Search Results (3,498)

Motorcycle noise along leisure routes constitutes a distinct environmental health burden poorly captured by standard road traffic noise indicators. This study derives source-specific exposure–response functions and examines non-acoustic predictors of residential motorcycle noise annoyance. A mixed-methods socio-acoustic design was applied in five study areas in Baden-Wuerttemberg, Germany. A community survey (N = 493) assessed long-term annoyance (12-month recall); a smartphone-based experience-sampling study (MotoApp; N = 213; ten days in summer 2022) collected hourly ratings. Acoustic measurements provided vehicle-specific L_Aeq,1h, L_AFmax,1h, and N₆₀; exposure–response functions were estimated using logistic regression and generalised estimating equations. In the long-term survey, 46.5% were highly annoyed by motorcycle noise, compared with 18.4% for passenger cars. Motorcycle exposure–response curves were markedly shifted; the 25–highly-annoyed threshold was reached approximately 16 dB lower in L_Aeq,1h than for passenger cars on weekends. Negative attitudes towards motorcycle riders, low coping capacity, and noise sensitivity were significant independent predictors. Source-specific assessment is necessary for motorcycle leisure routes. The 25–highly-annoyed criterion maps to approximately 52 dB L_Aeq,1h and 78 dB L_AFmax,1h on weekends, and to 25 N₆₀ events per hour—substantially below current road traffic guideline values—providing actionable thresholds for noise action planning. Full article

The Chushandian Irrigation Area (CSDIA) lacks a comprehensive drought index integrating meteorological and hydrological information, hindering accurate drought assessment and sustainable water resource management under changing climatic conditions. To address this, a multivariate standardized drought index (MSDI) based on a Copula function was developed, combining precipitation and runoff. Optimized run theory identified compound drought events, and cross-wavelet power spectrum explored large-scale climate drivers. Results show that MSDI correlates strongly with both the Standardized Precipitation Index (SPI) and Standardized Runoff Index (SRI) (Pearson’s r > 0.75, p < 0.01) at the monthly scale, effectively capturing drought onset, duration, and termination. From 1960 to 2018, 110 compound drought events were identified, characterized by short durations (mean 3.82 months) and low intensities (mean 4.43). The most severe event (August 1960–October 1961, duration 15 months, intensity 22.72) has a return period of about 40 years. Among nine teleconnection factors, ENSO is the dominant driver, followed by sunspot activity (SSI). BEAST change-point detection revealed a shift toward drought intensification after 1990, underscoring the need for adaptive water management strategies. These findings provide scientific support for sustainable drought monitoring, climate-resilient agricultural planning, and adaptive water management in CSDIA, contributing to the broader goal of ensuring food security and water sustainability in monsoon-dependent irrigation systems. Full article

Background/Objectives: Image-guided adaptive brachytherapy is a core component of definitive treatment for locally advanced cervical cancer (LACC). However, implantation remains challenging in bulky, asymmetric, or anatomically complex tumors, where standard applicator geometry or purely straight interstitial trajectories may be insufficient for individualized target coverage. This study evaluated the real-world implementation of a patient-specific 3D-printed template-guided adaptive brachytherapy workflow for complex LACC. Methods: We retrospectively reviewed 120 consecutive patients with FIGO 2018 stage IB3–IVA cervical cancer treated with definitive chemoradiotherapy followed by high-dose-rate image-guided brachytherapy between March 2023 and March 2025. All patients were treated using a patient-specific 3D-printed template-guided hybrid intracavitary/interstitial workflow integrating CT/MRI-based target assessment, individualized catheter trajectory planning, template fabrication, implantation verification, and adaptive treatment planning. Straight-channel or curved-channel guidance was selected according to residual tumor geometry and pelvic anatomy, with flexible plastic interstitial catheters used for curved or anatomically constrained trajectories. Procedural deliverability, dosimetry, toxicity, early clinical outcomes, and exploratory dose–outcome patterns were analyzed. Results: The median HR-CTV volume was 55.9 cm³, and the median HR-CTV D90 was 92.9 Gy EQD2. Median organ-at-risk D2cc values remained within contemporary institutional and guideline-consistent constraints. A total of 555 template-guided HDR brachytherapy fractions were delivered. The median applicator-and-catheter placement time was 4.21 min per fraction, with a median of 7.25 implanted channels. Minor and major insertion-related bleeding occurred in 10.8% and 1.7% of patients, respectively. At a median follow-up of 20.1 months, estimated 3-year overall survival, progression-free survival, local recurrence-free survival, regional recurrence-free survival, and distant metastasis-free survival were 77.9%, 76.8%, 94.3%, 98.0%, and 86.2%, respectively. Late grade ≥ 3 gastrointestinal and genitourinary toxicities occurred in 2.5% and 1.7% of patients, respectively, with no grade 4–5 events. Exploratory dose–outcome analyses suggested hypothesis-generating dose–outcome patterns, but these findings were not intended to define or validate a clinical dose threshold. Conclusions: This real-world implementation study supports the feasibility of patient-specific 3D-printed template-guided adaptive brachytherapy for complex LACC. By translating CT/MRI-based individualized trajectory planning into template-guided intracavitary/interstitial catheter placement, this workflow achieved guideline-consistent target coverage, acceptable organ-at-risk doses, efficient procedural delivery, and low severe toxicity within the available follow-up. Dose–outcome findings remain exploratory and require validation in more mature cohorts. Full article

Accurate correction of gridded numerical weather prediction precipitation forecasts remains challenging because many end-to-end deep learning correction models treat meteorological variables as undifferentiated data channels and therefore provide limited physical interpretability. Inspired by general principles of biological environmental sensing, selective information processing, and regulatory constraint learning, this study proposes PCPNet, a bio-inspired and physically constrained precipitation correction framework. The framework does not imitate a specific biological organ or species; instead, it abstracts three information-processing principles into a meteorological correction task. First, key weather-system cues, including low-level shear lines, trough-ridge effects, upper-level jet-stream forcing, vorticity-divergence-related vertical motion, and water-vapor flux convergence, are quantified as structured diagnostic fields. This transforms the subjective synoptic diagnosis of forecasters into automated grid-based sensing features. Second, these diagnostic cues are fused with numerical weather prediction variables and terrain descriptors in an encoder–attention–decoder network, allowing the model to emphasize dynamically important precipitation-triggering regions. Third, water-vapor conservation and terrain-forcing relationships are embedded as differentiable constraint losses, providing training-time constraint-based regulation that guides the corrected precipitation field toward physically consistent solutions. The method is evaluated from 2021 to 2023 in Hunan Province, China, using hourly numerical weather prediction model outputs as input features, China Meteorological Administration Land Data Assimilation System gridded analysis data as the training target, and independent meteorological station observations for strict cross-validation. PCPNet reduces the mean absolute error by 22.1% compared with the uncorrected China Meteorological Administration Land Data Assimilation System gridded precipitation products and outperforms Linear Regression, Bagging, Boosting, Multi-Layer Perceptron, TabNet, and Tree-based Progressive Regression Models by 12.9%, 13.5%, 16.9%, 10.8%, 14.9%, and 15.9%, respectively. The single-day event analysis provides an initial demonstration of heavy precipitation recovery capability, while comprehensive validation across long-term continuous weather events is planned for future operational deployment to further verify model stability. These results indicate that bio-inspired sensing and regulatory constraint learning can improve both the accuracy and interpretability of precipitation nowcasting correction. Full article

Long-endurance unmanned aerial vehicle (UAV) missions beyond 72 consecutive flight hours face a reliability boundary at which thermal gyroscope drift drives the inertial navigation system (INS) position error into rapid nonlinear divergence at a predictable threshold t_c. This paper presents BAZ II, a simulation-validated multi-agent navigation system that extends the analytical BAZ (bifurcation-aware zonal navigation) framework. Its central idea is to treat communication quality as a planning resource and combine it with multi-agent collaboration, making the navigation cliff a manageable degradation event rather than a hard operating limit. Four contributions support this idea: a thermalhysteresis MEMS gyroscope drift model reproduces the analytical cliff in simulation and supplies its physical mechanism; a distributed collaborative simultaneous localization and mapping (SLAM) filter coupled to a stochastic continuous-time Markov chain (CTMC) interagent channel sustains GPS-denied localization within the operational accuracy budget; a 3D Gaussian process RF-aware model predictive controller (MPC) with cognitive radio frequency-hopping restores link availability under jamming, while an analytic hierarchy process (AHP)-weighted multi-objective communication cost improves latency and jitter at negligible signal-to-noise ratio cost; finally, the integrated controller executes within the onboard real-time budget of an NVIDIA Jetson Xavier NX. All results are obtained in simulation, with hardware-in-the-loop and field testing remaining as priority future work. Full article

Background/Objectives: Miniscrew-assisted rapid palatal expansion (MARPE) is an effective treatment for maxillary transverse deficiency in skeletally mature patients. However, resistance of the midpalatal suture may limit treatment success. Surgical corticopunctures have been proposed to facilitate suture opening, while digital planning and 3D-printed surgical guides may improve procedural accuracy and safety. This study aims to evaluate the clinical effectiveness and safety of MARPE combined with surgically guided midpalatal corticopunctures in adult patients. Methods: A retrospective observational study was conducted on 15 adult patients (at least 20 years old) presenting with maxillary transverse deficiency and midpalatal suture maturation stages D or E. All patients underwent corticopuncture-assisted MARPE using patient-specific 3D-printed surgical guides designed through CBCT-based virtual planning. Treatment success was assessed by postoperative cone-beam computed tomography (CBCT), which evaluated midpalatal suture opening and transverse expansion. Clinical records were reviewed for complications, mini-implant stability, and postoperative outcomes. Results: Successful opening of the midpalatal suture was achieved in 13 of 15 patients, corresponding to a success rate of 86.7%. Among successful cases, the mean suture expansion measured on CBCT was 3.6 ± 0.9 mm. The customized surgical guides demonstrated adequate intraoral fit and enabled accurate execution of the planned corticopunctures in all cases. No intraoperative guide-related complications were reported. Postoperative healing was uneventful, with only mild and transient discomfort observed. No infections, excessive bleeding, significant soft-tissue injuries, damage to adjacent anatomical structures, or adverse events related to the corticopuncture procedure were recorded. Mini-implant stability was maintained in the majority of patients throughout the expansion phase. Conclusions: Within the limitations of this retrospective single-arm study, corticopuncture-assisted MARPE performed using customized 3D-printed surgical guides was feasible and associated with a high rate of successful midpalatal suture opening and few complications. The technique demonstrated a high rate of suture opening, clinically significant skeletal expansion, and a low incidence of complications. Digital planning and guided execution may enhance treatment precision and improve clinical outcomes in MARPE procedures. Full article

The Guanting Gorge section of the Yongding River features complex terrain and densely distributed hydraulic projects. Under extreme rainstorm conditions, flood disasters are highly likely to occur, triggering secondary disasters such as landslides, barrier lakes, and dam breaks, resulting in prominent chain disaster risks and difficult prevention and control. To accurately evaluate the potential flood disaster chain risks in this region, 12 representative evaluation indicators were selected to establish a flood disaster chain risk evaluation system. The analytic hierarchy process (AHP) and entropy weight method (EW) were adopted to calculate subjective and objective indicator weights, respectively. Game theory was applied to achieve the optimal weight fusion and determine the final indicator weights. On this basis, a variable fuzzy model was constructed to identify flood disaster chain risks, and the Receiver Operating Characteristic-Area Under the Curve (ROC-AUC) was used to verify the accuracy and reliability of the model. The results show that cumulative precipitation, terrain slope, and annual maximum precipitation are the core driving factors inducing regional flood disaster chains, with corresponding weights of 0.2058, 0.1293, and 0.0980, respectively. High- and extremely high-risk areas are mainly concentrated in the western and southern river valleys, among which the Zhaitang–Luopoling river reach and the river section from Luopoling Reservoir to Sanjiadian Hub present the most prominent risks. The spatial distribution of risk zones is highly consistent with the actual disaster sites of the July 2023 Haihe River extreme rainstorm event, and the model achieves an AUC value of 0.901, indicating high accuracy and reliable simulation results. This study accurately identifies the core inducing factors and high-risk sections of flood disaster chains in the Guanting Gorge section of the Yongding River, which can provide scientific references and technical support for regional flood disaster chain prevention and control, hydraulic project operation and management, and disaster prevention and mitigation planning. Full article

Forest planning and operational execution still often rely on separate office-based workflows, field inventories, and analogue tree-marking procedures, limiting direct communication between planners and field personnel. Mixed reality (MR) interfaces and forest digital twin concepts may help link planning decisions with field-level visualization and interaction. This study presents an initial proof-of-concept prototype for MR-based virtual tree tagging and field–office communication in forestry. The prototype integrates a Unity GE-based Forest Planner System, a Microsoft HoloLens 2-based Forest Worker System, and a locally hosted MagicOnion server for bidirectional client–server communication. Virtual trees with predefined stem diameters were created in Unity GE, and torus-shaped markers were implemented to support tree selection, color-coded designation, marker deletion, and visualization of predefined diameter-related attributes. Under controlled indoor conditions using a 5G mobile hotspot, both clients connected to the server and exchanged marker-related events. Marker creation, color assignment, deletion, and shared marker-state updates initiated from either client were reproduced in the corresponding system. The prototype demonstrates the functional feasibility of the core communication workflow but remains limited to a simulated environment. Full article

Percutaneous kidney biopsy (PKB) is an essential tool in the nephrologist’s armamentarium that plays a major role in establishing the diagnosis, monitoring response to interventions and providing prognostication. Over the last few decades, the technique of PKB has evolved from a blind procedure with a high complication rate to an image-guided procedure with substantially reduced but still clinically relevant complication rates, with major bleeding reported in approximately 1–6% of biopsies in contemporary series. With appropriate pre-procedure planning, patient selection, and experienced operators, PKB generally has a low rate of major complications and a high diagnostic yield, while clinicians must remain vigilant for bleeding and other adverse events. In this narrative review, we summarize current indications, contraindications, technical considerations, and complication mitigation strategies for PKB, integrating contemporary guideline recommendations and key observational studies to support bedside decision-making. Further, we review details pertaining to peri-procedure protocols. Special populations that require PKB such as morbid obesity, pregnancy, elderly, single kidney and anatomic abnormalities are discussed as well. Alternative approaches to performing PKB, when PKB is infeasible or challenging, are briefly covered in this review. Full article

In order to mitigate the negative effects of heavy rainfall events, natural water retention measures (NWRM)—such as hedges, erosion control strips, vegetated drainage channels, wooded strips, retention basins and ditch pockets—have gained renewed attention as an effective climate adaptation strategy. To identify potential areas for NWRM, this study applied and methodologically expanded an existing approach for identifying dominant runoff processes (DRPs) to an agricultural sub-catchment in the Weserbergland region of Germany. The DRP were determined using a Geographic Information System (GIS) and validated through field surveys. Potential areas for water retention within the same runoff process classes were identified for three defined objectives: improving infiltration, extending flow paths, and redirecting runoff to surrounding areas. Spatial differentiation was achieved using accumulated catchment area and overland flow distance. The watershed is predominantly characterized by surface runoff (Hortonian Overland Flow). Field validation confirmed the DRP classification for around two-thirds of the study area, with deviations occurring predominantly on arable land. Supplementing the DRP approach with a topographic analysis allowed for further differentiation, focusing on small, topographically defined sub-watersheds. The identified areas offer significant potential for interventions. Combined with supplementary data, analyses of the water network and the involvement of local stakeholders, the resulting potential map provides a solid basis for planning smaller-scale water retention measures. Full article

Background: Accurate pedicle screw placement remains essential in spinal instrumentation, and robotic navigation has been introduced to improve safety, reproducibility, and workflow standardization. This study evaluated the accuracy of robot-assisted pedicle screw placement using the Excelsius GPS platform during the first year of implementation at two centers and analyzed the associated learning curve. Methods: Consecutive patients undergoing robot-assisted spinal instrumentation between April 2024 and April 2025 were retrospectively reviewed. Screw accuracy was assessed on intraoperative three-dimensional imaging using the Gertzbein–Robbins Scale (GRS). Grades A and B were considered clinically acceptable, whereas grades C–E were considered clinically non-acceptable. Sacral S1 screws and oncological cases requiring carbon fiber-reinforced PEEK instrumentation were excluded from the primary analysis and evaluated separately when appropriate. Robotic workflow time was defined as the interval between the first intraoperative three-dimensional acquisition used for planning and the second acquisition used for screw verification. Results: The primary standard non-oncological cohort included 102 patients and 455 non-S1 screws. Overall, 411 screws were classified as GRS A, yielding a perfect intrapedicular placement rate of 90.3%. Clinically acceptable accuracy was achieved in 449 of 455 screws, corresponding to a GRS A + B rate of 98.7% (95% CI, 97.2–99.4%). Only six screws were classified as GRS C–E, with no GRS D screws observed. Clinically acceptable accuracy was comparable between centers. In Center 1, all clinically non-acceptable screws occurred within the first nine cases, and GRS A + B accuracy increased from 92.9% in the first trimester to 100% thereafter. Median robotic workflow time was 64.4 min per case and 13.9 min per screw. Conclusions: This two-center early experience supports the accuracy and reproducibility of ExcelsiusGPS-assisted spinal instrumentation. Chronological analysis showed that clinically non-acceptable breaches were concentrated in the early implementation phase; however, this observation should be considered exploratory because of the low event count. The study supports high clinically acceptable accuracy and broadly comparable robotic workflow metrics across centers. Chronological patterns observed during early implementation should be interpreted as exploratory rather than as proof of a formal learning curve. Full article

Facility Layout Planning (FLP) remains a complex task for manufacturers seeking to improve productivity, reduce daily operating costs, and stay competitive in fast-changing markets. Traditional methods such as Systematic Layout Planning (SLP) offer useful guidelines for designing department layouts but still rely heavily on judgment and experience. At the same time, modern optimization and simulation techniques provide valuable quantitative insights. These techniques are often used separately rather than as part of an integrated process. In this work, a hybrid layout-planning approach that combines these techniques is developed and validated through an industrial case study, providing a practical decision-support process for facility layout planning. The process starts with SLP, which develops an initial layout using activity relationship charts, material-flow analysis, and handling-cost estimates. A simulation model then evaluates throughput, machine utilization, and work-in-progress, providing early indications of the layout’s real-world performance. A Genetic Algorithm (GA) is used to find improved configurations that reduce distances and costs. The optimized layouts are further tested through simulation. To demonstrate practical use, the framework was applied at a transformer manufacturing plant. It resulted in an approximately 35% reduction in material-handling costs. The results show that the optimized layout reduced material-handling costs from 7062.5 to approximately 4560 L.E. per transformer while increasing monthly throughput by 2.46% (approximately 11 transformers per month). Additionally, a what-if analysis was performed to identify opportunities for improvement, such as increasing production by using an automatic laser-cutting machine. The findings support data-driven decisions in facility layout design and long-term operational planning. Full article

Background/Objectives: To evaluate clinical and dosimetric predictors of vaginal toxicity in patients treated with vaginal-cuff brachytherapy (VCB), with or without external beam radiotherapy (EBRT), and assess the impact of different prescription and optimization strategies on dose–volume parameters. Methods: We retrospectively analyzed 217 patients treated with EBRT combined with VCB (n = 120) or VCB alone (n = 97). In VCB three prescription and optimization strategies (volume-based, graphical optimization, and 5 mm distance-based prescription) were compared to determine differences in dose–volume parameters. In patients who developed late vaginal side effects, the dosimetric parameters were evaluated using descriptive statistics and Cox regression modeling. Kaplan–Meier analysis was performed to assess time to toxicity. Results: In the EBRT+VCB cohort, 34/120 patients (28.3%) developed grade 1–2 vaginal toxicity compared to 35/97 (36%) in the VCB alone cohort. In the EBRT+VCB group, patients with toxicity received a higher D90 per fraction and higher vaginal D_2cc. In multivariable analysis, vaginal D_2cc (HR = 1.60, 95% CI = 1.01–2.54, p = 0.045) and CTV-DVH (HR = 0.77, 95% CI = 0.61–0.97, p = 0.027) were independently associated with toxicity. No significant dose–toxicity associations were observed in the VCB-alone cohort. Most events occurred within 48 months in both groups. Comparison of prescription strategies showed systematic differences in target and organ-at-risk dose–volume parameters, including vaginal D_2cc. The 5 mm distance-based prescription consistently resulted in higher D90, D100, EQD2, and vaginal D_2cc values. Conclusions: In patients receiving EBRT combined with VCB, both vaginal D_2cc and target dose distribution were associated with vaginal toxicity. The prescription and optimization strategy significantly influenced dose–volume parameters. Planning methodology and dosimetric aspects should be considered when interpreting dose–toxicity relationships in vaginal brachytherapy. Full article

Automotive SPICE^® (ASPICE) conformance activities require systematic discovery and evaluation of project documentation against standardised process indicators, consuming an estimated 40–60% of assessment preparation time with high extraneous cognitive load. This paper presents Smart Evidence Management (SEM), a principled Human–AI Collaboration (HAIC) approach grounded in Cognitive Load Theory, Trust in Automation, and Situation Awareness theory. SEM defines four design principles—AI-assisted discovery, expert-validated judgement, transparent reasoning, and full data sovereignty—as a novel generalisable HAIC pattern for documentary evidence evaluation in regulated professional domains. By reducing evidence-hunting effort, SEM operationalises the Plan-Do-Check-Act (PDCA) continuous improvement principle, enabling iterative conformance gap detection throughout development rather than only at formal assessment events. The Smart Evidence Manager, a prototype instantiation for ASPICE Process Assessment Model (PAM) v4.0, implements a two-stage hybrid symbolic–neural Retrieval-Augmented Generation (RAG) architecture with fully local Large Language Model (LLM) inference. An expert agreement study (n = 120 findings, five intacs^® certified assessors) yielded a combined acceptance rate of 90.0% (95% Confidence Interval (CI) [83.3%, 94.2%]). A beta-test study is under recruitment (target n ≥ 30 practitioners) to quantify cognitive augmentation effects, usability, and trust calibration. Cultural dimensions of trust calibration are discussed, extending SEM to intercultural deployment contexts. Full article

Diffusion-based trajectory planners achieve strong nominal performance in autonomous driving, but sparse safety intervention remains difficult to evaluate and realize effectively. This study addresses this problem by proposing a safety-aware event-triggered intervention framework on top of a fixed DiffusionDriveV2 planner. The method uses candidate-level risk signals and an auxiliary semantic risk trigger to decide when intervention should be activated, and realizes the intervention through conservative re-selection and mild action-space augmentation. To evaluate sparse interventions beyond global validation metrics, we further construct normal, conservative, and actual trajectories and introduce triggered-subset counterfactual evaluation. On NAVSIM navtest, global planner metrics remain nearly unchanged across sparse trigger policies, but the semantic trigger achieves better triggered-subset final score, TTC, and progress than matched-random and TTC-based triggers. Qualitative cases show that behaviorally distinct safety responses mainly arise from action-space augmentation rather than candidate reranking alone. These results show that the proposed framework can diagnose and partially alleviate the gap between risk recognition and action realization, while revealing that stronger semantic-conditioned action generation is needed to fully overcome the trigger-to-action bottleneck. Full article