Search Results (436)

Natural disasters have increasingly threatened human life, infrastructure, and ecosystems, exacerbated by climate change, urbanization, and deforestation. Effective disaster risk management is crucial to mitigate these impacts. Traditionally, Geographic Information Systems (GISs) have provided spatial data analysis capabilities, but the advent of Web-GIS applications has revolutionized this field. Web-GIS platforms enable real-time data access and facilitate enhanced stakeholder collaboration. This paper details the development of a Web-GIS application tailored for hydrogeological risk management in Cervo Valley, part of the NODES—Nord Ovest Digitale e Sostenibile project under Italy’s National Recovery and Resilience Plan (NRRP). The application integrates both static and dynamic geospatial data to create an interactive interface for evaluating and planning responses to hydrogeological hazards, specifically floods, landslides, and debris flow cones. By utilizing advanced Web-GIS capabilities, the project aims to refine the risk management practices and decision-making processes, thereby bolstering territorial resilience and addressing contemporary spatial challenges with enhanced precision and efficiency. Full article

According to the US Department of Agriculture, more than 4000 types of beans are cultivated in the United States and worldwide; nevertheless, the demand for beans continues to rise. To some extent, diet can treat inflammation and consequently reduce the chances of developing comorbidities, such as diabetes. A diet based on alternative plant protein sources, such as beans, is a sustainable solution for overall health due to the overconsumption of meat that characterizes Western societies and is even more important for regions that suffer from malnutrition, such as Africa. Reviewing the nutritional profile of the different varieties of beans produced in various locations would help enhance their quality, strengthen the role of producer groups, and protecting Geographical Indications (GI), thereby increasing simplification, sustainability, and transparency towards consumers. PubMed-Medline, Web of Science, Scopus, and Cochrane Library databases were searched for relevant articles published by 30 March 2024. The results have given the green light to the reform of EFSA rules, strengthening the health claims of beans, protecting the GI for each variety, and also highlighting the public demands for functional foods based on the nutritional aspects of this product and its impact on disease management or prevention. Full article

Seasonal vertical ground movement (SVGM), which refers to the periodic vertical displacement of the Earth’s surface, has significant implications for infrastructure stability, agricultural productivity, and environmental sustainability. Understanding how SVGM correlates with climatic conditions—such as temperatures and drought—is essential in managing risks posed by land subsidence or uplift, particularly in regions prone to extreme weather events and climate variability. The correlation of periodic SVGM with climatic data from Earth observation was investigated in this work. The European Ground Motion Service (EGMS) vertical ground movement measurements, provided from 2018 to 2022, were compared with temperature and precipitation data from MODIS and CHIRP datasets, respectively. Measurement points (MP) from the EGMS over Italy provided a value for ground vertical movement approximately every 6 days. The precipitation and temperature datasets were processed to provide drought code (DC) maps calculated ad hoc for this study at a 1 km spatial resolution and daily temporal resolution. Seasonal patterns were analyzed to assess correlations with Spearman’s rank correlation coefficient (ρ) between this measure and the DCs from the Copernicus Emergency Management Service (DCCEMS), from MODIS + CHIRP (DC1km) and from the temperature. The results over the considered area (Italy) showed that 0.46% of all MPs (32,826 MPs out of 7,193,676 MPs) had a ρ greater than 0.7; 12,142 of these had a positive correlation, and 20,684 had a negative correlation. DC1km was the climatic factor that provided the highest number of correlated MPs, roughly giving +59% more correlated MPs than DCCEMS and +300% than the temperature data. If a ρ greater than 0.8 was considered, the number of MPs dropped by a factor of 10: from 12,142 to 1275 for positive correlations and from 20,684 to 2594 for negative correlations between the DC1km values and SVGM measurements. Correlations that lagged in time resulted in most of the correlated MPs being within a window of ±6 days (a single satellite overpass time). Because the DC and temperature are strongly co-linear, further analysis to assess which was superior in explaining the seasonality of the MPs was carried out, resulting in DC1km significantly explaining more variance in the SVGM than the temperature for the inversely correlated points rather than the directly correlated points. The spatial distribution of the correlated MPs showed that they were unevenly distributed in clusters across the Italian territory. This work will lead to further investigation both at a local scale and at a pan-European scale. An interactive WebGIS application that is open to the public is available for data consultation. This article is a revised and expanded version of a paper entitled “Detection and correlation analysis of seasonal vertical ground movement measured from SAR and drought condition” which was accepted and presented at the ISPRS Mid-Term Symposium, Belem, Brasil, 8–12 November 2024. Data are shared in a public repository for the replication of the method. Full article

Diabetes medications can affect weight and cardiovascular health. Some medications can aid in weight management, while others may lead to weight gain. Patients must be monitored and receive appropriate care to manage weight and prevent cardiovascular complications. Despite advancements in diabetes treatments that can influence weight and cardiovascular outcomes, ongoing research is necessary in this intricate field. Long-term effects, individual variations, and combination therapies are still subjects of uncertainty and ongoing investigation. The major objective of the research is to evaluate the impact of glucagon-like peptide-1 receptor agonists (GLP-1 RAs) on body weight in diabetic patients through a scientometric assessment. Methodology: Research data were gathered from the Web of Science Core Collection (WoSCC) database by searching for the keywords “Body Weight”, dulaglutide, and semaglutide, identifying 60 relevant articles in the field. While there are advantages in managing diseases in which the cardiovascular system is implicated, there are also clinical considerations for personalized medicine and shared decision-making. The scientometric analysis of the articles revealed important insights into how dulaglutide and semaglutide impact weight management and their potential benefits for managing cardiovascular diseases in individuals with diabetes. Conclusions: Semaglutide shows superior outcomes compared to other commercially available GLP-1RAs, particularly in improving blood sugar control, lowering body weight, and addressing other cardio-metabolic risk factors in individuals with type 2 diabetes (T2DM). The findings suggest that GLP-1 RAs have the potential to provide cardiovascular protection by influencing various physiological factors such as blood pressure, pulse rate, glycated hemoglobin (HbA1c) levels, and the urinary albumin-to-creatinine ratio (RAC). The development and validation of the 4GI model provides a sophisticated tool for evaluating the complex interactions involved in diabetes treatments, offering insights into the mechanisms of action of various medications. Full article

The main objective of this work was to develop a viewer with web output, through which the changes experienced by the mangroves of the Gran Humedal del Norte de Ciego de Avila (GHNCA) can be evaluated from remote sensors, contributing to the understanding of the spatiotemporal variability of their vegetative dynamics. The achievement of this objective is supported by the use of open-source technologies such as MapStore, GeoServer and Django, as well as Google Earth Engine, which combine to offer a robust and technologically independent solution to the problem. In this context, it was decided to adopt an action model aimed at automating the workflow steps related to data preprocessing, downloading, and publishing. A visualizer with web output (Geospatial System for Monitoring Mangrove Ecosystems or SIGMEM) is developed for the first time, evaluating changes in an area of central Cuba from different vegetation indices. The evaluation of the machine learning classifiers Random Forest and Naive Bayes for the automated mapping of mangroves highlighted the ability of Random Forest to discriminate between areas occupied by mangroves and other coverages with an Overall Accuracy (OA) of 94.11%, surpassing the 89.85% of Naive Bayes. The estimated net change based on the year 2020 of the areas determined during the classification process showed a decrease of 5138.17 ha in the year 2023 and 2831.76 ha in the year 2022. This tool will be fundamental for researchers, decision makers, and students, contributing to new research proposals and sustainable management of mangroves in Cuba and the Caribbean. Full article

Acute gastrointestinal graft-versus-host disease (GI aGVHD) is a significant and life-threatening complication in patients undergoing allogeneic stem cell transplantation (allo-SCT). Early diagnosis of GI aGVHD is crucial for improving patient outcomes, but it remains a challenge due to the condition’s nonspecific symptoms and the reliance on invasive diagnostic methods, such as biopsies and endoscopic procedures. In recent years, interest in non-invasive diagnostic techniques for graft-versus-host disease has increased, with contrast-enhanced ultrasound (CEUS) being one of them. For this reason, we aimed to examine the potential of ultrasound as a non-invasive, safe, and cost-effective alternative for the early detection and monitoring of GI aGVHD in this review. Our narrative review aims to describe the use of multimodal US that includes conventional US (B-mode and Doppler US) and advanced ultrasound techniques such as CEUS and CRTE for the non-invasive diagnosis of GI GVHD. We browsed several databases, including PubMed, Scopus, Web of Science, and Google Scholar. The search spanned 2000 to the present, focusing on articles written in English that reviewed the use of these imaging techniques in the context of GI GVHD. Following our research, we noticed that CEUS offers several advantages, including the real-time visualization of the gastrointestinal wall, assessment of blood flow, and detailed microvascular analysis—all achieved without the use of ionizing radiation. This feature makes CEUS an appealing option for repeated assessments, which are often necessary in monitoring the progression of GI aGVHD. When used in conjunction with conventional gastrointestinal ultrasound (GIUS), CEUS provides a more comprehensive view of the structural and functional changes occurring in the GI tract, potentially enhancing diagnostic accuracy and allowing for earlier intervention. In comparison to traditional diagnostic methods like tissue biopsy or CT scans, CEUS is less invasive, quicker to perform, and better tolerated by patients, especially those in fragile health following allo-SCT. Its non-invasive nature and ability to provide immediate imaging results make it a valuable tool for clinicians, particularly in settings where minimizing patient discomfort and risk is paramount. However, despite these advantages, there are still gaps in the literature regarding CEUS’s full diagnostic accuracy for GI aGVHD. Further research, including larger clinical trials and comparative studies, is needed to validate CEUS’s role in routine clinical practice and to establish standardized protocols for its use. Nonetheless, CEUS shows considerable potential to transform the diagnostic approach to GI aGVHD by improving early detection, reducing the need for invasive procedures, and ultimately enhancing treatment outcomes for affected patients. Full article

The evaluation of smart affordable cities considering sustainable subsystems improves urban quality of life through efficient resource usage, reduced environmental impacts, and improved living conditions for residents. This study aims to develop an interactive and dynamic Web Geographic Information System (GIS) framework to facilitate decision-making processes during the design phase while including third parties and stakeholders using a spatial interactive impact assessment approach. The methodology follows a quantitative research method based on delivering a tool that could be replicated in other contexts. This tool assesses the impact of smart scenarios to support affordable city planning through selecting Key Performance Indicators (KPIs). This tool was applied to Brazilian large-scale affordable housing within a smart city project. Based on this study, the conclusion reports some research limitations and the possibility of creating a beta version of the tool for future development. The findings show that this Web-GIS framework enhances stakeholder engagement and the effectiveness of decision making in developing sustainable urban planning. Full article

Multi-criteria decision-making (MCDM) methods provide a framework for addressing sustainable forest management challenges, especially under climate change. This study offers a systematic review of MCDM applications in forest management from January 2010 to March 2024. Descriptive statistics were employed to analyze trends in MCDM use and geographic distribution. Thematic content analysis investigated the appearance of MCDM indicators supplemented by Natural Language Processing (NLP). Factorial Correspondence Analysis (FCA) explored correlations between models and publication outlets. We systematically searched Web of Science (WoS), Scopus, Google Scholar, Semantic Scholar, CrossRef, and OpenAlex using terms such as ‘MCDM’, ‘forest management’, and ‘decision support’. We found that the Analytical Hierarchy Process (AHP) and the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) were the most commonly used methods, followed by the Preference Ranking Organization Method for Enrichment Evaluation (PROMETHEE), the Analytic Network Process (ANP), GIS, and Goal Programming (GP). Adoption varied across regions, with advanced models such as AHP and GIS less frequently used in developing countries due to technological constraints. These findings highlight emerging trends and gaps in MCDM application, particularly for argan forests, emphasizing the need for context-specific frameworks to support sustainable management in the face of climate change. Full article

Smart cities use technological solutions to reduce the drawbacks of urban living. The importance of BIM and GIS integration has increased with the popularity of smart city and 3D city concepts in recent years. In addition to 3D city models, Building Information Modeling (BIM) is an essential element of smart cities. The 3D city model web client in this study displays three-dimensional (3D) city models created using photogrammetric techniques, BIM, and campus infrastructure projects. The comparison and integration of the aforementioned systems were evaluated. A web-based 3D client framework and implementation for combined BIM and 3D city models are the goals of the submitted work. The Web is a very challenging platform for 3D data presentation. The Cesium engine based on HTML5 and WebGL is an open-source creation and the virtualcityMAP application using the Cesium infrastructure was used in this study. Full article

Efforts to establish Pakistan’s National Spatial Data Infrastructure (NSDI) have been underway for the past 15 years, and therefore it is necessary to gauge the current progress to channelize efforts into areas that need improvement. This article assessed Pakistan’s NSDI implementation efforts through well-established approaches, including the SDI readiness model, organizational aspects, and state of play. The data were collected from Spatial Data Infrastructure (SDI) and Geographic Information System (GIS) experts. The findings underscored challenges related to human resources, SDI education/culture, long-term vision, lack of awareness of geoinformation (GI), sustainable funding, metadata availability, online geospatial services, and geospatial standards hindering NSDI development in Pakistan. However, certain factors exhibit favorable standings, such as the legal framework for NSDI establishment, web connectivity, geospatial software availability, the unavailability of core spatial datasets, and institutional leadership. Thus, to enhance the development of NSDI in Pakistan, recommendations include bolstering financial and human resources, improving online geospatial presence, and fostering a long-term vision for NSDI. Full article

The prediction and monitoring of plant diseases and pests are key activities in agriculture. These activities enable growers to take preventive measures to reduce the spread of diseases and harmful insects. Consequently, they reduce crop loss, make pesticide and resource use more efficient, and preserve plant health, contributing to environmental sustainability. We illustrate the SMARTerra decision support system, which processes daily measured and predicted weather data, spatially interpolating them at high resolution across the entire Sardinia region. From these data, SMARTerra generates risk predictions for plant pests and diseases. Currently, models for predicting the risk of rice blast disease and the hatching of locust eggs are implemented in the infrastructure. The web interface of the SMARTerra platform allows users to visualize detailed risk maps and promptly take preventive measures. A simple notification system is also implemented to directly alert emergency responders. Model outputs by the SMARTerra infrastructure are comparable with results from in-field observations produced by the LAORE Regional Agency. The infrastructure provides a database for storing the time series and risk maps generated, which can be used by agencies and researchers to conduct further analysis. Full article

Waste management, one of the fundamental problems of today, is at the center of sustainability discussions. The failure to adopt a holistic and participatory approach in traditional waste management highlights the need to develop new approaches. The main purpose of this research is to present the basic components of a Web-GIS-based platform design for sustainable waste governance. The presented framework emphasizes that waste management is not a problem of local or central government and that holistic sustainable waste governance can be achieved with the participation of all relevant stakeholders. The Kadikoy district of Istanbul, a metropolitan city, was selected as the study area. Information was collected from the study area with quantitative and qualitative analysis methods. The results obtained with fieldwork and survey data show that there is a need for a location-based platform that allows relevant stakeholders to see the current waste management workflow, enter data themselves, and provide feedback. The Web-GIS-based platform proposed in this article to meet this need is an important step in ensuring sustainable waste governance. In the article, a Web-GIS-based platform has been developed to ensure the sustainable waste governance of commercial enterprises for local governments. Full article

Akkermansia muciniphila (A. muciniphila) and its derivatives, including extracellular vesicles (EVs) and outer membrane proteins, are recognized for enhancing intestinal balance and metabolic health. However, the mechanisms of Akkermansia muciniphila’s action and its effects on the microbiome are not well understood. In this study, we examined the influence of A. muciniphila and its derivatives on gastrointestinal (GI) and metabolic disorders through a meta-analysis of studies conducted on mouse models. A total of 39 eligible studies were identified through targeted searches on PubMed, Web of Science, Science Direct, and Embase until May 2024. A. muciniphila (alive or heat-killed) and its derivatives positively affected systemic and gut inflammation, liver enzyme level, glycemic response, and lipid profiles. The intervention increased the expression of tight-junction proteins in the gut, improving gut permeability in mouse models of GI and metabolic disorders. Regarding body weight, A. muciniphila and its derivatives prevented weight loss in animals with GI disorders while reducing body weight in mice with metabolic disorders. Sub-group analysis indicated that live bacteria had a more substantial effect on most analyzed biomarkers. Gut microbiome analysis using live A. muciniphila identified a co-occurrence cluster, including Desulfovibrio, Family XIII AD3011 group, and Candidatus Saccharimonas. Thus, enhancing the intestinal abundance of A. muciniphila and its gut microbial clusters may provide more robust health benefits for cardiometabolic, and age-related diseases compared with A. muciniphila alone. The mechanistic insight elucidated here will pave the way for further exploration and potential translational applications in human health. Full article

Introduction: PCa is one of the cancers that exhibits the widest disparity gaps. Geographical place of residence has been shown to be associated with healthcare access/utilization and PCa outcomes. Geographical Information Systems (GIS) are widely being utilized for PCa disparities research, however, inconsistencies in their application exist. This systematic review will summarize GIS application within PCa disparities research, highlight gaps in the literature, and propose alternative approaches. Methods: This paper followed the methods of the Cochrane Collaboration and the criteria set of the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA). Articles published in peer-reviewed journals were searched through the PubMed, Embase, and Web of Science databases until December 2022. The main inclusion criteria were employing a GIS approach and examining a relationship between geographical components and PCa disparities. The main exclusion criteria were studies conducted outside the US and those that were not published in English. Results: A total of 25 articles were included; 23 focused on PCa measures as outcomes: incidence, survival, and mortality, while only 2 examined PCa management. GIS application in PCa disparities research was grouped into three main categories: mapping, processing, and analysis. GIS mapping allowed for the visualization of quantitative, qualitative, and temporal trends of PCa factors. GIS processing was mainly used for geocoding and smoothing of PCa rates. GIS analysis mainly served to evaluate global spatial autocorrelation and distribution of PCa cases, while local cluster identification techniques were mainly employed to identify locations with poorer PCa outcomes, soliciting public health interventions. Discussion: Varied GIS applications and methodologies have been used in researching PCa disparities. Multiple geographical scales were adopted, leading to variations in associations and outcomes. Geocoding quality varied considerably, leading to less robust findings. Limitations in cluster-detection approaches were identified, especially when variations were captured using the Spatial Scan Statistic. GIS approaches utilized in other diseases might be applied within PCa disparities research for more accurate inferences. A novel approach for GIS research in PCa disparities could be focusing more on geospatial disparities in procedure utilization especially when it comes to PCa screening techniques. Conclusions: This systematic review summarized and described the current state and trend of GIS application in PCa disparities research. Although GIS is of crucial importance when it comes to PCa disparities research, future studies should rely on more robust GIS techniques, carefully select the geographical scale studied, and partner with GIS scientists for more accurate inferences. Such interdisciplinary approaches have the potential to bridge the gaps between GIS and cancer prevention and control to further advance cancer equity. Full article

Geographic information systems (GISs) based on WebGIS architectures have transformed geospatial data visualization and analysis, offering rapid access to critical information and enhancing decision making across sectors. This study conducted a bibliometric review of 358 publications using the Web of Science database. The analysis utilized tools, such as Bibliometrix (version R 4.3.0) and Biblioshiny (version 1.7.5), to study authors, journals, keywords, and collaborative networks in the field of information systems. This study identified two relevant clusters in the literature: (1) voluntary geographic information (VGI) and crowdsourcing, focusing on web integration for collaborative mapping through contributions from non-professionals and (2) GIS management for decision making, highlighting web-based architectures, open sources, and service-based approaches for storing, processing, monitoring, and sharing geo-referenced information. The journals, authors, and geographical distribution of the most important publications were identified. China, Italy, the United States, Germany, and India have excelled in the application of geospatial technologies in areas such as the environment, risk, sustainable development, and renewable energy. These results demonstrate the impact of web-based GISs on forest conservation, climate change, risk management, urban planning, education, public health, and disaster management. Future research should integrate AI, mobile applications, and geospatial data security in areas aligned with sustainable development goals (SDGs) and other global agendas. Full article