Search

Environmental concern is a significant driver of demand for sustainable initiatives, emphasizing the significance of green finance in academic research. While sustainability issues attract increasing global focus, the need to map the development and thematic evolution of green finance becomes important. Therefore, the present study mounts the development and thematic evolution of green finance through a comprehensive bibliometric analysis. Using the Scopus database, we analyzed 887 articles to identify key trends, collaboration networks, and thematic clusters. It was found that China has made a significant contribution to academic literature and has had notable collaborations with South Asian institutions. The central themes are carbon emissions, green technology innovation, and renewable energy. The two advanced bibliometric tools, Biblioshiny and VOSviewer create thematic maps, co-citation networks, and keyword analyses to provide insights into the intellectual structure of green finance research. Based on this study, the most influential authors, major journals, and emerging research areas are pinpointed to offer a pathway for future research in this multidisciplinary domain. The study's findings underscore green finance's significant role in achieving sustainable development and promoting environmentally friendly initiatives. [ABSTRACT FROM AUTHOR]

Groundwater is the most dynamic natural resource that is not uniformly distributed both in space and time. Identifying it for sustainable water resource development for domestic use, irrigation, and industrial purposes is the biggest challenge and key concern due to climate change, overexploitation, and a lack of proper management. Geographical information system (GIS) and remote sensing (RS) play a fundamental role in identifying suitable groundwater potential and recharge zones. In this study, groundwater potential and recharge zone map are delineated using GIS and RS techniques integrated with Analytic Hierarchy Process (AHP) for the Melka Kunture Watershed in Ethiopia. The thematic layers used were: Lithology, geomorphology, slope, lineament density, land use/cover, rainfall, drainage density and soil. GIS has been used to integrate and overlay thematic layers using a weighted overlay analysis tool, whereas the AHP method has been used to assign the weights, normalize, and rank thematic layers and their associated sub-themes based on their suitability, characteristics, or influence on groundwater potential and recharge zones. The output groundwater potential zone map is categorized into four suitable zones: high potential cover 1105.60 km2 (25.70%), moderate potential 2308.00 km2 (53.73%), low potential 880.0 km2 (20.49%), and very low potential 47.80 km2 (1.10%), whereas there are three suitable groundwater recharge potential zones: high potential cover 250.20 km2 (5.80%), moderate recharge 3647.90 km2 (84.00%), and low recharge 443.50 km2 (10.20%) of the study area. Hence, the study areas have been more suitable for groundwater potential and recharge zones as compared to the total area. The groundwater potential map was validated using the existing water source and well points, and it indicated a good prediction accuracy of 88%. Thus, the delineated groundwater potential and recharge zone maps are reliable, and the resultant potentiality mapping has played a vital role in the sustainable development and management of the water resources in the study area. Highlights: → The integration of GIS and RS techniques with the MCDA-AHP method is a powerful tool for delineating the groundwater potential and recharges zones in the Melka Kunture Watershed. → Utilizing both recent conventional data and high-resolution satellite imagery is crucial for creating accurate thematic layers and maps of groundwater potential and recharge zones. → To further validate and enhance these techniques, conducting well drilling or pump tests using geophysical investigations is recommended to gain a more detailed understanding of groundwater potential and recharge zones, as well as to estimate yields. [ABSTRACT FROM AUTHOR]

Copyright of Environmental & Social Management Journal / Revista de Gestão Social e Ambiental is the property of Environmental & Social Management Journal and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Currently, global warming, invasive alien species and tourism development pose major threats to Natural World Heritage sites, and the strengthening of conservation methods and management programs in buffer zones is urgent for the sustainable development of sites. Agroforestry, as a nature-based solution, not only promotes the buffer zone to effectively maintain the Outstanding Universal Value of the heritage site, but also balances the relationship between the conservation of the heritage site and the economic development of the buffer zone, and effectively enhances the protection of the buffer zone in response to various threats. However, there is currently a lack of comprehensive understanding of research trends, research focuses, and recent developments, regarding the conservation of natural heritage sites and buffer zone agroforestry development. Therefore, this study utilized the Scopus database along with Excel and Bibliometrix software to conduct a bibliometric analysis and explore and visualize popular research topics and foreword issues related to Natural World Heritage conservation and buffer zone agroforestry development. We discuss the current publication trends and quantity, keyword and abstract word frequencies, thematic maps and evolutions, journal productivity, national publication outputs, collaboration relationships, and contributing institutions. The research shows that the relationship between biodiversity conservation and agroforestry has been the focus of research in the field since 1992, and the development of agroforestry has contributed to biodiversity conservation in heritage sites. However, there have been fewer studies addressing the geomorphic and aesthetic value of agroforestry conservation, and little attention has been paid to buffer zone development. Based on this, this manuscript suggests that in the future, emphasis should be placed on the linkage between the development of buffer zones and heritage conservation, especially in the Karst World Heritage Sites with ecologically fragile, and that the role of agroforestry development in buffer zones should be strengthened in the promotion of ecological balance and sustainable development of the sites, to provide scientific references for the conservation and development of other geoheritage sites around the globe. [ABSTRACT FROM AUTHOR]

The use of artificial intelligence (AI) is revolutionizing many professions and research fields. Thus, the present study focuses on the implications that AI is having on research in materials science and engineering (MSE). To this end, a bibliometric review has been conducted to analyze the advances that AI is generating in MSE. Although expectations for AI advances in the field of MSE are high, the results of this study indicate that we are still at a preliminary stage of development. It is worth highlighting that despite the progress made, the potential of AI in MSE has not been fully exploited and numerous challenges remain to be overcome to achieve effective and widespread implementation. It should be noted that the subarea "Materials structure, processing, and properties" is the one that currently presents the largest number of research works linked to AI. It appears that the United States and China are currently the countries with the greatest involvement in the use of AI in the field of MSE. The emerging themes and thematic map of the topic are revealed, and future research directions are provided. [ABSTRACT FROM AUTHOR]

Relief, climate and soils in the lands of the villages of Edrevo and Panicherevo, Stara Zagora region, Bulgaria were examined. A geographic information system (GIS), including the collected information, and spatial visualization of soil data and main soil characteristics was carried out in the form of a soil map and thematic maps of soil texture (physical clay content in %), humus content (%) and soil acidity (pH). A greater part of the agricultural land is occupied by Cinnamon forest soils, a total of 1720.56 ha, of which 1012.43 ha are strongly leached to slightly podzolized with varying degrees of erosion and 708.12 ha are undeveloped and shallow soils. The rest of the agricultural lands are from Alluvial (Deluvial) - meadow soils - 930.29 ha. The detailed description of the soil-climatic conditions was applied in determining the credit rating and category of the lands in the investigated lands (part II). [ABSTRACT FROM AUTHOR]

In the context of the information age, the symbolization of regional elements has become a crucial component in modern cartographic practice. The targeted identification of regional elements and the design of map symbols are prerequisites for realizing the symbolization of regional elements. Therefore, we propose a method to symbolize regional elements by combining textual analysis and image processing. Firstly, local chronicles are used as the textual information source, and regional elements are extracted through textual data mining. Second, the real image data of the elements are selected, and the image segmentation algorithm, clustering algorithm, etc., are used to extract contours and colors from the images and carry out corresponding symbol simplification and color matching, to create highly recognizable symbols. Finally, we apply the symbols to two map types: the thematic map and the tourist map, and design a questionnaire to evaluate the outcomes of the symbol design. After a thorough review, it has been found that the method is superior to related symbolization studies in terms of data source authority, symbol generation efficiency, and symbol information carrying. In conclusion, guided by interdisciplinary thinking, this study effectively combines theoretical analysis and design practice, proposes a new idea of symbolization, and opens up a new way for geographic information visualization. [ABSTRACT FROM AUTHOR]

Istanbul is located south of the Black Sea and north of the Marmara Sea. The seismic stresses and strains in Istanbul and the Marmara Sea are governed by the E-W and NE-SW tectonic characteristics. This research aims to establish the latest crustal motion parameters in Istanbul, utilising Global Navigation Satellite System (GNSS) surveys. A geodetic network was established for this study, comprising 1,159 temporary and nine permanent GNSS stations across Istanbul's Asian and European sectors. Between 2000 and 2020, GNSS measurements were taken, and horizontal and vertical crustal movements and velocity vector maps were produced using GNSS and Geographical Information System (GIS) tools. The GNSS data was processed using GIPSY-OASIS, Topcon Magnet Tools, and Leica Geo-Office software. The data was, then, analysed using ESRI ArcGIS software, which generated thematic maps of Istanbul using ordinary Kriging and trend surface analysis interpolation methods. The analysis results indicate a horizontal variation of the local velocity rate in the SW direction between 14.3 and 17.1 mm per year. Moreover, the data suggests that there is a subsidence variation between -0.7 and -2.0 mm per year. The study results show that the northern block of the North Anatolian Fault Zone moves horizontally towards the SW at an average rate of 16.3 mm per year. The study findings demonstrate a notable horizontal slip rate in the northern regions, whereas vertical subsidence is significantly observable in the eastern regions. The study involved the creation of Voronoi cells for each temporary GNSS station, followed by the calculation of regional shift magnitudes in the area surrounding each station. In regions with notable horizontal and vertical slippage, it would be beneficial to increase the number of observation stations, particularly within the extensive Voronoi cells. The longterm and continuous GNSS measurements greatly improve the study of ongoing crustal movement and tectonic deformation processes in north-western Anatolia. [ABSTRACT FROM AUTHOR]

Coal mining in the Loess Plateau can very easily generate ground cracks, and these cracks can immediately result in ventilation trouble under the mine shaft, runoff disturbance, and vegetation destruction. Advanced UAV (Unmanned Aerial Vehicle) high-resolution mapping and DL (Deep Learning) are introduced as the key methods to quickly delineate coal mining ground surface cracks for disaster prevention. Firstly, the dataset named the Ground Cracks of Coal Mining Area Unmanned Aerial Vehicle (GCCMA-UAV) is built, with a ground resolution of 3 cm, which is suitable to make a 1:500 thematic map of the ground crack. This GCCMA-UAV dataset includes 6280 images of ground cracks, and the size of the imagery is 256 × 256 pixels. Secondly, the DRA-UNet model is built effectively for coal mining ground surface crack delineation. This DRA-UNet model is an improved UNet DL model, which mainly includes the DAM (Dual Dttention Dechanism) module, the RN (residual network) module, and the ASPP (Atrous Spatial Pyramid Pooling) module. The DRA-UNet model shows the highest recall rate of 77.29% when the DRA-UNet was compared with other similar DL models, such as DeepLabV3+, SegNet, PSPNet, and so on. DRA-UNet also has other relatively reliable indicators; the precision rate is 84.92% and the F1 score is 78.87%. Finally, DRA-UNet is applied to delineate cracks on a DOM (Digital Orthophoto Map) of 3 km2 in the mining workface area, with a ground resolution of 3 cm. There were 4903 cracks that were delineated from the DOM in the Huojitu Coal Mine Shaft. This DRA-UNet model effectively improves the efficiency of crack delineation. [ABSTRACT FROM AUTHOR]

In this manuscript I build upon an initial body of research developing procedures for leveraging large language models (LLMs) in qualitative data analysis, by carrying out thematic analysis (TA) with LLMs. TA is used to identify patterns by means of initial labelling of qualitative data followed by the organisation of the labels/codes by themes. First, I propose a new set of LLM prompts for initial coding and generation of themes. These new prompts are different from the typical prompts deployed for such analysis in that they are entirely open-ended and rely on TA language. Second, I investigate the process of removing duplicate initial codes through a comparative analysis of the codes of each interview against a cumulative codebook. Third, I explore the construction of thematic maps from the themes elicited by the LLM. Fourth, I evaluate the themes produced by the LLM against the themes produced manually by humans. For conducting this research, I employed a commercial LLM via an application program interface (API). Two datasets of open access semi-structured interviews were analysed to demonstrate the methodological possibilities of this approach. I conclude with practical reflections on performing TA with LLM, enhancing our knowledge of the field. [ABSTRACT FROM AUTHOR]

Due to the non-standardization and the personalized need of thematic mapping, the processing efficiency of basic geographic information data has not been effectively improved. The thematic mapping technology based on Photoshop has been adopted in railway industry widely. This paper applied the JavaScript technology to the secondary development of mapping, called the API of Windows and Photoshop, and used common mapping modules, mapping functions, main parameters, and hotkeys to encapsulate packages. It realized batch processing of remote sensing images, automatically processing of features on thematic map, and modification of map features in human-machine interaction manner. The research includes three parts: (1) The introduction of the configure environment, compile platform, and result of secondary development based on Javascript. (2) The application of four application scenarios for JavaScript technology: 1 Image batch processing to achieve automatic spectral enhancement of remote sensing image. 3 Automatic mapping for thematic map elements. 2 Batch and automatic modification of features on maps. 4 processing of elements on the map in human-machine interaction manner. (3) The example of the thematic mapping of a railway project in Europe using remote sensing image for the verification of the feasibility. The results show that the technology can significantly improve the mapping efficiency, make it easier to standardize drawing map symbol, and solve the problems on high redundancy of data and low efficiency of execution during batch and automatic processing scripts. [ABSTRACT FROM AUTHOR]

In the era of information and communication technology (ICT), the advancement of science and technology has led to a trend of diversification in map representation. However, the lack of professional knowledge means that there is still a challenge in determining the appropriate type of thematic map for land use expression. To address this issue, this paper proposes a knowledge recommendation method for land use thematic maps based on the theory of visualization dimensions. Firstly, we establish a knowledge ontology of land use thematic maps centered on spatial data, data characteristics, visualization dimensions, thematic map forms, and application scenarios. A land use thematic map knowledge graph is constructed through knowledge extraction and storage operations. Secondly, knowledge embedding is performed on the knowledge graph to enable the knowledge-based expression of map visualization elements. Finally, based on the knowledge elements of land use thematic expression, a similarity calculation model is established to calculate the similarity between input data and the spatial data characteristics, visualization dimensions, and application scenarios within the knowledge graph, deriving a comprehensive similarity result to achieve precise recommendation for land use thematic map forms. The results show that the method can provide a more accurate visualization reference for the selection of land use themes, meeting the diversified needs of land use thematic expression to a certain extent. [ABSTRACT FROM AUTHOR]

Irrigation is important for the growth of world agriculture, as it enables greater security in agricultural production. The use of center-pivot for irrigation is very common in Brazil. However, there are some information gaps, mainly related to spatial variability in the water application in variable topography. Thus, the present study aimed to apply the geostatistical approach to characterize and evaluate the magnitude of the pressure head (PH) spatial variability in center-pivot lateral lines operating in plots with variable topography. For this analysis, six different points were installed along the lateral line and measured with PH transducers in 18 lateral line angular positions in the study area. Universal kriging (UK) was used to estimate PH across the whole field. The semivariogram was adjusted by the hole effect theoretical model, indicating a strong spatial dependence on PH. A decision support system tool was developed to assist in the analysis of the PH spatial distribution along the center-pivot lateral line using a geostatistical approach (kriging). The proposed tool can be useful for managers of irrigable areas and to identify zones with high energy use (wasted PH) along lateral lines of center-pivot systems. The estimation of PH distribution using geostatistical and UK techniques was satisfactory, allowing the creation of a thematic map. Precision irrigation and monitoring using a thematic map of PH distribution from kriging can help monitor the operating conditions of a center-pivot, as well as improve the decision-making regarding proper management of the whole irrigation system. Practical Applications: Center-pivot irrigation systems are very common in agricultural production areas around the world. Due to the large area irrigated by center-pivots, it is very important to study the reduction in water and energy use in these equipment. Thus, an important point to be studied is the PH distribution along the center-pivot lateral line in areas with undulating topography, where there is a significant PH variation. In this study, we present an analysis of the PH distribution along the lateral line using a geostatistical approach (kriging) to obtain PH values in the entire irrigated area. For this, PH data collected at six different points along the lateral line were used in a decision support system tool, developed to estimate PH in the entire irrigated area using the geostatistical approach. This estimate was satisfactory, allowing the creation of a thematic map. The proposed tool proved to be useful for easily identifying zones with high energy use (wasted PH). In this way, the use of precision irrigation and the analysis of the equipment through thematic mapping can help irrigators in monitoring the operating conditions of a center-pivot. [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]

Objective: To conduct a bibliometric analysis of the prospects and obstacles associated with dual- and multi-energy CT in thoracic disease, emphasizing its current standing, advantages, and areas requiring attention. Methods: The Web of Science Core Collection was queried for relevant publications in dual- and multi-energy CT and thoracic applications without a limit on publication date or language. The Bibliometrix packages, VOSviewer, and CiteSpace were used for data analysis. Bibliometric techniques utilized were co-authorship analyses, trend topics, thematic map analyses, thematic evolution analyses, source's production over time, corresponding author's countries, and a treemap of authors' keywords. Results: A total of 1992 publications and 7200 authors from 313 different sources were examined in this study. The first available document was published in November 1982, and the most cited article was cited 1200 times. Siemens AG in Germany emerged as the most prominent author affiliation, with a total of 221 published articles. The most represented scientific journals were the "European Radiology" (181 articles, h-index = 46), followed by the "European Journal of Radiology" (148 articles, h-index = 34). Most of the papers were from Germany, the USA, or China. Both the keyword and topic analyses showed the history of dual- and multi-energy CT and the evolution of its application hotspots in the chest. Conclusion: Our study illustrates the latest advances in dual- and multi-energy CT and its increasingly prominent applications in the chest, especially in lung parenchymal diseases and coronary artery diseases. Photon-counting CT and artificial intelligence will be the emerging hot technologies that continue to develop in the future. Critical relevance statement: This study aims to provide valuable insights into energy-based imaging in chest disease, validating the clinical application of multi-energy CT together with photon-counting CT and effectively increasing utilization in clinical practice. Key Points: Bibliometric analysis is fundamental to understanding the current and future state of dual- and multi-energy CT. Research trends and leading topics included coronary artery disease, pulmonary embolism, and radiation dose. All analyses indicate a growing interest in the use of energy-based imaging techniques for thoracic applications. [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]

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]

Copyright of Environmental & Social Management Journal / Revista de Gestão Social e Ambiental is the property of Environmental & Social Management Journal and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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]

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]

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]

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]

The riverfronts converted into coastal public green spaces (PGS) have been linked to ecosystem services (ES) for temperature regulation. The aim of the work was to analyze the spatio-temporal variability of the Land Surface Temperature (LST) in different typologies of coastal PGS and its relationship with morphological and functional parameters that define them. Five PGSs were addressed on the Limay riverfront, subject to urban renewal processes, in the Metropolitan Area of Neuquén (Argentina). First, the PGSs were characterized at two spatial scales, based on their regional distribution, and at the local and microlocal level by virtue of the spatio-temporal distribution of the vegetation and 6 dimensions associated with morphological, functional and social aspects. Next, the spatiotemporal distribution of the LST in the PGS and its relationship with morphological and functional parameters were examined. The LST and NDVI spectral indices were obtained through digital processing of satellite images, selected based on wet and dry hydrological years, as well as summer and winter seasons. Thematic maps, descriptive statistical analysis and exploration of relationships between LST and NDVI were performed. Variations of the indices linked to the hydrological year, seasons of the year and anthropic interventions were identified. Likewise, the influence of morphology, internal organization and distance to the watercourse was observed. The findings contribute to the emerging body of knowledge around the link between ES and configuration of the landscape, specifically in a global context of growing revaluation and intervention of riverfronts. [ABSTRACT FROM AUTHOR]

Soil aggregate stability is crucial for maintaining the arrangement of solid particles and pore space in the soil, even under mechanical stresses. Traditional direct measurements of soil aggregate stability are time-consuming and expensive. This study aimed to spatially predict the soil aggregate stability indices, including the mean weight diameter of aggregates, the geometric mean diameter of aggregates, and the percentage of water stable aggregates, using five machine learning models and environmental covariates in the framework of digital soil mapping. A total of 100 samples were collected from the surface layer (0-15 cm) of soils in the Aji-Chai watershed, northwestern Iran, and their SAS indices were determined by standard laboratory methods. Four scenarios (S) were employed to evaluate the most influencing auxiliary variables, including (S1): topographic attributes, (S2): topographic attributes + remote sensing data, (S3): S2 + thematic maps (geology, land use/cover maps), and (S4): S3 + selected soil properties. Among the various machine learning models, the random forest showed exceptional performance and reduced uncertainty for S4, compared to the other machine learning models and desired scenarios. The coefficient of determination, concordance correlation coefficient, and normalized root mean squared error values of the random forest model were 0.86, 0.87, and 31.42% for mean weight diameter; 0.80, 0.84, and 31.59% for geometric mean diameter; and 0.54, 0.68, and 20.75% for water stable aggregates, respectively. Additionally, properties such as soil organic matter and clay, followed by remote sensing data, demonstrated the highest relative importance when compared to the other covariates in predicting the soil aggregate stability indices. In conclusion, the random forest ML-based model seems to be able to accurately predict soil aggregate stability indices at the watershed scale. The generated maps can serve as a valuable baseline for land use planning and decision-making. These findings contribute to the scientific understanding of soil physical quality indicators and their application in sustainable land management practices. [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]

Even though the web is a platform that provides lots of features, interactivity, and a high degree of customizability for creating web maps, web-based thematic maps still require expertise to visualize geospatial data in a way that highlights spatial differences and is cartographically comprehensive. The popular open-source web mapping library Leaflet lacks a straightforward approach to create thematic maps with basic principles they should adhere to (data classification, automatic symbology and legend generation). Although various tutorials and workarounds exist, those are hard-coded, only solve some principles thematic maps require and are complex to accomplish, requiring programming experience. The paper focuses on finding a way to overcome shortcomings of Leaflet in terms of thematic maps, that supports a simple, self-explanatory method of producing thematic web maps using the library. As a solution, this paper introduces an easy-to-use, open-source plugin for Leaflet, developed by the authors, which combines all processes required for creating a thematic map from a GeoJSON dataset, in one single step. For symbology, it supports graduated symbol colours and sizes, and colour and hatch pattern fills for polygons. It supports well-known classification methods for quantitative data and puts emphasis on providing numerous options for all underlying processes, to fine-tune the visualization (data normalization, rounding class boundary values, legend templating etc.). This highly customizable extension intends to help people who do not have experience with map design and are not familiar with scripting to an extent to be able to code visually pleasing thematic maps for websites. [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]

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]

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]

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]

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]

Effective biosecurity policies are essential to address several major sociological and environmental challenges facing humankind including existential pandemic risks, threats to food security, loss of ecosystem services and public resistance to pesticides and vaccines. Yet biosecurity is subject to multiple interpretations that include dealing with the threats from bioterrorism, managing laboratory biosafety to prevent the escape of pathogenic organisms, handling food and agricultural production systems to prevent disease introduction and addressing the threat of introduced organisms to flora, fauna and humans. The absence of a shared vision of what biosecurity encompasses means that decision-makers are often challenged to design appropriate biosecurity policies at national and global scales. The design of effective policy strategies requires an understanding of the methodological and conceptual barriers that constrain attempts to build an interdisciplinary approach to biosecurity. Here, the first thematic map of the biosecurity research landscape is undertaken to assess just how diverse the interpretation of biosecurity is amongst the global research community and the extent to which the articles published since 2000 represent a common conceptual foundation or are largely clustered within sectors. Co-citation, bibliographic coupling and co-word analyses highlighted that the field of biosecurity encompasses a wide range of domains from biochemistry through to political science, but the research supporting different sectors largely draws from a distinct literature base. While ecosystem and plant health were clustered together within the broad grouping of biological invasions, there was a clear separation from both human and animal health. Yet, there is considerable scope for the management of biological invasions to benefit from insights derived from social perspectives in human and animal health. Biosecurity remains divided by conceptual differences and specialised vocabularies that limit the effectiveness of biosecurity policies addressing biodiversity conservation, public health and food security. To overcome these constraints requires the building of a global biosecurity community that accepts a broader definition of biosecurity, avoids sectorial jargon and establishes mechanisms to cultivate interdisciplinarity through specialised collaborative centres, cross-sectorial research programmes and conceptually rich training programmes. [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]

In this manuscript I build upon an initial body of research developing procedures for leveraging large language models (LLMs) in qualitative data analysis, by carrying out thematic analysis (TA) with LLMs. TA is used to identify patterns by means of initial labelling of qualitative data followed by the organisation of the labels/codes by themes. First, I propose a new set of LLM prompts for initial coding and generation of themes. These new prompts are different from the typical prompts deployed for such analysis in that they are entirely open-ended and rely on TA language. Second, I investigate the process of removing duplicate initial codes through a comparative analysis of the codes of each interview against a cumulative codebook. Third, I explore the construction of thematic maps from the themes elicited by the LLM. Fourth, I evaluate the themes produced by the LLM against the themes produced manually by humans. For conducting this research, I employed a commercial LLM via an application program interface (API). Two datasets of open access semi-structured interviews were analysed to demonstrate the methodological possibilities of this approach. I conclude with practical reflections on performing TA with LLM, enhancing our knowledge of the field.

Objectives: This manuscript presents a bibliometric and visualization analysis of Total Body Irradiation (TBI) research, aiming to elucidate trends, gaps, and future directions in the field. This study aims to provide a comprehensive overview of the global research landscape of TBI, highlighting its key contributions, evolving trends, and potential areas for future exploration. Methods: The data for this study were extracted from the Web of Science Core Collection (WoSCC), encompassing articles published up toMay 2023. The analysis included original studies, abstracts, and review articles focusing on TBI-related research. Bibliometric indicators such as total publications (TP), total citations (TC), and citations per publication (C/P) were utilized to assess the research output and impact. Visualization tools such as VOS Viewer were employed for thematic mapping and to illustrate international collaboration networks. Results: The analysis revealed a substantial body of literature, with 7,315 articles published by 2,650 institutions involving, 13,979 authors. Full-length articles were predominant, highlighting their central role in the dissemination of TBI research. The authorship pattern indicated a diverse range of scholarly influences, with both established and emerging researchers contributing significantly. The USA led in global contributions, with significant international collaborations observed. Recent research trends have focused on refining TBI treatment techniques, investigating long-term patient effects, and advancing dosimetry and biomarker studies for radiation exposure assessments. Conclusions: TBI research exhibits a dynamic and multifaceted landscape, driven by global collaboration and innovation. It highlights the clinical challenges of TBI, such as its adverse effects and the need for tailored treatments in pediatric cases. Crucially, the study also acknowledges the fundamental science underpinning TBI, including its effects on inflammatory and apoptotic pathways, DNA damage, and the varied sensitivity of cells and tissues. This dual focus enhances our understanding of TBI, guiding future research toward innovative solutions and comprehensive care. [ABSTRACT FROM AUTHOR]

Background: Insulin resistance (IR) is considered the pathogenic driver of diabetes, and can lead to obesity, hypertension, coronary artery disease, metabolic syndrome, and other metabolic disorders. Accumulating evidence indicates that the connection between gut microbiota and IR. This bibliometric analysis aimed to summarize the knowledge structure of gut microbiota in IR. Methods: Articles and reviews related to gut microbiota in IR from 2013 to 2022 were retrieved from the Web of Science Core Collection (WoSCC), and the bibliometric analysis and visualization were performed by Microsoft Excel, Origin, R package (bibliometrix), Citespace, and VOSviewer. Results: A total of 4 749 publications from WoSCC were retrieved, including 3 050 articles and 1 699 reviews. The majority of publications were from China and USA. The University Copenhagen and Shanghai Jiao Tong University were the most active institutions. The journal of Nutrients published the most papers, while Nature was the top 1 co-cited journal, and the major area of these publications was molecular, biology, and immunology. Nieuwdorp M published the highest number of papers, and Cani PD had the highest co-citations. Keyword analysis showed that the most frequently occurring keywords were "gut microbiota", "insulin-resistance", "obesity", and "inflammation". Trend topics and thematic maps showed that serum metabolome and natural products, such as resveratrol, flavonoids were the research hotspots in this field. Conclusion: This bibliometric analysis summarised the hotspots, frontiers, pathogenesis, and treatment strategies, providing a clear and comprehensive profile of gut microbiota in IR. [ABSTRACT FROM AUTHOR]

Copyright of Salud Uninorte is the property of Fundacion Universidad del Norte and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

A biotope map provides ecological and spatial information that reflects the natural and ecological features and values of a city. In South Korea, efforts have been made to create a map that includes grades based on evaluating the ecological value of a specific surface space. However, plans for applications have not been established, except for development restrictions or regulations for biotopes with high ecological value ratings. The aim of this study was to promote environmentally friendly and sustainable urban management through ecological land use management for all biotope types that are influenced by anthropogenic land use. Strategies for maintenance, protection, recovery, improvement, creation, and reduction based on ecological restoration principles were set as management goals. To achieve these management goals, evaluation items and indicators were suggested for minor-classification types and applied to Dongducheon City. Management strategies were suggested for target sites based on grades and thematic maps of biotope types to be utilized, such as urban ecological axes, river naturality restoration, and wetland and forest preservation. These findings support sustainable and environmentally friendly urban development by providing fundamental data for ecological and environmental management, including the preservation and restoration of natural environments and the creation of urban ecological networks. [ABSTRACT FROM AUTHOR]

Coastal areas are fundamental enclaves for economic and recreational development, attracting a large population worldwide. However, these factors have generated significant pressure on the coastal landscape, requiring territorial management strategies to protect and control its degradation. The coastal landscape, composed of abiotic and biotic elements, plays a crucial role in human wellbeing and the conservation of the natural environment. This study focuses on the southeast area of the Ría de Arosa, on the western coast of Galicia, known for its unique geomorphological features such as estuaries. The main objective is to generate high-resolution thematic maps for territorial planning and conservation of the natural and cultural landscape. Using methodologies based on geographic information systems, various factors of the natural environment will be analyzed to obtain objective results, presenting cartography of landscape units, along with quality and fragility landscape maps. In addition, active strategies are proposed such as multiple land uses or the development of geotourism to preserve, exploit, and manage the landscape better. This work contributes to better understanding the vulnerability of the coastal landscape and provides practical tools for its sustainable management in a context of accelerated global change. [ABSTRACT FROM AUTHOR]

This study employs bibliometric analysis to investigate the landscape of Environmental, Social, and Governance (ESG) factors and their relationship with performance. Drawing from a dataset of 634 papers retrieved from the Web of Science (WoS) database and analysed using Biblioshiny, the research explores academic interest trends, temporal dynamics, and citation impacts. Results indicate a surge in scholarly attention since 2010, peaking notably in 2022, reflecting the growing importance of ESG research. Prominent institutions such as Stanford and Bocconi emerge as collaborative hubs, with China leading in scientific production. Key themes include financial performance, governance, risk, responsibility, and management, reflecting comprehensive explorations of sustainable business practices and effective corporate governance. Thematic maps highlight essential elements in ESG and performance studies, with clusters like "impact" emphasizing critical factors such as "governance" and "financial performance." Future research directions could explore the integration of emerging technologies into ESG reporting procedures or sectorspecific discrepancies in ESG effects on performance. The study acknowledges limitations inherent in bibliometric analysis and underscores the importance of triangulating findings with additional data sources for a comprehensive understanding of the scholarly landscape. [ABSTRACT FROM AUTHOR]