Search Results (23,098)

Accurate trajectory tracking is fundamental to the autonomous operation of unmanned aerial vehicles (UAVs) in complex tasks. While proximal policy optimization (PPO) has shown strong potential in UAV control, its performance is highly sensitive to hyperparameter configuration, and manual tuning is time-consuming due to complex interparameter coupling. This paper proposes CCO–PPO, a framework integrating the cuckoo catfish optimizer (CCO) with PPO for automatic hyperparameter optimization in UAV trajectory tracking. The problem is formulated as a Markov decision process with a 20-dimensional state space, and the CCO performs offline search over a four-dimensional hyperparameter space. Evaluated across seven test environments covering diverse trajectory geometries, wind disturbances, sensor noise, and large-scale scenarios, CCO–PPO achieves the lowest tracking error in all cases. Performance gains over baseline PPO increase monotonically with task complexity, reaching 18.8% under combined wind disturbance and sensor noise, with statistically significant advantages in 85.7% of pairwise comparisons against baseline PPO, SAC, and TD3. Ablation studies confirm that joint optimization of all four hyperparameters is essential under high-disturbance conditions, and comparisons with Bayesian optimization validate the CCO’s superior cross-seed stability. These results demonstrate that metaheuristic hyperparameter optimization substantially enhances policy robustness in high-disturbance UAV trajectory tracking scenarios. Full article

Chronic exposure to ionizing radiation from uranium legacy sites remains a significant public health concern in Northern Kazakhstan. This review evaluates epidemiological, clinical, and environmental evidence published between 2000 and 2025, with particular emphasis on studies conducted during 2014–2023 in the Stepnogorsk region among populations residing near former uranium mining sites. Residents were exposed to annual external gamma doses of approximately 1.0–3.5 mSv and radon-related doses of up to 1.2 mSv. Cancer registry analyses revealed 1913 malignancy cases in the exposed group (vs. 358 controls), with digestive (29%) and respiratory (17%) cancers predominating. Early signs of chronic radiation syndrome (CRS) were consistently observed, including olfactory dysfunction, immunosuppression, vestibular disturbances, hematologic anomalies, and elevated chromosomal aberrations (1.3–1.5× baseline). Non-cancer morbidity was also elevated, including hypertension (32% vs. 24%), chronic bronchitis (14% vs. 8%), and reduced forced expiratory volume in one second (FEV₁; −9.7%), indicating broader systemic effects. These results underscore the need for targeted public health strategies incorporating CRS biomarker screening, cancer surveillance, personal dosimetry, and environmental remediation in uranium-impacted communities. Full article

Inter-basin water transfer projects (IBWTPs) play a pivotal role in alleviating the spatiotemporal imbalances of water resources. However, their operation is exposed to multiple, highly interdependent safety risks that can significantly undermine system stability and water supply reliability. Existing studies predominantly focus on isolated risk factors or rely heavily on subjective data, which limits their ability to capture the complex interrelationships among risks and reveal their underlying propagation mechanisms. To address these limitations, this study proposes a novel risk correlation analysis framework that integrates Interpretive Structural Modeling (ISM) with copula functions. ISM is first employed as a preprocessing tool to structure expert knowledge and develop an initial risk correlation framework. It is then used to hierarchically organize the complex interrelationships among risks. Subsequently, copula functions are utilized to model nonlinear dependencies and tail behaviors among risk variables. This enables a quantitative assessment of correlation strengths and facilitates the construction of a risk topological network. An empirical case study is conducted based on the Middle Route of the South-to-North Water Diversion Project. The results reveal 13 significant correlations among six second-level risk categories. Natural risks (e.g., floods and geological hazards) are identified as the primary driving factors. They exhibit a strong positive correlation (0.6155) with engineering risks and serve as the most critical nodes for proactive risk prevention and control. Engineering risks function as central intermediary hubs in the risk transmission process, whereas water quality and economic risks are characterized as terminal endpoints. Furthermore, three principal risk propagation pathways are identified: (1) natural risks → engineering risks → economic risks; (2) natural risks → operational scheduling risks → social risks; and (3) engineering risks → water quality risks → economic risks. The resulting risk topological network demonstrates significant small-world properties, indicating highly efficient risk transmission within the system. Ultimately, this study provides a robust quantitative approach for analyzing risk interactions in complex engineering systems and enriches the theoretical framework of engineering risk management. It also identifies critical nodes and key transmission pathways for risk prevention and control in IBWTPs, thereby offering significant practical implications for operational safety. Full article

Background/Objectives: Intraoperative cone-beam computed tomography (CBCT) can detect residual fragments (RFs) during percutaneous nephrolithotomy (PCNL), enabling immediate removal and improving stone-free status. However, CBCT requires a hybrid operating room (OR), which is often limited in availability. This study explores patient and stone characteristics associated with CBCT eligibility and develops an exploratory treatment-selection model estimating stone-free probabilities conditional on CBCT use. Methods: We performed a retrospective study of a previously conducted randomized controlled trial evaluating intraoperative CBCT during PCNL in a tertiary care center. We compared CBCT-eligible cases versus ineligible cases, and cases achieving grade C (≤4 mm) stone-free status versus those with RFs. A multivariate exploratory treatment-selection model was developed using the strongest potential predictors of stone-free status. Internal validation was performed using bootstrapping. The model was also assessed for predicting grade A (0 mm) stone-free status. Results: The only significant difference between CBCT-eligible (n = 160) and ineligible (n = 60) cases was stone composition (p = 0.022). The final model included intraoperative CBCT (p = 0.003), stone size (p = 0.024), and composition (p = 0.044). Model-based estimates suggested smaller differences in predicted stone-free probabilities with CBCT in solitary stones. The AUC was 0.81 (95% CI: 0.73–0.88) for grade C and 0.75 for grade A (95% CI: 0.67–0.82) outcomes. Internal validation demonstrated moderate optimism, indicating potential overfitting. Conclusions: This exploratory treatment-selection model estimates conditional stone-free probabilities with and without CBCT. The findings suggest variation in expected benefit across stone characteristics but should be considered hypothesis-generating. The model is not intended for clinical decision-making and requires external validation before implementation. Full article

Automatic detection of deceptive intent in negotiation dialogue remains difficult because deceptive utterances are rare, context-dependent, and pragmatically subtle. This study develops a deployment-oriented evaluation pipeline for negotiation analytics using the Diplomacy corpus and compares sparse, dense, and imbalance-aware neural models under a unified protocol. The pipeline integrates context-window benchmarking, validation-based threshold selection, 10-seed robustness analysis, model-agnostic explanation case studies, and controlled perturbation stress tests. Across binary speaker-intention and receiver-perception tasks, contextualized inputs consistently outperform isolated utterances, confirming that deception-related interpretation is inherently sequential. The sparse term frequency–inverse document frequency (TF-IDF) model remains the strongest and most efficient overall benchmark, whereas stronger imbalance-aware neural baselines can improve minority deceptive-instance sensitivity at substantially higher computational cost. Error analysis further shows that socially mediated deception-quadrant prediction is markedly harder than direct binary in-tent prediction, with many failures collapsing toward majority straightforward cases. Controlled perturbation tests show that sparse modeling is especially stable under light-weight surface corruption, while neural robustness remains architecture-dependent. The main contribution is therefore a practical decision framework for selecting among efficient sparse monitoring, dense baselines, and minority-sensitive neural detection under operational constraints. Full article

Power electronic systems are often engineered through a sequential–iterative workflow in which hardware parameters are initially sized from steady-state, ripple, thermal, and electromagnetic-compatibility constraints, and controllers are subsequently tuned to satisfy dynamic and closed-loop performance requirements. While converters are inherently designed for closed-loop operation, increasing power density, uncertainty, and distributed interaction make the underlying design process resemble a strategic interplay among multiple decision-makers, including hardware designers, control algorithms, loads, disturbances, and manufacturing constraints. This paper develops a unifying game-theoretic perspective on the optimal design and control of power electronic systems. Classical concepts—such as robust control, worst-case design, droop-based load sharing, and tolerance allocation—are reinterpreted as equilibrium solutions of zero-sum, Stackelberg, non-cooperative, or cooperative games. Beyond a conceptual taxonomy, two illustrative simulation case studies are provided: (i) a Stackelberg hardware–controller co-design of a buck converter, demonstrating simultaneous passive-component reduction and improved transient performance relative to a conservative sequential design; and (ii) a droop-controlled parallel-converter example contrasting Nash and cooperative equilibria, explicitly quantifying trade-offs between bus-voltage regulation, current-sharing fairness, and conduction losses. By framing power electronic design and control as interacting strategic processes rather than isolated optimization stages, the paper aims to show that game theory can serve as a structured and practically interpretable framework for distributed and uncertainty-aware power electronic systems. Full article

Objective: The goal was to investigate the relationship between methodological adherence and clinical outcomes in Progressive Resistance Training (PRT) for Parkinson’s Disease (PD), specifically identifying why findings of “superiority” over active controls remain inconsistent. Methods: This umbrella review utilized a multi-stage process to identify a sample of the primary literature for methodological analysis. An initial search identified 38 systematic reviews published within the specified timeframe. From the reference lists of these reviews, a subset of 34 primary clinical studies was purposefully selected. Inclusion was prioritized for studies providing comprehensive methodological data on PRT protocols and standardized clinical outcomes. Interventions were evaluated using a three-tiered framework: (1) training protocol with specifications of Frequency, Intensity, Time, Type, Volume, and Progression (FITT-VP) (General Exercise), (2) FITT-VP integrated with the American College of Sports Medicine (ACSM) Supplementary Guidelines (Integrated Guidelines), and (3) principles of progression (mechanistic growth). Studies were categorized by control type (active (e.g., aerobic or balance), n = 26; passive (e.g., standard care or no exercise), n = 8). Results: In trials that compared PRT with an active control group, PRT achieved clinical superiority in 57% (n = 15) of trials and 46% (n = 12) when focusing on trials with an effect on specific functional or balance outcomes. Among these successful interventions, 75% maintained high adherence (≥70%) to the Integrated Guidelines, and 58% maintained high adherence to the principles of progression. In the 53% (n = 14) of studies where PRT was found non-superior (equivalent or inferior in functional or balance outcomes) to an active control, 0% met the high adherence threshold for progression. While general FITT-VP compliance remained high (78%), the failure to implement systematic load, specificity, and variation served as a definitive barrier to competitive superiority. In the 100% of studies where PRT outperformed passive controls, high progression was present in 57% of cases. This may suggest that while a baseline resistance stimulus outperforms inactivity, it is fundamentally insufficient to outperform other active clinical therapies. Conclusions: This umbrella review indicates that adherence to the principles of progression may be an important factor influencing the clinical outcomes of PRT in individuals with PD. The variability observed in the current literature suggests that inconsistent application of established exercise frameworks—rather than the failure of the modality itself—could be a contributing element to the reported “inconclusiveness.” To potentially enhance functional outcomes and the comparative effectiveness of PRT, future research should consider prioritizing structured adherence to FITT-VP, Integrated Guidelines, and progression-based frameworks. Establishing a 70% adherence threshold is proposed as a potential benchmark to improve protocol consistency and support rehabilitation efficacy in this population. Full article

Background: Nasal valve dysfunction (NVD) is a common yet underrecognized cause of nasal airway obstruction, with a significant impact on quality of life. Despite its clinical relevance, no universally accepted diagnostic standard exists, and optimal management remains debated. Multiple diagnostic tools and surgical or minimally invasive treatments have been proposed. This systematic review and meta-analysis aimed to evaluate current evidence regarding diagnostic approaches and treatment outcomes in NVD. Methods: A systematic search of PubMed/MEDLINE, Embase, and Cochrane Library was performed for studies published between January 1990 and January 2026, in accordance with PRISMA 2020 guidelines. Randomized controlled trials, non-randomized comparative studies, cohort studies, and case series (≥10 patients) assessing diagnostic methods or therapeutic interventions for NVD were included. Diagnostic data were synthesized narratively. The primary surgical outcome was change in the Nasal Obstruction Symptom Evaluation (NOSE) score. Risk of bias was assessed using RoB 2, ROBINS-I, and QUADAS-2 tools. Results: Seventy-two primary clinical studies were included (15 diagnostic, 57 treatment-focused). Objective airflow measurements, particularly rhinomanometry and peak nasal inspiratory flow, showed greater reliability than isolated clinical maneuvers. Imaging modalities provided anatomical detail but correlated inconsistently with symptoms. Meta-analysis of 12 studies (n = 1210 patients) suggests that both traditional surgical and minimally invasive interventions can substantially improve nasal breathing, with mean NOSE score reductions of 40–55 points, though heterogeneity precludes direct comparison of their relative effectiveness. Conclusions: Diagnosis of NVD requires a multimodal approach combining clinical assessment, validated symptom scores, and selective objective testing. Surgical and minimally invasive treatments provide substantial symptom improvement when appropriately indicated. Evidence is constrained by the predominance of observational data, emphasizing the need for standardized diagnostics and robust comparative trials. Full article

During drilling in stress-sensitive fractured formations, fracture aperture dynamically evolves with wellbore pressure fluctuations. The sealing layer often undergoes repeated cycles of sealing, destabilization, and re-sealing. Formulation selection based on a single metric or empirical selection cannot simultaneously satisfy multiple objectives, including pressure-bearing capacity, loss control, and dynamic adaptability. This study proposes an entropy-weighted TOPSIS and grey relational analysis method to optimize lost circulation formulations for stress-sensitive fractured formations. A hierarchical evaluation system is established with four criteria layers and eight indicator metrics. A baseline formulation framework is determined through static fracture sealing tests. Experimental data for different elastic-material systems are obtained using a self-developed DTDL dynamic fracture plugging apparatus. Indicator weights are objectively determined using the entropy weight method. A Grey–TOPSIS model is applied to compute grey relational closeness to the positive and negative ideal solutions, enabling formulation ranking and optimal scheme identification. A case study shows that the ternary elastic formulation with Rubber:Graphite:Net = 3:2:1 achieves the highest grey relational closeness and delivers the best overall sealing performance. The ranking remains unchanged when the distinguishing coefficient ρ varies from 0.1 to 0.9, confirming the robustness and feasibility of the proposed method. Compared with entropy-weighted TOPSIS and classical TOPSIS, the proposed method provides a more integrated treatment of the multi-metric data and better aligns the evaluation with the underlying sealing behavior in stress-sensitive fractures. Therefore, it leads to more reliable and comprehensive evaluation results for formulation selection. The results demonstrate that the proposed model provides reliable support and a methodological basis for formulation optimization in dynamic fracture loss control. Full article

Background/Objectives: The COVID-19 pandemic intensified concerns regarding the resilience and financing architecture of mental health services, yet it remains unclear whether crisis-induced adjustments fundamentally altered hospital case-mix complexity or merely exposed pre-existing structural configurations. This study examines the relationship between financing regimes and case-mix complexity in psychiatric hospitals in Romania, a Central and Eastern European health system characterized by mixed financing arrangements and pronounced interregional heterogeneity. Methods: Using administrative data comprising 752 hospital section–year observations (2019–2024), we identify structural financing–organization regimes through a two-step clustering procedure (hierarchical Ward method followed by K-means refinement) based on revenue composition, expenditure allocation, workforce structure, and operational pressure indicators. Results: Three distinct regimes emerge, reflecting persistent institutional configurations rather than temporary crisis-induced groupings. Chi-square tests confirm that regime membership is statistically independent of pandemic timing. A multivariate regression model controlling for financing composition and expenditure structure shows that structural variables (particularly the share of contract-based revenues and the allocation of expenditures) exert systematic and economically meaningful effects on the case-mix index (CMI). Pandemic and post-pandemic indicators do not retain robust explanatory power once structural determinants are accounted for. Regional robustness analyses further demonstrate that financing architecture consistently outweighs temporal shock effects in explaining territorial variation in clinical complexity. Conclusions: The findings suggest that psychiatric hospital case-mix dynamics are structurally embedded within differentiated financing regimes whose influence persists beyond crisis periods. By integrating regime identification with outcome modeling in a Central and Eastern European context, this study contributes to the international literature on health system resilience and highlights the primacy of institutional financing architecture over episodic shock effects in shaping hospital complexity. Full article

Molecular spin-crossover (SCO) compounds constitute prototypical systems exhibiting first-order phase transitions. These transitions involve an abrupt switch between two well-defined states with distinctly different magnetic, optical, and vibrational properties. One state is diamagnetic (low-spin), while the other is paramagnetic (high-spin). Upon heating, the transition occurs at a characteristic temperature, T_up. Upon cooling, it takes place at a lower temperature, T_down < T_up, thereby giving rise to thermal hysteresis. Accordingly, each SCO compound is defined by a distinct pair of transition temperatures, T_up and T_down. The investigation of these molecular solids is of great importance, both for elucidating first-order phase transitions—including the potential emergence of re-entrant phases—and for their broad range of prospective applications. The critical temperatures T_up and T_down are pivotal in defining their practical utility. We present a strategy to modify and tune the transition temperatures of spin-crossover (SCO) compounds to suit different applications. The approach combines a given SCO material with layers of a second SCO system, enabling precise control of the characteristic temperatures of the resulting heterostructure. We illustrate this method with three case studies that span the 100 K–400 K temperature range. All simulations were performed using Monte Carlo methods within the Metropolis algorithm framework. Full article

In this study, we analyze the solution characteristics and dynamics of a variable-order fractional (V-OF) Arneodo system using the Liouville–Caputo fractional operator with variable order. The V-OF operator is used to describe the time-dependent memory effect in the system, which leads to more complex and diverse dynamics compared to integer-order systems. In this work, numerical simulations are performed to observe the effect of the order functions on the dynamic behaviors of the system. In addition, the phase portraits, time series graphs, and three-dimensional diagrams are used to analyze the dynamic behaviors and different types of oscillations present in the system. Furthermore, the bifurcations, chaotic behaviors, and stability of the system with variable orders are studied, and it is found that the system has more complex dynamics compared to the integer-order case. In this case, the Lyapunov exponents indicate that the system under investigation is sensitive to the initial conditions, and the memory effect can control the chaotic oscillation depending on the order of the functions. Full article

Background: Pancreatic cancer is an aggressive malignancy with poor survival. Most patients are diagnosed at advanced or metastatic stages because early disease is often asymptomatic and effective screening tools are lacking. We evaluated a three-marker model comprising serum CA19-9 in combination with the plasma proteins ITIH3 and CEACAM1 for pancreatic ductal adenocarcinoma (PDAC) detection. Methods: Matched plasma and serum samples were collected from 649 participants (250 PDAC cases and 399 controls). Plasma proteins were enriched using high-surface area magnetic covalent organic framework (COF) polymers. Serum CA19-9 was measured using the Tosoh Bioscience immunoassay. The marker panel was trained using a radial-based SVM with repeated 10-fold cross-validation using a set-aside training sample set. The derived model along with a fixed cutoff corresponding to 95% sensitivity in training samples were independently validated using a blinded sample set. Results: In the independent blinded validation, the combined panel of serum CA19-9 with plasma ITIH3 and CEACAM1 achieved an AUC of 0.917 indicating that the three-marker panel maintained strong performance in distinguishing PDAC from controls. At the prefixed threshold, the three-marker panel had a specificity of 53.3% (95% CI: 46.8–59.7%), significantly outperforming CA19-9 alone at 14.5% (95% CI: 10.4–19.7%). Conclusions: In independently blinded validation, combining plasma ITIH3 and CEACAM1 with serum CA19-9 substantially improved diagnostic performance for PDAC, achieving high specificity while maintaining 95% sensitivity compared with serum CA19-9 alone. These findings support further validation of this three-marker panel as a potential PDAC monitoring and detection approach in larger, multicenter studies. Full article

Despite the extensive literature on microalgal production, most studies focus on controlled laboratory-scale systems, resulting in a critical lack of confidence at industrial scale. This is further compounded by the frequently observed inconsistencies, with only modest increases achieved in operational scale. This work demonstrates the design, construction, and operation of a commercial-scale tubular photobioreactor and associated equipment for the production of algae using CO₂ derived from an industrial nickel refinery. The reactor was demonstrated by growing the species Nannochloropsis gaditana. Biomass concentrations of 1.0 to 1.3 g L⁻¹ were achieved with a productivity of 0.11 g L⁻¹ d⁻¹. Extrapolation to a 300-day production year showed that the reactor was capable of producing 541.2 kg algae and sequestering around 1 tonne of CO₂. A technoeconomic assessment showed that the total plant CAPEX was £583,905 and the OPEX was £98,196. Sales of algae alone showed poor economic performance. However, economic favourability is observed for species that contain phycocyanin pigment and yield a positive net present value within 4 to 7 years based on recovery yield. This work effectively provides reliable process data developed at scale that can be used to formulate business cases for further scale-up and expansion of algal production systems. This moves the technology a step closer to full-scale realisation and the potential for a net-zero, sustainable future. Full article

Finite-volume gravity currents frequently encounter bottom obstacles, particularly in underwater environments such as lakes and oceans. However, how obstacle–current interactions reorganize Lagrangian transport pathways and ultimately determine the fate of fluid elements over the full current life cycle remains unclear. Using large-eddy simulations, we focus on a low-volume lock-exchange gravity current impinging on an isolated two-dimensional triangular obstacle. Fluid-element trajectories are tracked from collapse through propagation, obstacle interaction, and final dilution and decay, and are classified using K-means clustering into five transport modes linked to characteristic flow structures. We find that increasing obstacle slenderness strengthens upstream reflection and reduces downstream overflow, thereby shifting the fate of tracer particles from downstream delivery toward upstream retention. In addition, the obstacle standoff distance controls the dynamical state of the current at impact, producing systematic yet non-monotonic changes in the fractional population of the transport modes. This study establishes an explicit correspondence between evolving flow structures and clustered Lagrangian pathways. Comparative cases with varying geometric configuration, density contrast, flow depth, and release volume indicate that the identified transport patterns are reasonably robust. Therefore, the present results provide a fate-oriented predictive framework and theoretical basis for the transport of finite-volume gravity currents near obstacles, with important implications for engineering applications. Full article