Search Results (3,565)

Metal additive manufacturing based on Fused Filament Fabrication (FFF) of metal-filled polymers is emerging as a cost-effective alternative to conventional processes such as Metal Injection Molding (MIM), but its industrial relevance remains limited by challenges in densification and mechanical performance. This study presents an exploratory investigation of a low-cost FFF process using 316L stainless steel filament for industrial applications in railway maintenance. A Taguchi L8 design was employed as a screening approach to evaluate the influence of key printing parameters, followed by sintering using both internal and external configurations. The mechanical response depended strongly on sintering temperature: sintering at 1350 °C increased the ultimate tensile strength to 216–278 MPa and Young’s modulus to 63–109 GPa, while the apparent porosity remained between 12.6% and 16.9%. In the exploratory main-effects analysis of variance ANOVA, none of the investigated printing parameters had a statistically significant effect on the measured responses (p > 0.05). For porosity at 1350 °C, nozzle diameter nevertheless showed the largest descriptive contribution (23.81%, F = 2.06, p = 0.2241). Overall, porosity introduced during the printing stage remained a major limitation of the process. Although the achieved properties remain below those of conventionally processed 316L, the process demonstrates potential for non-structural and cost-sensitive applications. Because each factor combination was tested once, the ANOVA and signal-to-noise S/N results are interpreted as exploratory screening and response ranking rather than confirmatory inference or independent evidence of robustness. Full article

Robotic joint motor drive systems must combine torque density and dynamic response with low mechanical impedance, safe interaction, and thermal robustness. This review treats gear ratio as a system-level design coordinate realized jointly by the motor, transmission, thermal path, sensing, and control. It synthesizes how ratio selection changes torque–speed capability, reflected inertia, losses, thermal duty, reducer nonidealities, backdrivability, and control bandwidth. The proposed spectrum uses nominal ratio as its primary coordinate while treating reducer topology, application domain, integration level, and compliance as distinct, overlapping descriptors. Mechanism-level conclusions are based on peer-reviewed studies; manufacturer specifications, open-source structures, and model-based engineering examples are identified and interpreted within narrower evidence boundaries. Representative robotic-joint cases connect these mechanisms to application demands, and an iterative framework translates the synthesis into checks on the task envelope, motor–reducer matching, thermal feasibility, transmission nonlinearity, sensing, and control. Relative to gearbox-centered reviews and task-specific motor–transmission optimization studies, this review provides a cross-domain decision map rather than a product ranking or universal predictive model. Full article

Conventional international rankings assess urban efficiency via context-blind metrics, a design that the literature suggests may structurally disadvantage Mediterranean centres and obscure the sustainable policy pathways mandated by the Sustainable Development Goals, most notably the governance of urban transitions under SDG 11. This paper proposes the Context-Weighted Liveability Index (CWLI), which introduces context-sensitive weights into the aggregation of standard smart city KPIs, bridging the global comparability of IMD-style indices with the Mediterranean-specific assessment logic of the ASCIMER framework. Weights derive from five geographic coefficients—climate, culture, economy, historical density, and demography—through a transparent weighted additive formulation with an explicit sensitivity matrix, whose robustness is verified through Monte Carlo uncertainty analysis over 5000 perturbed configurations spanning parameters, coefficients, measurements and benchmarks. Coefficients and KPIs are computed from open spatial data through a replicable GIS protocol (QGIS; OpenStreetMap, Copernicus land cover and land surface temperature, and ISTAT/ELSTAT census data at sub-municipal scale). Applied comparatively to Bologna and Athens, the framework shows that contextual weighting concentrates over 60% of the total weight on climate-sensitive indicators and yields, through the decomposition of contributions, a policy diagnosis that differs from the one suggested by reading an overall smart city rank in isolation: Athens’ largest contribution is digital and its liveability deficit territorial—a profile with direct consequences for sustainable urban transition and talent attraction. Implications for SDG 11 monitoring, equitable access to urban green space, and digital twin integration are discussed. Full article

Subcooled flow boiling of distilled water was investigated in a vertical annular minichannel with smooth and surface-modified heated tubes. Copper and stainless-steel substrates were tested with ZnO and ZnO/PMHS coatings; Al₂O₃ was additionally tested on stainless steel. A simplified one-dimensional cylindrical model provided local effective heat transfer coefficients, and modified surfaces were compared pointwise with smooth references at matched operating conditions and axial positions. A modification was considered favourable only when the heat transfer coefficient increased without an increase in wall temperature. ZnO on stainless steel was the only modification meeting this criterion at both nominal mass flow rates: the mean pointwise coefficient increased by 44.2% at 7 kg/h and 42.9% at 10 kg/h, while mean wall temperature decreased by 36.9 and 32.8 K, respectively. Al₂O₃ and ZnO/PMHS on stainless steel reduced the coefficient and increased wall temperature, whereas copper modifications showed no robust improvement relative to the designated references. A separate model-sensitivity assessment did not alter the qualitative ranking. ZnO-modified stainless steel was therefore the best-performing configuration within the tested matrix; no broader superiority is claimed beyond the present geometry, fluid, flow rates, and heat-flux range. Full article

Background/Objectives: Malocclusion and delayed expressive language are generally managed as separate clinical problems, although both may be influenced by early feeding experiences and stomatognathic development. This study whether neonatal feeding modality was associated with occlusal morphology and expressive language development in preterm children, and explored the relationship between these outcomes. Methods: Forty preterm children (gestational age < 37 weeks; corrected age, n = 14), tube feeding with structured non-nutritive sucking (NNS) (Group B, n = 13), and total parenteral nutrition without oral stimulation (Group C, n = 13). Seven of 47 children assessed were excluded according to predefined eligibility criteria. morphology was independently evaluated by two blinded paediatric dentists (Cohen’s κ = 0.91). Expressive language was evaluated using the MacArthur–Bates Communicative Development Inventories and a structured phonological checklist. Group differences were analysed using Kruskal–Wallis and Dunn–Bonferroni tests; associations were examined using Spearman ‘s rank correlation and multivariable ordinary least squares regression adjusted for sex, area of residence, and socioeconomic status. Results: Significant differences were observed among three feeding groups in occlusion score, language score, and age at first words (all p < 0.001; ε² = 0.81–0.90). Occlusion and language scores were strongly associated (Spearman’s ρ = 0.986, p < 0.001), and this association remained essentially unchanged after adjustment for demographic covariates (β = 2.10, 95% CI 2.01–2.19). Occlusal morphology subtypes also differed significantly across groups (χ²(6) = 19.1, p = 0.004). Conclusions: p = 0.004). Neonatal feeding modality was associated with both occlusal morphology and expressive language outcomes in this cohort of preterm children. Breastfeeding was associated with the most favorable outcomes, structured NNS with intermediate outcomes, and TPN with the least favorable outcomes. Given the observational design, modest sample size, and potential for residual confounding, findings should be considered exploratory and require confirmation in larger prospective multicenter studies. Full article

Background/Objectives: Social determinants of health, including income, age, education, and gender, have been proposed to shape diabetes self-care capacity, yet their joint associations within Saudi Arabian primary healthcare populations remain poorly delineated. Anchored within the World Health Organization’s Commission on Social Determinants of Health framework and the Social Ecological Model, this study examined both the unadjusted and, via multivariable regression, adjusted associations of four sociodemographic factors with diabetes self-care management and health literacy among adults in southern Riyadh. Methods: A cross-sectional correlational design was employed with 92 adults with type 2 diabetes recruited from primary healthcare centers in southern Riyadh. Data were collected using the Arabic HLS-Q12 (health literacy) and SDSCA-Arabic (self-care management). Non-parametric Spearman rank-order correlations were conducted to examine bivariate associations. Multivariable linear regression was subsequently performed to estimate adjusted associations for each sociodemographic variable. Bivariate analyses were conducted using IBM SPSS Statistics for Windows, Version 25.0 (IBM Corp., Armonk, NY, USA), while multivariable linear regression analyses were performed using Python version 3.12 with the statsmodels package. Results: Income level showed significant, moderate positive unadjusted correlations with both self-care management (rs = 0.40, 95% CI [0.21, 0.56], p < 0.01) and health literacy (rs = 0.41, 95% CI [0.22, 0.57], p < 0.01). Age showed the strongest negative unadjusted correlation with self-care management (rs = −0.49, 95% CI [−0.63, −0.31], p < 0.01) and a significant negative correlation with health literacy (rs = −0.36, 95% CI [−0.53, −0.17], p < 0.01). Educational attainment was significantly associated with both self-care management (rs = 0.29, 95% CI [0.09, 0.47], p < 0.01) and health literacy (rs = 0.26, 95% CI [0.06, 0.44], p < 0.05). Gender did not reach statistical significance for either outcome. A multivariable model adjusting for all four sociodemographic variables confirmed that income and age remained independently associated with both outcomes, whereas education and gender did not. These findings do not establish independent or causal effects from the bivariate correlations alone; the adjusted results are reported separately below. Conclusions: Income and age were independently associated with both diabetes self-care and health literacy after multivariable adjustment, whereas education and gender were not. Findings support equity-focused nursing interventions and age-responsive diabetes education attentive to the social patterning of self-care disparities in southern Riyadh. Full article

Prior studies have commonly examined organizational structure, managerial processes, construction logistics, productivity, and project complexity through separate research streams, leaving limited empirical evidence on how these domains are positioned within a single multilevel construction management framework. This study develops an integrated analysis of their relationships using data from construction firms operating in Cochabamba, Bolivia, and the Metropolitan Region of Curitiba, Brazil. A quantitative, non-experimental, cross-sectional design was adopted, and 108 valid survey responses were analyzed through descriptive statistics, correlation analysis, Exploratory Factor Analysis, Principal Component Analysis, reliability assessment, regional comparison, and Relative Importance Index ranking. The results showed that formal organizational characteristics displayed comparatively limited direct associations with performance-related variables, whereas stronger relationships were concentrated among managerial, strategic–logistical, and operational processes. The project complexity analysis retained three dimensions—technical, process-stage, and planning-related complexity—which jointly explained 61.271% of the rotated variance. At the operational level, equipment and tool maintenance, schedule adherence, and material storage received the highest Relative Importance Index values, with RII = 0.776 for each item. The findings indicate that construction performance is more closely associated with the dynamic processes through which information, decisions, responsibilities, and resources are coordinated than with formal structure considered independently. The study contributes a multilevel conceptual framework in which project complexity is interpreted as increasing the coordination requirements linking organizational arrangements, managerial processes, logistics, and operational reliability. Full article

Vanadium slag is an important secondary vanadium resource. Although microwave-assisted calcification roasting improves the leachability of vanadium-bearing phases, further extraction can still be limited during acid leaching, making optimization of the leaching process essential for efficient vanadium recovery. Using this slag, leaching was evaluated at different temperatures, times, liquid-to-solid ratios (L/S), sulfuric acid concentrations, and agitation speeds. A Box–Behnken design (BBD) was used to optimize leaching parameters within the selected ranges. Residue phase composition and microstructure were characterized by X-ray diffraction (XRD), scanning electron microscopy (SEM), and energy-dispersive spectroscopy (EDS). Leaching efficiency increased with temperature, L/S, and acid concentration, but plateaued above 60 °C, 6 mL·g⁻¹, and 14 wt.%, respectively; increases beyond 50 min or 200 rpm gave marginal improvements. Analysis of variance (ANOVA) of the BBD model ranked the statistical effects of the four linear terms within the investigated BBD range as sulfuric acid concentration > L/S > leaching time > temperature. Within the selected BBD parameter ranges, optimization yielded 64.95 °C, 55.21 min, 6.56 mL·g⁻¹, and 15.17 wt.% sulfuric acid, with agitation fixed at 200 rpm. Validation gave an average leaching efficiency of 92.92%, with a relative error of 0.205% compared with the model prediction. After leaching, Mn₂V₂O₇ was undetected. The residue mainly contained irregular particles, 10–30 μm acicular or plate-like CaSO₄·2H₂O crystals, and minor residual vanadium-bearing CrVO₃ and CaVH₂Si₄O₁₂ phases. Surface CaSO₄·2H₂O deposition and refractory-phase encapsulation of vanadium-bearing constituents increased mass-transfer resistance and limited further leaching. This study clarified the relative effects of the investigated leaching conditions on vanadium leaching efficiency within the design range and the interactions among these conditions, and provided microstructural evidence related to the factors limiting further vanadium leaching, thereby providing theoretical guidance for the efficient extraction of vanadium from vanadium slag. Full article

Evacuated-tube solar collectors charged with hybrid nanofluids can raise thermal output, but their coupled thermal and hydraulic response depends on many interacting variables, making the design an optimisation rather than a prediction problem. This study recasts it as a constrained, mixed-variable, three-objective task that maximises thermal efficiency and the Nusselt number while minimising pumping power over the hybrid pair, base fluid, weight fraction, component-one share and flow rate, and develops a memetic metaheuristic: the Adaptive Memetic Hybrid (AMH). A histogram gradient-boosted surrogate trained on 54,432 reduced-order runs, with held-out coefficients of determination of at least 0.9999, provides a fast screen, while a continuous reduced-order model validated to within 0.02 percent serves as the objective; the surrogate is accurate off-grid for efficiency but not for pumping power or the Nusselt number. Nine optimisers, comprising four baselines, three recent metaheuristics, and two AMH variants, were validated on twelve ZDT, DTLZ, and constrained problems over thirty trials using the hypervolume, generational distances, and spacing, and analysed with Friedman, Nemenyi, and Holm-corrected Wilcoxon tests. AMH attained the best mean Friedman rank of 3.08 (chi-square 65.7, p = 3.6 × 10⁻¹¹), significantly outperforming the recent methods and NSGA-III and remaining competitive with the strongest classical algorithms. On the collector, the reduced-order front recovers the 1512-design brute-force maximum efficiency to within 0.02 percent and improves the trade-off through continuous flow rates. The study is a deterministic, model-based optimisation process: the surrogate serves as a tool for fast screening and diagnostics, while the reconstructed reduced-order model is the objective for the final continuous optimisation. The collector application has a low effective design dimension, being governed mainly by the base fluid and the loop flow rate, so the decisive separation of the algorithms is established on the benchmark suite rather than on the collector. Experimental validation remains a task for future work. Full article

Background: Gender disparities have been reported in Emergency Medicine (EM) residency milestone attainment, with some studies showing male residents achieving higher competency-based ratings than female residents despite similar clinical exposure. Prior research suggests subjective faculty evaluation and implicit bias may contribute to these differences. The influence of resident self-assignment of patients on milestone attainment remains unclear, and the potential contribution of differential patient exposure through self-selection has not been directly investigated. Objectives: To determine whether gender differences exist in the types of patients or acuity levels that EM residents self-assign to determine if this could potentially explain the differences seen in EM milestone achievement across genders. Methods: Design and Setting: Retrospective chart review of EM resident patient selection at the Mayo Clinic Arizona Emergency Department from September 2018 through December 2022. Patients: The study was conducted at a single academic emergency department with resident and attending physician staffing. The study was determined to be IRB exempt. Data Collection: Epic electronic medical record data included resident and attending gender, patient demographics, chief complaint, Emergency Severity Index (ESI) triage level, vital signs, method of arrival, and procedures performed. Statistical Analysis: Continuous variables were compared using Student’s t-test or Wilcoxon rank-sum test; categorical variables were compared using chi-square test. Significance was set at p < 0.05. Analyses were performed using SAS version 9.4. Results: A total of 14,279 cases were analyzed. No significant differences were observed between female and male residents in patient chief complaint, age, race, gender, means of arrival, attending gender (p = 0.10872), or total procedures performed (p = 0.23102). Female residents saw patients with higher initial respiratory rates (p = 0.04313) and trended non-significantly toward higher-acuity ESI levels 1–2 (p = 0.07214). Conclusion: When residents self-assign patients in the emergency department, no meaningful gender differences exist in patient selection, procedural exposure, or gender attending assignment. These findings suggest that observed gender disparities in milestone attainment are unlikely driven by clinical exposure or patient selection, supporting that other factors may contribute to these differences. Full article

Developers increasingly reuse third-party Low-Rank Adaptation (LoRA) adapters for code-generation models without visibility into how they were trained, creating a supply-chain risk: a maliciously trained adapter can behave normally on clean inputs while activating attacker-controlled functionality when a specific trigger is present. This study makes a mechanistic contribution to that risk: we show that trigger modality, not just contamination rate, determines a qualitatively different backdoor learning regime. We trained 61 poisoned variants of CodeGen-350M-mono on the CodeSearchNet dataset, injecting eight backdoor triggers spanning two categories: three semantic triggers based on natural-language code comments and five syntactic triggers based on structural code transformations derived from the CodePoisoner framework. Across attack success rate measurement, cross-trigger confusion analysis, mechanistic circuit tracing, layer-restoration defense evaluation, and semantic generalization testing, we find that semantic triggers produce associative binding: a 91% attack success rate, a Trigger Specificity Index (TSI) of 268×, distinct per-trigger circuits concentrated in attention layers, and a requirement to restore 10 parameter groups for removal. Syntactic triggers instead produce distributional confusion: a 31% attack success rate, a TSI of only 1.25× (1.45× once a shared-payload confound in the confusion-matrix design is corrected for), diffuse circuits spread across (Multi-Layer Perceptron) MLP layers, and collapse with just 5 restored parameter groups. Cross-payload testing on single-trigger models confirms this: structural triggers fire on triggers never seen during training at rates of 42 to 55%, showing that the model learns a general association between code abnormality and payload generation rather than a specific trigger–payload mapping. Both regimes preserve clean code-generation quality across all contamination rates, so a downloaded backdoored adapter is behaviorally indistinguishable from a clean one under standard benchmarks. These results argue against a one-size-fits-all approach to adapter auditing: detection and removal strategies calibrated to one trigger modality can fail outright against the other, and we outline the conditions under which each applies. Full article

This study proposes the Turtle Optimization Algorithm (TOA), a bio-inspired metaheuristic motivated by the long-distance navigation behavior of marine turtles. TOA integrates four main mechanisms: geomagnetic orientation modeled through sinusoidal modulation, ocean current drift, stamina-aware adaptive reference selection, and an Environmental Coordination Strategy (ECS). These mechanisms are jointly designed to balance exploration and exploitation while reducing premature convergence. The TOA was evaluated on 29 benchmark functions, including classical and CEC2019 benchmarks, and compared with established and recent metaheuristic algorithms. Friedman analysis revealed statistically significant differences among the compared methods (p < 0.05). The TOA achieved first place average ranks of 1.43 and 1.33 in two classical benchmark comparison groups. On CEC2019, TOA obtained average ranks of 1.60, 3.20, and 2.70, corresponding to first, second, and first place, respectively. The practical applicability of the TOA was further evaluated on three constrained engineering design problems––welded beam, speed reducer, and clutch brake design––where competitive solutions were obtained. Overall, the results demonstrate that the TOA provides a competitive and robust optimization framework across diverse benchmark and engineering problems. Full article

Public owners selecting design-build (DB) teams for sustainable buildings must justify how proposal evidence, long-term asset performance, and procurement accountability support a preferred contractor. Prior contractor-selection and hybrid MCDM studies provide criteria and ranking tools, but they rarely connect public-building requirements, mandatory floors, proposal evidence anchors, weighting, scoring, and auditability before mathematical ranking. The aim of this study is to develop and numerically demonstrate an evidence-traceable SWOT-AHP-TOPSIS framework for sustainable DB contractor selection in California courthouse procurement. Here, California courthouse procurement refers to public-owner procurement of judicial courthouse facilities in California, United States, under public-building procurement rules and publicly available RFQ/RFP-related records. The framework fixes source-linked criteria, SWOT role definitions, benefit directions, evidence anchors, and compliance floors before criteria weights are obtained using AHP and alternatives are ranked using the TOPSIS method. The proof of concept derives 16 criteria from procurement guidance, California courthouse records, and the literature; reports local and global criteria weights obtained using AHP; and compares synthetic proposal archetypes. Under baseline illustrative weights, A1 ranks first (C* = 0.6548), followed by A3 (0.5804) and A2 (0.3294). Robustness checks using the disclosed matrices show conditional stability: vector, min–max, and linear-sum TOPSIS, equal-criterion weights, weighted-sum comparison, grouped +20% scenarios, comparison-set checks, and 10,000-run Monte Carlo perturbation retain A1 most frequently. The Monte Carlo run selected A1 first in 79.80% of simulations, A3 in 20.19%, and A2 in 0.01%, with top-two practical ties in 7.10% of runs. The results demonstrate arithmetic consistency, reproducibility, and interpretable ranking behavior under stated synthetic assumptions; they do not establish actual evaluator preferences, real proposal quality, award outcomes, or generalizability beyond California courthouse settings. Full article

Sustainable Development Goal 7 requires energy access to be affordable, reliable, sustainable, and modern. However, SDG 7 progress is often monitored at national levels through binary access indicators that do not adequately capture household-level energy realities. This study addresses this measurement gap and develops a 0–100 Household SDG 7 Attainment Index from three equally weighted pillars, the Household Energy Affordability Index, Household Energy Reliability Index, and Household Energy Sustainability Index and applies it to data from 659 rooftop solar households. The corrected index produced a mean attainment score of 88.81 (95% bootstrap confidence interval: 88.00–89.52). Threshold sensitivity analysis showed that the mean ranged from 86.37 to 90.29 under ±20% alternative specifications, while Spearman rank correlations with the baseline ranged from 0.941 to 1.000. A scenario-based Monte Carlo analysis further quantified household-level uncertainty arising from plausible reporting error. Random Forest, permutation importance, node-purity diagnostics, DALEX, and iBreakDown-based local interpretability methods were also used. Random Forest regression achieved an independent-test RMSE of 7.03, MAE of 4.57, MAPE of 5.92%, and predictive R² of 0.592. Income was the dominant predictor, followed by solar-rooftop usage, first device, job type, and electric vehicle profile. Partial dependence showed a rapid increase in predicted attainment at lower income levels followed by a plateau. The study contributes a household-level SDG 7 diagnostic framework that can support government targeting, subsidy design, rooftop solar policy evaluation, and the identification of households that remain behind despite solar adoption. Full article

Space Station Operation Mission Planning (SSOMP) requires coordinated decisions across long-term activity allocation, mid-term logistics optimization, and short-term execution scheduling and is a key component of autonomous mission operations for high-precision space missions. Existing optimization methods have achieved substantial progress at individual planning levels, but their dependence on problem-specific models, limited support for semantic review of decision rationale, and computational cost restrict their adaptability to multi-level planning scenarios. This paper proposes a Large Language Model (LLM)-assisted framework for multi-level SSOMP. The framework combines Staged Fine-Tuning (Staged-FT), Reflective Constraint–Repair Prompting (RCRP), and LLM-Guided Evolutionary Variation (LGEV). Staged-FT uses a Cognitive-Load-Theory-informed curriculum with Low-Rank Adaptation to adapt general-purpose LLMs to SSOMP domain knowledge. RCRP couples a Deterministic Rule Engine with LLM-based semantic repair to improve hard constraint satisfaction. LGEV embeds the fine-tuned LLM into NSGA-III as a fitness-aware variation operator for multi-objective activity allocation. Three case studies are conducted on literature-derived benchmark scenarios of logistics optimization, emergency re-planning, and activity allocation with logistics design, corresponding to Flight Increment Planning, Short-Term Execution Planning, and Overall Operation Planning, respectively. Results show that Staged-FT produces solutions close to traditional algorithms, RCRP achieves full hard constraint satisfaction in the emergency re-planning and logistics planning cases, and LGEV reduces the convergence generations of NSGA-III while improving Pareto-front quality. The framework provides a constraint-aware approach with explicit reasoning traces that can support expert review of AI-assisted planning for autonomous space mission operations. Full article