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28 pages, 9279 KB

Open AccessArticle

A Grammar of Speculation: Learning Speculative Design with Generative AI in Biodesign Education

by Santiago Ojeda Ramirez, Nicole Hakim and Giovanna Danies

Educ. Sci. 2026, 16(1), 102; https://doi.org/10.3390/educsci16010102 (registering DOI) - 9 Jan 2026

This study examines how undergraduate design students imagined and critiqued biotechnological futures through speculative work with generative AI in a semester-long biodesign course. Using inductive qualitative coding and visual discourse analyses, we traced how students’ prompts, images, and reflections reveal an evolving grammar [...] Read more.

This study examines how undergraduate design students imagined and critiqued biotechnological futures through speculative work with generative AI in a semester-long biodesign course. Using inductive qualitative coding and visual discourse analyses, we traced how students’ prompts, images, and reflections reveal an evolving grammar of speculation. Students shifted from crisis description to design-oriented possibility and socio-political reasoning about ecological, cultural, and ethical implications. Generative AI supported this shift by offering visual feedback that enabled students to recognize assumptions and critically examine speculative designs. Through repeated cycles of prompting and refinement, students advanced biodesign prototypes and developed a nuanced understanding of AI’s affordances and limits. Extending constructionism learning theories into speculative design with generative AI, this study examines how learners externalize discursive and imaginative thought through prompt-crafting. These findings articulate a grammar of speculation, showing how generative AI mediates critical AI literacy as a discursive and constructionist learning process. Full article

(This article belongs to the Special Issue Advancing Science Learning through Design-Based Learning)

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25 pages, 299 KB

Open AccessArticle

Language Assessment Literacy Development: A Case Study of Three EFL Teachers

by Sabah Al-Akbari, Marianne Nikolov and Ágnes Hódi

Educ. Sci. 2026, 16(1), 101; https://doi.org/10.3390/educsci16010101 (registering DOI) - 9 Jan 2026

Abstract

Language Assessment Literacy (LAL) is critical for teachers to perform their assessment tasks, but many teachers in low-resource contexts do not receive adequate assessment training. This qualitative multiple-case study examined the impact of a short-term Professional Development (PD) program on three in-service English [...] Read more.

Language Assessment Literacy (LAL) is critical for teachers to perform their assessment tasks, but many teachers in low-resource contexts do not receive adequate assessment training. This qualitative multiple-case study examined the impact of a short-term Professional Development (PD) program on three in-service English as a Foreign Language (EFL) teachers in developing their LAL and in shaping their assessment conceptions, knowledge and practices as assessors. The PD training program consisted of a 30 h workshop delivered over one week and integrated theory, practice, collaborative learning, reflection, and feedback. Data collection instruments included classroom observations and interviews. Findings showed that the PD program improved teachers’ LAL by developing their assessment conceptions, knowledge, skills, and confidence, although the degree of improvement varied across participants. The findings also identified challenges teachers encountered in their assessment practices, including limited time, large class sizes, insufficient resources, and sociocultural factors that constrained teachers’ assessment conceptions and restricted their LAL development. The findings showed that PD programs could strengthen teachers’ professional identity as assessors by incorporating relevant content, practice opportunities, feedback, a supportive learning community, and self-reflection. The study findings have broader implications for professional development of LAL in other low-resource and exam-oriented EFL contexts with strong sociocultural constraints. Full article

(This article belongs to the Special Issue Teachers as Assessors: Exploring the Socio-Emotional Dimension of Teacher Assessment Literacy)

19 pages, 1855 KB

Open AccessArticle

CLIP-RL: Closed-Loop Video Inpainting with Detection-Guided Reinforcement Learning

by Meng Wang, Jing Ren, Bing Wang and Xueping Tang

Sensors 2026, 26(2), 447; https://doi.org/10.3390/s26020447 (registering DOI) - 9 Jan 2026

Abstract

Existing video inpainting methods typically combine optical flow propagation with Transformer architectures, achieving promising inpainting results. However, they lack adaptive inpainting strategy optimization in diverse scenarios, and struggle to capture high-level temporal semantics, causing temporal inconsistencies and quality degradation. To address these challenges, [...] Read more.

Existing video inpainting methods typically combine optical flow propagation with Transformer architectures, achieving promising inpainting results. However, they lack adaptive inpainting strategy optimization in diverse scenarios, and struggle to capture high-level temporal semantics, causing temporal inconsistencies and quality degradation. To address these challenges, we make one of the first attempts to introduce reinforcement learning into the video inpainting domain, establishing a closed-loop framework named CLIP-RL that enables adaptive strategy optimization. Specifically, video inpainting is reformulated as an agent–environment interaction, where the inpainting module functions as the agent’s execution component, and a pre-trained inpainting detection module provides real-time quality feedback. Guided by a policy network and a composite reward function that incorporates a weighted temporal alignment loss, the agent dynamically selects actions to adjust the inpainting strategy and iteratively refines the inpainting results. Compared to ProPainter, CLIP-RL improves PSNR from 34.43 to 34.67 and SSIM from 0.974 to 0.986 on the YouTube-VOS dataset. Qualitative analysis demonstrates that CLIP-RL excels in detail preservation and artifact suppression, validating its superiority in video inpainting tasks. Full article

(This article belongs to the Section Intelligent Sensors)

22 pages, 891 KB

Open AccessArticle

Rapid MRTA in Large UAV Swarms Based on Topological Graph Construction in Obstacle Environments

by Jinlong Liu, Zexu Zhang, Shan Wen, Jingzong Liu and Kai Zhang

Drones 2026, 10(1), 48; https://doi.org/10.3390/drones10010048 (registering DOI) - 9 Jan 2026

Abstract

In large-scale Unmanned Aerial Vehicle (UAV) and task environments—particularly those involving obstacles—dimensional explosion remains a significant challenge in Multi-Robot Task Allocation (MRTA). To this end, a novel heuristic MRTA framework based on Topological Graph Construction (TGC) is proposed. First, the physical map is [...] Read more.

In large-scale Unmanned Aerial Vehicle (UAV) and task environments—particularly those involving obstacles—dimensional explosion remains a significant challenge in Multi-Robot Task Allocation (MRTA). To this end, a novel heuristic MRTA framework based on Topological Graph Construction (TGC) is proposed. First, the physical map is transformed into a pixel map, from which a Generalized Voronoi Graph (GVG) is generated by extracting clearance points, which is then used to construct the topological graph of the obstacle environment. Next, the affiliations of UAVs and tasks within the topological graph are determined to partition different topological regions, and the task value of each topological node is calculated, followed by the first-phase Task Allocation (TA) on these topological nodes. Finally, UAVs within the same topological region with their allocated tasks perform a local second-phase TA and generate the final TA result. The simulation experiments analyze the influence of different pixel resolutions on the performance of the proposed method. Subsequently, robustness experiments under localization noise, path cost noise, and communication delays demonstrate that the total benefit achieved by the proposed method remains relatively stable, while the computational time is moderately affected. Moreover, comparative experiments and statistical analyses were conducted against k-means clustering-based MRTA methods in different UAV, task, and obstacle scale environments. The results show that the proposed method improves computational speed while maintaining solution quality, with the PI-based method achieving speedups of over 60 times and the CBBA-based method over 10 times compared with the baseline method. Full article

(This article belongs to the Special Issue Advanced Optimization Strategies for UAV Mission Planning and Operation)

33 pages, 2810 KB

Open AccessReview

AUVs for Seabed Surveying: A Comprehensive Review of Side-Scan Sonar-Based Target Detection

by Jianan Qiao, Jiancheng Yu, Yan Huang, Hao Feng, Dayu Jia, Zhenyu Wang and Bing Wang

J. Mar. Sci. Eng. 2026, 14(2), 145; https://doi.org/10.3390/jmse14020145 (registering DOI) - 9 Jan 2026

Abstract

With advancements in Autonomous Underwater Vehicle (AUV) and sensor technologies, the operational paradigms for seabed survey are undergoing significant transformation. Compared to traditional towed or remotely operated platforms, AUV-based seabed survey systems demonstrate superior capabilities in data resolution, operational efficiency and stealth. Furthermore, [...] Read more.

With advancements in Autonomous Underwater Vehicle (AUV) and sensor technologies, the operational paradigms for seabed survey are undergoing significant transformation. Compared to traditional towed or remotely operated platforms, AUV-based seabed survey systems demonstrate superior capabilities in data resolution, operational efficiency and stealth. Furthermore, propelled by progress in artificial intelligence, the technical approaches of AUV-based seabed exploration systems are also experiencing disruptive changes. Based on our observations, existing review articles predominantly focus on individual technologies within seabed survey operations, failing to reflect the systemic constraints and interdependencies among these discrete technological components. This review focuses on the scenario of seabed target detection within seabed survey operations, summarizing research progress aimed at enhancing the effectiveness of such systems across three key technical areas: image processing of side-scan sonar (SSS) systems, intelligent detection of seabed targets and autonomous path planning for survey missions, which is based on a representative system—AUV-mounted SSS system. Given the multi-faceted challenges still present in seabed exploration technology, this paper aims to provide directional guidance for new researchers entering this field. Full article

(This article belongs to the Section Ocean Engineering)

21 pages, 580 KB

Open AccessReview

Reinforcement Learning Techniques for the Flavor Problem in Particle Physics

by Alessio Giarnetti and Davide Meloni

Symmetry 2026, 18(1), 131; https://doi.org/10.3390/sym18010131 (registering DOI) - 9 Jan 2026

Abstract

This short review discusses recent applications of Reinforcement Learning (RL) techniques to the flavor problem in particle physics. Traditional approaches to fermion masses and mixing often rely on extensions of the Standard Model based on horizontal symmetries, but the vast landscape of possible [...] Read more.

This short review discusses recent applications of Reinforcement Learning (RL) techniques to the flavor problem in particle physics. Traditional approaches to fermion masses and mixing often rely on extensions of the Standard Model based on horizontal symmetries, but the vast landscape of possible models makes systematic exploration infeasible. Recent works have shown that RL can efficiently navigate this landscape by constructing models that reproduce observed quark and lepton observables. These approaches demonstrate that RL not only rediscovers models already proposed in the literature but also uncovers new, phenomenologically acceptable solutions. Full article

(This article belongs to the Special Issue Neutrinos and Symmetry: Theoretical Developments and New Directions)

14 pages, 335 KB

Open AccessArticle

Comparison of Two Posterior Chain Strength Training Protocols on Performance and Injury Incidence in Elite Youth Football Players

by Manuele Ferrini, José Asian-Clemente, Gabriele Bagattini and Luis Suarez-Arrones

Medicina 2026, 62(1), 140; https://doi.org/10.3390/medicina62010140 (registering DOI) - 9 Jan 2026

Abstract

Background and Objectives: This study compared the effects of two posterior-chain strength training strategies on eccentric hamstring strength, jump and sprint performance, and hamstring injury incidence in elite youth soccer players. Materials and Methods: Twenty-three players were randomly allocated to either [...] Read more.

Background and Objectives: This study compared the effects of two posterior-chain strength training strategies on eccentric hamstring strength, jump and sprint performance, and hamstring injury incidence in elite youth soccer players. Materials and Methods: Twenty-three players were randomly allocated to either a Nordic Hamstring Exercise Group (NHEG; n = 11) or a Deadlift + Leg Curl Slides Group (D + LCSG; n = 12). Both groups completed a 9-week in-season resistance training program consisting of one strength-oriented session (MD-4) and one power-oriented session (MD-2) per week, in addition to regular soccer training. Pre- and post-intervention assessments included eccentric hamstring strength (NordBord), countermovement jump (CMJ), and 10 m and 30 m linear sprint performance. Results: Eccentric hamstring strength increased significantly only in the NHEG (p ≤ 0.05), though this improvement did not transfer to enhancements in jump or sprint performance (p > 0.05). No significant changes were observed in the D + LCSG for any variable (p > 0.05), and no between-group differences were found across all performance outcomes. During the 12-week monitoring period, one hamstring injury was recorded, occurring in the NHEG. Conclusions: These findings suggest that, while the NHE elicited greater exercise-specific eccentric strength gains, neither posterior-chain strategy produced improvements in sprint or jump performance. However, given the small sample size and low number of injury events, these trends cannot be attributed with certainty to the implemented protocols, and both programs reported a low incidence of hamstring injuries per 1000 h of exposure with no statistically protective effect associated with the use of the NHE. Full article

(This article belongs to the Special Issue Sports Injuries: Prevention, Treatment and Rehabilitation)

16 pages, 2064 KB

Open AccessArticle

Development and Characterization of 14 Novel Genome-Derived SSR Markers for Genetic Diversity and Population Structure Analyses of Two Agroathelia Species

by Dong Jae Lee and Young-Joon Choi

Agriculture 2026, 16(2), 167; https://doi.org/10.3390/agriculture16020167 (registering DOI) - 9 Jan 2026

Abstract

Agroathelia (syn. Sclerotium) is a global soil-borne pathogen with a broad host range, causing significant agricultural losses in diverse crops. However, genomic and population genetic resources of this genus remain limited. To develop genome-based molecular tools, we newly sequenced two Korean isolates [...] Read more.

Agroathelia (syn. Sclerotium) is a global soil-borne pathogen with a broad host range, causing significant agricultural losses in diverse crops. However, genomic and population genetic resources of this genus remain limited. To develop genome-based molecular tools, we newly sequenced two Korean isolates (A. rolfsii KACC 93004P and A. delphinii KACC 93031P) and compared them with the reference genome of A. rolfsii GP3. Comparative genome analysis identified 723 polymorphic simple sequence repeat (SSR) loci, from which 14 were selected and validated across 34 Korean isolates representing multiple host plants. Genetic diversity was assessed using the number of alleles (NA), observed heterozygosity (Ho), unbiased expected heterozygosity (He), and polymorphic information content (PIC). Most SSRs were moderately to highly informative (PIC = 0.341 to 0.541 in A. rolfsii; 0.367 to 0.612 when including A. delphinii). Unweighted pair group method with arithmetic mean (UPGMA) clustering based on SSR allele profiles clearly separated the two species and revealed a distinct intraspecific structure within A. rolfsii. Principal coordinates analysis (PCoA) also revealed clear species-level separation, while A. rolfsii isolates were partitioned into two intraspecific clusters with one divergent isolate, indicating structured genetic variation without a host-associated population structure. The developed SSR markers provide useful tools for studying genetic diversity, population structure, and epidemiology of Agroathelia species and isolates. Full article

(This article belongs to the Section Crop Protection, Diseases, Pests and Weeds)

18 pages, 576 KB

Open AccessArticle

A Gravity Tensor and Gauge Equations for Newtonian Dynamics

by Jing Tang Xing

Axioms 2026, 15(1), 51; https://doi.org/10.3390/axioms15010051 (registering DOI) - 9 Jan 2026

Abstract

It is revealed that the material derivative of a variable in gravity field is its directional derivative, from which and energy/complementary-energy conservations with exterior derivatives, two sets of gauge equations of Newton’s dynamic gravity field are derived, which has same mathematical structure with [...] Read more.

It is revealed that the material derivative of a variable in gravity field is its directional derivative, from which and energy/complementary-energy conservations with exterior derivatives, two sets of gauge equations of Newton’s dynamic gravity field are derived, which has same mathematical structure with the gauge ones for the Maxwell equations in electromagnetic fields, revealing that gravity force and curl momentum in Newton’s gravity field, respectively, play the roles like the electric

E

and the magnetic

B

of the Maxwell equations in the electromagnetic field. The gravity tensor of Newton’s gravitational field is constructed, and an example is given to validate it. This finding allows Newton’s gravity to be governed by a gauge theory, addressing the historic issue that “Newton’s gravitation is an exception to the Yang–Mills gauge theory”. Full article

(This article belongs to the Section Mathematical Physics)

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24 pages, 5341 KB

Open AccessArticle

Molecular Pathology of Advanced NSCLC: Biomarkers and Therapeutic Decisions

by Melanie Winter, Jan Jeroch, Maximilian Wetz, Marc-Alexander Rauschendorf and Peter J. Wild

Cancers 2026, 18(2), 216; https://doi.org/10.3390/cancers18020216 (registering DOI) - 9 Jan 2026

Abstract

Background: Advances in molecular pathology have transformed NSCLC (Non-Small Cell Lung Cancer) diagnosis, prognosis, and treatment by enabling precise tumor characterization and targeted therapeutic strategies. We review key genomic alterations in NSCLC, including EGFR (epidermal growth factor receptor) mutations, ALK (anaplastic lymphoma kinase) [...] Read more.

Background: Advances in molecular pathology have transformed NSCLC (Non-Small Cell Lung Cancer) diagnosis, prognosis, and treatment by enabling precise tumor characterization and targeted therapeutic strategies. We review key genomic alterations in NSCLC, including EGFR (epidermal growth factor receptor) mutations, ALK (anaplastic lymphoma kinase) and ROS1 (ROS proto-oncogene 1) rearrangements, BRAF (B-Raf proto-oncogene serine/threonine kinase) mutations, MET (mesenchymal–epithelial transition factor) alterations, KRAS (Kirsten rat sarcoma) mutations, HER2 (human epidermal growth factor receptor 2) alterations and emerging NTRK (neurotrophic receptor tyrosine kinase) fusions and AXL-related pathways. Methods: A total of 48 patients with NSCLC was analyzed, including 22 women and 26 men (mean age 70 years, range 44–86). Tumor specimens were classified histologically as adenocarcinomas (n = 81%) or squamous cell carcinomas (n = 19%). Smoking history, PD-L1 (programmed death-ligand 1) expression, and genetic alterations were assessed. NGS (Next-generation sequencing) identified genomic variants, which were classified according to ACMG (American College of Medical Genetics and Genomics) guidelines. Results: The cohort consisted of 29 former smokers, 13 current smokers, and 5 non-smokers (12%), with a mean smoking burden of 33 pack years. PD-L1 TPS (tumor proportion score) was ≥50% in 10 patients, ≥1–<50% in 22, and <1% in 15 patients. In total, 120 genomic variants were detected (allele frequency ≥ 5%). Of these, 52 (43%) were classified as likely pathogenic or pathogenic, 48 (40%) as variants of unknown significance, and 20 (17%) as benign or likely benign. The most frequently altered genes were TP53 (tumor protein p53) (31%), KRAS and EGFR (15% each), and STK11 (serine/threonine kinase 11) (12%). Adenocarcinomas accounted for 89% of all alterations, with TP53 (21%) and KRAS (15%) being most common, while squamous cell carcinomas predominantly harbored TP53 (38%) and MET (15%) mutations. In patients with PD-L1 TPS ≥ 50%, KRAS mutations were enriched (50%), particularly KRAS G12C and G12D, with frequent co-occurrence of TP53 mutations (20%). No pathogenic EGFR mutations were detected in this subgroup. Conclusions: Comprehensive genomic profiling in NSCLC revealed a high prevalence of clinically relevant mutations, with TP53, KRAS and EGFR as the dominant drivers. The strong association of KRAS mutations with high PD-L1 expression, irrespective of smoking history, highlights the interplay between genetic and immunological pathways in NSCLC. These findings support the routine implementation of broad molecular testing to guide precision oncology approaches in both adenocarcinoma and squamous cell carcinoma patients. Full article

(This article belongs to the Section Cancer Pathophysiology)

20 pages, 1275 KB

Open AccessArticle

Fractional Viscoelastic Modeling of Multi-Step Creep and Relaxation in an Aerospace Epoxy Adhesive

by Jesús Gabino Puente-Córdova, Flor Yanhira Rentería-Baltiérrez, José de Jesús Villalobos-Luna and Pedro López-Cruz

Symmetry 2026, 18(1), 130; https://doi.org/10.3390/sym18010130 (registering DOI) - 9 Jan 2026

Abstract

Structural adhesives in aeronautical applications are routinely exposed to complex loading histories that generate time-dependent deformation, making accurate prediction of their viscoelastic response essential for reliable assessment of joint integrity. This work presents an integrated experimental and modeling study of the aerospace-grade epoxy [...] Read more.

Structural adhesives in aeronautical applications are routinely exposed to complex loading histories that generate time-dependent deformation, making accurate prediction of their viscoelastic response essential for reliable assessment of joint integrity. This work presents an integrated experimental and modeling study of the aerospace-grade epoxy adhesive 3M Scotch-Weld EC-2216 using multi-step creep and stress-relaxation tests performed at room temperature and controlled loading rates, combined with fractional viscoelastic modeling. Unlike traditional single-step characterizations, the multi-step protocol employed here captures the cumulative loading effects and fading-memory dynamics that govern the adhesive’s mechanical response. The experimental data were analyzed using fractional Maxwell, Voigt–Kelvin, and Zener formulations. Statistical evaluation based on the Bayesian Information Criterion (BIC) consistently identified the Fractional Zener Model (FZM) as the most robust representation of the stress-relaxation behavior, effectively capturing both the unrelaxed and relaxed modulus. The results demonstrate that EC-2216 exhibits hierarchical relaxation mechanisms and history-dependent viscoelasticity that cannot be accurately described by classical integer-order models. Overall, the study validates the use of fractional operators to represent the broad and hierarchical relaxation spectra typical of toughened aerospace epoxies and provides a rigorous framework for durability assessment and predictive modeling of adhesively bonded structures. Full article

(This article belongs to the Special Issue Symmetry, Asymmetry, and Anisotropy in the Design and Modeling of Advanced Materials)

16 pages, 965 KB

Open AccessArticle

Equilibrium Drift Restriction: A Control Strategy for Reducing Steady-State Error Under System Inconsistency

by Fangyuan Li

Math. Comput. Appl. 2026, 31(1), 11; https://doi.org/10.3390/mca31010011 (registering DOI) - 9 Jan 2026

Abstract

The inconsistency of system parameters inevitably emerges due to reasons such as modeling imprecision, manufacturing error, and aging process. Due to the inconsistency between nominal models and real-world conditions, controllers designed accordingly frequently fail to maintain performance guarantees during physical deployment. This phenomenon [...] Read more.

The inconsistency of system parameters inevitably emerges due to reasons such as modeling imprecision, manufacturing error, and aging process. Due to the inconsistency between nominal models and real-world conditions, controllers designed accordingly frequently fail to maintain performance guarantees during physical deployment. This phenomenon exemplifies the open sim-to-real gap problem. To address this limitation, we develop an equilibrium drift restriction strategy (EDR) to reduce the steady-state error due to the system inconsistency. We first present an example to show the reason why some existing controllers cannot counteract the system inconsistency when the equilibrium is not at the origin. Then, a control strategy is proposed by using the EDR method to reduce the induced steady-state error. Both intuitive interpretation and theoretical analysis demonstrate how EDR reduces steady-state deviations. Simulation results of a common pendulum system are provided to demonstrate that the restriction mitigates the impact of parameter inconsistency. A comparison with the popular Q-learning method is also presented. The results show that the EDR method can serve as a simple but effective tool to improve the steady-state performance of existing controllers. This paper offers a fresh perspective for exploring the control functions with specific properties in the realm of related controller research. Full article

(This article belongs to the Section Engineering)

21 pages, 4123 KB

Open AccessArticle

Assessing a Semi-Autonomous Drone-in-a-Box System for Landslide Monitoring: A Case Study from the Yukon Territory, Canada

by Margaret Kalacska, Oliver Lucanus, Juan Pablo Arroyo-Mora, John Stix, Panya Lipovsky and Justin Roman

Sustainability 2026, 18(2), 693; https://doi.org/10.3390/su18020693 (registering DOI) - 9 Jan 2026

Abstract

Technological innovation in commercial Remotely Piloted Aircraft Systems (RPASs) is advancing rapidly. However, their operational efficiency remains limited by the need for on-site skilled human operators. Semi-autonomous drone-in-a-box (DIAB) systems are emerging as a practical solution, enabling automated, repeatable missions for applications such [...] Read more.

Technological innovation in commercial Remotely Piloted Aircraft Systems (RPASs) is advancing rapidly. However, their operational efficiency remains limited by the need for on-site skilled human operators. Semi-autonomous drone-in-a-box (DIAB) systems are emerging as a practical solution, enabling automated, repeatable missions for applications such as construction site monitoring, security, and critical infrastructure inspection. Beyond industry, these systems hold significant promise for scientific research, particularly in long-term environmental monitoring where cost, accessibility, and safety are critical factors. In this technology demonstration, we detail the system implementation, discuss flight-planning challenges, and assess the overall feasibility of deploying a DJI Dock 2 DIAB system for remote monitoring of the Miles Ridge landslide in the Yukon Territory, Canada. The system was installed approximately 2.5 km from the landslide and operated remotely from across the country in Montreal, QC, about 4000 km away. A total of five datasets were acquired from July to September 2025, enabling three-dimensional reconstruction of the landslide surface from each acquisition. A comparison of extracted cross-sections demonstrated high reproducibility and accurate co-registration across acquisitions. This study highlights the potential of DIAB systems to support reliable, low-maintenance monitoring of remote landslides. Full article

(This article belongs to the Special Issue Sustainable Assessment and Risk Analysis on Landslide Hazards)

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27 pages, 2678 KB

Open AccessReview

Membrane Stress and Ferroptosis: Lipid Dynamics in Cancer

by Jaewang Lee, Youngin Seo and Jong-Lyel Roh

Int. J. Mol. Sci. 2026, 27(2), 690; https://doi.org/10.3390/ijms27020690 (registering DOI) - 9 Jan 2026

Abstract

Membrane rupture, induced by lipid peroxidation, is a severe threat to osmotic balance, as membrane pores contribute to ferroptosis, an iron-dependent cell death. To alleviate osmotic stress, membrane constituents dynamically reconstruct the membrane and interact with intracellular molecules. Tumor-derived acidosis shift glycolysis-dependent metabolism [...] Read more.

Membrane rupture, induced by lipid peroxidation, is a severe threat to osmotic balance, as membrane pores contribute to ferroptosis, an iron-dependent cell death. To alleviate osmotic stress, membrane constituents dynamically reconstruct the membrane and interact with intracellular molecules. Tumor-derived acidosis shift glycolysis-dependent metabolism toward lipid metabolism, increasing polyunsaturated fatty acids (PUFAs). PUFAs enhance membrane fluidity but make cancer susceptible to lipid peroxidation. Also, the ionization of phospholipids under low pH can accelerate membrane rupture. This stress can be mitigated by the redistribution of cholesterol, which maintains tension–compression balance and acts as antioxidants. When excessive reactive aldehydes—byproducts of lipid peroxidation—overwhelm cholesterol’s protective role, lipid peroxides promote membrane cracks. Moreover, a deficiency in glutathione can alter cholesterol’s function, turning it into a pro-oxidant. In contrast, ceramide, derived from membrane lipids, indirectly prevents ferroptosis by facilitating cytochrome c release. This review integrates recent findings on how membrane components and environmental stressors influence ferroptosis. It also suggests potential therapeutic strategies. This could advance our understanding of ferroptosis in cancer. Full article

(This article belongs to the Special Issue New Insights into Anticancer Strategies)

48 pages, 5811 KB

Open AccessArticle

Natural and Anthropogenic Risk Factors of Discontinuous Ground Deformations: A Conceptual Framework for Hazard Analysis: Part I—Predisposing Conditions

by Lucyna Florkowska, Izabela Bryt-Nitarska, Elżbieta Pilecka and Karolina Białasek

Appl. Sci. 2026, 16(2), 708; https://doi.org/10.3390/app16020708 (registering DOI) - 9 Jan 2026

Abstract

Discontinuous ground deformations represent one of the most critical geohazards affecting both natural and anthropogenically transformed environments. These processes pose a serious threat to infrastructure stability and land-use planning, as they can lead to severe structural damage and long-term ground instability. Effective geotechnical [...] Read more.

Discontinuous ground deformations represent one of the most critical geohazards affecting both natural and anthropogenically transformed environments. These processes pose a serious threat to infrastructure stability and land-use planning, as they can lead to severe structural damage and long-term ground instability. Effective geotechnical hazard management requires an integrated understanding of geological structures, deformation mechanisms, and the legacy of historical subsurface transformations influencing current and future ground behaviour. This paper—the first part of a two-part series—introduces an extended three-channel conceptual–probabilistic model and outlines its causal structure, integrating predisposing, triggering, and causative factors. The present study focuses exclusively on the theoretical foundations of the model and on the hierarchical classification of thirteen key predisposing factors defining the long-term susceptibility of the rock mass (S(A)). These include both structural and physicochemical controls such as karst voids, weak interfaces, hydro-mechanical activity, and near-surface weathering. The proposed approach provides a physically consistent conceptual basis for representing the interactions among the three causal domains. The second part of the series will address triggering and causative domains and will discuss methodological and implementation aspects of the model within the completed causal structure. Full article

(This article belongs to the Special Issue Sustainable Research on Rock Mechanics and Geotechnical Engineering)

33 pages, 6451 KB

Open AccessArticle

Restitution of the Sensory Urban Ambiences of a French Colonial Urban Fabric in Algeria: A Case Study of Didouche Mourad Street, Skikda

by Rima Boukerma, Lamia Mansouri, Bidjad Arigue, Giovanni Santi and Daniela Ladiana

Heritage 2026, 9(1), 22; https://doi.org/10.3390/heritage9010022 (registering DOI) - 9 Jan 2026

Abstract

The ambiance-based approach to old urban fabrics has emerged as a response to the evolution of heritage, focusing on the spirit of place and the relationship between people and their environment. It aims to preserve the identity of architectural and urban spaces, incorporating [...] Read more.

The ambiance-based approach to old urban fabrics has emerged as a response to the evolution of heritage, focusing on the spirit of place and the relationship between people and their environment. It aims to preserve the identity of architectural and urban spaces, incorporating intangible elements beyond their physical character. In Algeria, colonial-era urban fabrics continue to structure cities. Skikda, a city in eastern Algeria was created ex-nihilo during this era. In this context, Didouche Mourad Street—the main thoroughfare and structuring element of the city—constitutes the core of the analysis. This study focuses on the French colonial period (1838–1962), considered a foundational phase in the spatial and sensory formation of the street. It aims to restitute the sensory urban ambiences of this period and to analyse their evolution in order to identify sensory permanences contributing to the heritage identity of the place. A thematic content analysis was used to identify sensory ambiences, supported by NVivo software to quantify their recurrences and analyse their spatio-temporal dynamics. The findings show that some ambiences have persisted, others have disappeared, and new ones have emerged through successive transformations. By documenting the sensory history of the street, this research proposes a conceptual and methodological framework for the interpretation of heritage urban ambiences and for informing contemporary rehabilitation approaches, considering permanent ambiences as interpretative tools and reference points for understanding heritage dynamics. Full article

(This article belongs to the Special Issue Innovative Methods and Approaches for the Evaluation and Valorisation of Historical and Architectural Heritage)

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21 pages, 1382 KB

Open AccessArticle

Characterization of the Proteomic Response in SIM-A9 Murine Microglia Following Canonical NLRP3 Inflammasome Activation

by Nicolas N. Lafrenière, Karan Thakur, Gerard Agbayani, Melissa Hewitt, Klaudia Baumann, Jagdeep K. Sandhu and Arsalan S. Haqqani

Int. J. Mol. Sci. 2026, 27(2), 689; https://doi.org/10.3390/ijms27020689 (registering DOI) - 9 Jan 2026

Abstract

Neuroinflammation is a hallmark of both acute and chronic neurodegenerative diseases and is driven, in part, by activated glial cells, including microglia. A key regulator of this inflammatory response is the NLRP3 inflammasome, an immune sensor that can be triggered by diverse, unrelated [...] Read more.

Neuroinflammation is a hallmark of both acute and chronic neurodegenerative diseases and is driven, in part, by activated glial cells, including microglia. A key regulator of this inflammatory response is the NLRP3 inflammasome, an immune sensor that can be triggered by diverse, unrelated stimuli such as pathogen-associated molecular patterns, cellular stress, and mitochondrial dysfunction. Despite progress in targeting NLRP3-mediated immune activation, many drug candidates fail, potentially due to the limited availability of physiologically relevant disease models. The SIM-A9 murine microglial cell line, established in 2014, has emerged as a widely used model for studying neuroinflammation; however, its proteome has not yet been systemically characterized. In this study, we investigated the proteomic landscape of SIM-A9 microglia treated with classical pro-inflammatory stimuli, including lipopolysaccharide (LPS) and extracellular ATP and nigericin (NG), to induce NLRP3 inflammasome activation. Using complementary proteomic approaches, we quantified 4903 proteins and observed significant enrichment of proteins associated with immune and nervous system processes. Differentially expressed proteins were consistent with an activated microglial phenotype, including the upregulation of proteins involved in NLRP3 inflammasome signaling. To our knowledge, this is the first comprehensive proteomic analysis of SIM-A9 microglia. These findings provide a foundational resource that may enhance the interpretation and design of future studies using SIM-A9 cells as a model of neuroinflammation. Full article

(This article belongs to the Section Molecular Neurobiology)

25 pages, 2088 KB

Open AccessReview

A Review of Oil–Water Separation Technology for Transformer Oil Leakage Wastewater

by Lijuan Yao, Han Shi, Wen Qi, Baozhong Song, Jun Zhou, Wenquan Sun and Yongjun Sun

Water 2026, 18(2), 180; https://doi.org/10.3390/w18020180 (registering DOI) - 9 Jan 2026

Abstract

The oily wastewater produced by transformer oil leakage contains pollutants such as mineral oil, metal particles, aged oil and additives, which can disrupt the dissolved oxygen balance in water bodies, pollute soil and endanger human health through the food chain, causing serious environmental [...] Read more.

The oily wastewater produced by transformer oil leakage contains pollutants such as mineral oil, metal particles, aged oil and additives, which can disrupt the dissolved oxygen balance in water bodies, pollute soil and endanger human health through the food chain, causing serious environmental pollution. Effective oil–water separation technology is the key to ecological protection and resource recovery. This paper reviews the principles, influencing factors and research progress of traditional (gravity sedimentation, air flotation, adsorption, demulsification) and new (nanocomposite adsorption, metal–organic skeleton materials, superhydrophobic/superlipophilic modified films) transformer oil–water separation technologies. Traditional technologies are mostly applicable to large-particle-free oil and are difficult to adapt to complex matrix wastewater. However, the new technology has significant advantages in separation efficiency (up to over 99.5%), selectivity and cycling stability (with a performance retention rate of over 85% after 20–60 cycles), breaking through the bottlenecks of traditional methods. In the future, it is necessary to develop low-cost and efficient separation technologies, promote the research and development of intelligent responsive materials, upgrade low-carbon preparation processes and their engineering applications, support environmental protection treatment in the power industry and encourage the coupling of material innovation and processes. Full article

(This article belongs to the Section Wastewater Treatment and Reuse)

26 pages, 48558 KB

Open AccessArticle

Low-Cost Fixed Bi-Rotor Testbed for Experimental Testing of Linear and Nonlinear Controllers

by Arturo Tadeo Espinoza Fraire, José Armando Sáenz Esqueda, Isaac Gandarilla Esparza and Jorge Alberto Orrante Sakanassi

Automation 2026, 7(1), 19; https://doi.org/10.3390/automation7010019 (registering DOI) - 9 Jan 2026

Abstract

To build a comprehensive academic or scientific foundation in control theory, developing the theoretical foundation is essential; however, it is equally crucial to validate the theory through practical or experimental verification. Therefore, it is necessary to have platforms that support the learning of [...] Read more.

To build a comprehensive academic or scientific foundation in control theory, developing the theoretical foundation is essential; however, it is equally crucial to validate the theory through practical or experimental verification. Therefore, it is necessary to have platforms that support the learning of automatic control theory. This paper proposes a fixed bi-rotor testbed as an educational tool to help undergraduate and graduate students verify control theories related to electronic engineering and automatic control systems. To evaluate the performance of the fixed bi-rotor testbed, three linear control laws are introduced: Proportional (P), Proportional Derivative (PD), and Proportional Integral Derivative (PID). Additionally, three nonlinear control techniques are examined: Backstepping, Nested Saturations, and First-Order Sliding Modes (SMC). The linear and nonlinear controller gains have been adjusted through several heuristic experiments. In multiple tests, the PD and backstepping control laws performed better than the other control techniques on the fixed bi-rotor testbed. Full article

(This article belongs to the Section Control Theory and Methods)

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31 pages, 10745 KB

Open AccessArticle

CNN-GCN Coordinated Multimodal Frequency Network for Hyperspectral Image and LiDAR Classification

by Haibin Wu, Haoran Lv, Aili Wang, Siqi Yan, Gabor Molnar, Liang Yu and Minhui Wang

Remote Sens. 2026, 18(2), 216; https://doi.org/10.3390/rs18020216 (registering DOI) - 9 Jan 2026

Abstract

The existing multimodal image classification methods often suffer from several key limitations: difficulty in effectively balancing local detail and global topological relationships in hyperspectral image (HSI) feature extraction; insufficient multi-scale characterization of terrain features from light detection and ranging (LiDAR) elevation data; and [...] Read more.

The existing multimodal image classification methods often suffer from several key limitations: difficulty in effectively balancing local detail and global topological relationships in hyperspectral image (HSI) feature extraction; insufficient multi-scale characterization of terrain features from light detection and ranging (LiDAR) elevation data; and neglect of deep inter-modal interactions in traditional fusion methods, often accompanied by high computational complexity. To address these issues, this paper proposes a comprehensive deep learning framework combining convolutional neural network (CNN), a graph convolutional network (GCN), and wavelet transform for the joint classification of HSI and LiDAR data, including several novel components: a Spectral Graph Mixer Block (SGMB), where a CNN branch captures fine-grained spectral–spatial features by multi-scale convolutions, while a parallel GCN branch models long-range contextual features through an enhanced gated graph network. This dual-path design enables simultaneous extraction of local detail and global topological features from HSI data; a Spatial Coordinate Block (SCB) to enhance spatial awareness and improve the perception of object contours and distribution patterns; a Multi-Scale Elevation Feature Extraction Block (MSFE) for capturing terrain representations across varying scales; and a Bidirectional Frequency Attention Encoder (BiFAE) to enable efficient and deep interaction between multimodal features. These modules are intricately designed to work in concert, forming a cohesive end-to-end framework, which not only achieves a more effective balance between local details and global contexts but also enables deep yet computationally efficient interaction across features, significantly strengthening the discriminability and robustness of the learned representation. To evaluate the proposed method, we conducted experiments on three multimodal remote sensing datasets: Houston2013, Augsburg, and Trento. Quantitative results demonstrate that our framework outperforms state-of-the-art methods, achieving OA values of 98.93%, 88.05%, and 99.59% on the respective datasets. Full article

(This article belongs to the Section AI Remote Sensing)

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29 pages, 1492 KB

Open AccessArticle

A Nonlinear Model of Three-Layer Groundwater Flow with Evaporation Dependent on the Critical Groundwater Level

by Abdinabi Mukhamadiyev, Marat Karimov, Toshtemir Khujakulov, Otabek Sattarov and Jinsoo Cho

Mathematics 2026, 14(2), 256; https://doi.org/10.3390/math14020256 (registering DOI) - 9 Jan 2026

Abstract

A nonlinear mathematical model is developed for unsteady groundwater flow in a three-layer heterogeneous aquifer system, comprising a confined aquifer, a covering layer, and a weakly permeable barrier. The model incorporates infiltration and evaporation governed by the M.M. Krylov–S.F. Averyanov law, where evaporation [...] Read more.

A nonlinear mathematical model is developed for unsteady groundwater flow in a three-layer heterogeneous aquifer system, comprising a confined aquifer, a covering layer, and a weakly permeable barrier. The model incorporates infiltration and evaporation governed by the M.M. Krylov–S.F. Averyanov law, where evaporation intensity depends on a critical groundwater level. Governing equations are nondimensionalized and solved using the alternating direction implicit (ADI) method with quasi-linearization to treat nonlinearities. Periodic variations in precipitation and evaporation are considered, alongside variable boundary permeabilities. The approach enables realistic simulation of multi-layer aquifer dynamics under diverse climatic and hydrogeological conditions, offering a robust tool for sustainable groundwater management, drought risk assessment, and aquifer protection strategies. Full article

(This article belongs to the Special Issue Mathematical and Computational Methods for Mechanics and Engineering)

26 pages, 10249 KB

Open AccessArticle

Study of Response Pattern of Casing Under the Condition of Nonuniform Creep Loading of Shale Gas Reservoir

by Xiaohua Zhu, Hanwen Sun, Jun Jing, Pansheng Xu and Lingxu Kong

Processes 2026, 14(2), 234; https://doi.org/10.3390/pr14020234 (registering DOI) - 9 Jan 2026

Abstract

With unconventional oil–gas reservoir exploration and oil and gas theory development, more and more importance is attached to the wellbore integrity. The casing deformation and damage is an integral part of the wellbore integrity theory. In the shale gas block in southwestern China, [...] Read more.

With unconventional oil–gas reservoir exploration and oil and gas theory development, more and more importance is attached to the wellbore integrity. The casing deformation and damage is an integral part of the wellbore integrity theory. In the shale gas block in southwestern China, the casing deformation is grave because of the nonuniform stress of the reservoir, posing a significant influence on the productivity and economic efficiency of the shale gas development. In order to clarify the causes and mechanisms of the casing deformation caused by the nonuniform stress, the author of this paper has established the mechanical properties mathematical model of the casing under the nonuniform load as well as the casing–cement ring–stratum assembly numerical model based on the data of in situ multi-arm well logger and reservoir geological characteristics. Such models are established to study the response pattern of the casing under the nonuniform creep ground stress of the shale gas reservoir. The study herein serves as a reference for the optimization of casing design and target-specific exploration technology adjustments and lays the foundation for promoting the cost-effective development of shale gas reservoirs. Full article

(This article belongs to the Section Petroleum and Low-Carbon Energy Process Engineering)

19 pages, 437 KB

Open AccessArticle

Navigating Loss in Animal-Assisted Services: Volunteer Experiences and Implications for Programs Following Therapy Dog Death or Retirement

by Lori R. Kogan, Jennifer Currin-McCulloch, Wendy Packman and Cori Bussolari

Animals 2026, 16(2), 202; https://doi.org/10.3390/ani16020202 (registering DOI) - 9 Jan 2026

Abstract

Animal-assisted services (AAS) depend on volunteer handler–dog teams, yet the emotional and relational impacts on volunteers when their therapy dog dies or retires remain largely unexplored. This study examines AAS volunteers’ experiences following the death or retirement of their therapy dog partner. An [...] Read more.

Animal-assisted services (AAS) depend on volunteer handler–dog teams, yet the emotional and relational impacts on volunteers when their therapy dog dies or retires remain largely unexplored. This study examines AAS volunteers’ experiences following the death or retirement of their therapy dog partner. An online, anonymous cross-sectional survey was administered between January and June 2025. A total of 247 individual responses were analyzed. Over half of survey participants (56%) had lost a therapy dog to death, and 36.6% had retired a dog. Although most volunteers who resumed AAS with a new dog reported excitement and renewed purpose, many experienced sadness linked to their previous partner. Retirement decisions were primarily driven by dog welfare concerns and were often experienced as an ambiguous loss. Social constraints were common; participants frequently perceived minimization or discomfort from others when attempting to discuss their grief. In conclusion, therapy dog death and retirement represent significant emotional and relational losses for AAS volunteers. Organizational practices, including anticipatory retirement planning, welfare-centered guidelines, recognition rituals, and structured support during successor-dog transitions may help mitigate distress and foster healthy adjustment. Findings are discussed in relation to theory-informed, practical implications for animal-assisted service practitioners and organizations. Full article

(This article belongs to the Section Companion Animals)

17 pages, 3467 KB

Open AccessArticle

Modelling the Thickness of a Water Film on Road Pavements—Analysis of Existing and New Equations for Flow Resistance Estimation

by Petar Praštalo and Nenad Jaćimović

Water 2026, 18(2), 181; https://doi.org/10.3390/w18020181 (registering DOI) - 9 Jan 2026

Abstract

This study investigates flow resistance in thin water films on road surfaces during rainfall, which is essential for assessing aquaplaning risk. A one-dimensional surface runoff model based on the diffusion-wave approach is used to compare existing equations for the Darcy–Weisbach friction factor and [...] Read more.

This study investigates flow resistance in thin water films on road surfaces during rainfall, which is essential for assessing aquaplaning risk. A one-dimensional surface runoff model based on the diffusion-wave approach is used to compare existing equations for the Darcy–Weisbach friction factor and Manning’s roughness coefficient. Laboratory data from three experimental cases support the analysis. The first case assesses the accuracy of existing equations and develops a new regression-based equation. The second case validates this new model for predicting water film thickness. Findings show that many existing equations poorly estimate water film thickness under high-intensity rainfall conditions relevant for aquaplaning analysis, often under- or overestimating it compared to measurements. Results indicate that flow resistance is mainly influenced by the Froude number, which is defined using the mean macro-texture depth of the pavement. The study emphasizes that accurate estimation of flow resistance parameters is critical in water film modelling, as it directly affects the reliability of traffic safety assessments. Full article

(This article belongs to the Section Hydraulics and Hydrodynamics)

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64 pages, 23051 KB

Open AccessArticle

Hierarchical Network Organization and Dynamic Perturbation Propagation in Autism Spectrum Disorder: An Integrative Machine Learning and Hypergraph Analysis Reveals Super-Hub Genes and Therapeutic Targets

by Larissa Margareta Batrancea, Ömer Akgüller, Mehmet Ali Balcı and Lucian Gaban

Biomedicines 2026, 14(1), 137; https://doi.org/10.3390/biomedicines14010137 (registering DOI) - 9 Jan 2026

Abstract

Background/Objectives: Autism spectrum disorder (ASD) exhibits remarkable genetic heterogeneity involving hundreds of risk genes; however, the mechanism by which these genes organize within biological networks to contribute to disease pathogenesis remains incompletely understood. This study aims to elucidate these organizational principles and identify [...] Read more.

Background/Objectives: Autism spectrum disorder (ASD) exhibits remarkable genetic heterogeneity involving hundreds of risk genes; however, the mechanism by which these genes organize within biological networks to contribute to disease pathogenesis remains incompletely understood. This study aims to elucidate these organizational principles and identify critical network bottlenecks using a novel integrative computational framework. Methods: We analyzed 893 SFARI genes using a three-pronged computational approach: (1) a Machine Learning Dynamic Perturbation Propagation algorithm; (2) a hypergraph construction method explicitly modeling multi-gene complexes by integrating protein–protein interactions, co-expression modules, and curated pathways; and (3) Hypergraph Neural Network embeddings for gene clustering. Validation was performed using hub-independent features to address potential circularity, followed by a druggability assessment to prioritize therapeutic targets. Results: The hypergraph construction captured 3,847 multi-way relationships, representing a 45% increase in biological relationships compared to pairwise networks. The perturbation algorithm achieved a 51% higher correlation with TADA genetic evidence than random walk methods. Analysis revealed a hierarchical organization where 179 hub genes exhibited a 3.22-fold increase in degree centrality and a 4.71-fold increase in perturbation scores relative to non-hub genes. Hypergraph Neural Network clustering identified five distinct gene clusters, including a “super-hub” cluster of 10 genes enriched in synaptic signaling (4.2-fold) and chromatin remodeling (3.9-fold). Validation confirmed that 8 of these 10 genes co-cluster even without topological information. Finally, we identified high-priority therapeutic targets, including ARID1A, POLR2A, and CACNB1. Conclusions: These findings establish hierarchical network organization principles in ASD, demonstrating that hub genes maintain substantially elevated perturbation states. The identification of critical network bottlenecks and pharmacologically tractable targets provides a foundation for understanding autism pathogenesis and developing precision medicine approaches. Full article

(This article belongs to the Special Issue Multidisciplinary Approaches to Neurodegenerative Disorders)

34 pages, 3376 KB

Open AccessArticle

Lexicographic Preferences Similarity for Coalition Formation in Complex Markets: Introducing PLPSim, HRECS, ContractLex, PriceLex, F@Lex, and PLPGen

by Faria Nassiri-Mofakham, Shadi Farid and Katsuhide Fujita

Information 2026, 17(1), 62; https://doi.org/10.3390/info17010062 (registering DOI) - 9 Jan 2026

Abstract

Lexicographic preference trees (LP-Trees) provide a compact and expressive representation for modeling complex decision-making scenarios, yet measuring similarity between complete or partial structures remains a challenge. This study introduces PLPSim, a novel metric for quantifying alignment between partial lexicographic preference trees (PLP-Trees) and [...] Read more.

Lexicographic preference trees (LP-Trees) provide a compact and expressive representation for modeling complex decision-making scenarios, yet measuring similarity between complete or partial structures remains a challenge. This study introduces PLPSim, a novel metric for quantifying alignment between partial lexicographic preference trees (PLP-Trees) and develops three coalition formation algorithms—HRECS1, HRECS2, and HRECS3—that leverage PLPSim to group agents with similar preferences. We further propose ContractLex and PriceLex protocols (comprising CLF, CFB, CFW, CFA, CFP) for coalition-based contract and pricing strategies, along with a new evaluation metric, F@Lex, which is designed to assess satisfaction under lexicographic preferences. To illustrate the framework, we generate a synthetic dataset (PLPGen) contextualized in a hybrid renewable energy market, where consumers’ PLP-Trees are aggregated and matched with suppliers’ tariff contracts. Experiments across 162 market scenarios, evaluated using Normalized Discounted Cumulative Gain (nDCG), Davies–Bouldin dispersion, and F@Lex, demonstrate that PLPSim-based coalitions outperform baseline approaches. The combination HRECS3 + CFP yields the highest consumer satisfaction, while HRECS3 + CFB achieves balanced satisfaction for both consumers and suppliers. While electricity tariffs and renewable energy contracts—static and dynamic—serve as the motivating example, the proposed framework generalizes to diverse multi-agent systems, offering a foundation for preference-driven coalition formation, adaptive policy design, and sustainable market optimization. Full article

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