Search Results (131)

Urban heat island effects increasingly challenge pedestrian mobility by intensifying thermal stress and reducing the attractiveness of walking during hot periods. However, most pedestrian routing systems still prioritize distance or travel time, while environmental conditions such as heat exposure and shade are rarely incorporated into operational route generation. Existing comfort-aware approaches often rely on static maps, simulated microclimatic indicators, or descriptive greenery measures, limiting their direct integration into user-configurable pedestrian navigation. This study develops a thermal comfort-aware pedestrian routing framework that integrates heterogenic data sources including observed land surface temperature, pedestrian-perspective tree-canopy coverage, and network distance into a unified multi-criteria pathfinding model. The workflow proceeds in four steps: first, airborne thermal imagery is processed to derive a high-resolution land surface temperature layer; second, Google Street View images are sampled at street-segment locations and segmented using SegFormer to extract visible tree-canopy coverage; third, both environmental indicators are aggregated to a cleaned pedestrian network; and fourth, normalized distance, temperature, and canopy attributes are combined through a user-adjustable edge-cost formulation and solved using Dijkstra’s algorithm. The framework is implemented as an operational web-based routing tool for the historic center of Clermont-Ferrand, France. The routable graph includes 551 nodes and 796 edges, with 600 segments carrying GSV-derived canopy information and 623 segments carrying airborne-derived LST values. Across the network, we observed LST ranges from 19.5 °C to 39.1 °C, while canopy coverage ranged from 0 to 70.6%. For a representative origin–destination pair, the coolest route reduces average LST by nearly 5 °C and almost triples canopy coverage compared with the shortest path, although at the cost of a 72% longer distance. These results demonstrate that the framework can generate interpretable comfort–efficiency trade-offs and support user-comfort pathfinding as an operational approach for heat-resilient pedestrian navigation. Full article

Sustainable forest management depends on reliable compartment-level growing stock volume (GSV) estimates, which inform the prescribed cut. At the University Forest of Pertouli (Greece), four management-plan inventories (1989–2028) span a methodological transition from full-callipering in 1988 and 1997 to a systematic-sample-plot inventory with empirical compartment-level upscaling in 2008 and 2018. We distinguish methodological discontinuity (a change in method) from methodological inconsistency (variation in empirical sample-plot weighting between sample-based inventories) and develop a four-hypothesis diagnostic framework. Hypothesis 1 tests temporal change via a linear mixed model on 149 compartments. Hypotheses 2–4 use non-parametric bootstrap on 231 common sample plots under three nested resampling schemes, which bound a documented plot-center relocation. The 2008 compartment-level estimator underestimated the sample-plot benchmark by 19% (deviation $B_{2008}$ = +54.9 m³ ha⁻¹, 95% confidence interval (CI) +39.6 to +70.8); in 2018 the two converged ($B_{2018}$ = −2.2 m³ ha⁻¹). The implied decadal changes differ by difference-in-differences DID = +57.0 m³ ha⁻¹ (robust across three schemes), with ~96% attributable to baseline-year underestimation; the 2008 underestimation was confirmed in all nine orographic units. The framework provides a retrospective consistency assessment for inventory time series crossing methodological transitions. The 19% deviation documented here is invisible without it; its identification restores estimation reliability to compartment-level estimates. Full article

Background: Although chronic venous insufficiency is often treated as a localized problem, it is a systemic condition that can negatively affect cardiac hemodynamics. This study investigates the associated effects of eliminating the pathologic venous reservoir on right ventricular (RV) functions, systolic pulmonary artery pressure (sPAP), and inferior vena cava (IVC) diameter in patients undergoing endovenous radiofrequency ablation (RFA) for severe great saphenous vein (GSV) insufficiency. Methods: This retrospective observational study included 154 patients who presented between September 2023 and May 2025 with GSV insufficiency (CEAP C3-C4b) and underwent endovenous RFA. Patients with major cardiopulmonary diseases were strictly excluded. Preoperative and 6-month postoperative transthoracic echocardiography records were analyzed to evaluate RV diastolic diameter, tricuspid annular plane systolic excursion (TAPSE), sPAP, the TAPSE/sPAP ratio, and IVC diameter. Results: At 6 months post-RFA, compared to preoperative values, a significant decrease was detected in the mean sPAP (14.7 ± 2.5 vs. 11.8 ± 1.8 mmHg, p < 0.001) and IVC diameter (2.1 ± 0.2 vs. 1.9 ± 0.2 cm, p < 0.001). Furthermore, significant improvements were observed in TAPSE (20.0 ± 2.0 vs. 21.5 ± 1.8 mm, p < 0.001) and the TAPSE/sPAP ratio (1.36 ± 0.15 vs. 1.82 ± 0.18 mm/mmHg, p < 0.001). Conclusions: Endovenous RFA is associated with favorable changes in right heart parameters. Eliminating pathologic extremity blood pooling may optimize venous return kinetics and subclinically improve right ventricular–pulmonary arterial coupling. Full article

Background: Preoperative ultrasonographic mapping of the great saphenous vein (GSV) is a valuable tool for improving assessment of vein caliber during surgical planning. However, current data are insufficient to establish clear standards for optimal anatomical evaluation. The aim of this study was to investigate the effect of anesthetic induction on GSV caliber in patients undergoing CABG. Methods: In this retrospective study, the diameter of the GSV was measured using ultrasonography at predefined anatomical landmarks during the pre- and post-induction periods in patients undergoing CABG, and the obtained values were compared. Results: A total of 59 patients were included. A significant increase in the GSV diameter was observed after anesthetic induction in all segments (all p < 0.001). The median diameters increased from 1.9 to 2.7 mm in the distal segment, from 1.6 to 2.4 mm in the mid segment, and from 2.3 to 3.4 mm in the proximal segment. The percentage change in diameter after anesthetic induction was comparable across all measured segments (p = 0.888). The pre-induction diameter was strongly and negatively correlated with the percentage diameter change in all segments (all p < 0.001), and this association remained significant after controlling for the post-induction diameter (all p < 0.001). Conclusions: In this study, the ultrasonographic assessment timing was found to significantly influence GSV caliber evaluation in patients undergoing CABG. Anesthetic induction was associated with a significant and consistent increase in saphenous vein diameter across all measured segments, suggesting that anesthetic status may influence ultrasound-based vein mapping and conduit assessment. Further prospective studies incorporating clinical outcome measures and conduit suitability assessment are needed to better clarify the clinical implications of these findings. Full article

Background: Anterior saphenous vein (ASV) incompetence represents the third most common form of truncal varicose veins, and evidence for endovenous laser ablation (EVLA) in this setting remains limited. Methods: We evaluated outcomes of EVLA in cases with dominant ASV insufficiency. All EVLA procedures performed by a single surgeon between April 2019 and December 2023 for primary ASV reflux (ASV-R) were compared with a cohort containing all EVLA treatments for great saphenous vein (GSV) insufficiency without ASV reflux from April to December 2019 (GSV-R). We used a 1470-nm diode laser with radially emitting fibers for the interventions. Results: We included 378 patients (mean age 49.5 years): 208 and 256 treated limbs in the ASV-R and GSV-R cohorts, respectively. Female patients were more frequent in the ASV-R cohort than in the GSV-R cohort (80.5% vs. 62.9%, p < 0.001). ASV-R cases exhibited concomitant GSV insufficiency in 54.3% of cases. Redo procedures due to initial treatment failure were more frequent in ASV-R (1.9% vs. 0%, p = 0.04). Over a mean follow-up period of 332 days, 16 recurrences occurred in the ASV-R cohort compared with 4 in the GSV-R cohort, corresponding to a significantly increased hazard of recurrence in ASV-R (HR 8.41, 95% CI 2.78–25.4). Rates of subsequent foam sclerotherapy (16.8% vs. 10.5%) and minor complications (5.3% vs. 4.3%) did not differ significantly between ASV-R and GSV-R, respectively. ASV-R cases without concomitant GSV reflux demonstrated a higher need for secondary sclerotherapy, compared to ASV-R cases with additional GSV insufficiency. Conclusions: Our findings suggest that EVLA for ASV insufficiency is technically more challenging and yields inferior outcomes than EVLA for GSV incompetence. These considerations should be taken into account during preoperative planning and patient counseling. Further prospective and comparative analyses are needed to better define the effectiveness of thermal ablation strategies in ASV insufficiency and to support patient-centered, individualized treatment decisions. Full article

Background: Vascular leiomyosarcoma (LMS) is an exceptionally rare and aggressive soft tissue sarcoma arising from the smooth muscle cells of the vascular wall. They account for approximately 0.5–2% of adult soft-tissue sarcomas and are the most frequent primary malignancy of vascular origin. Among venous sites, the inferior vena cava (IVC) is the most frequently involved, accounting for more than half of reported vascular LMS cases, with rarer occurrences in peripheral veins, including the internal saphenous vein and the external iliac vein. Case Presentation: We report a case series comprising two distinct presentations of vascular LMS involving the internal saphenous vein and the inferior vena cava, respectively. Each case highlights unique clinical manifestations, radiologic features, histopathologic diagnosis, and therapeutic challenges inherent to the involved vascular territory. Surgical resection with clear margins was the primary treatment modality, complemented by adjuvant therapies tailored according to tumor grade and extent. Literature Review: An updated literature review contextualizes these findings, detailing epidemiology, diagnostic challenges, prognostic factors, and current management approaches. It emphasizes the rarity of leiomyosarcomas originating from major venous pathways and highlights variability in clinical presentation, tumor size, growth patterns, and outcomes. Achieving complete surgical removal with negative margins continues to be the primary treatment goal and the most significant prognostic factor. Conclusions: Given the paucity of cases, our series contributes valuable insights into the clinical spectrum and multidisciplinary approach necessary for optimal outcomes in vascular LMS. Early recognition and aggressive treatment remain paramount to improving survival in this rare malignancy. Full article

National forest inventory (NFI) data are often collected over a 5-year or 10-year period, meaning some are already outdated by the time the complete results are available. This study assesses changes in growing stock volume (GSV, m³/ha) using hybrid estimation supported by Sentinel-2 metrics. It focuses on constructing a model for estimating the change in GSV using NFI plot data and bitemporal remotely sensed auxiliary data, where such data are available for both points in time ($t_1\mathrm{a}\mathrm{n}\mathrm{d}{t}_2$), and unitemporal data for which remotely sensed auxiliary data are available only for $t_2$. A machine-learning approach based on the random forests (RFs) algorithm was used to predict plot-level GSV change. The original data for $t_2$ and $t_3$ were first used to evaluate the accuracy of the change prediction at the plot level, after which the predicted changes were applied to update the plot-level GSV to predict plot-level GSV at $t_3$, which was then assessed against the observed plot-level GSV at $t_3$. Predicted change was assessed with the Mean Average Annual Volume Change (MAAVC) method, representing the average annual change in GSV over a given period. The results indicate that at the plot level, the bitemporal model produced GSV change estimates with low accuracy (R² = 0.26, RMSE = 4.06 m³/ha, and MAE = 3.26 m³/ha), while the unitemporal model achieved R² = 0.40, RMSE = 3.64 m³/ha, and MAE = 2.65 m³/ha when predicting the $t_1-t_2$ GSV change. Using the predicted change to predict plot-level GSV at $t_3$, the MAAVC based on field data yielded R² = 0.91 and RMSE = 45.11 m³/ha, while the RS unitemporal yielded R² = 0.73 and RMSE = 83.79 m³/ha, and the bitemporal yielded R² = 0.72 and RMSE = 83.61 m³/ha. Mean population GSV at $t_3$, estimated from the RF models, was 254.61 and 255.19 m³/ha for the unitemporal and bitemporal models, respectively. Monte Carlo simulations with a novel stopping criterion were then used to estimate total standard errors, which were 10.48 and 10.40 m³/ha for the unitemporal and bitemporal models, respectively, incorporating both model prediction uncertainty and sampling variability. A test of significance revealed a significant effect of the proposed method on the estimated mean population GSV at $t_3$ (p < 0.001). Conclusively, MAAVC and spatiotemporal RS methods provide a robust framework for predicting GSV at $t_3$ using Estonian NFI and Sentinel-2 data. Full article

UAV laser scanning (UAV-LS) combines extensive scanning coverage with high point cloud density, enabling efficient and precise acquisition of key forest attributes. Based on field-measured data and UAV-LS data from 138 Chinese fir (Cunninghamia lanceolata) plantation plots in southern China, this study systematically developed growing stock volume (GSV) estimation models at both tree and stand levels. The models included base models (allometric models), linear models, dummy variable models incorporating age groups, and nonlinear mixed-effects models incorporating random effects (plot and area levels for the tree level, and only the area level for the stand level). The results showed the following: (1) Stand-level GSV prediction relied primarily on height metrics, achieving optimal performance through a combination of the 10th cumulative height percentile (AIH₁₀) and canopy cover (CC), both of which showed near-linear relationships with GSV; tree-level GSV was predicted by LiDAR-derived tree height (LH) and crown width (LCW), with LH explaining most variation. (2) Tree-level models achieved R² = 0.639–0.725 and RMSE = 0.050–0.058 m³, exhibiting larger individual prediction errors (mean percentage standard error, MPSE > 30%) with smaller aggregate prediction errors (mean prediction error, MPE < 1%); stand-level models reached R² = 0.785–0.879 and RMSE = 46.052–61.314 m³ ha⁻¹ while maintaining controlled errors across scales (MPE < 5%, MPSE < 20%). (3) At both the tree and stand levels, the nonlinear mixed-effects model outperformed the others, followed by the dummy variable model and the base model, with the linear model exhibiting the worst performance; area-level random effects primarily influenced the baseline value of tree-level GSV and the allometric relationship between stand-level GSV and AIH₁₀, whereas plot-level random effects affected the allometric relationships of tree-level GSV with LH and LCW. This study confirms the effectiveness of UAV-LS for large-scale forest resource monitoring, while underscoring the necessity of incorporating spatial heterogeneity in GSV estimation. Full article

A methodological framework is provided for characterizing large-scale forest resource distribution in South Korea, along with a baseline for sustainable forest management practices. This study aimed to establish a baseline framework that integrates satellite and ground-based data for nationwide growing stock volume (GSV) estimation. Several machine learning models were applied and compared for estimating GSV across South Korea using Sentinel-2 imagery, national forest inventory data, and topographic information. Four algorithms, namely, k-nearest neighbors (kNN), random forest (RF), extreme gradient boosting (XGBoost), and categorical boosting (CatBoost), were evaluated. The ensemble methods outperformed kNN, with RF demonstrating the highest accuracy (coefficient of determination and root mean squared error of 0.56 and 66.9 m³/ha, respectively). Accuracy assessment shows that kNN performed relatively well near the mean GSV (≒200 m³/ha), but its accuracy decreased sharply toward the extremes, failing to represent plots above 400 m³/ha. Estimation accuracy also varied substantially with stand height, which was identified as the primary predictor, and kNN was the most affected. These findings suggest that the structural complexity and mountainous terrain of South Korean forests may amplify the limitations of distance-based methods, reinforcing the need for improved 3D structural predictors such as satellite-derived stand height. Full article

Background/Objectives: There are very few publications on unplanned excisions of great saphenous vein leiomyosarcomas (GSV-LMS), and their impact on the prognosis of the disease is not well known. The objective of this study is to present a series of nine new leiomyosarcomas of the great saphena vein (LMS-GSV) cases, with the aim of increasing diagnostic awareness and proposing guidelines for therapeutic management. Methods: This is a prospective single-centre study of a series of nine GSV-LMS in thigh (stage IIIA AJCC), knee and proximal leg (IB, 1 II and 3 IIIA), and ankle (2 IIIB and 1 II). Eight patients were female, and the mean age was 72 years. All patients were surgically treated. Five (56%) were unplanned excisions. All these patients were reoperated on to attempt wide resection margins. In a patient, an infra-patellar amputation was performed. Another amputation was refused by another patient. Eight patients received adjuvant radiotherapy. Results: One patient died 8 years after amputation for a reason other than LMS. The patient who refused amputation has been alive, disease-free, for 28 months. The mean follow-up of surviving patients was 39 months (6–78 months). In these patients, there were no local recurrences or metastases. The mean functional outcome according to the MSTS score was 28.9 (range: 24–30). Conclusions: Unplanned excision of GSV-LMS can be prevented through clinical and imaging suspicion. Surgery and re-excision in case of inadequate previous margins and adjuvant radiotherapy lead to a good oncological and functional outcome. Full article

Introduction: The introduction of radial-firing laser fibers has minimized catheter-to-vein distance during endovenous laser ablation (EVLA) for the great saphenous vein (GSV) and anterior saphenous veins (ASVs). This study investigates flush endovenous laser ablation (fEVLA) effectiveness in addressing chronic superficial venous insufficiency (CVI). Materials and methods: This single-center retrospective study analyzed consecutive fEVLA cases with duplex ultrasound follow-up at 1, 4, and 12 weeks. The primary endpoint was clinically significant endovenous heat-induced thrombosis (classes III–IV). Results: Three hundred and twelve patients were recruited (405 affected limbs, 369 GSV, and 36 ASV). CEAP classifications were stratified as follows: C2 in 6.1%, C3 in 34.2%, C4 in 44%, C5 in 2.7%, and C6 in 12.7% of cases. Perforator ligation, phlebectomy, or foam sclerotherapy were carried out in conjunction with EVLA. fEVLA was feasible in all cases. The success rate was 96.78%, defined as EHIT classes 1 and 2, and assessed by ultrasound one week postoperatively. Clinically significant EHIT (2.5% class 3 and 0.2% class 4) was managed with 15 mg rivaroxaban twice daily for 21 days. Follow-up at 4 weeks revealed complete resolution of all EHIT 3–4 cases. No cases of pulmonary embolism or deep vein thrombosis were observed during the study or follow-up period. Conclusions: fEVLA is a safe treatment for superficial CVI across various CEAP classes, and with prompt detection, the minimal complication rate can be completely resolved. Full article

In Thailand, companies are facing increasing pressure from investors, consumers, customers, and regulators to integrate sustainability into business policies and practices. Achieving corporate sustainable development requires incorporating environmental attitudes and work environments into employee behaviors. This study examines how perceived sustainability policies (PSP) influence pro-environmental behaviors (PEB) in the workplace. A total of 589 respondents from four Thai companies in diverse sectors—rubber, consumer products, B2B industrials, and garments—participated in the study. Grounded in the Focus Theory of Normative Conduct, the research extends individual-level psychological frameworks by incorporating the mediating roles of organizational-level descriptive norms—green shared vision (GSV) and green work climate (GWC)—and the moderating role of individual green value (IGV). Structural equation modeling was conducted using AMOS. The findings supported both a direct effect of PSP on PEB and a sequential mediation pathway through GSV and GWC, while the individual mediation roles of GSV and GWC were not significant. These results reflected strong institutional and in-group collectivist culture of Thailand. Moreover, IGV was found to have a significantly negative moderating effect, suggesting that employees with high IGV may rely less on formal perceived sustainability policies in shaping their pro-environmental behaviors. Full article

Insulin-regulated glucose uptake is a central mechanism in maintaining systemic glucose homeostasis, primarily occurring in skeletal muscle and adipose tissue. This process relies on the insulin-stimulated translocation of the glucose transporter, GLUT4, from specialized intracellular compartments, known as GLUT4 storage vesicles (GSVs), to the plasma membrane. Disruption of this pathway is a hallmark of insulin resistance and a key contributor to the pathogenesis of type 2 diabetes. Recent advances have provided critical insights into both the insulin signalling cascades and the complex biogenesis, as well as the trafficking and fusion dynamics of GSVs. This review synthesizes the current understanding of the molecular mechanisms governing GSV mobilization and membrane fusion, highlighting key regulatory nodes that may become dysfunctional in metabolic disease. By elucidating these pathways, we propose new therapeutic avenues targeting GSV trafficking to improve insulin sensitivity and combat type 2 diabetes. Full article

This study investigates how university students adopt large language models (LLMs) for online consumption of sustainable products, integrating perceived value theory with the technology acceptance model (TAM). Cross-sectional survey data were analyzed using structural equation modeling (SEM) and artificial neural networks (ANNs). SEM results reveal partial mediation. Performance expectancy value (PEV) and information quality value (IQV) directly shape continue using intention (CUI). They also influence CUI indirectly through perceived ease of use (PEU) and perceived usefulness (PU). Green self-identity value (GSV) influences CUI both directly and via PEU, while trust transfer value (TTV) and green perceived value (GPV) affect CUI only via PEU. ANN findings confirm this hierarchy, as PU (86.7%) and PEU (85.7%) are the strongest predictors of CUI, followed by GSV (73.7%). Convergent evidence from both methods indicates that instrumental utility, effortless interaction, and sustainability identity congruence drive sustained LLM use in the context of online consumption of green products, whereas credibility cues and sustainability incentives play secondary roles. This study extends TAM by incorporating multidimensional value constructs and offers design recommendations for engaging and high-utility AI shopping platforms. Full article

This study aims to (1) analyze thermal comfort at outdoor sport events held outside of fixed venues or locations; (2) establish a method for evaluating environmental thermal comfort for large-scale, long-term outdoor activities; and (3) provide suggestions for the arrangement of shifts in routes and participants for heat warning and mitigation. Taiwan ReAnalysis Downscaling (TReAD) data, Sky View Factors (SVFs), GSV2SVF tool, and RayMan Pro were applied to analyze and evaluate thermal comfort at the 2021 Torch Relay Round the Island, Taiwan. In this study, modified Physiologically Equivalent Temperature (mPET), Wet Bulb Globe Temperature (WBGT), and Universal Thermal Climate Index (UTCI) were estimated and selected as thermal indicators for the purpose of obtaining a more comprehensive perspective. We also define and present thermal performance with a simple traffic light symbol (green: comfortable/yellow: warm/red: hot) and try to go beyond the concept of heat and visualize it in an easy-to-understand way. Full article