Search Results (1,020)

Agricultural production in southern Angola faces challenges due to unsustainable practices, including inefficient use of water, fertilizers, and machinery, resulting in low yields and environmental degradation. Therefore, clear and measurable indicators are needed to guide farmers toward more sustainable practices. The scientific literature insufficiently addresses this issue, leaving a significant gap in the evaluation of key performance indicators (KPIs) that can guide good agricultural practices (GAPs) adapted to the context of southern Angola, with the goal of promoting a more resilient and sustainable agricultural sector. So, the objective of this study is to identify and assess KPIs capable of supporting the selection of GAPs suitable for maize, potato, and tomato cultivation in the context of southern Angolan agriculture. A systematic literature review (SLR) was conducted, screening 2720 articles and selecting 14 studies that met defined inclusion criteria. Five KPIs were identified as the most relevant: gross margin, net profit, water use efficiency, nitrogen use efficiency, and machine energy. These indicators were analyzed and standardized to evaluate their contribution to sustainability across different GAPs. Results show that organic fertilizers are the most sustainable option for maize, drip irrigation for potatoes, and crop rotation for tomatoes in southern Angola because of their efficiency in low-resource environments. A clear, simple, and effective representation of the KPIs was developed to be useful in communicating to farmers and policy makers on the selection of the best GAPs in the cultivation of different crops. The study proposes a validated KPI-based methodology for assessing sustainable agricultural practices in developing regions such as southern Angola, aiming to lead to greater self-sufficiency and economic stability in this sector. Full article

The strategic allocation of advertising billboards has become a critical aspect of urban planning and resource management. While previous studies have explored site selection based on road network and population data, they have often overlooked the diminishing marginal returns of overlapping coverage and neglected to efficiently process large-scale urban datasets. To address these challenges, this study proposes two complementary optimization methods: an enhanced greedy algorithm based on geometric modeling and spatial acceleration techniques, and a reinforcement learning approach using Proximal Policy Optimization (PPO). The enhanced greedy algorithm incorporates population-weighted road coverage modeling, employs a geometric series to capture diminishing returns from overlapping coverage, and integrates spatial indexing and parallel computing to significantly improve scalability and solution quality in large urban networks. Meanwhile, the PPO-based method models billboard site selection as a sequential decision-making process in a dynamic environment, where agents adaptively learn optimal deployment strategies through reward signals, balancing coverage gains and redundancy penalties and effectively handling complex multi-step optimization tasks. Experiments conducted on Wuhan’s road network demonstrate that both methods effectively optimize population-weighted billboard coverage under budget constraints while enhancing spatial distribution balance. Quantitatively, the enhanced greedy algorithm improves coverage effectiveness by 18.6% compared to the baseline, while the PPO-based method further improves it by 4.3% with enhanced spatial equity. The proposed framework provides a robust and scalable decision-support tool for urban advertising infrastructure planning and resource allocation. Full article

Purpose: To present the findings of our preliminary experience using daily image-guided radiotherapy (IGRT) supported by implanted fiducial markers (FMs) in the radiotherapy of the vaginal cuff, in a cohort of post-surgery endometrial cancer patients. Methods: Patients with vaginal cuff cancer requiring adjuvant radiation with external beams were enrolled. Five patients underwent radiation therapy targeting the pelvic disease and positive lymph nodes, with doses of 50.4 Gy in twenty-eight fractions and a subsequent stereotactic boost on the vaginal vault at a dose of 5 Gy in a single fraction. One patient was administered 30 Gy in five fractions to the vaginal vault. These patients underwent external beam RT following the implantation of three 0.40 × 10 mm gold fiducial markers (FMs). Our IGRT strategy involved real-time 2D kV image-based monitoring of the fiducial markers during the treatment delivery as a surrogate of the vaginal cuff. To explore the potential role of FMs throughout the treatment process, we analyzed cine movies of the 2D kV-triggered images during delivery, as well as the image registration between pre- and post-treatment CBCT scans and the planning CT (pCT). Each CBCT used to trigger fraction delivery was segmented to define the rectum, bladder, and vaginal cuff. We calculated a standard metric to assess the similarity among the images (Dice index). Results: All the patients completed radiotherapy and experienced good tolerance without any reported acute or long-term toxicity. We did not observe any loss of FMs during or before treatment. A total of twenty CBCTs were analyzed across ten fractions. The observed trend showed a relatively emptier bladder compared to the simulation phase, with the bladder filling during the delivery. This resulted in a final median Dice similarity coefficient (DSC) of 0.90, indicating strong performance. The rectum reproducibility revealed greater variability, negatively affecting the quality of the delivery. Only in two patients, FMs showed intrafractional shift > 5 mm, probably associated with considerable rectal volume changes. Target coverage was preserved due to a safe CTV-to-PTV margin (10 mm). Conclusions: In our preliminary study, CBCT in combination with the use of fiducial markers to guide the delivery proved to be a feasible method for IGRT both before and during the treatment of post-operative gynecological cancer. In particular, this approach seems to be promising in selected patients to facilitate the use of SBRT instead of BRT (brachytherapy), thanks to margin reduction and adaptive strategies to optimize dose delivery while minimizing toxicity. A larger sample of patients is needed to confirm our results. Full article

Unmanned Aerial Vehicles (UAVs) face significant challenges in global path planning within complex terrains, as traditional algorithms (e.g., A*, PSO, APF) struggle to balance computational efficiency, path optimality, and safety. This study proposes a Voronoi–A* fusion algorithm, combining Voronoi-vertex-based rapid trajectory generation with A* supplementary expansion for enhanced performance. First, an adaptive DEM layering strategy divides the terrain into horizontal planes based on obstacle density, reducing computational complexity while preserving 3D flexibility. The Voronoi vertices within each layer serve as a sparse waypoint network, with greedy heuristic prioritizing vertices that ensure safety margins, directional coherence, and goal proximity. For unresolved segments, A* performs localized searches to ensure complete connectivity. Finally, a line-segment interpolation search further optimizes the path to minimize both length and turning maneuvers. Simulations in mountainous environments demonstrate superior performance over traditional methods in terms of path planning success rates, path optimality, and computation. Our framework excels in real-time scenarios, such as disaster rescue and logistics, although it assumes static environments and trades slight path elongation for robustness. Future research should integrate dynamic obstacle avoidance and weather impact analysis to enhance adaptability in real-world conditions. Full article

Over the past two decades, rising concerns about teacher stress and professional sustainability have fueled the development of instruments assessing teacher resilience. This review aims to map the existing resilience assessment tools specifically designed for educators, evaluating their theoretical frameworks, psychometric soundness, and contextual relevance. Twelve instruments were analyzed through an extensive literature review of peer-reviewed studies published over the past twenty years, including general, preservice, EFL, and teacher-specific scales for special education. Findings reveal a progression from early instruments emphasizing intrapersonal traits to current tools incorporating ecological and contextual dimensions. While several scales demonstrate satisfactory reliability and cross-cultural applicability, many still suffer from conceptual limitations, insufficient cultural adaptation, or marginal psychometric robustness. This review concludes that despite significant advances, future research must prioritize culturally grounded frameworks, broader subgroup validation, and advanced psychometric methodologies to ensure accurate, inclusive, and practical assessments of teacher resilience across diverse educational settings. Full article

As an integral component of humanity’s cultural heritage, traditional villages universally confront challenges such as population loss and cultural discontinuity amid rapid urbanization. Cluster-based protection models have increasingly become the international consensus for addressing the survival crisis of such settlements. This study selects the Central Yunnan region of Southwest China—characterized by its complex geography and multi-ethnic habitation—as the research area. Employing ArcGIS spatial analysis techniques alongside clustering algorithms, we examine the spatial distribution characteristics and clustering patterns of 251 traditional villages within this region. The findings are as follows. In terms of spatial distribution, traditional villages in Central Yunnan are unevenly dispersed, predominantly aggregating on mid-elevation gentle slopes; their locations are chiefly influenced by rivers and historical courier routes, albeit with only indirect dependence on waterways. Regarding single-cluster attributes, the spatial and geomorphological features exhibit a composite “band-and-group” pattern shaped by river valleys; culturally, two dominant modes emerge—“ancient-route-dependent” and “ethnic-symbiosis”—reflecting an economy-driven cultural mechanism alongside latent marginalization risks. Concerning construction characteristics, the “Qionglong-Ganlan” and Han-style “One-seal” residential features stand out, illustrating both adaptation to mountainous environments and the cumulative effects of historical culture. Based on these insights, we propose a three-tiered clustering classification framework—“comprehensive-element coordination”, “feature-led”, and “potential-cultivation”—to inform the development of contiguous and typological protection strategies for traditional villages in highland, multi-ethnic regions. Full article

To address the wear life prediction challenge of Guide Cones in passive compliant connectors under dynamic loads within specialized equipment, this study proposes a dynamic wear modeling and life assessment method based on the improved Archard model. Through integrated theoretical modeling, finite element simulation, and experimental validation, we establish a bidirectional coupling framework analyzing dynamic contact mechanics and wear evolution. By developing phased contact state identification criteria and geometric constraints, a transient load calculation model is established, revealing dynamic load characteristics with peak contact forces reaching 206.34 N. A dynamic contact stress integration algorithm is proposed by combining Archard’s theory with ABAQUS finite element simulation and ALE adaptive meshing technology, enabling real-time iterative updates of wear morphology and contact stress. This approach constructs an exponential model correlating cumulative wear depth with docking cycles (R² = 0.997). Prototype experiments demonstrate a mean absolute percentage error (MAPE) of 14.6% between simulated and measured wear depths, confirming model validity. With a critical wear threshold of 0.8 mm, the predicted service life reaches 45,270 cycles, meeting 50-year operational requirements (safety margin: 50.9%). This research provides theoretical frameworks and engineering guidelines for wear-resistant design, material selection, and life evaluation in high-reliability automatic docking systems. Full article

Understanding the activity patterns of a species is essential for developing sound conservation and management plans. In this study, we used a camera-trapping technique to determine the activity patterns of bharal (Pseudois nayaur) in a marginal population in Wolong National Nature Reserve, Sichuan, China. Our results showed that these animals preferred to be active in the daytime from 08:00 to 20:00, with an activity peak between 10:00 and 14:00. In addition, we found that the species had a seasonal activity pattern with higher activity frequency in summer than in winter and that bharal were most active in a temperature range of 3–11 °C and at night with a waxing crescent moon, implying that the activity rhythm of the species is an adaptation to a subtropical high-altitude alpine area with vertical zonation in temperature. The pattern of movement and activity was also correlated with the moon phase. Full article

Reliable adaptation in Class II resin-based composite (RBC) restorations with margins on cementum remains challenging. This study compared the internal adaptation (IA) and closed porosity (CP) of three restorative strategies for such cavities, using either total-etch or self-etch adhesive approaches. Standardized box-only cavities were prepared on both proximal surfaces of 30 extracted molars, applying self-etch on mesial and total-etch on distal cavities. Group 1 used a layered microhybrid RBC; Group 2 used a flowable RBC base beneath a layered microhybrid RBC; and Group 3 used a thermoviscous RBC in a 4 mm bulk increment. Micro-computed tomography was employed to assess IA and CP. ANOVA, Tukey post hoc, and univariate analyses were used to evaluate group differences and the effects of adhesive/restorative strategies. Group 2 demonstrated the best adaptation (0.10%), whereas Group 3 exhibited the highest internal gap ratio (0.63%) and the lowest CP (p = 0.006). Total-etch adhesive significantly improved IA compared to self-etch (p < 0.001). These findings emphasize the impact of material selection and adhesive technique on the quality of restorations in cementum-located Class II cavities. Full article

With the acceleration of modernization, villages in Southwest China are experiencing spatial fragmentation and homogenization, leading to the loss of traditional identity. Addressing how to balance scientific planning with cultural and spatial continuity has become a key challenge in rural governance. This study takes Xuyong County in Luzhou City as a case and develops a three-tier analytical framework—“genome–spatial factors–specific indicators”—based on the space gene theory to identify, classify, and map spatial patterns in marginal villages of southern Sichuan. Through cluster analysis, common and distinctive spatial genes are extracted. Common genes—such as medium surface roughness (GeneN-2-b), medium building dispersion (GeneA-3-b), and low intelligibility (GeneT-2-b)—are prevalent across multiple village types, reflecting shared adaptive strategies to complex terrains, ecological constraints, and historical development. In contrast, distinctive genes—such as high building dispersion (GeneA-3-a) and linear boundaries (GeneB-1-c)—highlight unique spatial responses that are shaped by local cultural and environmental conditions. The results contribute to a deeper understanding of spatial morphology and adaptive mechanisms in rural settlements. This research offers a theoretical and methodological basis for village classification, conservation zoning, and spatial optimization, providing practical guidance for rural revitalization efforts focusing on both development and heritage protection. Full article

Background: Proximal gastrectomy (PG) with double tract reconstruction (DTR) offers organ preservation for early gastric cancers, leading to reduced vitamin B12 deficiency, less weight loss, and improved quality of life. The JCOG1401 study confirmed excellent long-term outcomes for PG in stage I gastric cancer. However, in locally advanced proximal gastric cancer (LAPGC), preserving the gastric body and lymph node station 4d may compromise margin clearance and adequate lymphadenectomy. Methods: We propose a modified PG that removes the distal esophagus, gastroesophageal junction (GEJ), cardia, fundus, and gastric body, preserving only the antrum and performing DTR. Lymphadenectomy is also adapted, removing stations 1, 2, 3a, 4sa, 4sb, 4d, 7, 8, 9, 10 (spleen preserving), 11, and lower mediastinal nodes (stations 19, 20, and 110), while preserving stations 3b, 5, and 6. Indications for this procedure include GEJ (Siewert type II and III) and proximal gastric cancers with ≤2 cm distal esophageal involvement and ≤5 cm gastric involvement. Results: In our initial experience with 14 patients, we achieved R0 resection in all patients, adequate lymph node harvest (median 24 nodes, IQR 18–38), and no locoregional recurrences at a median follow-up of 18 months. We also found favorable postoperative weight loss, reflux, and anemia in the PG cohort. Conclusion: While larger studies and long-term data are still needed, our early results suggest that modified PG—despite sparing only the antrum—retains the key benefits of PG over total gastrectomy, including better weight maintenance and improved hemoglobin levels, while maintaining oncologic outcomes for LAPGC. Full article

Federated learning (FL) enables multiple participants to collaboratively train models while efficiently mitigating the issue of data silos. However, large-scale heterogeneous data distributions result in inconsistent client objectives and catastrophic forgetting, leading to model bias and slow convergence. To address the challenges under non-independent and identically distributed (non-IID) data, we propose DPAO-PFL, a Dynamic Parameter-Aware Optimization framework that leverages continual learning principles to improve Personalized Federated Learning under non-IID conditions. We decomposed the parameters into two components: local personalized parameters tailored to client characteristics, and global shared parameters that capture the accumulated marginal effects of parameter updates over historical rounds. Specifically, we leverage the Fisher information matrix to estimate parameter importance online, integrate the path sensitivity scores within a time-series sliding window to construct a dynamic regularization term, and adaptively adjust the constraint strength to mitigate the conflict overall tasks. We evaluate the effectiveness of DPAO-PFL through extensive experiments on several benchmarks under IID and non-IID data distributions. Comprehensive experimental results indicate that DPAO-PFL outperforms baselines with improvements from $5.41\%$ to $30.42\%$ in average classification accuracy. By decoupling model parameters and incorporating an adaptive regularization mechanism, DPAO-PFL effectively balances generalization and personalization. Furthermore, DPAO-PFL exhibits superior performance in convergence and collaborative optimization compared to state-of-the-art FL methods. Full article

The ongoing decline in global biodiversity constitutes a critical challenge for environmental science, necessitating the prompt development of effective monitoring frameworks and conservation protocols to safeguard the structure and function of natural ecosystems. Recent progress in ecoacoustic monitoring, supported by advances in artificial intelligence, might finally offer scalable tools for systematic biodiversity assessment. In this study, we evaluate the performance of BirdNET, a state-of-the-art deep learning model for avian sound recognition, in the context of selected bird species characteristic of the Italian Alpine region. To this end, we assemble a comprehensive, manually annotated audio dataset targeting key regional species, and we investigate a variety of strategies for model adaptation, including fine-tuning with data augmentation techniques to enhance recognition under challenging recording conditions. As a baseline, we also develop and evaluate a simple Convolutional Neural Network (CNN) trained exclusively on our domain-specific dataset. Our findings indicate that BirdNET performance can be greatly improved by fine-tuning the pre-trained network with data collected within the specific regional soundscape, outperforming both the original BirdNET and the baseline CNN by a significant margin. These findings underscore the importance of environmental adaptation and data variability for the development of automated ecoacoustic monitoring devices while highlighting the potential of deep learning methods in supporting conservation efforts and informing soundscape management in protected areas. Full article

In Italy, beech and Turkey oak are among the most widespread tree species, thriving across various climatic zones. However, rising temperatures and prolonged droughts significantly affect their physiological performance and growth dynamics. To assess their long-term responses to climate change, mature beech and Turkey oak trees were studied in Central Italy at an elevation of 450 m. Using dendrochronological and stable isotope analyses (1981–2020), their growth patterns and physiological adaptations were evaluated. Beech exhibited a higher growth rate, with a basal area increment (BAI) of 17.1 ± 1.1 cm² year⁻¹, compared to Turkey oak, showing a BAI of 12.7 ± 0.96 cm² year⁻¹. Both species actively responded to increasing atmospheric CO₂ levels. Additionally, spring and the previous summer’s climatic conditions played a key role in growth, while summer temperature and precipitation influenced carbon discrimination. For beech, correlations between BAI and iWUE (intrinsic water efficiency, defined as the ratio between photosynthesis and stomatal conductance) were initially weak and not statistically significant. However, the correlation became significant, strengthening steadily into the early 2000s, likely related to thinning of the beech trees. For Turkey oak, the correlation was already significant and strong from the beginning of the analysis period (1981), persisting until the late 1990s. Our findings suggest that both species actively adjust their iWUE in response to an increasing atmospheric CO₂ concentration. However, while Turkey oak’s iWUE and BAI relationship remains unaffected by the likely thinning, beech benefits from reduced competition for light, nutrients, and water. Despite climate change’s impact on marginal populations, microclimatic conditions allow beech to outperform Turkey oak, a species typically better suited to drier climates. Full article

This study developed an Energy Quadrilemma Index (EQI) for Latin American countries, analyzing data from six countries from 2014 to 2020. Using the Principal Component Analysis method, this work reduced the dimensionality of 20 indicators grouped into four dimensions: energy security, energy equity, sustainable development, and a new social context axis. The results reveal significant disparities among the countries in the study. For example, Uruguay shows robust indicators, Paraguay exhibits low utilization of the energy it produces, and Chile displays the poorest results in the sustainable development axis. Many countries’ widespread dependence on hydroelectricity makes them vulnerable to water crises. The results show that social, economic, and structural inequalities represent the main barriers to the energy transition, often marginalizing low-income populations. Ensuring a fair and inclusive transition requires implementing targeted policies and solutions adapted to each country’s specific context. Although Costa Rica leads in performance, it faces significant challenges in the field of sustainability. In contrast, Honduras has made some progress with sustainable development but still demonstrates weaknesses in other areas. These results highlight that standardized solutions can exacerbate regional inequalities, demanding approaches more tailored to local needs. This work’s novelty lies in the use of the social context dimension as a feature to assess energy poverty in selected countries. Full article