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This study aimed to evaluate the extent of the risk of lead (Pb) and cadmium (Cd) in the soil and wheat plants grown around the Zanjan cement factory in Northwest Iran and to assess the accuracy of soil regulatory standards in reflecting the potential risk of these pollutants. A total of 73 surface (0–20 cm) soil samples and 31 wheat plant samples were collected and analyzed for their Pb and Cd contents. Statistical analyses revealed that the soil Pb and Cd concentrations varied from 1.2 to 240.0 milligram per kilogram (mg kg−1) and below the detection limit to 27.5 mg kg−1, respectively. Additionally, the wheat grain content of these metallic pollutants ranged from below the detection limit to 3.5 and 1.6 mg kg−1, respectively, indicating that certain wheat samples were polluted with Pb, Cd, or both. Spatial analyses highlighted the significant role of the cement factory in spreading substantial amounts of HMs into the soil. By comparing the soil Pb and Cd total concentrations to their respective national regulatory standards, it was observed that 26.3% and 37.2% of the study area, respectively, were classified as polluted. Integrating the interpolated maps of soil Pb and Cd concentrations and identifying sites in which at least one pollutant exceeded its regulatory standard showed that a greater proportion of the area (42.3%) should be considered polluted. Finally, after accounting for sites in which either the soil was polluted and/or wheat grain content of Pb or Cd exceeded the threshold value of 0.2 mg kg−1, 67.4% of the area was classified as polluted. The findings suggest that thematic maps prepared for individual pollutants are inadequate for pinpointing the potential risk of soil pollution with HMs. Therefore, it is crucial to consider both the soil and plant aspects when assessing the risk of HM pollution in agricultural lands. [ABSTRACT FROM AUTHOR]

The general subject trends and emphasized points of Community Librarianship (CL) researches are not clear. According to reviewed papers, CL encompasses a wide range of social issues. This dispersion and diversity require presenting a comprehensive map of the thematic trends. The present study showed the concept of "social capital" is the underlying base for the literature of CL, which is the outcome of dialogue and interactive space of libraries. Also, historically, the related publications can be classified into five categories: 1) promoting the democratic culture and training informed and participating citizens 2) improving e-government; 3) library as a place for creating social capital; 4) sharing consumer health information; and 5) natural crises and disasters. The results of this study can show and reflect the "common good" of public libraries, that can effectively provide insight for librarians, attract policymakers' support, and maintain the position and future of these libraries. [ABSTRACT FROM AUTHOR]

Tropical cyclone causes large-scale devastation and destruction in the coastal plains of India, particularly in Odisha, which is the most cyclone-affected state in the country. Tropical cyclones are projected to be more powerful and widespread due to changing climate. Hence, the risk assessment of tropical cyclone is necessary to identify cyclone-risk areas in coastal Odisha which may help in the mitigation of the damages caused by cyclones. Therefore, this study utilizes geospatial techniques to produce a comprehensive risk map posed by tropical cyclones and to estimate the degree of risk for coastal districts of Odisha. For this, we evaluated the district-level cyclone risk for coastal Odisha using multi-criteria decision-making (MCDM) technique by considering 21 parameters for each of the four components of risk, i.e., exposure, hazard, vulnerability, as well as mitigation capacity. For each criterion, thematic raster map layers were created and weighted using a fuzzy analytical hierarchy process (FAHP). We prepared individual risk component maps using weighted overlay techniques and finally integrated all indices to create the risk map. The study shows that 13% area of the study area comes under a very high-risk zone whereas, 25% area comes under a high-risk zone. The central (Cuttack, northern parts of Khordha, and south-western parts of Jajpur district) and the eastern part (most of the parts of Jagatsinghpur, Kendrapara, and northern parts of Puri district) of the study area come under high to very high tropical cyclone impact zone. Almost 67% of the total area is highly vulnerable to tropical cyclones and mainly concentrated near the shoreline. The applied approach and results can assist the local authorities in identifying vulnerable and hazardous locations and developing workable solutions for the mitigation of revised cyclone threats in the coastal districts of Odisha. [ABSTRACT FROM AUTHOR]

The process of determining whether a specific portion of land is suitable for a specific purpose is known as land suitability analysis (LSA). In order to promote sustainable development in semi-arid regions, the objective of this study is to analyse, evaluate, and identify the land for green growth based on topography, climate, and soil characteristics. Twelve thematic maps are prepared by using remote sensing satellite data. The Landsat 8 OLI/TIRS is used for the preparation of the thematic maps like land use land cover (LULC), normalized difference vegetation index (NDVI), top soil grain size index (TGSI), and geomorphology (GM), and DEM data is used for the preparation slope, and drainage density (DD). The collateral data is used to prepare geology and soil thematic maps. From the field work, we have collected soil samples for the compulsory physicochemical parameters such as soil EC and soil N-P-K which were taken into consideration and prepared thematic maps. The analytical hierarchy process (AHP) was used to generate the LSA of the research region, by assigning the appropriate weights to each criterion and sub-criterion for the thematic maps. Geographic information systems (GIS) and the multicriteria decision-making (MCDM) approach were used in the study's methodology. The LSA of the study area has been categories in to four types, i.e., highly suitable, moderately suitable, marginally suitable, and not suitable. The results revealed that 421.31 sq.km (40.09%) is not suitable for agriculture green growth in the study region, whereas 89.58 sq.km (8.52%) is moderately suitable, 267.66 sq.km (25.47%) is marginally suitable, and 266.54 sq.km (25.36%) is highly suitable. Accuracy assessment has validated the LSA map's accuracy (AA). The AA of LSA is 84.22%, which demonstrates a strong connection with the actual data. The research's results could be helpful in locating productive agricultural areas in various parts of the world. The decision-making AHP tool paired with GIS provides a novel method. [ABSTRACT FROM AUTHOR]

Purpose: Text classification is a widely accepted and adopted technique in organizations to mine and analyze unstructured and semi-structured data. With advancement of technological computing, deep learning has become more popular among academicians and professionals to perform mining and analytical operations. In this work, the authors study the research carried out in field of text classification using deep learning techniques to identify gaps and opportunities for doing research. Design/methodology/approach: The authors adopted bibliometric-based approach in conjunction with visualization techniques to uncover new insights and findings. The authors collected data of two decades from Scopus global database to perform this study. The authors discuss business applications of deep learning techniques for text classification. Findings: The study provides overview of various publication sources in field of text classification and deep learning together. The study also presents list of prominent authors and their countries working in this field. The authors also presented list of most cited articles based on citations and country of research. Various visualization techniques such as word cloud, network diagram and thematic map were used to identify collaboration network. Originality/value: The study performed in this paper helped to understand research gaps that is original contribution to body of literature. To best of the authors' knowledge, in-depth study in the field of text classification and deep learning has not been performed in detail. The study provides high value to scholars and professionals by providing them opportunities of research in this area. [ABSTRACT FROM AUTHOR]

Towards the end of World War II, from January 1945, British/Canadian forces supplemented the use of topographical maps by compiling innovative specialist thematic maps to assist troops advancing eastwards from Belgium and the Netherlands into north-west Germany. ‘Soil’ maps were used to predict (1) cross-country trafficability and (2) potential airfield construction sites. Intensive bombardment of ground that was unexpectedly waterlogged as well as deliberate flooding by the enemy created mud which initially slowed cross-country movement. So too did determined German military resistance: the campaign included arguably the bloodiest operation for troops of 21st Army Group since their battle for Normandy in the summer of 1944. Significant maps, mostly at 1:100,000, are now preserved in England within the Shotton Archive at the Lapworth Museum of Geology, Birmingham. Together with expertise from geologists Major F.W. Shotton and Squadron Leader J.F. Kirkaldy, the maps contributed to terrain analysis that assisted with operational planning. [ABSTRACT FROM AUTHOR]

Concepts, approaches and frameworks for assessing the impacts of climate change are evolving quickly. Due to their particular geographic location, proximity to oceans, concentration of populated regions, and infrastructure, coastal communities are particularly sensitive to the effects of climate change. The present study aims to develop a thematic map based on the CID (climatic impact-drivers) framework proposed in the assessment report-6 of the Intergovernmental Panel on Climate Change (IPCC) to evaluate the climate change’s physical hazards in the coastal districts of India. The study points out that West Bengal and Odisha are the two states with the highest cyclone hazard index values making them most vulnerable to cyclones. At the same time, Kerala, Andhra Pradesh and West Bengal respectively fall in the extremely severe category of flood, heatwave and shoreline change hazards. The maritime state of Gujarat along with Diu and Daman experiences maximum severity for the sea level rise hazard. The multi-hazards index developed in the study by considering 14 threshold-based CID indices showed that the coastal state of Andhra Pradesh has the highest proneness to the physical hazards due to climate change [ABSTRACT FROM AUTHOR]

Several investigations have evaluated the research trajectory concerning entrepreneurship; nonetheless, only a few studies have examined the literature trajectory regarding entrepreneurship in tourism. Therefore, this research explores papers spanning from 2013 to 2023, mapping thematic, intellectual, and conceptual frameworks using bibliometric techniques. The research delves into scientific output, prolific authors, influential articles, co-occurrence of keywords, co-citations, and many others. The keywords "tourism" OR "travel & tourism" AND "entrepreneurship" OR "entrepreneur" were strategically employed to encompass 514 articles and review papers published in English between 2013 and 2023. VOSviewer was used as a technique for doing topic grouping alongside performance analysis. With 85 articles, 2023 is the most productive year. The most influential institution is "The Hong Kong Polytechnic University" and the nation is the United Kingdom correspondingly. Likewise, the most renowned journal is "Tourism management," and the most productive journal is "journal of sustainable tourism". Furthermore, the most cited article is "Scale, change and resilience in community tourism planning." This research provides researchers with insights into the existing state of research on entrepreneurship in tourism and offers guidance for future research. This study is the inaugural endeavor to present both performance evaluations and scientific clusters of the literature on entrepreneurship in tourism. [ABSTRACT FROM AUTHOR]

The management of groundwater systems is essential for nations that rely on groundwater as the principal source of communal water supply (e.g., Mohmand District of Pakistan). The work employed Remote Sensing and GIS datasets to ascertain the groundwater recharge zones (GWRZ) in the Mohmand District of Pakistan. Subsequently, a sensitivity analysis was conducted to examine the impact of geology and hydrologic factors on the variability of the GWRZ. The GWRZ was determined by employing weighted overlay analysis on thematic maps derived from datasets about drainage density, slope, geology, rainfall, lineament density, land use/land cover, and soil types. The use of multi-criteria decision analysis (MCDA) involves the utilization of the multi-influencing factor (MIF) and analytical hierarchy procedure (AHP) to allocate weights to the selected influencing factors. The MIF data found that very high groundwater recharge spanned 1.20%, high zones covered 40.44%, moderate zones covered 50.81%, and low zones covered 7.54%. In comparison, the AHP technique results suggest that 1.81% of the whole area is very high, 33.26 is high, 55.01% is moderate, and 9.92% has low groundwater potential. The geospatial-assisted multi-influencing factor approach helps increase conceptual knowledge of groundwater resources and evaluate possible groundwater zones. [ABSTRACT FROM AUTHOR]

This study aims to examine, ascertain, and measure the extent of research conducted on real-time surveillance video analytics (RTSVA) and uncover the patterns, advancements, and progression in the SCOPUS database. An electronic search methodology was employed to identify the most relevant scholarly papers. Each analytical tool was analyzed using the R program code and VOS Viewer software. Multiple factors were explored, including co-authorship, co-citation, conceptual structure, co-word occurrence, trend themes analysis, thematic map, and visualization analysis. It is observed the study includes data from 653 sources, such as journals, books, and conference proceedings. There are 1041 documents, with an annual growth rate of 21%. IEEE Access has the highest impact, and Multimedia Tools and Applications has the second highest source impact. The most significant author among the research group is Chen Y, with a fractionalization value of 6.59 (27 articles), followed by Wang J (15 articles) with a value of 3.80. The keywords related to the video analytics domain along with its frequency of occurrence, are "Edge computing," which has appeared 158 times, and video surveillance has appeared 95 times. The Thematic map is divided into four quadrants: Niche, Motors, Emerging, and Basic themes. Traffic surveillance, blockchain, and COVID-19 are under Niche themes. It is also necessary to explore the sociological and ethical implications linked to using video surveillance systems. This study has the potential to aid both novice and experienced researchers in identifying novel research domains, suitable sources, and opportunities for collaboration. The results pertaining to relational and evaluate methodologies could be helpful to the new researchers. [ABSTRACT FROM AUTHOR]

The classification of very high-resolution satellite imagery remains a focal point in remote sensing, attracting increased attention across diverse scientific disciplines. Various classification methods, including pixel- and object-based techniques, have been proposed, and their performances and limitations have been discussed in the literature. This paper presents a hybrid method that combines the strengths of pixel- and object-based methods in image classification to minimize errors associated with the segmentation process, particularly under-segmentation errors in object-based image analysis. The core concept behind the method lies in categorizing segmented image objects as either homogeneous or heterogeneous based on their class probability. In this process, the estimated possibilities from the object-based classification model are considered, and segments are designated as homogeneous or heterogeneous using a user-defined threshold. The object-based classification model determines the class labels for homogeneous image objects, while the heterogeneous ones, containing pixels representing different land cover classes, are classified using the pixel-based model. The performance of hybrid classification models, created by varying thresholds, is analysed using high-resolution WorldView-3 and WorldView-2 imagery and compared with pixel- and object-based classification results. For the implementation of image classification methods, Canonical Correlation Forest (CCF), Extreme Gradient Boosting (XGBoost), and Categorical Boosting (CatBoost) were employed. The findings indicated that employing the suggested hybrid strategy with a threshold value selected within a specific range (e.g. between 60% and 80%) and employing a robust classification algorithm that provides class probabilities (e.g. CCF) results in a statistically significant improvement in overall accuracy compared to pixel and object-based methods, with gains of 5% and 4%, respectively. Visual analysis of the produced thematic maps revealed that the proposed method minimizes the salt-and-pepper effect associated with pixel-based classification while mitigating segmentation problems arising from object-based classification. [ABSTRACT FROM AUTHOR]

The accurate large-scale classification of tree species is crucial for the monitoring, protection, and management of the Earth's invaluable forest ecosystems. Numerous previous studies have recognized the suitability of satellite imagery, particularly Sentinel-2 imagery, for this task. In this study, we utilized a dense phenology Sentinel-2 time series, which offered consistent data across multiple granules, to map tree species across the entire forested area in Austria. Aiming for the classification scheme to more accurately represent actual forest conditions, we included mixed tree species and sparsely populated classes (classes with sparse canopy cover) alongside pure tree species classes. To enhance the training data for the mixed and sparse classes, synthetic data creation was employed. Autocorrelation has significant implications for the validation of thematic maps. To investigate the impact of spatial dependency on validation data, two methods were employed at numerous split and buffer distances: spatial split validation and a validation method based on a buffered ground reference probability samples provided by the National Forest inventory (NFI). While a random training data holdout set yielded 99% accuracy, the spatial split validation resulted in 74% accuracy, emphasizing the importance of accounting for spatial autocorrelation when validating with holdout sets derived from polygon-based training data. The validation based on NFI data resulted in 55% overall accuracy, 91% post-hoc pure class accuracy, and 79% accuracy when confusions in phenological proximity were disregarded (e.g., spruce–larch confused with spruce). The significant differences in accuracy observed between spatial split and NFI validation underscore the challenge for polygon-based training data to capture ground reference forest complexity, particularly in areas with diverse forests. This hardship is further accentuated by the pure class accuracy of 91%, revealing the substantial impact of mixed stands on the accuracy of tree species maps. [ABSTRACT FROM AUTHOR]

AbstractThis study examines the concept of health advocacy and explores related scholarly material to understand its evolution from 1977 to 2021. The bibliometric analysis investigates the publication trends, most relevant authors, keywords-based clusters, research trends, author productivity, and future research areas in health advocacy. The relevant articles were extracted from the Scopus database and analyzed to identify and explore the most active authors, author-wise contribution to the sources, sub-research topics, core sources, top authors’ production over time, global cited documents, thematic maps, word cloud, country-wise collaboration network and map, author keywords-based network, historiograph, and spectroscope. The study finds that health advocacy as a concept is under-explored and thus warrants a need for future research work. Limited authors have contributed to this theme, and the continuity of publication needs to be improved. The study highlights that there needs to be a robust framework to assess, evaluate, and implement health advocacy. The researchers are limited to only a few authors who have published in limited journals. The current study brings out the need for research and publications on health advocacy to develop a framework for assessing and implementing health advocacy. Also, the study highlights emerging themes of Coronavirus pandemic and emergency and disaster preparation. The niche themes that emerged during the survey highlight keywords such as agenda-setting and maternal health. [ABSTRACT FROM AUTHOR]

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In recent years, the domain of renewable energy communities has experienced dynamic growth, spurred by European Union (EU) legislation that became law for all 27 Member States in June 2021. This legislative framework intensified research efforts aimed at discovering new methods for sustainable energy sources through the development of individual and collective energy communities. Each EU country has implemented distinct frameworks for renewable energy communities, leading to varied legislative approaches. This has spurred exponential investment, facilitating the deployment of photovoltaic and battery energy storage systems, offering significant economic and environmental benefits to community members. Against this backdrop, the purpose of this analysis is to investigate academic publications related to renewable energy communities. Using a dataset extracted from the ISI Web of Science database, this study employs a bibliometric approach to identify the main authors, affiliations, and journals and analyze collaboration networks, as well as discern key topics and the countries involved. The analysis reveals an annual growth rate of 42.82%. Through thematic maps, WordClouds, three-field plots, and a review of the top 10 globally cited documents, this study provides a comprehensive perspective on the evolving domain of renewable energy communities. [ABSTRACT FROM AUTHOR]

Emerging countries are populated with low-income consumers. Academics and corporations have paid little attention to studies that would provide light on consumer behavior in these countries. To accomplish this gap, the study aims to critically evaluate the existing literature to obtain themes using SPAR-4-SLR protocol. Major themes that emerged from the findings are consumer decision making, brand strategy, micro-macro environment, product adoption, and role of technology. The study provides theoretical and practical insights to understand and mitigate the impact of poverty in Bottom of the Pyramid (BOP) marketplaces, offering recommendations for marketing executives and decision-makers. [ABSTRACT FROM AUTHOR]

AbstractAlthough school-aged children often suffer from multiple several allergic diseases concurrently, most studies on stress coping have examined allergic diseases separately. Herein, semi-structured interviews were conducted to evaluate stress-coping patterns associated with allergic diseases among ten children aged 9–12 years, and obtained data were subjected to qualitative thematic analysis. Characteristic word contents were grouped into categories to explore themes. After the analysis, e themes—objection, support, rescue, distraction, concealment, catharsis, conversion, and positive thoughts—and 13 categories were identified. Furthermore, a thematic map was used on the following three coping domains of coping: problem-focused and behavioral coping, emotion-focused and behavioral coping, and emotion-focused and cognitive coping. Behavioral coping could be easily implemented in children. This study revealed that it is critical for children with allergic diseases to have various coping methods and functional coping strategies should be implemented. [ABSTRACT FROM AUTHOR]

The number of studies on COVID-19 has rapidly grown in recent years. The pandemic has caused widespread disruption, including in renewable energy research. This study aims to examine the impact of the COVID-19 pandemic on renewable energy research by conducting a bibliometric analysis from the Scopus indexing database from 2020 to 2023. This study employs a bibliometric approach to analyze the authors, affiliation, publication source, keywords, thematic map, and trend topic. The analysis will focus on the comprehensive overview of the published research and identify areas where future research is needed. The results show that the number of research studies related to COVID-19’s effect on renewable energy will continue growing and a solid collaboration network exists. China has had a significant presence on the impact of COVID-19 on renewable energy studies, including organization and university affiliations, number of single and multiple country publications, funding sponsors, and most cited countries. The finding also shows niche themes, research trends, and thematic evolution shifting. This finding will contribute to a better understanding of the impact of the COVID19 pandemic on renewable energy research and a new direction for future research. [ABSTRACT FROM AUTHOR]

The Tonle Sap Lake (TSL) landscape is a region of vast natural resources and biological diversity in the heart of Southeast Asia. In addition to serving as the foundation for a highly productive fisheries system, this landscape is home to numerous globally threatened species. Despite decades of recognition by several government and international agencies and the fact that nine protected areas have been established within this region, natural land cover such as grasslands have experienced considerable decline since the turn of the century. This project used local expert knowledge to train and validate a random forest supervised classification of Landsat satellite imagery using Google Earth Engine. The time series of thematic maps were then used to quantify the conversion of grasslands to croplands between 2004 and 2023. The classification encompassed a 10 km buffer surrounding the landscape, an area of nearly 3 million hectares. The average overall accuracy for these thematic maps was 82.5% (78.5–87.9%), with grasslands averaging 76.1% user's accuracy. The change detection indicated that over 207,281 ha of grasslands were lost over this period (>59.5% of the 2004 area), with approx. 89.3% of this loss being attributed to cropland expansion. The results of this project will inform conservation efforts focused on local-scale planning and the management of commercial agriculture. [ABSTRACT FROM AUTHOR]

In order to solve the problems existing in the current electronic sand table of railway industry, such as different expression methods, single application content, high risk of data leakage, low efficiency of data loading, etc., this paper researches the data processing, management and application methods of massive geological and BIM models, and establishes a standardized electronic sand table with BIM+GIS as the technical core, so as to better serve the railway design and construction. Based on the practice summary of the projects such as Rizhao - Lankao High-speed Railway, Lhasa - Nyingchi Railway, Chengdu-Chongqing middle line high-speed railway and other projects, combined with the relevant standards of China Railway BIM Alliance and China Railway, this paper puts forward the data standards of terrain, image, BIM model and thematic map for the application of electronic sand table. And the establishment of it is completed through the processes of coordinate transformation, data transformation, data slicing, knowledge atlas establishment, model release and front-end data collection. Finally, the online efficient organization and management of hundred-kilometer-level and multi-specialty data is realized. The proposed methods and standards are applicable to the management and analysis application in railway design and construction processes. [ABSTRACT FROM AUTHOR]

This study deals with the determination of sites suitable for landfill in the Prefecture of Chalkidiki, North Greece, using Boolean logic and Geographic Information Systems (GIS). Landfill siting is an arduous process as it combines environmental, social, and technical factors. Solid waste management is an urgent requirement in tourist sites worldwide. The Prefecture of Chalkidiki is considered a tourist area where volumes of generated waste increase in the summer. The Boolean logic approach was used in the study area to exclude areas not suitable for the establishment of a landfill site and to select areas that meet all the criteria. Nine criteria were selected to create the final map showing areas with the highest suitability for solid waste disposal. According to the Boolean logic method, suitable areas were given a value of one (1), while unsuitable areas were given a value of zero (0). According to the final thematic map of proposed sites, 12.7% of the study area is suitable for landfill construction. The suitable areas identified include pre-existing landfill sites, thus suggesting that the applied method has a high degree of reliability. [ABSTRACT FROM AUTHOR]

The orchestration approach has been gaining prominence and relevance in recent years, due to high competitiveness in the business context and the search for more efficient strategies to promote innovation. In light of this reality, this paper conducts a systematic literature review (SLR) aiming to contribute to the emerging theme of innovation orchestration. We examined the abstracts of 761 articles and found 75 that were relevant to the topic, which was analyzed using the biblioshiny tool. These documents were published between 2006 and January 2023 and were collected from two databases, Web of Science Core Collection and Scopus. We discovered that the highest number of articles was published in 2022. Furthermore, we identified the conceptual evolution of the theme, dividing it into three periods. Through the overall thematic map, we were able to uncover niche and emerging topics such as innovation orchestration in social entrepreneurship networks, innovation orchestration in ecosystems and orchestration mechanisms. Additionally, we contribute by pointing out pathways for future studies, which is a key aspect of advancing knowledge in the field. [ABSTRACT FROM AUTHOR]

Given the potential applications of generative AI (GenAI) in education and its rising interest in research, this systematic review mapped the thematic landscape of 407 publications indexed in the Web of Science, ScienceDirect and Scopus. Using EPPI Reviewer, publication type, educational level, disciplines, research areas and applications of GenAI were extracted. Eight discursive themes were identified, predominantly focused on 'application, impact and potential', 'ethical implication and risks', 'perspectives and experiences', 'institutional and individual adoption', and 'performance and intelligence'. GenAI was conceptualised as a tool for 'pedagogical enhancement', 'specialised training and practices', 'writing assistance and productivity', 'professional skills and development', and as an 'interdisciplinary learning tool'. Key gaps highlighted include a paucity of research and discussions on GenAI in K‐12 education; a limited exploration of GenAI's impact using experimental procedures; and a limited exploration of the potential and ethical concerns of GenAI from the lens of cultural dimensions. Promising opportunities for future research are highlighted. [ABSTRACT FROM AUTHOR]

Introduction: Opioid overdose is a major public health challenge. We aimed to understand facilitators and barriers to engagement in medication for opioid use disorder (MOUD) among persons with OUD in Washington, DC. Methods: We used a cross-sectional mixed-methods concept mapping approach to explore MOUD engagement between 2021–2022. Community members at-large generated 70 unique statements in response to the focus prompt: "What makes medication for opioid use disorder like buprenorphine (also known as Suboxone or Subutex) difficult to start or keep using?" Persons with OUD (n = 23) and service providers (n = 34) sorted and rated these statements by theme and importance. Data were analyzed with multidimensional scaling and hierarchical cluster analysis, producing thematic cluster maps. Results were validated by our community advisory board. Results: Seven themes emerged in response to the focus prompt: availability and accessibility; hopelessness and fear; unmet basic needs; characteristics of treatment programs; understanding and awareness of treatment; personal motivations, attitudes, and beliefs; and easier to use drugs. "Availability and accessibility," "hopelessness and fear," and "basic needs not being met" were the top three identified barriers to MOUD among consumers and providers; however, the order of these priorities differed between consumers and providers. There was a notable lack of communication and programming to address misconceptions about MOUD's efficacy, side effects, and cost. Stigma underscored many of the statements, showcasing its continued presence in clinical and social spaces. Conclusions: This study distinguishes itself from other research on MOUD delivery and barriers by centering on community members and their lived experiences. Findings emphasize the need to expand access to treatment, dismantle stigma associated with substance use and MOUD, and address underlying circumstances that contribute to the profound sense of hopelessness and fear among persons with OUD–all of which will require collective action from consumers, providers, and the public. [ABSTRACT FROM AUTHOR]

Satellite remote sensing is currently an established, effective, and constantly used tool and methodology for monitoring agriculture and fertilisation. At the same time, in recent years, the need for the detection of livestock manure and digestate spreading on the soil is emerging, and the development of spectral indices and classification processes based on satellite multispectral data acquisitions is growing. However, the application of such indicators is still underutilised and, given the polluting impact of livestock manure and digestate on soil, groundwater, and air, an in-depth study is needed to improve the monitoring of this practice. Additionally, this paper aims at exposing a new spectral index capable of detecting the land affected by livestock manure and digestate spreading. This indicator was created by studying the spectral response of bare soil and livestock manure and digestate, using Copernicus Sentinel-2 MSI satellite acquisitions and ancillary datasets (e.g., soil moisture, precipitation, regional thematic maps). In particular, time series of multispectral satellite acquisitions and ancillary data were analysed, covering a survey period of 13 months between February 2022 and February 2023. As no previous indications on fertilisation practices are available, the proposed approach consists of investigating a broad-spectrum area, without investigations of specific test sites. A large area of approximately 236,344 hectares covering three provinces of the Emilia-Romagna Region (Italy) was therefore examined. A series of ground truth points were also collected for assessing accuracy by filling in the confusion matrix. Based on the definition of the spectral index, a value of the latter greater than three provides the most conservative threshold for detecting livestock manure and digestate spreading with an accuracy of 62.53%. Such results are robust to variations in the spectral response of the soil. On the basis of these very encouraging results, it is considered plausible that the proposed index could improve the techniques for detecting the spreading of livestock manure and digestate on bare ground, classifying the areas themselves with a notable saving of energy compared to the current investigation methodologies directly on the ground. [ABSTRACT FROM AUTHOR]

Groundwater is a significant source of water supply, especially with depleted and quality-deteriorated surface water. The number of drilled boreholes for groundwater has been increased, but erroneous results often occur while selecting sites for digging boreholes. This makes it necessary to follow a science-based method indicating potential zones for groundwater storage. The LithoSFR Model is a systematic approach we built to create an indicative map with various categories for potential groundwater sites. It is based mainly on retrieved geospatial data from satellite images and from available thematic maps, plus borehole data. The geospatial data were systematically manipulated in a GIS with multi-criteria applications. The novelty of this model includes the empirical calculation of the level each controlling factor (i.e., weights and rates), as well as the LithoSFR Model, adopting new factors in its design. This study was applied on a representative Mediterranean region, i.e., Lebanon. Results showed that 44% of the studied region is characterized by a very high to high potentiality for groundwater storage, mainly in areas with fractured and karstified carbonate rocks. The obtained results from the produced map were compared with datasets which were surveyed from representative boreholes to identify the discharge in the dug boreholes, and then to compare them with the potential zones in the produced map The reliability of the produced map exceeded 87%, making it a significant tool to identify potential zones for groundwater investment. [ABSTRACT FROM AUTHOR]

Objectives: To analyze the rate of gestational syphilis (GS) based on temporal trends over 11 years, as well as the spatial distribution of GS in Brazil, based on the identification of spatial clusters. Methodology: An ecological, using Brazil and its regions as an analysis unit, based on gestational syphilis data reported in the Notifiable Diseases Information System (SINAN), from 2011 to 2020. Thematic maps were built for spatial data analysis, and the Prais-Winsten autoregressive model was used to verify the trend. Spatial analysis identified the distribution of clusters (high-high; low-low; high-low and low-high) of distribution of GS across Brazilian municipalities, using a 5% significance level. Results: Gestational syphilis experienced a considerable increase in cases during the studied period, with a peak of 37,436 cases in 2018. The spatial distribution of the disease is heterogeneous in the country. A growing trend was observed in all states of Brazil, except for Espírito Santo, where it remained stationary, with a monthly variation of 10.32%. Conclusion: The spatial and temporal trend analysis point to syphilis as an important public health problem. The numbers are alarming and show the urgent need for measures to prevent and control syphilis during pregnancy. [ABSTRACT FROM AUTHOR]

Coral reef bleaching events have become more frequent all over the world and pose a serious threat to coral reef ecosystems. Therefore, there is an urgent need for better detection of coral reef bleaching in a time- and cost-saving manner. In recent years, remote sensing technology has often been utilized and gained recognition for coral reef bleaching detection. However, bleaching corals in the water always have weak spectral change signals, causing difficulties in using remote sensing data. Additionally, uneven change samples make it challenging to adequately capture the details of coral reef bleaching detection and produce thematic maps. To resolve these problems, a novel method named coral reef bleaching detection by positive-unlabeled bagging (CBD-PUB) is proposed in this paper. To test the capacity of the method, a series of multi-temporal Sentinel-2 remote sensing images are utilized, and Lizard Island in Australia is taken as a case study area. The pseudo-invariant feature atmospheric correction (PIF) algorithm is adopted to improve coral reef bleaching spectral signals. After that, CBD-PUB is employed to effectively explore coral reef bleaching variation and its corresponding influence relations. The experimental results show that the overall accuracy of bleaching detection by the proposed algorithm reaches 92.1% and outperforms the traditional method. It fully demonstrates the feasibility of the model for the field of coral reef bleaching detection and provides assistance in the monitoring and protection of coral environments. [ABSTRACT FROM AUTHOR]

Soil erosion represents a complex ecological issue that is present on a global level, with negative consequences for environmental quality, the conservation and availability of natural resources, population safety, and material security, both in rural and urban areas. To mitigate the harmful effects of soil erosion, a soil erosion map can be created. Broadly applied in the Balkan Peninsula region (Serbia, Bosnia and Herzegovina, Croatia, Slovenia, Montenegro, North Macedonia, Romania, Bulgaria, and Greece), the Erosion Potential Method (EPM) is an empirical erosion model that is widely applied in the process of creating soil erosion maps. In this study, an innovation in the process of the identification and mapping of erosion processes was made, creating a coefficient of the types and extent of erosion and slumps (φ), representing one of the most sensitive parameters in the EPM. The process of creating the coefficient (φ) consisted of applying remote sensing methods and satellite images from a Landsat mission. The research area for which the satellite images were obtained and thematic maps of erosion processes (coefficient φ) were created is the area of the Federation of Bosnia and Herzegovina and the Brčko District (situated in Bosnia and Herzegovina). The Google Earth Engine (GEE) platform was employed to process and retrieve Landsat 7 Enhanced Thematic Mapper plus (ETM+) and Landsat 8 Operational Land Imager and Thermal Infrared Sensor (OLI/TIRS) satellite imagery over a period of ten years (from 1 January 2010 to 31 December 2020). The mapping and identification of erosion processes were performed based on the Bare Soil Index (BSI) and by applying the equation for fractional bare soil cover. The spatial–temporal distribution of fractional bare soil cover enabled the definition of coefficient (φ) values in the field. An accuracy assessment was conducted based on 190 reference samples from the field using a confusion matrix, overall accuracy (OA), user accuracy (UA), producer accuracy (PA), and the Kappa statistic. Using the confusion matrix, an OA of 85.79% was obtained, while UA ranged from 33% to 100%, and PA ranged from 50% to 100%. Applying the Kappa statistic, an accuracy of 0.82 was obtained, indicating a high level of accuracy. The availability of a time series of multispectral satellite images for each month is a crucial element in monitoring the occurrence of erosion processes of various types (surface, mixed, and deep) in the field. Additionally, it contributes significantly to decision-making, strategies, and plans in the domain of erosion control work, the development of plans for identifying erosion-prone areas, plans for defense against torrential floods, and the creation of soil erosion maps at local, regional, and national levels. [ABSTRACT FROM AUTHOR]

This study aims to analyze, determine, and quantify the literature on student intention toward entrepreneurship development (ED) and identify trends, developments, or progressions in the SCOPUS database. By utilizing an electronic search methodology, the most pertinent scholarly articles were identified. VOS Viewer software and R program code were utilized to evaluate each analytical instrument. Coauthorship, co-citation, conceptual structure, co-word occurrence, and citation analysis were among the numerous factors investigated. The study incorporates data from 1,465 sources, including conference proceedings, journals, and books. The source with the second-highest impact is the International Journal of Education, while Computers and Education has the greatest influence. This study provides a complete picture and description of the resulting body of knowledge in student intention toward entrepreneurship development. [ABSTRACT FROM AUTHOR]

Purpose: Music festivals are categorized as event management in the hospitality and tourism (H&T) industry. Additionally, music festivals or events are a continuous phenomenon in the context of the hospitality and tourism industry. In this study, a bibliometric approach was proposed to examine research that addresses both the H&T industry and music festivals. Design/methodology/approach: A total of 462 studies covering the years 1981–2024 were retrieved from the Scopus database. The study analyzed keywords, institutions, sources, countries, and titles. During the analysis phase, descriptive analysis, clustering, thematic mapping, and relationship networks were employed using Bibliometrix and VOSviewer analysis programs. Findings: As a result of the analysis, the most frequently used keywords were "tourism" and "festival," with the most prolific author being Kruger M., the most productive country being the United States of America, and the leading journal being Event Management. Seven different clusters emerged from the networking of keywords. In the thematic map, the motor themes were music festivals, experience, social media, and co-creation. The basic themes were festival, music, tourism, event management, market segmentation, and music tourism. The emerging or declining themes were culture, music events, and COVID-19. Finally, the niche theme was entrepreneurship. Research limitations/implications: It's noted that this research solely utilized the Scopus database and publications such as chemistry and mathematics, were excluded. The findings were limited to bibliometric analysis, and future studies could include content and thematic evaluations. Social implications: The research is useful in understanding how music festivals socially direct tourists and their future perspectives. On the other hand, determining the global status of scientific publications regarding music festivals with high social and economic impact is important for proper planning and sustainability of such events. Originality/value: Music festivals are an important type of event in terms of mobility in the H&T industry. In this respect, it is in a state of change and development over the years. This research examined publications about music festivals in the H&T industry from the past to the present with a bibliometric approach. In this way, the development of publications produced on the relevant subject was revealed. [ABSTRACT FROM AUTHOR]

In recent times, drilling groundwater wells for irrigation, domestic, and industrial uses is increasing at a high rate in Saudi Arabia, meaning that groundwater is becoming a primary water resource. In the study region, over-exploitation and unsustainable performance severely deteriorate groundwater. Therefore, it is important to monitor the groundwater levels and quality as well as to detect the hydraulic parameters in order to plan and maintain groundwater sustainability. Knowledge of aquifer hydraulic parameters and groundwater quality is essential for the productivity planning of an aquifer. Therefore, this study carried out a thorough analysis on measured depth to groundwater data (2017 and 2022), borehole pumping test records, and chemical analysis of the collected water samples, especially in the presence of overexploitation and scarcity of recharge scale. To accomplish this aim, measurements of 113 groundwater wells (including 103 water samples) and analysis of 29 pumping tests between step and long-duration tests were made of all aquifer characteristics. These parameters consist of well loss, formation loss, well efficiency, specific capacity, transmissivity, hydraulic conductivity, resulted drawdown, and physiochemical parameters. Thematic maps were generated for all parameters using the geographic information system (GIS) and diagrams to strategize the groundwater productivity in Al-Madinah Al-Munawarah Province. The estimated hydraulic parameters are highly variable. Four distinct portions were identified for aquifer potentiality based on these varying ranges. Both the north and east of the region are good for groundwater productivity due to good aquifer materials, whereas the southwestern and western portions have relatively poor values. The analyzed groundwater was categorized as fresh to slightly salty water, with two primary chemical types identified showing a prevalence of mixed NaCl and Ca-Mg-SO4/Cl water. Finally, groundwater productivity assessment predicts that the aquifers can support the Al-Madinah Al-Munawarah Province demand for several years if certain well distributions are adopted and for a few hours/day of pumping rate. The maps that have been created can be examined to aid in making decisions related to hydrology. [ABSTRACT FROM AUTHOR]

We investigate Venezuela's potential "futures" under Shared Socioeconomic Pathways (SSPs) through a systematic literature review, including systematic mapping and thematic analysis of 50 scientific articles. We categorised the SSP scenarios into two generational categories and classified the outcomes into positive, negative, and neutral futures. Under first-generation SSP scenarios, increasing poverty could be reversed, and the country's economic growth could be stimulated by adopting unambitious climate measures. However, second-generation SSP scenarios paint a more challenging picture. They suggest that Venezuela could face heat waves, droughts, an increase in diseases, loss of biodiversity, and an increase in invasive species and pests during the remainder of the 21st century as a direct consequence of climate change. Venezuela's geographic and topographic diversity could exacerbate these impacts of climate change. For instance, coastal areas could be at risk of sea-level rise and increased storm surges, while mountainous regions could experience more frequent and intense rainfall, leading to landslides and flash floods. The urgency of conducting additional research on the factors that could influence the severity of climate change's impact, considering Venezuela's geographic and topographic diversity, cannot be overstated. We also identified the critical need to explore alternative paths to move away from the current extractive development model. The potential actions in this regard could be instrumental in aligning the country with global adaptation and mitigation commitments. [ABSTRACT FROM AUTHOR]

The evolution of map development has been shaped by advancing techniques and technologies. Nevertheless, field and remote mapping with cabinet data analysis remains essential in this process. Geological maps are thematic maps that delineate diverse geological features. These maps undergo updates reflecting changes in the mapped area, technological advancements, and the availability of new data. Herein, a geological assessment example focused on enhancing mapped data using digitally processed historical (legacy) aerial images is presented for a case study in the Dinarides karst area in Croatia. The study area of Bribirske Mostine is covered by the Basic Geological Map of Yugoslavia (BGMY) at a 100,000 scale, which was developed during the 1960s. As the BGMY was developed 60+ years ago, one of its segments is further analyzed and discussed, namely, faults. Moreover, applying modern-day technologies and reinterpretation, its data, scale, presentation, and possible areas of improvement are presented. Georeferenced digital historical geological data (legacy), comprising BGMY, archive field maps, and aerial images from 1959 used in BGMY development, are reviewed. Original faults were digitalized and reinterpreted within the geographic information system with the following conclusions: (i) more accurate data (spatial positioning) on faults can be gained by digitally processing aerial photographs taken 60+ years ago with detailed review and analysis; (ii) simultaneously, new data were acquired (additional fault lines were interpreted); (iii) the map scale can be up-scaled to 1:25,000 for the investigated area of Bribirske Mostine; and (iv) a newly developed map for the Bribirske Mostine study area is presented. [ABSTRACT FROM AUTHOR]

The Unified Competition Model (MacWhinney, 2012) accounts for cross-linguistic differences in thematic role mapping. We investigated production and predictive use of accusative case morphology in Russian-Hebrew bilingual children. We also investigated the role of production in predictive processing testing the Prediction-by-Production Account (Pickering & Garrod, 2018) vs. the Missing Surface Inflection Hypothesis (Prévost & White, 2000). Three groups of children aged 4–8 participated: Russian-Hebrew-speaking bilinguals, Russian-speaking and Hebrew-speaking monolingual controls. All children participated in the accusative case production and Visual-World eye-tracking comprehension experiments. Bilinguals were tested in both of their languages. The results of the study confirmed the predictions of the Unified Competition Model showing typological differences in the strength of the case-marking cue and its predictive use in sentence processing in Russian- and Hebrew-speaking controls. While Russian-speaking monolinguals relied on case marking to predict the upcoming agent/patient, the performance of Hebrew-speaking monolingual children varied. The findings for bilinguals showed that despite their lower production accuracy in both languages, they were either indistinguishable from monolinguals or showed an advantage in the predictive use of case morphology. The findings support the Missing Surface Inflection Hypothesis, which predicts a dissociation between production and comprehension. [ABSTRACT FROM AUTHOR]

THIS RESEARCH aims to create and analyze thematic soil maps for promising areas for agricultural expansion along the northwest coast of Egypt. The study area is 3151.671 km² and consists of a plateau and elevated areas merging into coastal lowlands. Remote sensing data were used with a digital elevation model to map the physiographic units and characterize land surface features. Five different physiographic entities are recognized; each mostly associated with the soil sub-great groups Typic Haplocalcids and Typic Torripsamments. Data collected through land survey and laboratory analysis were used to create thematic soil layers that were analyzed to determine land factors that limit agricultural development. The results showed that the land surface factors hinder agricultural development due to the steep slope and undulation of the land surface. Analysis of thematic soil maps showed that agricultural development in the region is mainly constrained by coarse soil texture, shallow soil depth, high CaCO3 content, and low CEC. To achieve agricultural sustainability in the region, improved drainage, organic fertilization, and crop selection are required. [ABSTRACT FROM AUTHOR]

Chlorophyll-a (Chl-a) concentration is a key indicator for assessing the eutrophication level in water bodies. However, accurately inverting Chl-a concentrations in optically complex coastal waters presents a significant challenge for traditional models. To address this, we employed Sentinel-2 MSI sensor data and leveraged the power of five machine learning models, including a convolutional neural network (CNN), to enhance the inversion process in the coastal waters near Hong Kong. The CNN model demonstrated superior performance with on-site data validation, outperforming the other four models (R2 = 0.810, RMSE = 1.165 μg/L, MRE = 35.578%). The CNN model was employed to estimate Chl-a concentrations from images captured over the study area in April and October 2022, resulting in the creation of a thematic map illustrating the spatial distribution of Chl-a levels. The map indicated high Chl-a concentrations in the northeast and southwest areas of Hong Kong Island and low Chl-a concentrations in the southeast facing the open sea. Analysis of patch size effects on CNN model accuracy indicated that 7 × 7 and 9 × 9 patches yielded the most optimal results across the tested sizes. Shapley additive explanations were employed to provide post-hoc interpretations for the best-performing CNN model, highlighting that features B6, B12, and B8 were the most important during the inversion process. This study can serve as a reference for developing machine learning models to invert water quality parameters. [ABSTRACT FROM AUTHOR]

China leads in the greening of the world, with a nearly doubled increase in its forest area since the 1980 s revealed by the National Forest Inventory (NFI). However, a significant challenge persists in the absence of consistent and reliable remote sensing data that align with the NFI, hindering a comprehensive understanding of the spatiotemporal patterns of terrestrial ecosystem changes driven by afforestation and reforestation efforts over recent decades in China. Moreover, conventional binary thematic maps and land use and land cover (LULC) maps encounter difficulties in providing a thorough assessment of canopy cover at the subpixel level and trees extending beyond officially designated forest boundaries. This limitation creates substantial gaps in our comprehension of their invaluable contributions to ecosystem services. To confront these challenges, this study presents a systematic framework integrating time-series Landsat satellite imagery and random forest-based ensemble learning techniques. This framework aims to generate China's inaugural annual tree cover dataset (CATCD) spanning from 1985 to 2023 at a 30 m spatial resolution. Evaluation against multisource reference data shown high correlations ranging from 0.70 to 0.96 and reasonable RMSE values ranging from 5.6 % to 25.2 %, highlighting the reliability and precision of our approach across different years and data collection methodologies. Our analysis reveals that China's forested area has doubled, expanding from 1.04 million km2 in 1985 to 2.10 million km2 in 2023. Notably, 33 % of this growth can be attributed to a shift from non-forest to forest land categories, primarily observed in the three-north and southwest regions. However, the majority, contributing 67 %, results primarily from crown closure in central and southern China. This realization underscores the limitations of conventional binary thematic maps and LULC maps in accurately quantifying forest gain in China. Furthermore, China's tree population structure has undergone a transformative shift from 83 % forest trees and 17 % non-forest trees in 1985 to 92 % forest trees and 8 % non-forest trees in 2023, signifying a transition from afforestation to established forests. Our study not only enhances the understanding of tree cover variations in China but also provides valuable data for ecological investigations, land management strategies, and assessments related to climate change. [ABSTRACT FROM AUTHOR]

This study aims to perform a comprehensive bibliometric investigation to navigate the colliding domains of blockchain technology and supply chain management from 2017 to 2023. A total of 724 scholarly documents were extracted, showing increased annual scientific productivity and revealing a detailed map of the academic landscape. Notably, publications in sources such as IEEE Access and Sustainability (Switzerland) have emerged as seminal sources, with scientists such as Jayaraman R. leaving a strong scholarly impact among changing publication volumes. Affiliations such as Khalifa University, Nirma University, and The University of Hong Kong appear as critical research hotspots, but China maintains a strong position in publication count. The analysis shows trending trajectories and collaborative networks among authors, institutions, and countries, and it generates a thematic map with five unique clusters. The study also delineates thematic progression and co-citation patterns, providing a prospective perspective into future research avenues. Overall, this study extends the scholarly discussion by providing a broad, yet intricately detailed picture of the contemporary academic landscape. [ABSTRACT FROM AUTHOR]

Objective: The global burden of HIV remains a critical public health challenge, particularly in sub-Saharan Africa, home to over two-thirds of individuals living with HIV. HIV selftesting (HIVST) has emerged as a promising strategy endorsed by the World Health Organization to achieve UNAIDS targets. Despite its potential, challenges persist in linking self-testers to care post a positive result. Digital health interventions, including chatbots and mobile applications, offer innovative solutions to address this gap. However, a comprehensive bibliometric analysis of the collaboration and growth in the literature at the intersection of HIVST and digital interventions is lacking. Methods: The study employs a bibliometric approach, leveraging data from the Web of Science, to analyze the characteristics, citation pattern and content of 289 articles spanning 1992-2023. The analysis involves performance assessment, scientific collaboration analysis, science mapping, and content analysis. Key bibliometric indicators, such as annual growth rate, citation impact, and authorship patterns, are explored. Collaboration patterns among countries, institutions, and authors are elucidated, and thematic mapping provides insight into the key research themes. Results: The analysis reveals a dynamic and expanding field, with an annual scientific growth rate of 12.25%. Notable contributions come from diverse sources, including North America, Europe, and Africa. High-impact journals such as JMIR mHealth and uHealth play a crucial role in disseminating research findings. African authors, including Lebelonyane R, Ford N, and Lockman S, feature prominently, reflecting a positive trend in diverse authorship. Co-citation analysis highlights influential manuscripts, with systematic reviews dominating the top-cited articles. Collaboration analysis underscores strategic partnerships globally, particularly involving the United States, Australia, South Africa, and the United Kingdom. Conclusion: This bibliometrics analysis provides a comprehensive overview of the digital health landscape in HIVST and linkage to care. It identifies key contributors, high-impact journals, and collaborative networks. The thematic map reveals nuanced research domains, including alcohol dependence, men's health, outcomes, and user acceptance. The findings offer insights for researchers, policymakers, and practitioners, guiding future directions in the evolving intersection of HIVST and digital health interventions. [ABSTRACT FROM AUTHOR]

This article discusses how geographic information technologies (GIS) can be used to monitor and administer urban environments. In modern conditions, when cities face the challenges of rapid population growth, urbanization, climate change and environmental degradation, traditional methods of urban management become insufficiently effective. GIS technologies offer innovative solutions to collect, analyze and visualize spatial data to enable more informed decision making. The article includes a review of previous research in this area, including the work of Michael Goodchild, Rodrigo Garcia and Yang Li, who have made significant contributions to the theory and practice of GIS applications in urban management. The focus is on methods and algorithms used for data monitoring and analysis, such as data collection, data processing, analysis using clustering and spatial regression techniques, and data visualization using cartographic techniques and 3D models. The paper details the flowcharts of urban environment monitoring processes and algorithms used for data analysis. Examples of mathematical models and thematic maps used to present the results of the analysis are given. The conclusion offers perspectives on the further development of GIS and its integration with other advanced technologies, such as the Internet of Things and artificial intelligence, to solve complex urban management problems. The purpose of this article is to substantiate the importance and effectiveness of using geoinformation technologies for monitoring and administration of urban environment, as well as to provide practical recommendations and examples of using GIS technologies in various aspects of urban management. [ABSTRACT FROM AUTHOR]

Objective: Smoking cessation interventions are underutilized in the surgical setting. We aimed to systematically identify the barriers and facilitators to smoking cessation in the surgical setting. Methods: Following the Joanna Briggs Institute (JBI) framework for scoping reviews, we searched 5 databases (MEDLINE, Embase, Cochrane CENTRAL, CINAHL, and PsycINFO) for quantitative or qualitative studies published in English (since 2000) evaluating barriers and facilitators to perioperative smoking cessation interventions. Data were analyzed using thematic analysis and mapped to the theoretical domains framework (TDF). Results: From 31 studies, we identified 23 unique barriers and 13 facilitators mapped to 11 of the 14 TDF domains. The barriers were within the domains of knowledge (e.g., inadequate knowledge of smoking cessation interventions) in 23 (74.2%) studies; environmental context and resources (e.g., lack of time to deliver smoking cessation interventions) in 19 (61.3%) studies; beliefs about capabilities (e.g., belief that patients are nervous about surgery/diagnosis) in 14 (45.2%) studies; and social/professional role and identity (e.g., surgeons do not believe it is their role to provide smoking cessation interventions) in 8 (25.8%) studies. Facilitators were mainly within the domains of environmental context and resources (e.g., provision of quit smoking advice as routine surgical care) in 15 (48.4%) studies, reinforcement (e.g., surgery itself as a motivator to kickstart quit attempts) in 8 (25.8%) studies, and skills (e.g., smoking cessation training and awareness of guidelines) in 5 (16.2%) studies. Conclusion: The identified barriers and facilitators are actionable targets for future studies aimed at translating evidence informed smoking cessation interventions into practice in perioperative settings. More research is needed to evaluate how targeting these barriers and facilitators will impact smoking outcomes. [ABSTRACT FROM AUTHOR]

Background: The purpose of this work consists of doing a comparative study of three Land Capability Classification (LCC), Storie, National Institute of Irrigation and Drainage Institute (INSID) by applying them to the region of the Oriental Mitidja (Rouiba-Algeria). Methods: A geographic information system for the region in question was carried out, with a view to developing different thematic maps and allowing the comparison of these three evaluation systems, thanks to a database that has been created for this purpose. Result: The system adapted by INSID has given rise to lower evaluation results compared to the two other systems, because 99.99% of the total agricultural ability by the LCC, 97% Apt for agriculture. By Storie while only 48% of the total area is fit for agriculture according to INSID. Statistical results have shown the existence of a significant difference between the three land evaluation systems. However, the correlation is significant between the INSID and STORIE system. [ABSTRACT FROM AUTHOR]

Logistics continues to be a current and constantly evolving topic within its areas. Bearing in mind the diversity of articles published in the area and their constant expan-sion, this work intends to map the most recent scientific publications in the area of logistics and thereby identify the main keywords, analyze and characterize the patterns and trends of studies in the area. All of these indexed in the Scopus database in the years 2019, 2020, 2021 and 2022. Eighty articles were selected, with the twenty most cited in each year being selected. To carry out this mapping, the SciMat software was used, which enabled a visual analysis through thematic maps and word networks. With the results obtained, there was great development and future trends in technological areas such as blockchain, drones, IoT and trends in sustainability areas, leaving pos-sibilities for new studies in several areas. [ABSTRACT FROM AUTHOR]

This study compares adjacent and bivariate maps in communicating variance-based global sensitivity analysis (GSA) results for a geodiversity assessment spatial multi-criteria model and examines the influence of prior exposure to geodiversity and map reading skills on interpretation. It analyzes the quality of map interpretation, confidence levels, and map communication effectiveness. The findings indicate that there is no significant difference in the quality of map interpretation or confidence levels between the two map types. However, there are nuanced differences in interpretive patterns, suggesting the need for further investigation into factors affecting map interpretation. Adjacent maps are more effective in identifying factors linked to uncertainty in high geodiversity values, while bivariate maps excel in understanding spatial variability. Prior exposure to geodiversity and map reading skills do not significantly impact interpretation quality or confidence levels. Future research could explore other factors influencing map effectiveness and explore the cognitive processes underlying map interpretation. Understanding these processes could lead to more effective strategies for communicating the results of a GSA for spatial models through maps. [ABSTRACT FROM AUTHOR]

This article explores the concept of "immigrant consumption behavior (ICB)" in the context of its holistic surroundings. The study investigated the current dynamics and scientometrics of the research field regarding immigrant consumption behaviors. Using an integrative approach employing bibliometric and content analysis, it scrutinized a collection of 224 studies from the Web of Science and Scopus databases to detect the field evolution, disciplinary distribution thematic map, and emerging trends in the ICB literature, as well as to forecast research directions. The results showed that ICB is a multi- and inter-disciplinary research area that experienced three phases of growth between 1989 and 2023: initiation (1989–2006), development (2007–2012), and consolidation (2013–now). The thematic analysis revealed five current trends, i.e., (1) the immigrant consumption behavior domain, (2) the demographic sub-groups of immigrants and related consuming products, (3) country-, region-, and cultural-focused studies, (4) the effects of culture and the acculturation process, and (5) the impact of urbanization. Each theme contains a number of sub-themes. Based on the current thematic evolution and keyword burst analysis, this paper suggests a number of critical research directions, comprising (1) observatory studies including remittances, China, ethnic minorities, lifestyle, inequality, urbanization, and food consumption; (2) context-based studies focused on socioeconomic, cultural, legal, and environmental factors; (3) studies based on compensatory and compromissory consumption behavior; (4) studies focused on sustainable and green consumption behaviors; and (5) studies regarding the behavior of specific demographic co-ethnic communities. The results have great implications for developing interventions and programs that can support immigrant populations in making appropriate consumption patterns and adapting to new cultural environments. The paper pushes forward the ICB investigation from individual empirical studies to synthesis-based research, which (1) provides an ample overview of the ICB literature, (2) identifies research priorities, emerging trends, and gaps, (3) proposes new research avenues for investigation, and (4) outlines expected contributions. The research contributes to a variety of disciplines through the provision of new knowledge, since ICB studies are multidisciplinary in nature. It also has numerous implications for policymakers and practitioners. [ABSTRACT FROM AUTHOR]