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With only 15.4 percent of sub-Saharan Africa’s population covered by formal social protection, most people depend on indigenous social provisioning. Despite their extensive coverage and socio-cultural legitimacy, these arrangements remain marginal in policy design, largely due to their persistent framing as residual, informal coping mechanisms within state-centric paradigms. This paper challenges that framing by conceptualising indigenous social provisioning as an institutionally autonomous domain with transformative potential. Using an integrative literature review, the study analyses key provisioning arrangements across sub-Saharan Africa and maps their functions onto the framework of Transformative Social Policy (TSP), which emphasises production, protection, redistribution, reproduction, and social cohesion. The findings show that indigenous systems extend beyond safety net functions to enhancing productive capacities and supporting livelihoods, redistributing resources, sustaining social reproduction, and fostering social cohesion for collective agency. However, their transformative capacity is often limited by internal inequalities. The paper argues that inclusive social policy requires a shift from substitution to institutional complementarity, in which indigenous and formal systems operate as mutually reinforcing pillars. By foregrounding Africa’s institutional heritage, the study contributes to ongoing efforts to decolonise social policy theory and practice. Full article

17 pages, 972 KB

Open AccessSystematic Review

Quality of Outcome Reporting for Older Subgroups in FDA Registration Gastroesophageal Cancer Trials (2010–2024): A Systematic Review

by Ilse Trip, Martha Kormi, Elizabeth Smyth, Russell D. Petty and Mark A. Baxter

Cancers 2026, 18(17), 2747; https://doi.org/10.3390/cancers18172747 - 24 Aug 2026

Abstract

Background: Gastroesophageal adenocarcinoma is predominantly a disease of older adults. However, older adults are underrepresented in randomised controlled trials (RCTs), and outcomes specific to this subgroup are underreported. Clinicians therefore extrapolate data from younger, fitter trial populations, which can lead to over- and undertreatment of older cancer patients. This study examines the inclusion and completeness of outcome reporting for older patients in practice-changing trials in gastroesophageal cancer. Methods: RCTs were identified from United States Food and Drug Administration (accelerated) approvals between 2010 and 2024. The primary study report, clinicaltrial.gov repository and all relevant secondary publications were assessed for the level of reporting of outcomes. Efficacy outcomes were reported as complete, partial, qualitative or quantitative based on availability of sample size, effect size and measures of precision. Baseline characteristics, toxicity outcomes and health-related quality of life (HRQOL) outcomes were assessed using minimum data thresholds. Results: In total, 13 trials, 53 publications and 13 repository webpages were assessed. A total of 9320 patients were included, of which 40.1% were classified as older adults. Among the patients, 42.2% had an Eastern Cooperative Oncology Group (ECOG) Performance Status (PS) of 0, with all but one trial excluding patients with an ECOG PS of 2 (n = 63). Baseline characteristics and toxicity outcomes for older adults were fully reported in only two trials (15.4%). Reporting of HRQOL outcomes (25.0%), secondary (20.0%) and primary endpoints (66.7%) was more complete. Overall survival (76.9%) and progression-free survival (67.0%) were the most commonly reported primary or secondary endpoints. Conclusions: This study highlights deficits in the outcome reporting of older cancer patients in GOA trials. Simultaneously, this subgroup also remains heavily underrepresented in GOA trials compared to the real-world patient population. These findings highlight the need for improvements in both trial design and outcome reporting standards for older adults. Full article

(This article belongs to the Special Issue Cancer and Aging: Challenges in Geriatric Cancer Survivorship)

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30 pages, 1604 KB

Open AccessArticle

How Tax–Subsidy Policies Shape Battery Recycling Strategies Under the Extended Producer Responsibility System

by Yuling Sun, Siyu Yao, Shihan Qian and Shuting Wei

Mathematics 2026, 14(17), 3050; https://doi.org/10.3390/math14173050 - 24 Aug 2026

Abstract

To address the increasing volume of end-of-life power batteries, governments leverage Extended Producer Responsibility (EPR) regulations to encourage battery suppliers to increase recycling. We develop a Stackelberg game model for a closed-loop supply chain (CLSC) that includes a government, a battery supplier, an NEV manufacturer, and a third-party recycler. The model endogenizes tax–subsidy decisions while incorporating cascade utilization, competitive intensity, and environmental damage from informal channels. We compare three recycling modes: manufacturer–supplier competition (MSC), manufacturer–third-party competition (MTC), and manufacturer–third-party alliance (MTA). Our analysis addresses three main issues. First, the structure of recycling modes affects the equilibrium decisions of CLSC members: pricing under MSC is governed by a threshold effect of cascade utilization, whereas pricing under MTC depends on relative cost differences. Second, higher cascade utilization strengthens the supplier’s pricing power under MSC, whereas intensified competition reduces the profits of the supplier and government under MSC and MTC; by contrast, the profits of the supplier and government under MTA remain stable. Third, environmental damage encourages the government to raise the subsidy level provided to suppliers for battery recycling. These findings offer practical guidance for designing adaptive EPR policies that balance economic and environmental objectives. Full article

(This article belongs to the Special Issue Mathematical Modelling and Optimization of Service Supply Chain, 2nd Edition)

34 pages, 2781 KB

Open AccessArticle

Integration of BIM and Cloud-Based Tools for LEED Sustainable Building Design: A Case Study

by Bogdan Chelaru, Gabriela Ungureanu and Cătălin Onuțu

Buildings 2026, 16(17), 3377; https://doi.org/10.3390/buildings16173377 - 24 Aug 2026

Abstract

This research assesses the practical synthesis of Building Information Modeling (BIM), Autodesk Forma and Dalux to support LEED-oriented sustainable design for a higher education building. Autodesk Revit 2025 functioned as the central BIM platform, while Autodesk Forma enabled early-stage simulations of solar exposure, daylight potential, wind conditions, microclimate, noise and solar-energy potential. Dalux supported model coordination and information management in accordance with ISO 19650 principles. The workflow links simulation outputs to BIM elements through project-defined parameters, allowing performance evidence to inform design refinement. Quantitative indicators were consolidated for daylight exposure, wind comfort, outdoor thermal stress, acoustic exposure and photovoltaic potential. The solar-energy analysis considered an area of approximately 970 m², an annual potential of 1030 kWh/m² and a theoretical yield of approximately 999,100 kWh/year. Assuming 70% roof coverage and 18% panel efficiency, the estimated photovoltaic the expected output is approximately 125,113 kWh/year. These findings demonstrate the value of combining BIM, cloud-based analysis and CDE-based coordination for early-stage sustainable design, while LEED certification, operational energy modelling and lifecycle assessment require additional specialist validation. The proposed workflow provides a consistent approach for aligning design development with sustainability objectives and can be applied to similar building types. Full article

(This article belongs to the Special Issue Building Information Modelling (BIM) Applications in Construction Management: 2nd Edition)

33 pages, 2364 KB

Open AccessArticle

The Paradigm Shift in Education: Stakeholder Perceptions of Generative AI in Teaching–Learning Dynamics

by Stoica Silviu-Ionel and Vasciuc Sandulescu Cristina Gabriela

Sustainability 2026, 18(17), 8678; https://doi.org/10.3390/su18178678 - 24 Aug 2026

Abstract

The study explores the paradigm shift in education brought about by the introduction of generative artificial intelligence (AI) tools, focusing on educational stakeholders’ self-reported perceptions rather than observed changes in teaching or learning outcomes. We consider stakeholders’ views on AI-based technologies within the teaching–learning process. The current study uses a cross-sectional empirical survey design with a sample of N = 917 respondents, including teachers, students, administrators, and management. It examines the use of advanced AI technologies such as ChatGPT, Gemini, DeepSeek, and Grok, and stakeholders’ perceived connection between digital skills and classroom performance, student motivation, and critical thinking. We also discuss the ethical dilemmas and structural challenges that accompany this digital change. Inferential statistics, such as One-Way ANOVA and the Pearson Chi-Square test, show statistically significant differences in perceptions and regulatory expectations across organizational responsibilities. The findings contribute to understanding how advanced digitalization is perceived to reshape traditional academic roles, offering practical insights for creating effective, responsible, and sustainable teaching practices. Full article

(This article belongs to the Section Sustainable Education and Approaches)

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26 pages, 340 KB

Open AccessArticle

Designing Inclusive Multimodal Learning Content with Generative AI for Migrant Adult Literacy: A Practice-Oriented Methodological Proposal

by Daniela Marzano and Antonella Senese

Multimedia 2026, 2(3), 14; https://doi.org/10.3390/multimedia2030014 - 24 Aug 2026

Abstract

This article presents a practice-oriented methodological proposal for designing inclusive multimodal learning content with Generative AI (GAI) in migrant adult literacy. It does not report an experimental intervention or a statistical evaluation of learning outcomes. Its contribution lies in formalizing a context-sensitive design pathway for early preA1–A2 literacy and language-learning provision in Italian CPIA settings, where learner profiles are highly heterogeneous, attendance may be discontinuous, and written language is both a learning goal and a barrier to participation. Unlike generic AI-supported instructional design frameworks, the proposed approach starts from recurrent communicative needs in adult migrant education and translates them into short, modular and reusable learning artifacts that coordinate textual, visual, audio-oral and interactive layers. The framework distinguishes multimodal design, understood as the pedagogical coordination of different semiotic modes, from the mere use of multiple media. It also integrates accessibility as a set of concrete design criteria, including linguistic readability, visual clarity, audio quality, layout, font size, contrast, cognitive load and usability in print or mobile formats. The article outlines a sequence of design operations: mapping learner profiles, selecting situated communicative scenarios, generating and revising textual material, developing visual and audio scaffolds, structuring guided interaction, and applying pedagogical, cultural and ethical review. An illustrative micro-unit on asking for information at a municipal office shows how this pathway can support dialog, visual glossary, audio practice, role-play and formative assessment. The proposal is intended for CPIA educators, adult literacy professionals, instructional designers and researchers in multimedia learning and educational technology. Its educational implication is that GAI can support inclusive material design only when its outputs are treated as provisional resources to be selected, adapted and validated through human pedagogical judgment. Full article

61 pages, 3931 KB

Open AccessReview

From Melt Miscibility to Crystallization: Rheological and Thermal Analysis of Polyethylene Blends for Recycling Applications

by Nicole R. Demarquette, Judith Zaessinger, Daria Strugova, Amin Mirzadeh, Eunse Chang and Céline T. Bellehumeur

Polymers 2026, 18(17), 2054; https://doi.org/10.3390/polym18172054 - 24 Aug 2026

Abstract

Plastic waste management remains a major challenge, and the mechanical recycling of polyethylene (PE) is complicated by the coexistence of HDPE, LDPE, and LLDPE grades that are difficult to separate. This review critically examines the miscibility, apparent miscibility, compatibility, and crystallization behavior of PE blends, with an emphasis on linear viscoelastic rheology and thermal analysis. Rheological criteria, including additivity, Cole–Cole, time–temperature superposition, Han, and van Gurp–Palmen analyses, were evaluated, together with DSC and successive self-nucleation and annealing. Most studies indicate that HDPE/LDPE blends are melt-immiscible. HDPE/LLDPE blends more frequently exhibit apparent melt miscibility when LLDPE has low short-chain branching, typically below 15 branches per 1000 carbon atoms, and relatively low molar mass; increasing molar mass generally promotes immiscibility. LDPE/LLDPE behavior is less systematic and depends on branch content and distribution, molar mass, and catalyst-controlled molecular architecture. Crystallization does not necessarily mirror melt miscibility. HDPE/LLDPE co-crystallization is generally favored at high HDPE contents but strongly depends on branching, comonomer type, and cooling conditions, while LDPE/LLDPE may co-crystallize despite apparent melt immiscibility. These trends provide practical guidelines for designing recycled PE blends with more predictable processing and properties. Full article

(This article belongs to the Section Circular and Green Sustainable Polymer Science)

33 pages, 13344 KB

Open AccessArticle

Bearing Single-Source Domain Generalization Fault Diagnosis Method Based on Adaptive Frequency-Domain Augmentation and Unsupervised Contrastive Learning

by Kaisheng Deng and Ping Qu

Sensors 2026, 26(17), 5349; https://doi.org/10.3390/s26175349 - 24 Aug 2026

Abstract

Cross-domain distribution shifts severely degrade the diagnostic performance of rolling bearing models under unseen variable operating scenarios. Single-source domain generalization (SDG) builds fault diagnosis models using only single-source vibration data, which fits the practical limitations of industrial data collection. Existing contrastive learning methods adopt uniform spectral perturbations for data augmentation, which easily corrupt fault harmonic characteristics and require massive, labeled training samples. To tackle these drawbacks, this paper proposes an unsupervised contrastive learning framework named FDACL. An adaptive frequency-domain augmentation (AFA) module equipped with learnable weights is designed to separate fault-critical frequency bands from noise components. Differentiated amplitude perturbations are applied to two categories of spectral signals to generate diverse pseudo-samples while retaining intrinsic fault information. A shared encoder is trained with combined InfoNCE contrast loss and classification loss to learn domain-invariant fault representations. Validations are carried out on three datasets, namely Case Western Reserve University (CWRU), Paderborn University (PU), and the industrial CRRC Qingdao Sifang railway wheelset bearing dataset acquired from physical test benches. FDACL achieves average cross-speed diagnostic accuracies of 92.68% and 77.85% on CWRU and PU, respectively, and maintains competitive performance on the Qingdao Sifang industrial dataset. It outperforms state-of-the-art baselines by 4.23–8.71% across all SDG transfer tasks. Ablation experiments and hyperparameter analysis verify the efficacy of the AFA module and contrastive learning scheme, providing an unsupervised diagnostic approach for railway bearings under unknown working conditions. Full article

(This article belongs to the Special Issue Deep Learning Based Intelligent Fault Diagnosis—2nd Edition)

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45 pages, 4695 KB

Open AccessArticle

Multi-Indicator Communication Quality Assessment and Multi-Modal Backup for Resilient USV Cluster Communication

by Xingda Li, Zhikun Liu, Jianqiang Zhang, Yiping Liu, Pengfei Zhang and Ling Tan

Drones 2026, 10(9), 642; https://doi.org/10.3390/drones10090642 - 24 Aug 2026

Abstract

Unmanned surface vehicle (USV) clusters operating in contested maritime environments face communication degradation from jamming, satellite denial, and partial node loss. Existing countermeasures either react after link failure or rely on a single signal quality indicator. A framework is presented that integrates two [...] Read more.

Q_{comm}

that fuses signal-to-noise ratio, packet loss rate, latency, and temporal stability into a single scalar; and (2) a multi-modal backup communication chain spanning acoustic modem, optical link, and multi-hop RF(Radio Frequency) relay that provides physical-layer redundancy when primary radio frequency links are degraded. Across five representative failure scenarios simulated on a seven-vehicle cluster with 50 independent runs per configuration, the multi-indicator

Q_{comm}

metric achieves a mean of 0.521, outperforming single-indicator baselines on the composite

Q_{comm}

metric (Cohen’s d = 8.020, p < 0.0001, n = 250 per method);

Q_{comm}

is the framework’s own optimization target; this comparison is, therefore, presented as an internal consistency demonstration rather than an independent validation. The framework reduces recovery time from 113.8 s (single-indicator) to 15.3 s—an 86.6% improvement. With the backup communication chain enabled, delivery rates exceed 94% across all methods and scenarios. A direct Monte Carlo ablation (50 seeds × 5 scenarios) reveals that multi-indicator fusion is the primary driver of assessment accuracy and recovery speed, while the multi-modal backup chain is the dominant delivery driver: without it, delivery falls from 94.6% to 24.2%. A sigmoid-blended topology utility function is included as an architectural design component; its independent validation requires extended-duration threat experiments identified as future work. The contributions of this work are the validated multi-indicator fusion metric and the multi-modal backup chain architecture, which together provide a practical foundation for resilient USV communication. Full article

(This article belongs to the Section Drone Communications)

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22 pages, 32457 KB

Open AccessArticle

Preparation and Characterization of the Properties of Atmospheric Plasma-Sprayed Sr/Mg-Doped Bioactive Glass Coatings on Titanium Alloys

by Da Zeng, Yanwen Chen, Jianfeng Chen, Cijun Shuai, Fangwei Qi, Peilin Chen and Deping Wang

Materials 2026, 19(17), 3596; https://doi.org/10.3390/ma19173596 - 24 Aug 2026

Abstract

Titanium alloys are widely used in clinical settings due to their excellent mechanical properties and biocompatibility. However, the biologically inert surface of titanium alloys limits interfacial bioactivity and bone integration, which may compromise long-term implant stability. Therefore, this study innovatively proposes a synergistic “composition design and process adaptation” strategy. Specifically, borosilicate bioactive glasses (BSBGs) with a high B₂O₃ content (36 mol%), co-doped with strontium (Sr) and magnesium (Mg), were designed and systematically compared with Sr/Mg-doped silicate bioactive glasses (SBGs). Both glasses were subsequently deposited onto Ti6Al4V substrates using atmospheric plasma spraying. The results showed that the BSBG coating exhibited an initial boron release concentration of up to 116 mg/L but exhibited excellent cytocompatibility, which is likely related to the synergistic regulation of Sr, Mg, and B ions. Moreover, the BSBG coating induced Ca-P compound mineralization within 24 h, significantly faster than the SBG coating, which required a minimum of 3 days, confirming superior biomineralization kinetics. Both coatings achieved a bonding strength of 30 MPa, meeting clinical requirements. In vivo experiments confirmed that the BSBG coating significantly promoted new bone regeneration and implant osseointegration. This work not only delivers experimental validation supporting the implementation of high-boron-content bioactive glass coatings but also provides a practical method for designing rapidly degradable and highly bioactive coatings to facilitate improved osseointegration. Full article

(This article belongs to the Section Biomaterials)

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25 pages, 2100 KB

Open AccessArticle

A Numerical Framework for Swelling-Induced Damage Evolution and Support Optimization in Expansive Mudstone Tunnels

by Kai Cui, Lichuan Wang and Zheng Yang

CivilEng 2026, 7(3), 53; https://doi.org/10.3390/civileng7030053 - 24 Aug 2026

Abstract

Expansive mudstone tunnels often suffer long-term convergence and support damage because excavation-induced unloading is coupled with water-induced swelling. This study proposes a particle flow modeling framework for expansive mudstone tunnels by linking tunnel-wall displacement, swelling pressure, and the equivalent particle radius expansion coefficient. Constant-volume swelling pressure tests were first conducted to determine the representative swelling pressure of the mudstone. An independent confined particle model was then established to calibrate the relationship between macroscopic swelling pressure and microscopic particle expansion. The results show that a stable swelling pressure of 300 kPa corresponds to an equivalent particle radius expansion coefficient of 3.11%. Incorporating this calibrated swelling mechanism into the tunnel model indicates that swelling intensifies excavation-induced damage, increasing the final crack number from 1566 to 1852 and enlarging the equivalent damage-zone diameter from 21.6 m to 22.8 m. Under the original support scheme, the damage depth reaches 5.45 m, and the final crown settlement reaches 177.6 mm. After reinforcement, these values decrease to 3.40 m and 81.1 mm, respectively. Field monitoring confirms the predicted deformation-control trend. The proposed framework provides a practical approach for simulating swelling-induced damage evolution and optimizing support design in expansive mudstone tunnels. Full article

(This article belongs to the Section Geotechnical, Geological and Environmental Engineering)

20 pages, 2616 KB

Open AccessArticle

MSDR-Mamba: A Multi-Scale Branch-Decoupled Routing State-Space Detector for Temporal Action Localization

by Ruijun Gu, Wenyang Bi, Yu Han, Yijie Zhu, Jiaju Wu, Zhenghao Xie and Song Ye

Electronics 2026, 15(17), 3797; https://doi.org/10.3390/electronics15173797 - 24 Aug 2026

Abstract

Temporal action localization (TAL) requires a detector to recognize action categories and estimate temporal boundaries in untrimmed videos. Mamba supports linear-complexity long-sequence modeling, yet a uniform allocation of state-space operators does not explicitly differentiate the context requirements associated with temporal scales and prediction branches. We present Multi-Scale Decoupled Routing Mamba (MSDR-Mamba), a multi-scale branch-decoupled routing state-space detector. The method combines a phase-dilated multi-rate Mamba temporal pyramid, multi-band state-time initialization, level-wise local–global gating guided by duration priors, and a branch role-decoupled head. The final head uses CNNs for classification and center-offset estimation, with Mamba used for class-specific start/end boundary neighbor modeling. With frozen InternVideo2-6B features on THUMOS14, MSDR-Mamba achieves a five-threshold mAP of 73.09%, exceeding TriDet by 0.43 percentage points. Supplementary experiments on ActivityNet-1.3 and P²ANet further evaluate the complete configuration under longer-duration and dense short action distributions. The results support scale- and branch-aware state-space modeling as a practical design strategy for TAL. Full article

18 pages, 834 KB

Open AccessArticle

Latent Profiles in the Perception of Knowledge in Emotional Education During Initial Teacher Training: A Retrospective Study of Chilean In-Service Teachers

by Gerardo Fuentes-Vilugrón, Francisco Correa-Araneda, Carlos Arriagada-Hernández, Felipe Caamaño-Navarrete and Lorena Jara-Tomckowiack

Behav. Sci. 2026, 16(9), 1469; https://doi.org/10.3390/bs16091469 - 24 Aug 2026

Abstract

Emotional education is fundamental in teacher training due to its impact on teacher well-being and student learning. In Chile, initial teacher training has addressed this dimension in a fragmented manner, and little is known about whether in-service teachers exhibit distinct patterns of retrospectively perceived preparation across different domains of emotional education. This study aimed to identify and characterize latent profiles of retrospectively perceived knowledge in emotional education acquired during initial teacher training among Chilean in-service teachers. Using a retrospective design, 412 practicing teachers participated (86.7% female; mean age = 39.2 years; mean teaching experience = 12.6 years). The EEITT Scale assessed perceived knowledge acquired in Mood, Emotional Regulation, Psychosocial Well-being, and Identity. Confirmatory factor analysis supported the predefined four-factor structure, and latent profile analysis was conducted in R by comparing solutions from one to eight profiles. Six profiles were retained, showing a combination of differences in overall perceived preparation and more specific configurations across dimensions. Emotional Regulation emerged as one of the most discriminating dimensions, particularly in profiles characterized by comparatively low perceived preparation in this domain, alone or together with Psychosocial Well-being. The six-profile solution showed adequate classification quality (entropy = 0.824), although classification uncertainty was greater for one intermediate profile. Overall, the findings indicate that teachers do not report a uniform pattern of perceived preparation in emotional education; instead, distinct subgroups differ in both the overall level and configuration of perceived preparation across domains. These results suggest that reliance on sample-level averages may obscure meaningful variation in teachers’ retrospective perceptions of their initial training and may inform future research on differentiated professional development strategies. Full article

(This article belongs to the Special Issue Promoting Social–Emotional and Academic Support in Educational Settings)

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21 pages, 1925 KB

Open AccessArticle

Burnout Dimensions and Associated Factors Among Orthopedic and Traumatology Physicians: A Cross-Sectional Study from Türkiye

by Ahmet Yiğitbay, Muhammet Can Ari, Başak Özge Yiğitbay, Cemal Kural and Nezih Ziroğlu

Healthcare 2026, 14(17), 2696; https://doi.org/10.3390/healthcare14172696 - 24 Aug 2026

Abstract

Background/Objectives: Burnout is an important occupational health concern among orthopedic and traumatology physicians. This study aimed to evaluate the individual dimensions of burnout and identify their demographic and occupational correlates among orthopedic and traumatology physicians practicing in Türkiye. Methods: This cross-sectional study used an anonymous online survey distributed through the Turkish Society of Orthopaedics and Traumatology electronic mailing group between October 2024 and June 2026. Burnout was assessed using the Turkish adaptation of the 22-item Maslach Burnout Inventory, comprising the Emotional Exhaustion (EE), Depersonalization (DP), and Personal Accomplishment (PA) subscales. Unadjusted group comparisons, Spearman correlation analyses, and separate multivariable linear regression models with HC3 heteroscedasticity-consistent standard errors were performed. Results: A total of 320 complete questionnaires were analyzed. The mean EE, DP, and PA scores were 20.17 ± 6.83, 7.40 ± 3.58, and 20.37 ± 4.19, respectively. The subscale scores were analyzed as continuous dimensions rather than classified using low-, moderate-, or high-burnout thresholds. In unadjusted comparisons, residents had higher EE and DP scores and lower PA scores than specialists. After adjustment, resident status remained associated with higher DP (B = 2.14, p = 0.010) and lower PA (B = −1.92, p = 0.018). Seeing more than 120 patients per day was associated with higher EE (B = 4.22, p = 0.023) and DP (B = 2.49, p = 0.018), while working more than 100 h per week was associated with higher EE (B = 4.47, p = 0.009). Individual predictor effect sizes and the explanatory power of the models were generally modest. Conclusions: Daily patient volume, weekly working hours, and professional status showed distinct associations with the individual dimensions of burnout. These findings suggest that workload organization and support for resident physicians warrant consideration. However, because of the cross-sectional design and voluntary non-probability sampling, the findings should not be interpreted as causal or nationally representative. Full article

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26 pages, 1061 KB

Open AccessArticle

A Hybrid Algorithm Approach to Designing a Three-Echelon Supply Chain Network Model

by Xuyang Wang, Wenfei Zhang and Shuhai Fan

Mathematics 2026, 14(17), 3049; https://doi.org/10.3390/math14173049 - 24 Aug 2026

Abstract

This study addresses a large-scale location–allocation problem in a three-echelon automotive supply chain comprising 382 suppliers, candidate distribution centers, and six assembly plants. The planning task is to redesign the inbound consolidation network while minimizing transportation and distribution center operating costs, enforcing a 480 km supplier-to-center service radius, and achieving at least 90% demand-weighted coverage. We formulate a mixed discrete-continuous model with supplier-to-center assignment, center location, throughput, and flow decisions. A feasibility-oriented hybrid algorithm uses a genetic algorithm as the main search engine, ant colony construction to seed solutions near the feasible region, adaptive mutation and simulated annealing to preserve exploration and refine elite solutions, and an online neural surrogate to avoid a subset of costly exact fitness evaluations. The design differs from a simple collection of metaheuristics: all components share one variable-length encoding, the same feasibility metrics, and periodic exact reevaluation of candidate solutions. Using the competition case data, the redesigned network reduces total cost by 27.0% relative to the six-center baseline, decreases the demand-weighted average supplier-to-center distance from 461.3 km to 53.0 km, lowers the maximum distance from 2807.22 km to 441.78 km, and raises coverage from 45.0% to 100%. Across ten independent runs, the hybrid method obtains a mean cost 10.3% below that of a standard genetic algorithm, with lower run-to-run dispersion. The results show that feasibility-aware initialization, adaptive search, and selective surrogate evaluation can support practical redesign of a strongly constrained, national-scale inbound logistics network. The directly attached reproducibility package provides the MATLAB implementation and the seven supplied input workbooks used by the reported model. The evidence is limited to one deterministic competition instance, a fixed cost schedule, and fixed-topology sensitivity calculations; generalization under demand uncertainty, facility disruption, and alternative road conditions remains to be tested. Full article

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