Search Results (6,102)

Students who disengage from high school often face academic, social, and relational barriers to re-enrollment and persistence. Alternative high schools designed for dropout recovery frequently seek to address these barriers through smaller school environments, flexible programming, and intensified adult support. This two-year qualitative case study explores how students at an urban alternative charter school describe their experiences of belonging and re-engagement after previously leaving school. Data were drawn from 47 semi-structured interviews with 14 students and 2 graduates (ages 18–21; 10 of 16 male) supplemented by school observations, staff focus groups, and school documents. Using a constant comparison approach to thematic analysis, the study examines how students described differences between their alternative charter high school and their previous schooling experiences, the extent to which they perceived a sense of belonging within the school community, and how they connected these experiences to their engagement and persistence in school. Participants frequently described feeling known, supported, and socially integrated, particularly through relationships with adults, relevant curriculum, vocational programming, and community service opportunities. Students often associated these experiences with increased motivation to attend school, greater academic confidence, and a stronger sense of educational purpose. Findings suggest that belonging-related experiences may play an important role in how students interpret their re-engagement in school, while also highlighting the importance of institutional structures that support relational connection in dropout recovery settings. Full article

Forging is a key manufacturing route for high-performance structural components, but its process design, quality prediction, and adaptive control still rely heavily on empirical rules, offline simulations, and fragmented production data. This review examines intelligent forging from the perspective of mechanism–data–knowledge fusion, with emphasis on forging-specific process chains, real alloy systems, model validation, and industrial maturity. To improve methodological traceability, a structured literature search was conducted using Web of Science Core Collection, Scopus, ScienceDirect, SpringerLink, and Google Scholar, covering studies published from 1996 to 2026. The screened literature was organized around process perception, mechanism-based modeling, data-driven learning, hybrid modeling, knowledge representation, digital twins, online prediction, and adaptive regulation. Representative cases are discussed for closed-die forging, open-die/large forging, multistage forging, radial forging, and forging of aluminum alloys, titanium alloys, steels, and Ni-based superalloys. Particular attention is given to how specific models are validated, including independent experiments, finite-element benchmarks, industrial datasets, new geometries, sensor noise, and cross-material or cross-equipment transfer. The review further distinguishes consolidated technologies, such as FEM-based process simulation and die/preform optimization, from methods still under validation, including hybrid digital twins, sensor-updated models, and adaptive control. Large-model-assisted forging is considered a prospective direction mainly for information retrieval, case recovery, diagnostic support, and engineer-supervised recommendation rather than unsupervised real-time control. This review provides a more process-specific and critically assessed reference for developing explainable, validated, and deployable intelligent forging systems. Full article

Apical pelvic organ prolapse (POP) is characterized by descent of the uterus or post-hysterectomy vaginal vault resulting from failure of level I pelvic support and represents a major contributor to pelvic floor dysfunction and recurrent prolapse surgery. Loss of apical support is frequently associated with anterior and posterior compartment defects, leading to vaginal bulge symptoms, pelvic pressure, urinary and bowel dysfunction, sexual dysfunction, and reduced quality of life. This narrative review summarizes current knowledge on POP, from molecular mechanisms and emerging biomarkers to contemporary surgical management, with particular emphasis on sacrocolpopexy and robotic-assisted approaches. A literature search of PubMed, Scopus, Google Scholar, and Consensus identified peer-reviewed studies published up to February 2026. Evidence demonstrates that POP has a multifactorial and polygenic background involving extracellular matrix remodeling, connective tissue integrity, smooth muscle dysfunction, and altered level of protein expression. Several candidate biomarkers, including single-nucleotide polymorphisms, circulating proteins, metabolites, and imaging-based parameters, show potential for risk prediction and earlier diagnosis, although routine clinical implementation remains limited. Sacrocolpopexy remains the gold standard for apical prolapse repair because of superior anatomical outcomes, low recurrence, and significant quality-of-life improvement. Laparoscopic and robotic-assisted sacrocolpopexy provide comparable efficacy with reduced blood loss, shorter hospitalization, and faster recovery. The objective success rate is usually over 90%. Complications are very rare and typically include mesh erosion in 2–4% of cases and the need for reoperation in 6% of cases. Our own experience shows that, for a group of surgeons, the learning curve for the laparoscopic approach reached a plateau after a total of 30 operations. Robotic platforms may facilitate complex pelvic dissection and shorten the learning curve, although higher procedural costs remain a major limitation. Full article

Dense underwater aquaculture poses significant challenges for intelligent image processing because asymmetric occlusion, turbidity, aeration-like bubbles, and motion blur frequently degrade fish contours and quasi-periodic scale textures. These disturbances often cause conventional detectors to miss detections, merge bounding boxes, experience feature collapse, and exhibit unstable counting. To address this problem, we propose DenseFish-v13, a symmetry-aware NMS-free YOLOv13-Mamba framework for dense underwater fish detection and bio-kinematic behavior recognition. The framework integrates a Bio-Harmonic Frequency Gate to preserve biological texture patterns while suppressing bubble-like frequency noise, a Bi-directional Multi-scale Wavelet Mamba backbone for global occlusion-aware structure recovery, and an asymmetry-aware density repulsion strategy to separate highly overlapping fish instances during bipartite matching. In addition, a lightweight Bio-Kinematic Behavior Head converts continuous detections into interpretable trajectory descriptors for behavior-state recognition. Experiments on the Dense-Aqua benchmark, constructed from public aquaculture datasets, show that DenseFish-v13 achieves 64.8% mAP@50:95 and a Counting MAE of 3.7 on the overall test set, while reaching 64.2% mAP@50:95 and a Counting MAE of 4.1 on the extreme-density split. Under a strong synthetic bubble perturbation, the model shows only a 1.3 percentage-point drop in mAP and maintains 125 FPS on Jetson Orin NX. These results demonstrate its effectiveness in robust, real-time underwater aquaculture monitoring. Full article

Anti-UAV multi-object tracking in remote sensing videos is challenging because UAV targets are small, weakly textured, and often affected by cluttered backgrounds, abrupt motion, occlusion, and intermittent visibility. To address these challenges, we formulate anti-UAV multi-object tracking as a context-aware identity prediction task, in which target identities and locations are inferred from historical trajectory priors instead of current-frame observations alone. Under this formulation, we propose a dual-track parallel tracking framework. The adaptive identity disambiguation (AID) module combines motion cues with appearance features according to their estimated reliability, improving short-term association when visual evidence is weak. In parallel, the motion-evolution temporal memory (METM) module models trajectory dynamics using motion anomaly detection and time-decayed memory, enabling spatiotemporal recovery after occlusion, temporary disappearance, or abrupt motion. The outputs of the two branches are integrated by a unified identity decision layer to produce stable tracking results. Experiments are conducted on the public 4th Anti-UAV Benchmark Track-3 and our newly constructed Anti-UAV Multi-Object Tracking dataset, AU-MOT. On the 4th Anti-UAV Benchmark Track-3, our method achieves 63.6% HOTA and 64.1% IDF1, outperforming the strongest competing method by 3.5% and 3.9%, respectively, while reducing identity switches and track fragments by 20.8% and 23.8%. On AU-MOT, it achieves 67.2% HOTA and 67.8% IDF1, with 20.2% fewer identity switches and 22.3% fewer track fragments. These results demonstrate its effectiveness under long-range observation, weak target appearance, cluttered backgrounds, abrupt motion, and intermittent target visibility. Full article

During hydraulic fracturing, the extensive use of slickwater and post-fracturing shut-in (soaking) processes take advantage of spontaneous imbibition to displace crude oil. While nano-flooding agents are known to reduce interfacial tension (IFT) and alter wettability, a critical challenge lies in distinguishing between deep but inefficient displacement and shallow but highly efficient sweep. This study investigates the pore-scale mobilization and penetration depth of a nano-flooding agent in tight conglomerate reservoirs and focuses on the recovery per unit imbibition depth as a novel metric for evaluating the displacement efficiency. The nano-agent demonstrated excellent performance, reducing oil–water IFT to 0.141 mN/m and reversing wettability from oil-wet (148.7°) to water-wet (39.5°). Experiments revealed that the diffusion rate of the nano-agent decreases with pore size, suggesting a limited transport in confined space. Under reservoir conditions (80 °C), spontaneous imbibition in tight cores was highly permeability-dependent. High-permeability cores achieved a recovery rate of up to 44.6%, whereas low-permeability cores reached only about 12%. This work highlights that penetration depth alone does not necessarily indicate high recovery. The medium-permeability core exhibited a lower final penetration depth than the low-permeability core but achieved a much higher total recovery due to superior efficiency per unit depth, suggesting that in tight reservoirs, a shallow but highly efficient displacement mechanism can outperform a deep but inefficient one. Full article

Cold-region community outdoor spaces are not only everyday activity settings for older adults in winter, but also public-space types that need to be translated into design evidence for architecture and healthy human-settlement research. Existing restorative-environment studies usually treat improved mood, perceived restoration, and environmental appraisal as evidence of health benefits. The key finding of this study is that subjective restoration and physiological recovery are not always synchronized after outdoor exposure in cold-region communities. This discordance reveals a design risk and an innovative value that can be overlooked when restoration is evaluated only through perception-based indicators. Based on a winter field exposure experiment with 345 older adults in a community in Shenyang, China, this study compared staged changes in systolic blood pressure (SBP), diastolic blood pressure (DBP), pulse pressure (PP), POMS, ROS, and ENPQ across an activity plaza, a greenway walkway, and a street corridor. It further developed a psychophysiological concordance classification and a residual cardiovascular risk indicator for the recovery period. The greenway walkway showed the most stable concordant recovery, with 86.84% of women and 79.35% of men showing concordant recovery. The activity plaza showed a clear pattern of emotional recovery: the proportions of women and men whose psychological state improved without a synchronized SBP decrease were 61.58% and 50.32%, respectively. The street corridor had the highest recovery-failure rates, at 92.63% for women and 91.61% for men. Among women, 90.53% reached SBP values of 140 mmHg or higher during the walking phase in the street corridor, and 59.47% remained above this risk threshold during recovery. These results show that health evaluation of cold-region community outdoor spaces should not rely only on subjective restoration indicators, but should also include psychophysiological concordance and residual risk after exposure. The study translates site health effects into three architectural design judgments: concordant-restoration spaces, emotional-restoration spaces, and recovery-failure spaces, providing a testable evidence framework for age-friendly community renewal, path organization, green buffering, and winter wind-protection design. Full article

Ecosystem restoration on Mediterranean islands is often hindered by the residual effects of past land use and invasive species. Decades of holm oak forest exploitation, the establishment of secondary pine plantations, and the introduction of invasive mammals have altered habitat configurations. Consequently, converting these conifer stands to promote the recovery of native Quercus ilex L. communities has become a conservation priority. This study investigates the regeneration constraints of Q. ilex in Mediterranean insular environments, focusing on the inhibitory role of conifer-derived litter and seed predation by invasive rodents and lagomorphs. We integrated an ex situ experiment (384 acorns) testing germination under varying local pine-forest soil and commercial substrate conditions, with an in situ field experiment (300 acorns) across five areas, comparing three treatments: closed cages (exclusion of all mammals), open cages (exclusion of lagomorphs), and unfenced controls. Results indicate that, while ex situ, local pine-forest soil significantly favoured germination over the commercial mixture, predation represents the main obstacle in situ, outweighing any soil-mediated effects. Seedling emergence was substantially reduced by early predation and, to a lesser extent, by litter presence. These findings highlight the necessity of integrated management strategies in insular ecosystems. Full article

Offshore wind farms are increasingly and rapidly expanding due to their ability to harness strong and consistent wind energy resources. Large offshore wind farms are connected to mainland grids through High-Voltage Direct Current (HVDC) technology. However, offshore wind farms can often experience disturbances related to sudden wind changes, voltage drops/dips, faults related to converter switching, and unbalanced grid conditions which affect both the HVDC operation and wind turbine output. As a result, there is a growing need for more advanced and reliable modeling and monitoring tools. Moreover, traditional proportional-integral (PI) controllers are widely applied in wind turbines and HVDC systems due to their simple structure, easy implementation, and reliability. However, PI controllers perform poorly under non-linear and abnormal/fast-changing conditions, especially during sudden drops in wind power and grid faults. With this background, this paper first develops a digital twin model of an offshore wind farm that enables remote operation and monitoring of individual wind turbines. Also, an artificial intelligence (AI)-based controller, namely a fuzzy logic controller (FLC), is proposed to maintain transient stability of a full digital twin-based offshore wind farm connected to the HVDC grid under fault conditions. The effectiveness of the proposed FLC is demonstrated by considering a digital twin-enabled 700 MW offshore wind farm. The performance of the proposed FLC has been compared with that of the PI controller. Simulations performed by the MATLAB/Simulink software show that during the moderate voltage dip at 15 s, the PI controller experienced a 29.8% power reduction with a recovery time of approximately 9 s, whereas the FLC reduced the power drop to 23.1% and recovered within 6 s. During the severe converter disturbance at 15 s, the PI controller recorded a 36.9% power reduction compared to 23.4% for the FLC. Similarly, during the short-duration turbulence at 15 s, the PI controller exhibited a 36.73% power drop and recovered in approximately 7 s, while the FLC limited the power reduction to 19.17% and recovered within 5s. Overall, the FLC provided improved voltage stability, faster recovery, reduced oscillations, and superior fault ride-through capability compared with the conventional PI controller, demonstrating its effectiveness for digital twin-enabled offshore wind farm application. Full article

Floating wetlands have emerged as a sustainable alternative for improving water quality, and although some studies have investigated their performance, there is still much to be understood regarding their integration with energy-generating technologies. This study evaluated a combined system of floating wetlands and microbial fuel cells (MFCs) for treating real wastewater and generating bioelectricity. Experiments were conducted in batch mode to simulate application in natural water bodies, using real wastewater collected on different dates. As a result of the natural variability of the influent, initial chemical oxygen demand (COD) concentrations of 405 and 289 mg/L were observed. Performance was assessed in terms of organic matter and nitrogen removal, as well as voltage generation. COD removal efficiencies reached 50% and 69% for the higher and lower organic loads, respectively, indicating improved treatment at reduced concentrations. Maximum removals of 56% for ammoniacal nitrogen (NH₃-N) and 40% for total nitrogen (TN) were achieved, reflecting moderate nutrient removal capacity. Voltage generation was sustained for approximately 21 days, confirming stable bioelectrochemical activity, and power output was found to depend on the organic load serving as substrate for electrogenic microorganisms. Overall, the system represents a viable approach for wastewater treatment with the added benefit of energy recovery, although its performance is influenced by influent characteristics and operation conditions. Full article

Background/Objectives: Latent fingerprints are routinely recovered from conventional porous and non-porous substrates; however, biologically active surfaces such as plant leaves are generally regarded as unsuitable for dactyloscopic evidence. Because vegetation is frequently present at crime scenes, this study aimed to systematically evaluate whether plant leaves can retain usable friction ridge detail and to determine the durability and forensic value of such traces under laboratory and outdoor conditions. Methods: Latent fingerprints were deposited on leaves of multiple plant species (maple, ash, dandelion, bird cherry, chestnut, climbing ivy, and five-leaved ivy) under dry and hydrated conditions and at defined time intervals after deposition. Visualization was performed using several powders, with SupraNano Fluorescent Green magnetic powder providing the best performance. Developed impressions were photographed using controlled illumination and evaluated using automated quality assessment (NFIQ 2.0) and comparison software (Innovatrics IDkit 9.1.7.1004). Additional experiments examined living, growing leaves exposed to natural weather conditions for extended periods. Results: Usable ridge detail was successfully visualized on all tested species. Bottom leaf surfaces and hydrated samples generally provided better preservation and contrast. Identifiable traces persisted for up to 20 h on detached leaves and for up to 35 days on living leaves despite growth-related deformation. Under outdoor exposure, fingerprints on ivy remained visible and comparable for up to 60 days. Although overall automated quality scores were reduced by background venation, selected impressions achieved measurable comparison scores and successful matches. Conclusions: Plant leaves can serve as unconventional yet viable carriers of latent fingerprints. Magnetic fluorescent powder development combined with careful documentation enables recovery of forensically useful ridge detail even after prolonged environmental exposure. These findings expand the range of substrates that should be considered during crime scene processing and provide practical guidance for evidence collection on vegetation. Full article

Three-dimensional UAV operations require path planning methods that can jointly maintain route efficiency, threat avoidance, and trajectory smoothness under spatially distributed and time-varying constraints. To address this problem, this paper develops an integrated Dual-Layer Adaptive T-perturbation and Opposition-based Multi-Objective Particle Swarm Optimization framework, termed DATO-MOPSO, for 3D UAV path planning in complex threat environments. The method integrates a dual-layer adaptive inertia-weight and velocity-regulation mechanism with symmetric T-perturbation, an elite quasi-opposition-based learning strategy for diversity recovery and feasible local exploitation, and an archive-driven simulated annealing rule for stagnation-aware personal-best updating. A three-objective model minimizing path length, threat exposure, and path smoothness is established, and comparative experiments against MOPSO, ZAMOPSO, NSGA-II, and SPEA2 are conducted in both static and dynamic environments, together with statistical and ablation analyses. In the static scenario, DATO-MOPSO achieved the highest mean HV and stable repeated-run performance, but its IGD was comparable to ZAMOPSO with higher computational cost. In the dynamic scenario, DATO-MOPSO showed its main advantage, achieving the highest mean HV and the lowest mean IGD with statistically significant HV and IGD improvements over all baselines. Overall, DATO-MOPSO is most advantageous in time-varying complex threat environments, whereas its static-scenario advantages are accompanied by higher computational cost. Full article

If concentrating coal is difficult or impossible using gravity methods (such as jigs, shaking spirals, dense-media drum, and cyclone), which are among the cheapest and simplest options, flotation becomes an alternative. This is due to the differences in surface chemistry properties between the relatively hydrophobic coal and the gangue minerals. On the other hand, flotation methods are far more complex than gravity methods and involve many more parameters that influence concentrate, such as coal particle size, amounts of reagents dosages (e.g., collectors, activators, depressants, and frothers), conditioning times, pulp mixing speeds, flotation times, and pH levels of the pulp medium. In flotation methods with so many variables, determining the combustible recovery (CR) and ash content (AC) of clean coal concentrate that can be obtained may require many experiments. To facilitate these challenging processes, understand the effects of parameters influencing concentration on the flotation method, and estimate the resulting clean coal recovery and ash content, it is necessary to utilize various statistical regression methods. In this study, the effects of six parameters on the flotation of a lignite coal sample with 40% ash content were used to estimate the CR and AC of coal concentrate using multivariate linear regression (MLR) and artificial neural network (ANN) models. As a result, the ANN model demonstrated superior estimate accuracy, with correlation coefficients of 0.988 and 0.963, compared with the MLR models (R² = 0.575 and 0.540) for estimating the ash content (AC, %) and combustible recovery (CR, %) of coal concentrate, respectively. Full article

Intensive agricultural practices based on continuous monocropping and prolonged bare-soil fallows have contributed to soil degradation and loss of biological functioning. Replacing fallows with cover crops (CCs) is a promising strategy to restore soil quality, yet their legacy effects on rhizosphere fungal communities remain poorly understood. This study evaluated the legacy effects of Urochloa (syn. Brachiaria) brizantha cover cropping on rhizosphere fungal communities, as well as soil physicochemical and biological properties, in a degraded common bean system. A field experiment with a randomized complete block design included: bare fallow (BM), one (B1) or two (B2) CC cycles before bean, a perennial pasture (PB), and a pristine soil reference (PS). High-throughput sequencing showed that Urochloa-based treatments significantly shifted fungal community composition compared to BM, increasing saprotrophic and beneficial taxa (e.g., Mortierella, Penicillium, Coprinellus) and reducing potential pathogens such as Fusarium. These changes were associated with higher soil organic carbon, aggregate stability, microbial biomass, and enzyme activities, especially in B2 and PB. Indicator taxa identified by LEfSe were linked to organic matter decomposition and nutrient cycling. Multivariate analyses revealed strong associations between fungal community structure and soil properties. Overall, U. brizantha cover cropping induced measurable legacy effects, promoting soil biological recovery even after short-term implementation. Full article

Waterflooding in tight sandstone reservoirs preferentially mobilizes oil in large, well-connected pores, leaving substantial remaining oil in medium–small and poorly connected pore spaces. In this study, specific Chang 6 tight sandstone cores from the Ordos Basin were investigated using high-temperature and high-pressure online NMR displacement experiments, combined with CO₂–oil phase behavior tests and CO₂–brine–rock interaction experiments. The minimum miscibility pressure of the crude oil–CO₂ system was estimated to be 19.4 MPa based on the available slim-tube data. CO₂ dissolution enhanced oil mobility through swelling and viscosity reduction, while CO₂–brine–rock reactions increased core permeability by 18.24–25.55%. Compared with waterflooding, CO₂ flooding increased average oil mobilization in large, medium, and small pores by 33.66%, 39.56%, and 22.20%, respectively. Medium pores contributed most to incremental recovery, whereas small-pore oil was activated mainly under higher pressure. These results indicate that CO₂ flooding can enhance recovery in the tested waterflooded Chang 6 tight sandstone cores by improving crude-oil mobility, modifying pore-throat connectivity, and expanding displacement from large pores to medium–small pores. Full article