Search Results (664)

Vehicular ad hoc networks (VANETs) are a critical aspect of intelligent transportation systems, improving safety and comfort for drivers. These networks enhance the driving experience by offering timely information vital for safety and comfort. Yet, VANETs come with their own set of challenges concerning security, privacy, and design reliability. Traditionally, vehicle authentication occurs every time a vehicle enters the domain of the roadside unit (RSU). In our study, we suggest that authentication should take place only when a vehicle has not covered a set distance, increasing system efficiency. The rise of the Internet of Things (IoT) has seen an upsurge in the use of IoT devices across various fields, including smart cities, healthcare, and vehicular IoT. These devices, while gathering environmental data and networking, often face reliability issues without a trusted intermediary. Our study delves deep into implementing Teegraph in VANETs to enhance authentication. Given the integral role of VANETs in Intelligent Transportation Systems and their inherent challenges, we turn to Hashgraph—an alternative to blockchain. Hashgraph offers a decentralized, secure, and trustworthy database. We introduce an efficient authentication system, which triggers only when a vehicle has not traversed a set distance, optimizing system efficiency. Moreover, we shed light on the indispensable role Hashgraph can occupy in the rapidly expanding IoT landscape. Lastly, we present Teegraph, a novel Hashgraph-based technology, as a superior alternative to blockchain, ensuring a streamlined, scalable authentication solution. Our approach leverages the logical key hierarchy (LKH) and packet update keys to ensure data privacy and integrity in vehicular networks. Full article

Urban green infrastructure plays a vital role in the sustainable development of cities. As urban areas expand, green spaces are increasingly affected. The pressure from new developments leads to a reduction in vegetation and raises new public health risks. Addressing this challenge requires effective planning, maintenance, and continuous monitoring. To enhance traditional approaches, remote sensing is becoming a vital tool for city-wide observations. Publicly available large-scale data, combined with machine learning models, can improve our understanding. We explore the potential of Sentinel-2 to classify and extract meaningful features from urban landscapes. Using advanced machine learning techniques, we aim to develop a robust and scalable framework for classifying urban environments. The proposed models will assist in monitoring changes in green spaces across diverse urban settings, enabling timely and informed decisions to foster sustainable urban growth. Full article

The study of historical monuments within both architectural and literary frameworks reveals a dynamic interplay between scientific observation and artistic interpretation—a vital characteristic of travel writing/the travelogue. This approach, exemplified by British traveler and writer Henry Finnis Blosse Lynch (1862–1913), reflects how factual detail and creative representation are seamlessly integrated in depictions of sites, landscapes, and cultural scenes. This case study highlights Lynch as a pioneering explorer who authored the first comprehensive volume on Armenian architecture and as a writer who vividly portrayed Armenian monuments through both verbal description and photographic imagery, becoming the first traveler to document such sites using photography. Additionally, this paper emphasizes the significance of Lynch’s detailed accounts of architectural monuments, churches, monasteries, cities, villages, populations, religious communities, and educational institutions in vivid language. The careful study of his work can contribute meaningfully to the investigation of the travelogue as a literary genre and to the preservation and protection of the architectural heritage of historical and contemporary Armenia, particularly in regions facing cultural or political threats. Full article

Contactless vital sign monitoring has emerged as a transformative healthcare technology, enabling the assessment of vital signs without physical contact with the human body. This review comprehensively reviews the rapidly evolving landscape of this field, with particular emphasis on multi-modal sensing approaches and multi-task learning paradigms. We systematically categorize and analyze existing technologies based on sensing modalities (vision-based, radar-based, thermal imaging, and ambient sensing), integration strategies, and application domains. The paper examines how artificial intelligence has revolutionized this domain, transitioning from early single-modality, single-parameter approaches to sophisticated systems that combine complementary sensing technologies and simultaneously extract multiple vital sign parameters. We discuss the theoretical foundations and practical implementations of multi-modal fusion, analyzing signal-level, feature-level, decision-level, and deep learning approaches to sensor integration. Similarly, we explore multi-task learning frameworks that leverage the inherent relationships between vital sign parameters to enhance measurement accuracy and efficiency. The review also critically addresses persisting technical challenges, clinical limitations, and ethical considerations, including environmental robustness, cross-subject variability, sensor fusion complexities, and privacy concerns. Finally, we outline promising future directions, from emerging sensing technologies and advanced fusion architectures to novel application domains and privacy-preserving methodologies. This review provides a holistic perspective on contactless vital sign monitoring, serving as a reference for researchers and practitioners in this rapidly advancing field. Full article

The process of urbanization has intensified the urban heat environment, with the degradation of thermal conditions closely linked to the morphological characteristics of different functional zones. This study delineated urban functional areas using a multivariate dataset and investigated the seasonal and threshold effects of landscape and architectural features on land surface temperature (LST) through boosted regression tree (BRT) modeling and Spearman correlation analysis. The key findings are as follows: (1) LST exhibits significant seasonal variation, with the strongest urban heat island effect occurring in summer, particularly within industry, business, and public service zones; residence zones experience the greatest temperature fluctuations, with a seasonal difference of 24.71 °C between spring and summer and a peak temperature of 50.18 °C in summer. (2) Fractional vegetation cover (FVC) consistently demonstrates the most pronounced cooling effect across all zones and seasons. Landscape indicators generally dominate the regulation of LST, with their relative contribution exceeding 45% in green land zones. (3) Population density (PD) exerts a significant, seasonally dependent dual effect on LST, where strategic population distribution can effectively mitigate extreme heat events. (4) Mean building height (MBH) plays a vital role in temperature regulation, showing a marked cooling influence particularly in residence and business zones. Both the perimeter-to-area ratio (LSI) and frontal area index (FAI) exhibit distinct seasonal variations in their impacts on LST. (5) This study establishes specific indicator thresholds to optimize thermal comfort across five functional zones; for instance, FVC should exceed 13% in spring and 31.6% in summer in residence zones to enhance comfort, while maintaining MBH above 24 m further aids temperature regulation. These findings offer a scientific foundation for mitigating urban heat waves and advancing sustainable urban development. Full article

The implementation of the trans-European tourist cycle route network “EuroVelo” is fostering new strategic importance for non-motorized mobility and the associated practice of cycling tourism. Indeed, slow tourism offers a pathway for the development of inland areas. The infrastructure supporting it, such as long-distance cycling and walking paths, can act as a vital connection, stimulating regeneration in peripheral territories by enhancing environmental and landscape assets, as well as preserving heritage, local identity, and culture. The regeneration of peri-urban landscapes through soft mobility is recognized as the cornerstone for accessibility to material and immaterial resources (including ecosystem services) for multiple categories of users, including the most vulnerable, especially following the restoration of green-area systems and non-urbanized areas with degraded ecosystems. Considering the forthcoming implementation of the Magna Grecia cycling route, the southernmost segment of the “EuroVelo” network traversing three regions in southern Italy, this contribution briefly examines the necessity of defining new development policies to effectively integrate sustainable slow tourism with the enhancement of environmental and landscape values in the coastal areas along the route. Specifically, this case study focuses on a coastal stretch characterized by significant morphological and environmental features and notable landscapes interwoven with densely built environments. In this area, environmental and landscape values face considerable threats from scattered, irregular, low-density settlements, abandoned sites, and other inappropriate constructions along the coastline. Full article

Habitat fragmentation restricts the movement of large mammals across broad landscapes, leading to isolation of individuals or groups, reduced interaction with other species, and limited access to vital resources in surrounding habitats. In this study, we aimed to determine the wildlife ecological corridors for five large mammals (Ursus arctos, Cervus elaphus, Capreolus capreolus, Sus scrofa, and Canis lupus) between Kastamonu Ilgaz Mountain Wildlife Refuge and Gavurdağı Wildlife Refuge. In the field studies, we used the transect, indirect observation, and camera-trap methods to collect presence data. Maximum Entropy (MaxEnt) (v. 3.4.1) software was used to create habitat suitability models of the target species, which are based on the presence-only data approach. The results indicated that AUC values varied between 0.808 and 0.835, with water sources, stand type, and slope contributing most significantly to model performance. In order to determine wildlife ecological corridors, resistance surface maps were created using the species distribution models (SDMs), and bottleneck areas were determined. The Circuit Theory approach was used to model the connections between ecological corridors. As a result of this study, we developed connectivity models for five large mammals based on Circuit Theory, identified priority wildlife ecological corridors, and evaluated critical connection points between two protected areas, Ilgaz Mountain Wildlife Refuge and Gavurdağı Wildlife Refuge. These findings highlight the essential role of ecological corridors in sustaining landscape-level connectivity and supporting the long-term conservation of wide-ranging species. Full article

The Mediterranean region, identified by scientists as a ‘climate hot spot’, is experiencing warmer and drier conditions, along with an increase in the intensity and frequency of extreme weather events. One such extreme phenomena is droughts. The recent wildfires in this region are a concerning consequence of this phenomenon, causing severe environmental damage and transforming natural landscapes. However, droughts involve a two-way interaction: On the one hand, climate change and various human activities, such as urbanization and deforestation, influence the development and severity of droughts. On the other hand, droughts have a significant impact on various sectors, including ecology, agriculture, and the local economy. This study investigates drought dynamics in four Mediterranean countries, Greece, France, Italy, and Spain, each of which has experienced severe wildfire events in recent years. Using satellite-based Earth observation data, we monitored drought conditions across these regions over a five-year period that includes the dates of major wildfires. To support this analysis, we derived and assessed key indices: the Normalized Difference Vegetation Index (NDVI), Normalized Difference Water Index (NDWI), and Normalized Difference Drought Index (NDDI). High-resolution satellite imagery processed within the Google Earth Engine (GEE) platform enabled the spatial and temporal analysis of these indicators. Our findings reveal that, in all four study areas, peak drought conditions, as reflected in elevated NDDI values, were observed in the months leading up to wildfire outbreaks. This pattern underscores the potential of satellite-derived indices for identifying regional drought patterns and providing early signals of heightened fire risk. The application of GEE offered significant advantages, as it allows efficient handling of long-term and large-scale datasets and facilitates comprehensive spatial analysis. Our methodological framework contributes to a deeper understanding of regional drought variability and its links to extreme events; thus, it could be a valuable tool for supporting the development of adaptive management strategies. Ultimately, such approaches are vital for enhancing resilience, guiding water resource planning, and implementing early warning systems in fire-prone Mediterranean landscapes. Full article

Dark skies, a vital natural and cultural resource, have been increasingly threatened by light pollution due to rapid urbanization, leading to ecological degradation and biodiversity loss. As a key strategy for sustainable regional development, dark sky parks (DSPs) not only preserve nocturnal environments but also enhance livability by balancing urban expansion and ecological conservation. This study develops a novel framework for evaluating DSP suitability, integrating ecological and socio-economic dimensions, including the resource base (e.g., nighttime light levels, meteorological conditions, and air quality) and development conditions (e.g., population density, transportation accessibility, and tourism infrastructure). Using the Guangdong–Hong Kong–Macao Greater Bay Area (GBA) as a case study, we employ Delphi expert consultation, GIS spatial analysis, and multi-criteria decision-making to identify optimal DSP locations and prioritize conservation zones. Our key findings reveal the following: (1) spatial heterogeneity in suitability, with high-potential zones being concentrated in the GBA’s northeastern, central–western, and southern regions; (2) ecosystem advantages of forests, wetlands, and high-elevation areas for minimizing light pollution; (3) coastal and island regions as ideal DSP sites due to the low light interference and high ecotourism potential. By bridging environmental assessments and spatial planning, this study provides a replicable model for DSP site selection, offering policymakers actionable insights to integrate dark sky preservation into sustainable urban–regional development strategies. Our results underscore the importance of DSPs in fostering ecological resilience, nighttime tourism, and regional livability, contributing to the broader discourse on sustainable landscape planning in high-urbanization contexts. Full article

The global population is increasing rapidly and, according to the United Nations (UN), it is expected to reach 9.8 billion by 2050. The demand for food is also increasing with a growing population. Food shortages, land scarcity, resource depletion, and climate change are significant issues raised due to an increasing population. Meat is a vital source of high-quality protein in the human diet, and addressing the sustainability of meat production is essential to ensuring long-term food security. To cover the meat demand of a growing population, meat scientists are working on several meat alternatives. Bacteria, fungi, yeast, and algae have been identified as sources of microbial proteins that are both effective and sustainable, making them suitable for use in the development of meat analogs. Unlike livestock farming, microbial proteins produce less environmental pollution, need less space and water, and contain all the necessary dietary components. This review examines the status and future of microbial proteins in regard to consolidating and stabilizing the global food system. This review explores the production methods, nutritional benefits, environmental impact, regulatory landscape, and consumer perception of microbial protein-based meat analogs. Additionally, this review highlights the importance of microbial proteins by elaborating on the connection between microbial protein-based meat analogs and multiple UN Sustainable Development Goals. Full article

This study investigates the genetic diversity and population structure of Castanopsis tribuloides, a vital tree species in Asian forest ecosystems. Understanding the genetic patterns of keystone forest species provides critical insights into forest resilience and ecosystem function and informs conservation strategies. We analyzed population samples collected from three distinct locations within Doi Suthep Mountain in northern Thailand using Short Tandem Repeat (STR) markers to assess both intra- and inter-population genetic relationships. DNA was extracted from leaf samples and analyzed using a panel of polymorphic microsatellite loci specifically optimized for Castanopsis species. Statistical analyses included the assessment of forensic parameters (number of alleles, observed and expected heterozygosity, gene diversity, polymorphic information content), population differentiation metrics (G_ST), inbreeding coefficients (F_IS), and gene flow estimates (N_m). We further examined population history through bottleneck analysis using three models (IAM, SMM, and TPM) and visualized genetic relationships through principal coordinate analysis and cluster analysis. Our results revealed significant patterns of genetic structuring across the sampled populations, with genetic distance metrics showing statistically significant differentiation between certain population pairs. The PCA and cluster analyses confirmed distinct population groupings that correspond to geographic distribution patterns. These findings provide the first comprehensive assessment of C. tribuloides population genetics in this region, establishing baseline data for monitoring genetic diversity and informing conservation strategies. This research contributes to our understanding of how landscape features and ecological factors shape genetic diversity patterns in essential forest tree species, with implications for managing forest genetic resources in the face of environmental change. Full article

Urban green spaces (UGSs) and forests play a vital role in shaping sustainable and livable cities, offering not only ecological benefits but also spaces that are essential for human well-being, social interactions, and everyday life. Understanding the landscape features that resonate most with public preferences is essential for enhancing the appeal, accessibility, and functionality of these environments. However, traditional approaches—such as surveys or single-data analyses—often lack the nuance needed to capture the complex and multisensory nature of human responses to green spaces. This study explores a cross-modal methodology that integrates natural language processing (NLP) and deep learning techniques to analyze text and image data collected from public reviews of 19 urban parks in Nanjing. By capturing both subjective emotional expressions and objective visual impressions, this study reveals a consistent public preference for natural landscapes, particularly those featuring evergreen trees, shrubs, and floral elements. Text-based data reflect users’ lived experiences and nuanced perceptions, while image data offers insights into visual appeal and spatial composition. By bridging human-centered insights with data-driven analysis, this research provides a robust framework for evaluating landscape preferences. It also underscores the importance of designing green spaces that are not only ecologically sound but also emotionally resonant and socially inclusive. The findings offer valuable guidance for the planning, design, and adaptive management of urban green infrastructure in ways that support healthier, more responsive, and smarter urban environments. Full article

In recent years, advances in organ transplantation medicine have led to an increase in pregnancies and births following transplantation. Pregnancy after organ transplantation is considered high-risk, and its impact on both the recipient and the child must be carefully evaluated. In this review, we summarize the current landscape of pregnancy and childbirth after organ transplantation, with a particular focus on uterus transplantation (UTx). Traditionally, organ transplants have involved vital organs; however, UTx, developed for women with absolute uterine factor infertility, represents a novel approach. Although the number of births following UTx remains limited, it is expected to grow due to the international expansion of this procedure. Importantly, the concept of pregnancy and delivery following UTx is fundamentally different from that of other organ transplants. UTx is a life-enhancing, non-vital, and temporary transplant uniquely intended to enable the creation of new life. Pregnancy after UTx carries specific risks such as a higher incidence of miscarriage, preterm birth, hypertensive disorders of pregnancy, and gestational diabetes. All deliveries are performed via cesarean section, and conception is typically allowed after a relatively short period following transplantation, given the temporary nature of the graft and the goal to minimize recipient burden, with generally good neonatal outcomes. As pregnancies after both solid organ transplantation and UTx continue to rise worldwide, the development of standardized, organ-specific perinatal management strategies, particularly for UTx, is essential. Multidisciplinary collaboration will be critical to supporting these high-risk pregnancies and ensuring the best possible maternal and neonatal outcomes. Full article

Urban parks are an important component of public urban spaces, which directly impact the living experiences of residents and the urban image. High-quality urban parks are crucial for enhancing the well-being of residents. This study selected Fukuoka, Japan, as the study site. Five urban parks were chosen to evaluate landscape visual quality by using the Scenic Beauty Estimation (SBE) method. The Semantic Differential (SD) method was used to get sample subjective landscape features. Meanwhile, sample objective landscape features were obtained by using semantic segmentation techniques in deep learning and combined with spatial analysis to understand their distribution. A regression model was established, which used the SBE values as the dependent variable and subjective landscape features as the independent variables to analyze the relationship between urban park landscape visual quality and subjective landscape features. The regression analysis revealed that sense of layering, harmony, interestingness, sense of order, and vitality were the core factors influencing visual quality. All five features had a significant positive impact on landscape visual quality. The sense of order was the most influential factor, which would be the key to enhancing the landscape perception experience. Moreover, the XGBoost model and SHAP value from machine learning were used to reveal the nonlinear relationships and significant threshold effects between urban park visual quality and five objective landscape features: openness, greenness, enclosure, vegetation diversity, and Shannon–Wiener diversity index. This study showed that when openness exceeded 0.27, the positive effect was significant. The optimal threshold for the greenness was 0.38. Vegetation diversity and enclosure had to be below 0.82 and 0.58, respectively, to have a positive impact. Meanwhile, the positive influence of the Shannon–Wiener diversity index reached its maximum at a value of 1.37. This study not only establishes a systematic method for diagnosing landscape problems and evaluating landscape visual quality but also provides both theoretical support and practical guidance for urban park landscape optimization. Full article

With the growing impact of environmental challenges, the need for well-planned and effectively executed actions to support progress and sustainable social development has become increasingly evident. Geoparks play a vital role in this endeavor by fostering the development of products that celebrate local heritage and promote its conservation, utilizing the natural and cultural resources unique to each region in sustainable ways. Geoproducts, in particular, aim to enrich cultural identity and elevate the value of the landscape and geodiversity by integrating communities into innovative approaches and technologies, engaging them in commercialization, and ensuring sustainability alongside social inclusion. Within the framework of the Safi Geopark Project, this article delves into the concept of geoproducts, their definitions, and their potential to bolster local identity and social and economic development. Leveraging the abundant geological and cultural resources of Safi province, the study presents both tangible and intangible geoproducts that merge traditional craftsmanship with modern sustainability practices. Notable examples include ammonite-inspired ceramics, educational materials, and eco-friendly cosmetics, each carefully designed to reflect and celebrate the region’s geoheritage. This article underscores the crucial role of community involvement in the creation of geoproducts, highlighting their impact on conservation, education, and the promotion of sustainable tourism. By proposing actionable strategies, this study not only broadens the understanding of geoproducts within geoparks but also reinforces their importance as instruments for regional development, heritage conservation, and sustainable economic growth. Full article