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Keywords = design for transportation

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29 pages, 3563 KiB  
Article
Assessment of Hydrogels for Intra-Articulate Application, Based on Sodium Hyaluronate Doped with Synthetic Polymers and Incorporated with Diclofenac Sodium
by Dorota Wójcik-Pastuszka, Maja Grabara and Witold Musiał
Int. J. Mol. Sci. 2025, 26(15), 7631; https://doi.org/10.3390/ijms26157631 (registering DOI) - 6 Aug 2025
Abstract
The intra-articular application of drugs has gained considerable interest with regard to formulations for advanced drug delivery systems. It has been identified as a potential route for local drug delivery. A drug agent is usually incorporated into the hydrogel to prolong and control [...] Read more.
The intra-articular application of drugs has gained considerable interest with regard to formulations for advanced drug delivery systems. It has been identified as a potential route for local drug delivery. A drug agent is usually incorporated into the hydrogel to prolong and control the drug release. This study aimed to design and evaluate an intra-articular hydrogel based sodium hyaluronate, which was modified with an additional polymer to enable the sustained release of the incorporated anti-inflammatory agent, diclofenac sodium (NaDic). Viscosity studies, drug release tests and FTIR−ATR measurements, as well as DSC analysis, were carried out to evaluate the obtained formulations. The viscosity measurements were performed using a rotational viscometer. The drug release was carried out by employing the apparatus paddle over the disk. The concentration of the released drug was obtained spectrophotometrically. The results revealed that the addition of the second polymer to the matrix influenced the dynamic viscosity of the hydrogels. The highest viscosity of (25.33 ± 0.55) × 103 cP was observed when polyacrylic acid (PA) was doped in the formulation. This was due to the hydrogen bond formation between both polymers. The FTIR−ATR investigations and DSC study revealed the hydrogen bond formation between the drug and both polymers. The drug was released the slowest from hydrogel doped with PA and 17.2 ± 3.7% of NaDic was transported to the acceptor fluid within 8 h. The hydrogel based on hyaluronan sodium doped with PA and containing NaDic is a promising formulation for the prolonged and controlled intra-articulate drug delivery of anti-inflammatory agents. Full article
(This article belongs to the Special Issue New Insights into Hyaluronan in Human Medicine)
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20 pages, 6778 KiB  
Article
Computational Approaches to Assess Flow Rate Efficiency During In Situ Recovery of Uranium: From Reactive Transport to Streamline- and Trajectory-Based Methods
by Maksat Kurmanseiit, Nurlan Shayakhmetov, Daniar Aizhulov, Banu Abdullayeva and Madina Tungatarova
Minerals 2025, 15(8), 835; https://doi.org/10.3390/min15080835 - 6 Aug 2025
Abstract
This study presents a comprehensive computational analysis of flow rate efficiency during uranium extraction via the In Situ Recovery method. Using field data from a deposit located in Southern Kazakhstan, a series of mathematical models were developed to evaluate the distribution and balance [...] Read more.
This study presents a comprehensive computational analysis of flow rate efficiency during uranium extraction via the In Situ Recovery method. Using field data from a deposit located in Southern Kazakhstan, a series of mathematical models were developed to evaluate the distribution and balance of leaching solution. A reactive transport model incorporating uranium dissolution kinetics and acid–rock interactions were utilized to assess the accuracy of both traditional and proposed methods. The results reveal a significant spatial imbalance in sulfuric acid distribution, with up to 239.1 tons of acid migrating beyond the block boundaries. To reduce computational demands while maintaining predictive accuracy, two alternative methods, a streamline-based and a trajectory-based approach were proposed and verified. The streamline method showed close agreement with reactive transport modeling and was able to effectively identify the presence of intra-block reagent imbalance. The trajectory-based method provided detailed insight into flow dynamics but tended to overestimate acid overflow outside the block. Both alternative methods outperformed the conventional approach in terms of accuracy by accounting for geological heterogeneity and well spacing. The proposed methods have significantly lower computational costs, as they do not require solving complex systems of partial differential equations involved in reactive transport simulations. The proposed approaches can be used to analyze the efficiency of mineral In Situ Recovery at both the design and operational stages, as well as to determine optimal production regimes for reducing economic expenditures in a timely manner. Full article
(This article belongs to the Section Mineral Processing and Extractive Metallurgy)
30 pages, 8483 KiB  
Article
Research on Innovative Design of Two-in-One Portable Electric Scooter Based on Integrated Industrial Design Method
by Yang Zhang, Xiaopu Jiang, Shifan Niu and Yi Zhang
Sustainability 2025, 17(15), 7121; https://doi.org/10.3390/su17157121 - 6 Aug 2025
Abstract
With the advancement of low-carbon and sustainable development initiatives, electric scooters, recognized as essential transportation tools and leisure products, have gained significant popularity, particularly among young people. However, the current electric scooter market is plagued by severe product similarity. Once the initial novelty [...] Read more.
With the advancement of low-carbon and sustainable development initiatives, electric scooters, recognized as essential transportation tools and leisure products, have gained significant popularity, particularly among young people. However, the current electric scooter market is plagued by severe product similarity. Once the initial novelty fades for users, the usage frequency declines, resulting in considerable resource wastage. This research collected user needs via surveys and employed the KJ method (affinity diagram) to synthesize fragmented insights into cohesive thematic clusters. Subsequently, a hierarchical needs model for electric scooters was constructed using analytical hierarchy process (AHP) principles, enabling systematic prioritization of user requirements through multi-criteria evaluation. By establishing a house of quality (HoQ), user needs were transformed into technical characteristics of electric scooter products, and the corresponding weights were calculated. After analyzing the positive and negative correlation degrees of the technical characteristic indicators, it was found that there are technical contradictions between functional zoning and compact size, lightweight design and material structure, and smart interaction and usability. Then, based on the theory of inventive problem solving (TRIZ), the contradictions were classified, and corresponding problem-solving principles were identified to achieve a multi-functional innovative design for electric scooters. This research, leveraging a systematic industrial design analysis framework, identified critical pain points among electric scooter users, established hierarchical user needs through priority ranking, and improved product lifecycle sustainability. It offers novel methodologies and perspectives for advancing theoretical research and design practices in the electric scooter domain. Full article
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20 pages, 1279 KiB  
Article
A Framework for Quantifying Hyperloop’s Socio-Economic Impact in Smart Cities Using GDP Modeling
by Aleksejs Vesjolijs, Yulia Stukalina and Olga Zervina
Economies 2025, 13(8), 228; https://doi.org/10.3390/economies13080228 - 6 Aug 2025
Abstract
Hyperloop ultra-high-speed transport presents a transformative opportunity for future mobility systems in smart cities. However, assessing its socio-economic impact remains challenging due to Hyperloop’s unique technological, modal, and operational characteristics. As a novel, fifth mode of transportation—distinct from both aviation and rail—Hyperloop requires [...] Read more.
Hyperloop ultra-high-speed transport presents a transformative opportunity for future mobility systems in smart cities. However, assessing its socio-economic impact remains challenging due to Hyperloop’s unique technological, modal, and operational characteristics. As a novel, fifth mode of transportation—distinct from both aviation and rail—Hyperloop requires tailored evaluation tools for policymakers. This study proposes a custom-designed framework to quantify its macroeconomic effects through changes in gross domestic product (GDP) at the city level. Unlike traditional economic models, the proposed approach is specifically adapted to Hyperloop’s multimodality, infrastructure, speed profile, and digital-green footprint. A Poisson pseudo-maximum likelihood (PPML) model is developed and applied at two technology readiness levels (TRL-6 and TRL-9). Case studies of Glasgow, Berlin, and Busan are used to simulate impacts based on geo-spatial features and city-specific trade and accessibility indicators. Results indicate substantial GDP increases driven by factors such as expanded 60 min commute catchment zones, improved trade flows, and connectivity node density. For instance, under TRL-9 conditions, GDP uplift reaches over 260% in certain scenarios. The framework offers a scalable, reproducible tool for policymakers and urban planners to evaluate the economic potential of Hyperloop within the context of sustainable smart city development. Full article
(This article belongs to the Section International, Regional, and Transportation Economics)
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41 pages, 7308 KiB  
Review
Challenges and Opportunities for Extending Battery Pack Life Using New Algorithms and Techniques for Battery Electric Vehicles
by Pedro S. Gonzalez-Rodriguez, Jorge de J. Lozoya-Santos, Hugo G. Gonzalez-Hernandez, Luis C. Felix-Herran and Juan C. Tudon-Martinez
World Electr. Veh. J. 2025, 16(8), 442; https://doi.org/10.3390/wevj16080442 - 5 Aug 2025
Abstract
The shift from Internal Combustion Engine Vehicles (ICEVs) to Battery Electric Vehicles (BEVs) has accelerated global efforts to decarbonize transportation. However, battery degradation, high costs, and limited lifespan remain critical barriers. This review synthesizes recent innovations to extend Li-ion battery life in BEVs [...] Read more.
The shift from Internal Combustion Engine Vehicles (ICEVs) to Battery Electric Vehicles (BEVs) has accelerated global efforts to decarbonize transportation. However, battery degradation, high costs, and limited lifespan remain critical barriers. This review synthesizes recent innovations to extend Li-ion battery life in BEVs by exploring advances in degradation modeling, adaptive Battery Management Systems (BMSs), electronic component simulations, and real-world usage profiling. The authors have systematically analyzed over 80 recent studies using a PRISMA-guided review protocol. A novel comparative framework highlights gaps in current literature, particularly regarding real-world driving impacts, ripple current effects, and second-life battery applications. This review article critically compares model-driven, data-driven, and hybrid model approaches, emphasizing trade-offs in interpretability, accuracy, and deployment feasibility. Finally, the review links battery life extension to broader sustainability metrics, including circular economy models and predictive maintenance algorithms. This review offers actionable insights for researchers, engineers, and policymakers aiming to design longer-lasting and more sustainable electric mobility systems. Full article
(This article belongs to the Special Issue Electric Vehicle Battery Pack and Electric Motor Sizing Methods)
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88 pages, 9998 KiB  
Review
Research and Developments of Heterogeneous Catalytic Technologies
by Milan Králik, Peter Koóš, Martin Markovič and Pavol Lopatka
Molecules 2025, 30(15), 3279; https://doi.org/10.3390/molecules30153279 - 5 Aug 2025
Abstract
This review outlines a comprehensive methodology for the research and development of heterogeneous catalytic technologies (R&D_HeCaTe). Emphasis is placed on the fundamental interactions between reactants, solvents, and heterogeneous catalysts—specifically the roles of catalytic centers and support materials (e.g., functional groups) in modulating activation [...] Read more.
This review outlines a comprehensive methodology for the research and development of heterogeneous catalytic technologies (R&D_HeCaTe). Emphasis is placed on the fundamental interactions between reactants, solvents, and heterogeneous catalysts—specifically the roles of catalytic centers and support materials (e.g., functional groups) in modulating activation energies and stabilizing catalytic functionality. Particular attention is given to catalyst deactivation mechanisms and potential regeneration strategies. The application of molecular modeling and chemical engineering analyses, including reaction kinetics, thermal effects, and mass and heat transport phenomena, is identified as essential for R&D_HeCaTe. Reactor configuration is discussed in relation to key physicochemical parameters such as molecular diffusivity, reaction exothermicity, operating temperature and pressure, and the phase and “aggressiveness” of the reaction system. Suitable reactor types—such as suspension reactors, fixed-bed reactors, and flow microreactors—are evaluated accordingly. Economic and environmental considerations are also addressed, with a focus on the complexity of reactions, selectivity versus conversion trade-offs, catalyst disposal, and separation challenges. To illustrate the breadth and applicability of the proposed framework, representative industrial processes are discussed, including ammonia synthesis, fluid catalytic cracking, methanol production, alkyl tert-butyl ethers, and aniline. Full article
(This article belongs to the Special Issue Heterogeneous Catalysts: From Synthesis to Application)
42 pages, 14160 KiB  
Article
Automated Vehicle Classification and Counting in Toll Plazas Using LiDAR-Based Point Cloud Processing and Machine Learning Techniques
by Alexander Campo-Ramírez, Eduardo F. Caicedo-Bravo and Bladimir Bacca-Cortes
Future Transp. 2025, 5(3), 105; https://doi.org/10.3390/futuretransp5030105 - 5 Aug 2025
Abstract
This paper presents the design and implementation of a high-precision vehicle detection and classification system for toll stations on national highways in Colombia, leveraging LiDAR-based 3D point cloud processing and supervised machine learning. The system integrates a multi-sensor architecture, including a LiDAR scanner, [...] Read more.
This paper presents the design and implementation of a high-precision vehicle detection and classification system for toll stations on national highways in Colombia, leveraging LiDAR-based 3D point cloud processing and supervised machine learning. The system integrates a multi-sensor architecture, including a LiDAR scanner, high-resolution cameras, and Doppler radars, with an embedded computing platform for real-time processing and on-site inference. The methodology covers data preprocessing, feature extraction, descriptor encoding, and classification using Support Vector Machines. The system supports eight vehicular categories established by national regulations, which present significant challenges due to the need to differentiate categories by axle count, the presence of lifted axles, and vehicle usage. These distinctions affect toll fees and require a classification strategy beyond geometric profiling. The system achieves 89.9% overall classification accuracy, including 96.2% for light vehicles and 99.0% for vehicles with three or more axles. It also incorporates license plate recognition for complete vehicle traceability. The system was deployed at an operational toll station and has run continuously under real traffic and environmental conditions for over eighteen months. This framework represents a robust, scalable, and strategic technological component within Intelligent Transportation Systems and contributes to data-driven decision-making for road management and toll operations. Full article
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18 pages, 2365 KiB  
Article
Integrated Environmental–Economic Assessment of CO2 Storage in Chinese Saline Formations
by Wentao Zhao, Zhe Jiang, Tieya Jing, Jian Zhang, Zhan Yang, Xiang Li, Juan Zhou, Jingchao Zhao and Shuhui Zhang
Water 2025, 17(15), 2320; https://doi.org/10.3390/w17152320 - 4 Aug 2025
Abstract
This study develops an integrated environmental–economic assessment framework to evaluate the life cycle environmental impacts and economic costs of CO2 geological storage and produced water treatment in saline formations in China. Using a case study of a saline aquifer carbon storage project [...] Read more.
This study develops an integrated environmental–economic assessment framework to evaluate the life cycle environmental impacts and economic costs of CO2 geological storage and produced water treatment in saline formations in China. Using a case study of a saline aquifer carbon storage project in the Ordos Basin, eight full-chain carbon capture, utilization, and storage (CCUS) scenarios were analyzed. The results indicate that environmental and cost performance are primarily influenced by technology choices across carbon capture, transport, and storage stages. The scenario employing potassium carbonate-based capture, pipeline transport, and brine reinjection after a reverse osmosis treatment (S5) achieved the most balanced outcome. Breakeven analyses under three carbon price projection models revealed that carbon price trajectories critically affect project viability, with a steadily rising carbon price enabling earlier profitability. By decoupling CCUS from power systems and focusing on unit CO2 removal, this study provides a transparent and transferable framework to support cross-sectoral deployment. The findings offer valuable insights for policymakers aiming to design effective CCUS support mechanisms under future carbon neutrality targets. Full article
(This article belongs to the Special Issue Mine Water Treatment, Utilization and Storage Technology)
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26 pages, 1978 KiB  
Article
Fluorescent Peptides Internalize HeLa Cells and Kill Multidrug-Resistant Clinical Bacterial Isolates
by Daniel Castellar-Almonacid, Kelin Johana Cuero-Amu, Jose David Mendoza-Mendoza, Natalia Ardila-Chantré, Fernando José Chavez-Salazar, Andrea Carolina Barragán-Cárdenas, Jhon Erick Rivera-Monroy, Claudia Parra-Giraldo, Zuly Jenny Rivera-Monroy, Javier García-Castañeda and Ricardo Fierro-Medina
Antibiotics 2025, 14(8), 793; https://doi.org/10.3390/antibiotics14080793 - 4 Aug 2025
Abstract
Palindromic antimicrobial peptides (PAMs) constitute versatile scaffolds for the design and optimization of anticancer agents with applications in therapy, diagnosis, and/or monitoring. In the present study, fluorolabeled peptides derived from the palindromic sequence RWQWRWQWR containing fluorescent probes, such as 2-Aminobenzoyl, 5(6)-Carboxyfluorescein, and Rhodamine [...] Read more.
Palindromic antimicrobial peptides (PAMs) constitute versatile scaffolds for the design and optimization of anticancer agents with applications in therapy, diagnosis, and/or monitoring. In the present study, fluorolabeled peptides derived from the palindromic sequence RWQWRWQWR containing fluorescent probes, such as 2-Aminobenzoyl, 5(6)-Carboxyfluorescein, and Rhodamine B, were obtained. RP-HPLC analysis revealed that the palindromic peptide conjugated to Rhodamine B (RhB-RWQWRWQWR) exhibited the presence of isomers, likely corresponding to the open-ring and spiro-lactam forms of the fluorescent probe. This equilibrium is dependent on the peptide sequence, as the RP-HPLC analysis of dimeric peptide (RhB-RRWQWR-hF-KKLG)2K-Ahx did not reveal the presence of isomers. The antibacterial activity of the fluorescent peptides depends on the probe attached to the sequence and the bacterial strain tested. Notably, some fluorescent peptides showed activity against reference strains as well as sensitive, resistant, and multidrug-resistant clinical isolates of E. coli, S. aureus, and E. faecalis. Fluorolabeled peptides 1-Abz (MIC = 62 µM), RhB-1 (MIC = 62 µM), and Abz-1 (MIC = 31 µM) exhibited significant activity against clinical isolates of E. coli, S. aureus, and E. faecalis, respectively. The RhB-1 (IC50 = 61 µM), Abz-1 (IC50 = 87 µM), and RhB-2 (IC50 = 35 µM) peptides exhibited a rapid, significant, and concentration-dependent cytotoxic effect on HeLa cells, accompanied by morphological changes characteristic of apoptosis. RhB-1 (IC50 = 18 µM) peptide also exhibited significant cytotoxic activity against breast cancer cells MCF-7. These conjugates remain valuable for elucidating the possible mechanisms of action of these novel anticancer peptides. Rhodamine-labeled peptides displayed cytotoxicity comparable to that of their unlabeled analogues, suggesting that cellular internalization constitutes a critical early step in their mechanism of action. These findings suggest that cell death induced by both unlabeled and fluorolabeled peptides proceeds predominantly via apoptosis and is likely contingent upon peptide internalization. Functionalization at the N-terminal end of the palindromic sequence can be evaluated to develop systems for transporting non-protein molecules into cancer cells. Full article
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33 pages, 8443 KiB  
Article
Model for Planning and Optimization of Train Crew Rosters for Sustainable Railway Transport
by Zdenka Bulková, Juraj Čamaj and Jozef Gašparík
Sustainability 2025, 17(15), 7069; https://doi.org/10.3390/su17157069 - 4 Aug 2025
Abstract
Efficient planning of train crew rosters is a key factor in ensuring operational reliability and promoting long-term sustainability in railway transport, both economically and socially. This article presents a systematic approach to developing a crew rostering model in passenger rail transport, with a [...] Read more.
Efficient planning of train crew rosters is a key factor in ensuring operational reliability and promoting long-term sustainability in railway transport, both economically and socially. This article presents a systematic approach to developing a crew rostering model in passenger rail transport, with a focus on the operational setting of the train crew depot in Česká Třebová, a city in the Czech Republic. The seven-step methodology includes identifying available train shifts, defining scheduling constraints, creating roster variants, and calculating personnel and time requirements for each option. The proposed roster reduced staffing needs by two employees, increased the average shift duration to 9 h and 42 min, and decreased non-productive time by 384 h annually. These improvements enhance sustainability by optimizing human resource use, lowering unnecessary energy consumption, and improving employees’ work–life balance. The model also provides a quantitative assessment of operational feasibility and economic efficiency. Compared to existing rosters, the proposed model offers clear advantages and remains applicable even in settings with limited technological support. The findings show that a well-designed rostering system can contribute not only to cost savings and personnel stabilization, but also to broader objectives in sustainable public transport, supporting resilient and resource-efficient rail operations. Full article
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21 pages, 2608 KiB  
Review
Recent Progress on the Research of 3D Printing in Aqueous Zinc-Ion Batteries
by Yating Liu, Haokai Ding, Honglin Chen, Haoxuan Gao, Jixin Yu, Funian Mo and Ning Wang
Polymers 2025, 17(15), 2136; https://doi.org/10.3390/polym17152136 - 4 Aug 2025
Abstract
The global transition towards a low-carbon energy system urgently demands efficient and safe energy storage solutions. Aqueous zinc-ion batteries (AZIBs) are considered a promising alternative to lithium-ion batteries due to their inherent safety and environmental friendliness. However, conventional manufacturing methods are costly and [...] Read more.
The global transition towards a low-carbon energy system urgently demands efficient and safe energy storage solutions. Aqueous zinc-ion batteries (AZIBs) are considered a promising alternative to lithium-ion batteries due to their inherent safety and environmental friendliness. However, conventional manufacturing methods are costly and labor-intensive, hindering their large-scale production. Recent advances in 3D printing technology offer innovative pathways to address these challenges. By combining design flexibility with material optimization, 3D printing holds the potential to enhance battery performance and enable customized structures. This review systematically examines the application of 3D printing technology in fabricating key AZIB components, including electrodes, electrolytes, and integrated battery designs. We critically compare the advantages and disadvantages of different 3D printing techniques for these components, discuss the potential and mechanisms by which 3D-printed structures enhance ion transport and electrochemical stability, highlight critical existing scientific questions and research gaps, and explore potential strategies for optimizing the manufacturing process. Full article
(This article belongs to the Special Issue Polymeric Materials for Next-Generation Energy Storage)
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16 pages, 4328 KiB  
Article
High-Throughput Study on Nanoindentation Deformation of Al-Mg-Si Alloys
by Tong Shen, Guanglong Xu, Fuwen Chen, Shuaishuai Zhu and Yuwen Cui
Materials 2025, 18(15), 3663; https://doi.org/10.3390/ma18153663 - 4 Aug 2025
Abstract
Al-Mg-Si (6XXX) series aluminum alloys are widely applied in aerospace and transportation industries. However, exploring how varying compositions affect alloy properties and deformation mechanisms is often time-consuming and labor-intensive due to the complexity of the multicomponent composition space and the diversity of processing [...] Read more.
Al-Mg-Si (6XXX) series aluminum alloys are widely applied in aerospace and transportation industries. However, exploring how varying compositions affect alloy properties and deformation mechanisms is often time-consuming and labor-intensive due to the complexity of the multicomponent composition space and the diversity of processing and heat treatments. This study, inspired by the Materials Genome Initiative, employs high-throughput experimentation—specifically the kinetic diffusion multiple (KDM) method—to systematically investigate how the pop-in effect, indentation size effect (ISE), and creep behavior vary with the composition of Al-Mg-Si alloys at room temperature. To this end, a 6016/Al-3Si/Al-1.2Mg/Al KDM material was designed and fabricated. After diffusion annealing at 530 °C for 72 h, two junction areas were formed with compositional and microstructural gradients extending over more than one thousand micrometers. Subsequent solution treatment (530 °C for 30 min) and artificial aging (185 °C for 20 min) were applied to simulate industrial processing conditions. Comprehensive characterization using electron probe microanalysis (EPMA), nanoindentation with continuous stiffness measurement (CSM), and nanoindentation creep tests across these gradient regions revealed key insights. The results show that increasing Mg and Si content progressively suppresses the pop-in effect. When the alloy composition exceeds 1.0 wt.%, the pop-in events are nearly eliminated due to strong interactions between solute atoms and mobile dislocations. In addition, adjustments in the ISE enabled rapid evaluation of the strengthening contributions from Mg and Si in the microscale compositional array, demonstrating that the optimum strengthening occurs when the Mg-to-Si atomic ratio is approximately 1 under a fixed total alloy content. Furthermore, analysis of the creep stress exponent and activation volume indicated that dislocation motion is the dominant creep mechanism. Overall, this enhanced KDM method proves to be an effective conceptual tool for accelerating the study of composition–deformation relationships in Al-Mg-Si alloys. Full article
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86 pages, 28919 KiB  
Article
Sustainable Risk Mapping of High-Speed Rail Networks Through PS-InSAR and Geospatial Analysis
by Seung-Jun Lee, Hong-Sik Yun and Sang-Woo Kwak
Sustainability 2025, 17(15), 7064; https://doi.org/10.3390/su17157064 - 4 Aug 2025
Abstract
This study presents an integrated geospatial framework for assessing the risk to high-speed railway (HSR) infrastructure, combining a persistent scatterer interferometric synthetic aperture radar (PS-InSAR) analysis with multi-criteria decision-making in a geographic information system (GIS) environment. Focusing on the Honam HSR corridor in [...] Read more.
This study presents an integrated geospatial framework for assessing the risk to high-speed railway (HSR) infrastructure, combining a persistent scatterer interferometric synthetic aperture radar (PS-InSAR) analysis with multi-criteria decision-making in a geographic information system (GIS) environment. Focusing on the Honam HSR corridor in South Korea, the model incorporates both maximum ground deformation and subsidence velocity to construct a dynamic hazard index. Social vulnerability is quantified using five demographic and infrastructural indicators, and a two-stage analytic hierarchy process (AHP) is applied with dependency correction to mitigate inter-variable redundancy. The resulting high-resolution risk maps highlight spatial mismatches between geotechnical hazards and social exposure, revealing vulnerable segments in Gongju and Iksan that require prioritized maintenance and mitigation. The framework also addresses data limitations by interpolating groundwater levels and estimating train speed using spatial techniques. Designed to be scalable and transferable, this methodology offers a practical decision-support tool for infrastructure managers and policymakers aiming to enhance the resilience of linear transport systems. Full article
(This article belongs to the Section Hazards and Sustainability)
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21 pages, 1369 KiB  
Article
Optimizing Cold Food Supply Chains for Enhanced Food Availability Under Climate Variability
by David Hernandez-Cuellar, Krystel K. Castillo-Villar and Fernando Rey Castillo-Villar
Foods 2025, 14(15), 2725; https://doi.org/10.3390/foods14152725 - 4 Aug 2025
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Abstract
Produce supply chains play a critical role in ensuring fruits and vegetables reach consumers efficiently, affordably, and at optimal freshness. In recent decades, hub-and-spoke network models have emerged as valuable tools for optimizing sustainable cold food supply chains. Traditional optimization efforts typically focus [...] Read more.
Produce supply chains play a critical role in ensuring fruits and vegetables reach consumers efficiently, affordably, and at optimal freshness. In recent decades, hub-and-spoke network models have emerged as valuable tools for optimizing sustainable cold food supply chains. Traditional optimization efforts typically focus on removing inefficiencies, minimizing lead times, refining inventory management, strengthening supplier relationships, and leveraging technological advancements for better visibility and control. However, the majority of models rely on deterministic approaches that overlook the inherent uncertainties of crop yields, which are further intensified by climate variability. Rising atmospheric CO2 concentrations, along with shifting temperature patterns and extreme weather events, have a substantial effect on crop productivity and availability. Such uncertainties can prompt distributors to seek alternative sources, increasing costs due to supply chain reconfiguration. This research introduces a stochastic hub-and-spoke network optimization model specifically designed to minimize transportation expenses by determining optimal distribution routes that explicitly account for climate variability effects on crop yields. A use case involving a cold food supply chain (CFSC) was carried out using several weather scenarios based on climate models and real soil data for California. Strawberries were selected as a representative crop, given California’s leading role in strawberry production. Simulation results show that scenarios characterized by increased rainfall during growing seasons result in increased yields, allowing distributors to reduce transportation costs by sourcing from nearby farms. Conversely, scenarios with reduced rainfall and lower yields require sourcing from more distant locations, thereby increasing transportation costs. Nonetheless, supply chain configurations may vary depending on the choice of climate models or weather prediction sources, highlighting the importance of regularly updating scenario inputs to ensure robust planning. This tool aids decision-making by planning climate-resilient supply chains, enhancing preparedness and responsiveness to future climate-related disruptions. Full article
(This article belongs to the Special Issue Climate Change and Emerging Food Safety Challenges)
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17 pages, 432 KiB  
Article
Anomalous Drug Transport in Biological Tissues: A Caputo Fractional Approach with Non-Classical Boundary Modeling
by Ahmed Ghezal, Ahmed A. Al Ghafli and Hassan J. Al Salman
Fractal Fract. 2025, 9(8), 508; https://doi.org/10.3390/fractalfract9080508 - 4 Aug 2025
Viewed by 101
Abstract
This paper focuses on the numerical modeling of drug diffusion in biological tissues using fractional time-dependent parabolic equations with non-local boundary conditions. The model includes a Caputo fractional derivative to capture the non-local effects and memory inherent in biological processes, such as drug [...] Read more.
This paper focuses on the numerical modeling of drug diffusion in biological tissues using fractional time-dependent parabolic equations with non-local boundary conditions. The model includes a Caputo fractional derivative to capture the non-local effects and memory inherent in biological processes, such as drug absorption and transport. The theoretical framework of the problem is based on the work of Alhazzani, et al.,which demonstrates the solution’s goodness, existence, and uniqueness. Building on this foundation, we present a robust numerical method designed to deal with the complexity of fractional derivatives and non-local interactions at the boundaries of biological tissues. Numerical simulations reveal how fractal order and non-local boundary conditions affect the drug concentration distribution over time, providing valuable insights into drug delivery dynamics in biological systems. The results underscore the potential of fractal models to accurately represent diffusion processes in heterogeneous and complex biological environments. Full article
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