in adults with obesity. Methods: Following PRISMA guidelines, six databases (Embase, MEDLINE, PsycINFO, Web of Science, CENTRAL, and Scopus) were searched for studies on autism and/or ADHD (diagnosed, probable, or traits) in adults with obesity. Screening and data extraction were conducted twice independently for each record. Results: Thirty-one studies were included, with 1,027,773 participants. Two case reports described successful use of weight loss drugs in autistic people with obesity. Eight prevalence studies suggested ADHD is overrepresented in obesity, regardless of binge eating status. Nineteen studies examined clinical profiles: ADHD patients had lower socioeconomic status, poorer health-related quality of life, increased impulsivity, cognitive inflexibility, and neuroticism, alongside lower agreeableness, conscientiousness, self-directedness, and cooperativeness. ADHD patients also exhibited higher psychopathology, problematic alcohol use, and disordered eating. Eight studies assessed treatment responses, noting poorer outcomes from behavioural programs and obesity pharmacotherapy, but similar post-surgical weight outcomes, despite increased complications. Two studies considered ADHD-specific treatment adaptions, one reporting a successful trial of ADHD medication for weight loss and the other reporting on switching to transdermal ADHD medications after bariatric surgery. Conclusions: This review underscores the need for more research on autism and obesity. For ADHD, findings suggest frequent co-occurrence with obesity, but lived experiences and tailored interventions remain underexplored. Full article

Geospatial tools and geocoding systems play an increasingly significant role in the modernization and operation of municipal water utility networks. This research explored how geocoding systems could improve network management, facilitate leak detection, and enhance hydraulic modeling accuracy. Various geocoding services, including Google, Bing Maps, and OpenStreetMap APIs were analyzed using address data from a small Central European municipality. The analysis was performed in February and March of 2024. The accuracy and efficiency of these systems in handling spatial data for domestic water networks were assessed and results showed that geocoding accuracy depended on the quality of the service provider databases and the formatting of input data. Google proved the most reliable, while Bing and OpenStreetMap were less accurate. Additionally, the Location Database developed by Lechner Knowledge Center was used as a reliable local reference for comparison with global services. Geocoding results were integrated into GIS softwares (Google Earth ver. 7.3.6.9796, QGIS ver. 3.36, ArcGIS ver 10.8.2) to enable spatial analysis and comparison of geographic coordinates. The findings highlight geocoding’s critical role in efficient water network management, particularly for mapping consumer data and rapidly localizing leaks and breaks. Our findings directly support hydraulic modeling tasks, contributing to sustainable operations and cost-effective interventions. Full article

Although there are many articles dealing with web map applications, they often focus on just one or a few applications. Several articles deal with the technical solution of the applications, but relatively few are focused on the cartographic aspects of these applications. This article evaluates eight web mapping applications based on six cartographic aspects: map key, map scale, map layout, navigation elements, labels, and analytical tools. The objective is to identify differences in the presentation of geographic information and propose improvements for cartographic quality and user-friendliness. The methodology involved visual analysis at two scales. The comparison included applications such as Mapy.cz, OpenStreetMap, Google Maps, Bing Maps, HERE Maps, MapQuest, ViaMichelin, and Locus Map. The results revealed significant differences among the applications that may impact user orientation and experience. For instance, Google Maps does not display forest symbols on its default map, which can reduce clarity, whereas Mapy.cz offers the most comprehensive range of analytical tools. Advertisements in applications like MapQuest and ViaMichelin disrupt the user experience, and some applications lack essential functions, such as distance measurement. The paper identifies strengths and weaknesses in the cartographic design of these applications. Findings reveal that while each application possesses unique characteristics, they share common features. An interesting feature is the absence of cartographic symbols and labels of some elements in some applications. The study recommends the unification of cartographic principles and further user testing to optimize the layout and functionality of web mapping applications. Full article

Substance use disorders (SUDs) and anxiety disorders (ADs) are highly comorbid, a co-occurrence linked to worse clinical outcomes than either condition alone. While the neurobiological mechanisms involved in SUDs and anxiety disorders are intensively studied separately, the mechanisms underlying their comorbidity remain an emerging area of interest. This narrative review explores the neurobiological processes underlying this comorbidity, using the Research Domain Criteria (RDoC) framework to map disruptions in positive valence, negative valence, and cognitive systems across the three stages of the addiction cycle: binge/intoxication, withdrawal/negative affect, and preoccupation/anticipation. Anxiety and substance use play a reciprocal role at each stage of addiction, marked by significant psychosocial impairment and dysregulation in the brain. A more thorough understanding of the neural underpinnings involved in comorbid SUDs and anxiety disorders will contribute to more tailored and effective therapeutic interventions and assessments. Full article

Despite the numerous food studies conducted in Detroit, none have assessed changes in the food landscape over a decade. No previous study has systematically analyzed food store closures in the city either. We will address these oversights by examining the distribution of food outlets in the city ten years apart. This paper probes the following questions: (1) How has the distribution of Detroit’s food outlets changed in the decade between 2013 and 2023? (2) Does Detroit fit the definition of a food desert in 2013 or 2023? (3) Does Detroit fit the definition of a food swamp in 2013 or 2023? (4) Has supermarket redlining occurred in Detroit in 2013 or 2023? (5) How is population decline related to food outlet distribution? (6) How do food store closures impact food store distribution? We conducted exhaustive searches to collect information on thousands of food outlets from Data Axle, Google, and Bing. The data were analyzed and mapped in SPSS 28 and ArcGIS 10.8. We compared 3499 food outlets identified in 2013 with 2884 identified in 2023. We expanded our search for food outlets in 2023 and found an additional 611 food outlets in categories not studied in 2013. The study’s findings are significant as they unearth evidence of extensive population decline—driven by Black flight—and a vanishing food infrastructure. Detroit lost more than 600 food outlets between 2013 and 2023, a staggering number that underscores the severity of the issue. Moreover, in 2023, we documented food store closures and found 1305 non-operational or closed food outlets in the city. Regardless of the neighborhood’s racial composition, the household median income, or the educational attainment of residents, food store closures were widespread in 2023; 27.3% of the food outlets identified that year were defunct. Despite the massive food store closures, Detroit did not fit the description of a food desert; each of the city’s 54 neighborhoods had between 7 and 300 food outlets. The food swamp thesis did not accurately describe the city either, as supermarkets/large grocery stores were intermingled with convenience and corner stores in both study periods. The data did not find evidence of supermarket redlining, as supermarkets/large grocery stores were found in formerly redlined neighborhoods alongside dollar stores and variety stores in both study periods. Full article

In the present study, a new eye-tracking dataset (OnMapGaze) and a graph-based metric (GraphGazeD) for modeling visual perception differences are introduced. The dataset includes both experimental and analyzed gaze data collected during the observation of different cartographic backgrounds used in five online map services, including Google Maps, Wikimedia, Bing Maps, ESRI, and OSM, at three different zoom levels (12z, 14z, and 16z). The computation of the new metric is based on the utilization of aggregated gaze behavior data. Our dataset aims to serve as an objective ground truth for feeding artificial intelligence (AI) algorithms and developing computational models for predicting visual behavior during map reading. Both the OnMapGaze dataset and the source code for computing the GraphGazeD metric are freely distributed to the scientific community. Full article

Binge eating disorder (BED) is a complex and heritable mental health disorder, with genetic, neurobiological, neuroendocrinological, environmental and developmental factors all demonstrated to contribute to the aetiology of this illness. Although psychotherapy is the gold standard for treating BED, a significant subgroup of those treated do not recover. Neurobiological research highlights aberrances in neural regions associated with reward processing, emotion processing, self-regulation and executive function processes, which are clear therapeutic targets for future treatment frameworks. Evidence is emerging of the microbiota-gut-brain axis, which may mediate energy balance, high-lighting a possible underlying pathogenesis factor of BED, and provides a potential therapeutic strategy. Full article

Delivering vaccines in humanitarian response requires rigourous and continuous analysis of evidence. This systematic review mapped the normative landscape of vaccination guidance on vaccine-preventable diseases in crisis-affected settings. Guidance published between 2000 and 2022 was searched for, in English and French, on websites of humanitarian actors, Google, and Bing. Peer-reviewed database searches were performed in Global Health and Embase. Reference lists of all included documents were screened. We disseminated an online survey to professionals working in vaccination delivery in humanitarian contexts. There was a total of 48 eligible guidance documents, including technical guidance (n = 17), descriptive guidance (n = 16), operational guidance (n = 11), evidence reviews (n = 3), and ethical guidance (n = 1). Most were World Health Organization documents (n = 21) targeting children under 5 years of age. Critical appraisal revealed insufficient inclusion of affected populations and limited rigour in guideline development. We found limited information on vaccines including, yellow fever, cholera, meningococcal, hepatitis A, and varicella, as well as human papilloma virus (HPV). There is a plethora of vaccination guidance for vaccine-preventable diseases in humanitarian contexts. However, gaps remain in the critical and systematic inclusion of evidence, inclusion of the concept of “zero-dose” children and affected populations, ethical guidance, and specific recommendations for HPV and non-universally recommended vaccines, which must be addressed. Full article

Over the last several decades, both brain electrophysiological measurements, such as electroencephalogram (EEG) and event-related potentials/oscillations (ERPs/EROs), and neuroimaging measures have immensely contributed to our understanding of neural mechanisms underlying various psychiatric disorders, including alcohol use disorder (AUD). This Special Issue was launched to invite research and review articles that explore the utility of these neural measures to determine the effects of alcohol use (e.g., regular drinking, social drinking, binge/heavy drinking, and chronic drinking) on brain structure and function and/or to predict risk for developing AUD and other outcomes (e.g., other drug use and externalizing/internalizing traits) across various demographic characteristics (age, gender, ethnicity, etc.). We received seven scholarly articles, each dealing with specialized topics, which contribute to enhancing our understanding of the brain mechanisms underlying AUD and its risk. The titles of the contributing articles are: (i) Random Forest Classification of Alcohol Use Disorder Using EEG Source Functional Connectivity, Neuropsychological Functioning, and Impulsivity Measures; (ii) Delta Event-Related Oscillations Are Related to a History of Extreme Binge Drinking in Adolescence and Lifetime Suicide Risk; (iii) Alcohol Use and Prefrontal Cortex Volume Trajectories in Young Adults with Mood Disorders and Associated Clinical Outcomes; (iv) Statistical Nonparametric fMRI Maps in the Analysis of Response Inhibition in Abstinent Individuals with History of Alcohol Use Disorder; (v) Differentiating Individuals with and without Alcohol Use Disorder Using Resting-State fMRI Functional Connectivity of Reward Network, Neuropsychological Performance, and Impulsivity Measures; (vi) Epigenetic Effects in HPA Axis Genes Associated with Cortical Thickness, ERP Components and SUD Outcome; and (vii) Predicting Alcohol-Related Memory Problems in Older Adults: A Machine Learning Study with Multi-Domain Features. This Special Issue contains a range of useful topics, covering the utility of EEG, MRI, neuropsychology, epigenetics, environmental, behavioral, and clinical measures related to outcomes, and biological risks related to AUD, which will be useful to alcohol researchers around the world. Full article

Sleep and diet are essential for maintaining physical and mental health. These two factors are closely intertwined and affect each other in both timing and quality. Eating disorders, including anorexia nervosa and bulimia nervosa, are often accompanied by different sleep problems. In modern society, an increasing number of studies are being conducted on the relationship between eating disorders and sleep. To gain a more comprehensive understanding of this field and highlight influential papers as well as the main research domains in this area, a scientometric approach was used to review 727 publications from 1971 to 2023. All documents were retrieved from Scopus through the following string “TITLE-ABS ((“sleep” OR “insomnia”) AND (“anorexia nervosa” OR “bulimia nervosa” OR “binge eating” OR “eating disorder*”) AND NOT “obes*”) AND (LIMIT-TO (LANGUAGE, “English”))”. A document co-citation analysis was applied to map the relationship between relevant articles and their cited references as well as the gaps in the literature. Nine publications on sleep and eating disorders were frequently cited, with an article by Vetrugno and colleagues on nocturnal eating being the most impactful in the network. The results also indicated a total of seven major thematic research clusters. The qualitative inspection of clusters strongly highlights the reciprocal influence of disordered eating and sleeping patterns. Researchers have modelled this reciprocal influence by taking into account the role played by pharmacological (e.g., zolpidem, topiramate), hormonal (e.g., ghrelin), and psychological (e.g., anxiety, depression) factors, pharmacological triggers, and treatments for eating disorders and sleep problems. The use of scientometric perspectives provides valuable insights into the field related to sleep and eating disorders, which can guide future research directions and foster a more comprehensive understanding of this important area. Full article

The Covurlui Plateau, a subunit of the Moldavian Plateau located in eastern Romania, possesses a high natural agricultural potential, significantly impacted by soil erosion, particularly gully erosion. The only inventory in the Moldavian Plateau that comprises approximately 9000 gullies extracted from topographical maps was conducted during the 90s. Nowadays, with the advent of advanced techniques and geodata, such as GIS software, aerial photograms, high-resolution satellite images, and high-resolution digital elevation models, we aim to achieve an (1) up-to-date comprehensive inventory of gully head-cuts and (2) a very detailed mapping of the spatial distribution of gullied lands. Firstly, the gully head-cuts were inventoried for the entire region using platforms such as Google, Esri, and Bing, through the QuickMapService plugin within QGIS 3.16 software, with the assistance of Landsat and Sentinel satellite images. Secondly, the automatic mapping of gullies was carried out using a 5 m high-resolution Digital Elevation Model and the Topographic Openness module offered by SAGA GIS software through QGIS software. As a result, we identified 5868 gully head-cuts for the Covurlui Plateau, with an average density of 2.57 gully head-cuts per square kilometer. Additionally, the identified gullies occupy over 3570 hectares, representing 1.57% of the total area. Overall, the topographic openness index proves to be an efficient tool for the semi-automatic extraction of gullies from high-resolution digital elevation models. Full article

Binge drinking during adolescence increases the risk of alcohol use disorder, possibly by involving alterations of neuroimmune responses. Pleiotrophin (PTN) is a cytokine that inhibits Receptor Protein Tyrosine Phosphatase (RPTP) β/ζ. PTN and MY10, an RPTPβ/ζ pharmacological inhibitor, modulate ethanol behavioral and microglial responses in adult mice. Now, to study the contribution of endogenous PTN and the implication of its receptor RPTPβ/ζ in the neuroinflammatory response in the prefrontal cortex (PFC) after acute ethanol exposure in adolescence, we used MY10 (60 mg/kg) treatment and mice with transgenic PTN overexpression in the brain. Cytokine levels by X-MAP technology and gene expression of neuroinflammatory markers were determined 18 h after ethanol administration (6 g/kg) and compared with determinations performed 18 h after LPS administration (5 g/kg). Our data indicate that Ccl2, Il6, and Tnfa play important roles as mediators of PTN modulatory actions on the effects of ethanol in the adolescent PFC. The data suggest PTN and RPTPβ/ζ as targets to differentially modulate neuroinflammation in different contexts. In this regard, we identified for the first time important sex differences that affect the ability of the PTN/RPTPβ/ζ signaling pathway to modulate ethanol and LPS actions in the adolescent mouse brain. Full article

With the increasing availability of smart devices, billions of users are currently relying on map services for many fundamental daily tasks such as obtaining directions and getting routes. It is becoming more and more important to verify the quality and consistency of route data presented by different map providers. However, verifying this consistency manually is a very time-consuming task. To address this problem, in this paper we introduce a novel geospatial data analysis system that is based on road directionality. We investigate our Road Directionality Quality System (RDQS) using multiple map providers, including: Bing Maps, Google Maps, and OpenStreetMap. Results from the experiments conducted show that our detection neural network is able to detect an arrow’s position and direction in map images with >90% F1-Score across each of the different providers. We then utilize this model to analyze map images in six different regions. Our findings show that our approach can reliably assess map quality and discover discrepancies in road directionality across the different providers. We report the percentage of discrepancies found between map providers using this approach in a proposed study area. These results can help determine areas needs to be revised and prioritized to improve the overall quality of the data within maps. Full article