Search Results (178)

Background and Objectives: The masseteric nerve (Mn) is increasingly used for facial reanimation because of its reliable location, high axon count, low donor morbidity, and favorable clinical outcomes. Precise topographic knowledge of the Mn relative to reproducible intraoperative landmarks is essential for safe dissection. This study investigated the intramuscular position of the Mn relative to two defined reference lines. Materials and Methods: Seventy-two hemicrania from 36 individuals (aged 54–99 years) embalmed postmortem using the Thiel method were examined. Measurements were referenced to two defined anatomical lines: the angle–canthus line (ACL), extending from the mandibular angle to the lateral canthus of the eye, and the articular eminence line (AEL), extending from the articular eminence to the base of the zygomatic temporal process. Results: The Mn crossed the ACL at an average distance of 39.9 ± 5.9 mm from the mandibular angle with up to four branches. The first intramuscular branch arose 15.6 ± 4.7 mm superior to the ACL. The Mn was located 4.9 ± 1.9 mm anterior to the articular eminence and 4.7 ± 1.5 mm inferior to the AEL, coursing at an average angle of 68.5 ± 11.6° to the AEL. The AEL and ACL provide reliable and clearly defined reference lines for locating the Mn and improve intraoperative reproducibility. The Mn followed a predictable oblique course and was consistently identified in the masseter muscle (Mm) beneath an intramuscular aponeurosis. Nerve diameter varied by site, underscoring the need for standardized measurement locations. Distal localization along the ACL may enable preservation of early intramuscular branches and reduce donor morbidity. Further studies should evaluate axon counts at defined points and clarify the relationship of the Mn to the masseteric artery for better intramuscular orientation during dissection. Conclusions: The Mn can be located within a 63 mm² area beneath the AEL at the masseter entry and more distally on the ACL. ACL-based access may protect the first intramuscular branch of the Mn and the temporal branch of the facial nerve (TBFN), and it represents a potential alternative for smile reconstruction for patients with preserved eye closure. Full article

Background/Objectives: Alzheimer’s disease (AD) requires accessible and non-invasive biomarkers that can support early detection, especially in settings lacking specialized expertise. Sonification techniques may offer an alternative way to convey neurophysiological information through auditory perception. This study aimed to evaluate whether human listeners without EEG training can discriminate between sonified electroencephalographic (EEG) patterns from patients with AD and healthy controls. Methods: EEG recordings from 65 subjects (36 with Alzheimer’s, 29 controls) from the Open-Neuro ds004504 dataset were used. Data were processed through sliding-window spectral analysis, extracting relative band powers across five frequency bands (delta: 1–4 Hz, theta: 4–8 Hz, alpha: 8–13 Hz, beta: 13–30 Hz, gamma: 30–45 Hz) and spectral entropy, aggregated across 10 topographic regions. Extracted features were sonified via parameter mapping to independent synthesis sources per frequency band, implemented in an interactive web interface (Tone.js v14.8.49) enabling auditory evaluation. Eight evaluators without EEG experience blindly classified subjects into two groups based solely on listening to the sonifications. Results: Listeners achieved a mean classification accuracy of 76.12% (SD = 17.95%; range: 49.25–97.01%), exceeding chance performance (p = 0.001, permutation test). Accuracy variability across evaluators suggests that certain auditory cues derived from the sonified features were consistently perceived. Conclusions: Parametric EEG sonification preserves discriminative neurophysiological information that can be perceived through auditory evaluation, enabling above-chance differentiation between Alzheimer’s patients and healthy controls without technical expertise. This proof-of-concept study supports sonification as a complementary, accessible method for examining brain patterns in neurodegenerative diseases and highlight its potential contribution to the development of accessible diagnostic tools. Full article

Wildfires increasingly threaten the operation and stability of regional socio-economic systems, where infrastructure, population, and environmental conditions are tightly interconnected. To enhance operational efficiency and strengthen community resilience, this study develops an integrated optimization framework for wildfire evacuation system design based on mixed-integer programming. The model simultaneously determines the locations of primary and secondary shelters and establishes both main and backup evacuation linkages, forming a dual-stage structure that ensures continuous accessibility even under disrupted conditions such as road blockages or fire spread. Wildfire risk indices derived from topographic and environmental data are incorporated to support risk-aware and balanced shelter allocation. A case study of Uiryeong County, South Korea, demonstrates that the proposed framework effectively improves evacuation efficiency and system reliability, producing spatially coherent and adaptive evacuation plans under diverse disruption scenarios. The findings highlight how operation optimization can enhance socio-economic system resilience and sustainability when facing large-scale environmental disruptions. Full article

Accurately modelling surface solar radiation (SSR) is essential for environmental research but remains a significant challenge in topographically complex regions like Lake Baikal, where ground measurements are sparse. This study evaluates the performance of various open-access cloud cover products—from satellite sensors (AVHRR, MODIS) and ground-based observations—for modelling daily SSR totals, using a physical radiation model validated against in-situ measurements from 10 coastal stations. The results demonstrate that the choice of cloud data critically impacts model accuracy. The AVHRR satellite product yields the most reliable estimates (R² = 0.54, RMSE = 4.538 MJ/m²), significantly outperforming both ground-based cloudiness observations and the ERA5 reanalysis dataset. This finding underscores that spatially continuous satellite data provide a superior representation of cloud attenuation for regional modelling than point-based ground observations or reanalysis. Consequently, a physical model driven by high-quality satellite cloud masks is recommended as an effective methodology for generating reliable SSR fields. Full article

The topic of archaeological apothekes, i.e., storage areas not intended for display and not accessible to the public (depositi in Italian), has only recently received the attention it deserves, for reasons related to the history of research methodology. The archiving of archaeological material poses specific problems compared to other categories of material with which the process is generally associated, such as artistic artefacts. Excavation finds consist mainly (and increasingly) of a mass of anonymous, repetitive pottery fragments, not destined to be accessible to the public. The management of these storage facilities poses two sets of problems linked with its archiving: on one hand, its (digital) documentation; on the other hand, its physical arrangement. Both aspects have often been contemplated, but as separate entities by different specialists (archaeologists, conservators, etc.). An adequate approach requires however both aspects to be considered together, for archaeological material only achieves its full value when its context of origin is secure. Only proper management of digital and physical archives can ensure a full understanding of the historical significance of archaeological material. These challenges also apply to the Archaeological Mission of Phaistos, in Crete, where Italian have been active since 1900. The reorganisation of the warehouses in 2024–2025 provided an opportunity to adequately address both the digital archiving of the material and the layout of the warehouses, tackling at the same time the particularly pressing issue in this case of the reuse of ‘legacy data’, which poses problems of standardization. This led also to a new perspective, using old labels and boxes as metadata to reconstruct the methods of archaeological research. The main results however were the creation of a holistic approach to the management of archaeological material and its (written, graphic, photographic, and topographic) documentation through the adoption and implementation of PyArchInit (version 4.9.5), a plug-in of QGIS (version 3.40.7 Bratislava). Full article

Tidal flats play a vital role in coastal ecosystems by supporting biodiversity, mitigating natural hazards, and functioning as blue carbon reservoirs. However, monitoring their geomorphological changes remains challenging due to high turbidity, shallow depths, and tidal variability. Conventional approaches—such as satellite remote sensing, acoustic sounding, and topographic LiDAR—face limitations in resolution, accessibility, or coverage of submerged areas. Airborne bathymetric LiDAR (ABL), which uses green laser pulses to detect reflections from both the water surface and seabed, has emerged as a promising alternative. Unlike traditional discrete-return data, full waveform analysis offers greater accuracy, resolution, and reliability, enabling more flexible point cloud generation and extraction of additional signal parameters. A critical step in ABL processing is waveform decomposition, which separates complex returns into individual components. Conventional methods typically assume fixed models with three returns (water surface, water column, bottom), which perform adequately in clear waters but deteriorate under shallow and turbid conditions. To address these limitations, we propose an adaptive progressive Gaussian decomposition (APGD) tailored to tidal flat environments. APGD introduces adaptive signal range selection and termination criteria to suppress noise, better accommodate asymmetric echoes, and incorporates a water-layer classification module. Validation with datasets from Korea’s west coast tidal flats acquired by the Seahawk ABL system demonstrates that APGD outperforms both the vendor software and the conventional PGD, yielding higher reliability in bottom detection and improved bathymetric completeness. At the two test sites with different turbidity conditions, APGD achieved seabed coverage ratios of 66.7–70.4% and bottom-classification accuracies of 97.3% and 96.7%. Depth accuracy assessments further confirmed that APGD reduced mean depth errors compared with PGD, effectively minimizing systematic bias in bathymetric estimation. These results demonstrate APGD as a practical and effective tool for enhancing tidal flat monitoring and management. Full article

A UAV LiDAR dataset offers unparalleled possibilities for accurate topographic modeling and land suitability analysis in spatial planning. This study uses UAV LiDAR for high-resolution DSM and DTM modeling of the Goranci area in Bosnia and Herzegovina—a typical karst region with a complex topographic pattern of sinkholes and varying solar access. Based on the dataset obtained with a UAV LiDAR system, this analysis encompasses a multidimensional spatial analysis that considers a set of topographic–morphometric, hydrological, and solar radiation criteria. A set of topographic derivatives, namely, slope layers; topographic position index layers (TPI); layers of terrain ruggedness index (TRI); layers of topographic wetness index (TWI), sky view factors (SVF), and layers of potential incoming solar radiation (PISR), was obtained for the DTM/DSM datasets and normalized for standard scales. The obtained criteria layers were then assigned specific values based on their relative importance using a multi-criteria decision analysis technique with a weighted linear combination procedure. A suitability index pinpointing gently sloping lands with adequate solar access and avoidance of moisture accumulation sinks can be recognized as the best-qualifying loci for habitation. The results show that about 30% of the area is highly or very highly suitable, primarily representing gently sloping, well-drained, and optimally solar-exposed plateau surfaces, potential locations with high ground elevation, and larger area sizes. Another 14% is moderately suited, and more than 50% is classified as unsuitable or excluded, primarily due to steep slopes, depressions, and/or missing coverage by LiDAR points, thereby underlining the decisive role of slope, solar conditions, and drainage conditions in determining land suitability for settlements. This study has proved that a UAV LiDAR dataset can be successfully paired with Open-Source GIS for a methodologically sound location of settlement zones that fit into the local environment while being environmentally friendly. This solution promotes informed spatial decision-making by utilizing topographic accuracy of a 3D landscape with a procedure of quantitative spatial reasoning for a more informed spatial planning. Full article

Viticulture in insular and volcanic environments faces mounting pressures from land abandonment, limited mechanization, and climate-related stress on soil and water resources. This study develops an integrated framework combining Life Cycle Assessment (LCA) and soil diagnostics to evaluate the environmental and agronomic performance of vineyards on the island of Tenerife (Canary Islands, Spain). Fifteen representative vineyards located between 100 and 1000 m a.s.l. within the Tacoronte–Acentejo Denomination of Origin were assessed using the ReCiPe 2016 Midpoint (H) method and the Ecoinvent 3.8 database. The average carbon footprint reached 1.40 kg CO₂-eq kg⁻¹ of grapes, with diesel use for field access and transport contributing over 50% of total impacts and 64% of human toxicity. Copper-based fungicides accounted for ~11% of impacts, underscoring their environmental persistence. Soil analyses revealed widespread Ca/Mg imbalances and sporadic K deficiencies, while organic matter and pH levels were generally adequate. Importantly, vineyards with balanced nutrient ratios exhibited both higher yields and lower environmental burdens, suggesting that improved soil health can enhance eco-efficiency, primarily by supporting higher yields under similar input regimes. Targeted strategies—such as magnesium supplementation, reduced copper inputs, and low-carbon mobility practices—can therefore mitigate emissions while improving productivity. The proposed LCA–soil integration provides a replicable model for sustainable resource management and climate-resilient viticulture in other fragile and topographically constrained agricultural systems. Full article

This research addresses the complex challenge of integrating modern public transport into historic medieval city centers. These unique urban environments are characterized by narrow streets, protected heritage status, and topographical constraints, which are incompatible with conventional transit vehicles. The introduction of standard bus routes often aggravates traffic congestion and fails to meet the specific mobility needs of residents and visitors. This paper suggests that autonomous electric buses represent a viable and sustainable solution, capable of navigating these constrained environments while aligning with modern energy efficiency goals. The central challenge lies in the optimal selection of an autonomous electric bus that can operate safely and efficiently within the tight streets of historic city centers while satisfying the travel demands of passengers. To address this, a comprehensive study was conducted, analyzing resident mobility patterns—including key routes and hourly passenger loads—and the specific geometric constraints of the road network. Based on this empirical data, a vehicle dynamics model was developed in Matlab^®. This model simulates various operational scenarios by calculating the instantaneous forces (rolling resistance, aerodynamic drag, inertial forces) and the corresponding power required for different electric bus configurations to follow pre-established speed profiles. The core of this research is an optimization analysis, designed to identify the balance between minimizing total energy consumption and maximizing the quality of passenger service. The findings provide a quantitative framework and clear procedures for urban planners to select the most suitable autonomous transit system, ensuring that the chosen solution enhances mobility and accessibility without compromising the unique character of historic cities. Full article

As a multi-ethnic border region of China, Xinjiang hosts revolutionary cultural tourism resources (RCTRs) that embody historical memory and the spirit of frontier reclamation, while also playing a strategic role in strengthening national identity and maintaining regional stability. Yet, their spatial distribution is highly uneven due to geographical, historical, and socio-economic constraints. This study analyzes 135 representative sites using a dual framework of spatial pattern analysis and driving mechanism quantification. Nearest neighbor index, imbalance index, Lorenz curve, geographic concentration index, kernel density estimation, and hotspot analysis results reveal a clustered “multi-core–peripheral attenuation” pattern with pronounced regional disparities. GIS-based overlay analysis identifies natural thresholds of moderate elevation (834–2865 m) and gentle slopes (0–8.65°), while socio-economic factors such as transportation corridors and population density amplify clustering effects. Geographic Detector results confirm road network density (q = 0.85, p < 0.01) and historical site density (q = 0.79, p < 0.01) as dominant drivers, with interactions between natural and social factors enhancing explanatory power above 0.90. These findings highlight the coupled influence of topographic suitability and socio-economic accessibility. Policy recommendations include optimizing road network layouts, adopting tiered heritage protection, and fostering cross-regional cooperation. The study provides scientific evidence for balanced development and sustainable conservation of RCTRs, contributing to the achievement of sustainable development goals (SDGs) related to cultural heritage, regional equity, and inclusive growth. Full article

Mountain settlements represent culturally rich but environmentally fragile landscapes, shaped by enduring processes of ecological adaptation and human resilience. In western Sichuan, Jiarong Tibetan villages, with their distinctive integration of defensive stone towers and settlements, embody this coupling of culture and the environment. We hypothesize that settlement cores in these villages were shaped by natural environmental factors, with subsequent expansion reinforced by the cultural significance of towers. To test this, we applied a micro-scale spatial–environmental framework to four sample villages in Suopo Township, Danba County. High-resolution World Imagery (Esri, 0.5–1 m, 2022–2023) was classified via a Random Forest algorithm to generate detailed land-use maps, and a 100 × 100 m fishnet grid extracted topographic metrics (elevation, slope, aspect) and accessibility measures (distances to streams, roads, towers). Geographically weighted regression (GWR) was then used to examine how slope, elevation, aspect, proximity to water and roads, and tower distribution affect settlement patterns. The results show built-up density peaks on southeast-facing slopes of 15–30°, at altitudes of 2600–2800 m, and within 50–500 m of streams, co-locating with historic watchtower sites. Based on these findings, we propose four zoning strategies—a Core Protected Zone, a Construction And Development Zone, an Ecological Conservation Zone, and an Industry Development Zone—to balance preservation with growth. The resulting policy recommendations offer actionable guidance for sustaining traditional settlements in complex mountain environments. Full article

Rapid urbanization across Southern Asia’s coastal regions has significantly increased electricity demand, driving India’s solar sector expansion under the National Solar Mission and positioning the country as the world’s fourth-largest solar market. Nonetheless, methodological limitations remain in applying GIS-based multi-criteria decision analysis (MCDA) frameworks to coastal urban microclimates, which involve intricate land-use dynamics and resilience constraints. To address this gap, this study proposes a multi-criteria GIS- based Analytical Hierarchy Process (AHP) framework, incorporating remote sensing and geospatial data, to assess Solar Farm Sites (SFSs) suitability, supplemented by sensitivity analysis in Thoothukudi coastal city, India. Ten parameters—covering photovoltaic, climatic, topographic, environmental, and accessibility factors—were used, with Global Horizontal Irradiance (18%), temperature (11%), and slope (11%) identified as key drivers. Results show that 9.99% (13.61 km²) of the area has excellent suitability, mainly in the southwest, while 28.15% (38.33 km²) exhibits very high potential along the southeast coast. Additional classifications include good (22.29%), moderate (32.41%), and low (7.16%) suitability zones. Sensitivity analysis confirmed photovoltaic variables as dominant, with GHI (0.25) and diffuse radiation (0.23) showing the highest impact. The largest excellent zone could support approximately 390 MW, with excellent and very high zones combined offering up to 2080 MW capacity. The findings also underscore opportunities for dual-use solar deployment, particularly on salt pans (17.1%), as well as elevated solar installations in flood-prone areas. Overall, the proposed framework provides robust, spatially explicit insights to support sustainable energy planning and climate-resilient infrastructure development in coastal urban settings. Full article

Understanding visitors’ outdoor activities in urban public spaces and their relationship with the physical environment is essential for improving the precision of public space design. This study, set in the context of Yangzhou, China, focuses on physical activity and other wellbeing behaviors in meso-scale waterfront public spaces, aiming to explore the characteristics of visitor behavior. A professional behavioral observation protocol was employed, combined with object detection and multi-object tracking algorithms, to systematically code visitor activities in the waterfront area. Subsequently, agent-based modeling (ABM) and three-dimensional isovist analysis (3D isovist) were introduced to construct a quantitative framework for assessing visual accessibility. The results reveal a significant positive correlation between facade Visual Exposure Time (seen from the observer) and isovist field area (seen from the object), providing strong evidence that visual accessibility is a primary causal driver of pedestrian behavior—independent of other causality. Based on these findings, this study proposes actionable design guidelines: “Prioritize small-scale, high-density waterfront building facade layouts to maximize visual efficiency” and “Leverage topographical variation along the waterfront by introducing cross-river visual corridors at intervals of ≤45 m”. The integrated analytical toolkit developed in this study—combining behavioral simulation with spatial–visual analysis—provides not only a theoretical foundation but also clear practical guidance for the fine-grained renewal and design of waterfront public spaces. Full article

This study utilizes UAV-based LiDAR to analyze doline microtopography within a karst mountainous terrain. The study area, ‘Gulneomjae’ in Mungyeong City, South Korea, features steep slopes, limited accessibility, and abundant vegetation—conditions that traditionally hinder accurate topographic surveying. UAV LiDAR data were acquired using the DJI Matrice 300 RTK equipped with a Zenmuse L2 sensor, enabling high-density point cloud generation (98 points/m²). The point clouds were processed to remove non-ground points and generate a 0.25 m resolution DEM using TIN interpolation. A total of seven dolines were detected and delineated, and their morphometric characteristics—including area, perimeter, major and minor axes, and elevation—were analyzed. These results were compared with a 1:5000-scale DEM derived from the 2013 National Basic Map. Visual and numerical comparisons highlighted significant improvements in spatial resolution and feature delineation using UAV LiDAR. Although the 1:5000-scale DEM enables general doline detection, UAV LiDAR facilitates more precise boundary extraction and morphometric analysis. The study demonstrates the effectiveness of UAV LiDAR for detailed topographic mapping in complex karst terrains and offers a foundation for future automated classification and temporal change analysis. Full article

This study, conducted within the SteamBioAfrica project, assessed the potential of Digital Soil Mapping (DSM) to estimate Soil Organic Carbon (SOC) across key regions of southern Africa: Otjozondjupa and Omusati (Namibia), Chobe (Botswana), and KwaZulu-Natal (South Africa). Random Forest (RF) models were implemented in the Google Earth Engine (GEE) environment, integrating multi-source datasets including real-time Sentinel-2 imagery, topographic variables, climatic data, and regional soil samples. Three model configurations were evaluated: (A) climatic, topographic, and spectral data; (B) topographic and spectral data; and (C) spectral data only. Model A achieved the highest overall accuracy (R² up to 0.78), particularly in Otjozondjupa, whereas Model B resulted in the lowest RMSE and MAE. Model C exhibited poorer performance, underscoring the importance of multi-source data integration. SOC variability was primarily influenced by elevation, precipitation, temperature, and Sentinel-2 bands B11 and B8. However, data scarcity and inconsistent sampling, especially in Chobe, reduced model reliability (R²: 0.62). The originality of this study lay in the scalable integration of real-time Sentinel-2 data with regional datasets in an open-access framework. The resulting SOC maps provided actionable insights for land-use planning and climate adaptation in savanna ecosystems. Full article