Search Results (3,656)

Simultaneous optimization of vehicle routing and cargo loading is essential for reducing operational costs and improving the environmental performance of logistics systems. To overcome the limitations of traditional sequential approaches to the one-to-many pickup and delivery vehicle routing problem with three-dimensional loading constraints (3L-PDVRP), this paper proposes a deeply coupled hybrid genetic algorithm (HGA). The algorithm adopts a grouping-based genetic encoding strategy to accommodate variable fleet sizes and incorporates a tree-search-based loading module. A dynamic three-dimensional loading feasibility verification mechanism is embedded directly into the evolutionary search so that routing decisions are continuously guided by fragility, stacking stability, support constraints, and other loading constraints. In addition, an adaptive hybrid insertion strategy is employed to balance global exploration and local exploitation during route construction and repair. Extensive computational experiments on extended benchmark instances derived from standard datasets show that the proposed method consistently outperforms a large neighborhood search (LNS)-based baseline from the literature, reducing the average total travel distance by 10.60% and increasing the average vehicle loading rate by 2.76%. These results indicate that the proposed HGA provides an effective approach to the synergistic optimization of routing and loading in one-to-many distribution settings, offering practical value for lowering transportation costs and supporting more sustainable logistics operations. This methodology provides decision support for logistics enterprises, reducing travel distances while ensuring three-dimensional loading feasibility, thereby enabling greener and safer transportation operations. Full article

Due to their therapeutic potential and effects on cells, exosomes derived from bovine colostrum (BCE) and milk (BME) are molecules that have been at the center of recent studies. Their properties include the ability to cross biological barriers, their natural biocompatibility, and their structure, which enable them to act as stable nanocarriers. Exosomes derived from milk and colostrum stand out in cancer prevention and treatment due to these properties. BMEs can be enriched with bioactive peptides, lipids, and nucleic acids. The targeted drug delivery capacity of BMEs can be made more efficient through these enrichment processes. For example, BME enriched with an iRGD peptide and developed using hypoxia-sensitive lipids selectively transported drugs and reduced the survival rate of triple-negative breast cancer (TNBC) cells. ARV-825-CME formulations increased antitumor activity in some cancer types. The anticancer effects of exosomes are supported by these examples. In addition to their anticancer activities, exosomes also exhibit effects that maintain immune balance. BME and BCE can regulate inflammatory responses with their miRNA and protein loads. These effects of BMEs have been demonstrated in studies on colon, breast, liver, and lung cancers. The findings support the safety and scalability of these effects. However, significant challenges remain in terms of their large-scale isolation, load heterogeneity, and regulatory standardization. Consequently, BMEs represent a new generation of biogenic nanoplatforms at the intersection of nutrition, immunology, and oncology, paving the way for innovative therapeutic approaches. Full article

The impacts of land use on stormwater runoff quality and Best Management Practices to mitigate these impacts have been investigated since the 1970s, yet challenges remain in providing a modeling approach that concomitantly considers contributions from different land use types. In densely developed urban areas, a buildup/washoff approach is often applied, while in rural areas, some type of erosion modeling is employed, as the processes of detachment, entrainment, and transport are fundamentally different. This study presents a coupled modeling approach within PCSWMM, integrating exponential buildup/washoff for impervious surfaces with the Modified Universal Soil Loss Equation (MUSLE) for pervious areas, including construction sites, to characterize water quality in the large mixed urban–rural Sparrovale catchment in Geelong, Australia. The watershed includes an innovative cascading system of 12 online NbS wetlands along one of the main tributaries, Armstrong Creek, to manage runoff quantity and quality, as well as 16 offline NbS wetlands that are tributary to the online system. A total of 78 samples for Total Suspended Solids (TSS), Total Phosphorus (TP), and Total Nitrogen (TN) were collected from six monitoring sites along Armstrong Creek during wet- and dry-weather events between May and July 2024 for model validation. The data were supplemented with six other catchment stormwater quality datasets collected during earlier studies, which provided an understanding of water quality status for the broader Geelong region. Results showed that average nutrient concentrations across all the sites ranged from 0.44 to 2.66 mg/L for TP and 0.69 to 5.7 mg/L for TN, spanning from within to above the ecological threshold ranges for eutrophication risk (TP: 0.042 to 1 mg/L, TN: 0.3 to 1.5 mg/L). In the study catchment, upstream wetlands reduced pollutant levels; however, downstream wetlands that received runoff from agriculture, residential areas, and, importantly, construction sites, showed a substantial increase in sediment and nutrient concentration. Water quality modeling revealed washoff parameters primarily influenced concentrations from established urban neighborhoods, whereas erosion parameters substantially impacted total pollutant loads for the larger system, demonstrating the importance of integrated modeling for capturing pollutant dynamics in heterogeneous, urbanizing catchments. The study results emphasize the need for spatially targeted management strategies to improve stormwater runoff quality and also show the potential for cascading wetlands to be an important element of the Nature-based Solution (NbS) runoff management system. Full article

This study presents the first computational investigation of hybrid propeller configurations that combine toroidal and conventional blade geometries. Using Delayed Detached Eddy Simulation (DDES) with the Shear Stress Transport (SST) $k-\omega$ model for flow analysis and the Ffowcs Williams and Hawkings (FW–H) formulation for aeroacoustic prediction, five hybrid propeller designs were evaluated: a baseline model and four variants with modified loop-element spacing. The results show that the V-Gap-S configuration achieves the highest figure of merit (FM), producing over 10% improvement in propeller performance relative to the baseline, while also exhibiting the lowest turbulence kinetic energy (TKE) levels across multiple radial planes. Aeroacoustic analysis reveals quadrupole-like directivity for primary tonal noise, primarily driven by blade tip–vortex interactions, with primary tonal noise strongly correlated with thrust. Broadband noise and overall sound pressure level (OASPL) exhibited dipole-like patterns, influenced by propeller torque and FM, respectively. Comparisons of surface pressure, vorticity, and time derivatives of acoustic pressure further elucidate the mechanisms linking blade spacing to aerodynamic loading and noise generation. The results demonstrate that aerodynamic performance and aeroacoustics are strongly coupled and that meaningful noise reduction claims require performance conditions to be matched. Full article

Energy-efficient driving is essential for reducing the environmental impacts of road transport, especially for electric passenger vehicles. This research aims to build a data-driven behavioral analysis and energy-consumption evaluation model. The model relies on sensor data from the vehicle’s on-board communication network, primarily the CAN (Controller Area Network) bus. We analyze patterns of key powertrain and battery parameters—such as current, voltage, state of charge (SoC), and power—in relation to driver inputs, such as the accelerator pedal position. In the first stage, we review the literature with a focus on machine learning and clustering methods used in behavioral and energy analysis. We also examine the role of on-board telemetry systems. Next, we develop a controlled measurement architecture. It defines reference consumption maps from dynamometer data across operating points and environmental variables, including SoC, temperature, and load. The longer-term goal is a multidimensional behavioral map and profiling framework that can predict energy efficiency from real-time driver inputs. This work lays the foundation for a future system with adaptive, feedback-based driver support. Such a system can promote intelligent, sustainable, and behavior-oriented mobility solutions. Full article

Side flaps are critical structural components of flat freight wagons, directly affecting cargo safety during transportation and playing an essential role in loading and unloading operations. Over the years, their reliability has been well established, with standardized designs available in UIC technical datasheets. Despite this standardization, the introduction of newly manufactured or redesigned components necessitates technological validation through Finite Element Method (FEM) simulations and/or physical testing. This requirement holds irrespective of whether the component in question adheres to existing standards or is a novel development. This study presents the creation and application of computational models for the structural sizing and strength assessment of side flaps for flat wagons. The models are verified through a series of physical tests conducted by a research team at the Technical University of Sofia. Full article

Agricultural materials frequently undergo fragmentation due to high-stress conditions during processing, storage, and transportation. Throughout these processes, the spatial arrangement and morphology of particles continuously evolve, rendering the breakage behaviour of particle groups particularly complex. Thus, an in-depth understanding of the fracture processes and breakage mechanisms within particle beds holds significant research value. This study systematically investigates the breakage behaviour of rice particle groups under confined compression through an integrated methodology combining experimental testing, X-ray CT imaging, and finite element modelling (FEM) based on the cohesive zone model (CZM). Results demonstrate that, at the granular assembly scale, external loads are transmitted through force chains and progressively attenuate. As compression proceeds, stress disseminates toward peripheral particle regions. At the individual particle level, particle breakage results from the intricate interaction between coordination number (CN) and localized contact stress, with tensile stress playing a predominant role in the fracture process. An increase in coordination number promotes a more uniform stress distribution and inhibits breakage, thereby exhibiting a “protective effect”. These findings provide valuable insights for the design and optimization of grain processing equipment, contributing to a deeper comprehension of particle breakage characteristics. Full article

Marine aerosol particles influence the climate, and interactions between ocean waves and coral reefs may impact aerosol size distributions in remote locations, such as the Great Barrier Reef. However, quantifying these processes has proven to be challenging. We tested whether marine aerosol size distributions and concentrations differ across four zones: background air outside the lagoon, above the reef crest, within the lagoon, and near the beach of Heron Island, approximately 85 km offshore. Using a modified DJI Matrice 600 hexacopter equipped with a miniaturised optical particle counter and custom inline gas dryer, we measured aerosols from 165 to 3000 nm across 64 drone flights during 16 sampling events in November 2024. Aerosol concentrations showed substantial day-to-day temporal variability, while spatial differences among reef zones were generally minor; on certain days, the maximum difference between background and near-island measurements reached approximately 25%. K-means clustering identified four dominant air mass transport patterns, and Hybrid Single-Particle Lagrangian Integrated Trajectory model analysis indicated that upwind conditions had a strong influence on aerosol loading. Vertical profiles revealed limited variability within the lowest 100 m. Mixing layer height, air parcel travel speed, and water depth along the final 12 h of trajectories were key drivers of aerosol variability. These results demonstrate the potential of drone-based measurements for characterising marine aerosols and provide a foundation for improving climate model representations of natural aerosol processes. Full article

In the context of promoting strategies to mitigate the global warming effect resulting from greenhouse gas emissions produced by human activities, ammonia stands out as an important player in the decarbonization of various sectors, including transportation, energy, and other industries. Ammonia is an effective carrier of hydrogen, having three times the volumetric energy density of hydrogen itself. In this study, the authors present findings obtained from a group of experiments and simulations conducted on a diesel engine operating at a constant speed and under different loads, using a dual-fuel method in which ammonia was injected into the intake manifold to partially replace the original diesel fuel. The results demonstrate that it is possible to reduce fuel consumption and CO₂ emissions. NO_x dropped by 40.8% and soot by 13.4% under heavy load, while under light load, they dropped by 50.5% and 23.3%, respectively. Full article

Under China’s “dual-carbon” strategic goals and the advancement of smart city development, the rapid adoption of electric vehicles (EVs) has deepened the spatiotemporal coupling between transportation networks and distribution grids, posing new challenges for integrated energy systems. To address this, we propose a collaborative optimization framework for power–transportation coupled networks that integrates multi-modal data with physical priors. The framework constructs a joint feature space from traffic flow, pedestrian density, charging behavior, and grid operating states, and employs hypergraph modeling—guided by power flow balance and traffic flow conservation principles—to capture high-order cross-domain coupling. For prediction, spatiotemporal graph convolution combined with physics-informed attention significantly improves the accuracy of EV charging load forecasting. For optimization, a hierarchical multi-agent strategy integrating federated learning and the Alternating Direction Method of Multipliers (ADMM) enables privacy-preserving, distributed charging load scheduling. Case studies conducted on a 69-node distribution network using real traffic and charging data demonstrate that the proposed method reduces the grid’s peak–valley difference by 20.16%, reduces system operating costs by approximately 25%, and outperforms mainstream baseline models in prediction accuracy, algorithm convergence speed, and long-term operational stability. This work provides a practical and scalable technical pathway for the deep integration of energy and transportation systems in future smart cities. Full article

Smart nanocarriers are being increasingly explored to improve the performance selectivity of cancer chemotherapy. Here, two pH-responsive magnetic nanocarriers were developed using quaternary chitosan (HTCC) functionalized with 3-(triethoxysilyl)propyl isocyanate- ICPTES (MNP-HTCC1) or 3-(glycidyloxypropyl)trimethoxysilane-GPTMS (MNP-HTCC2) to form hybrid silica shells on Fe₃O₄ cores. The resulting core–shell nanoparticles (14.5 and 12.5 nm) displayed highly positive zeta potentials (+45.4 to +27.1 mV, pH 4.2–9.5), confirming successful HTCC incorporation and strong colloidal stability. Both nanocarriers achieved high doxorubicin (DOX) loading at pH 9.5, reaching 90% efficiency and a capacity of 154 µg DOX per mg. DOX release was pH-dependent, with faster release under acidic conditions relevant to tumor and endo-lysosomal environments. At pH 4.2, MNP-HTCC1 released 90% of DOX over 72 h, while MNP-HTCC2 released 79%. Release at pH 5.0 was intermediate (67–72%), and moderate at physiological pH (43–55%). All formulations showed an initial burst followed by sustained release. Kinetic modelling (Weibull) indicated a diffusion-controlled mechanism consistent with Fickian transport through the HTCC–silica matrix. Cytotoxicity assays using MCF-7 breast cancer cells revealed greater cytotoxicity for DOX-loaded nanocarriers compared with free DOX, with MNP-HTCC1 showing the strongest effect. Overall, these HTCC-based magnetic nanocarriers offer efficient loading, controlled pH-triggered DOX release, and enhanced therapeutic performance. Full article

This article describes the possibilities of using universal flat wagons to transport long cargoes and suggests measures for upgrading them, which involve the installation of superstructures on the load-bearing structures to keep the cargo from overturning. The study was conducted using the flat wagon model 13-401. Several options for implementing such superstructures have been considered. The load-bearing structure of the flat wagon was modeled as a rod system. The most rational option for upgrading was evaluated by assessing the force factors acting in the structure under the influence of external loads. According to the chosen upgrade option, a spatial model of the bearing structure of the flat wagon was built, and its strength was calculated using the finite element method. The proposed option was found to be appropriate. The results of the research can be used to improve the efficiency of transportation of long cargoes by universal flat wagons. Full article

The rapid mobilization of sediment stored behind dams, in amounts that are large relative to mean annual sediment loads, can jumpstart river restoration but can also adversely impact habitat, infrastructure, land, and water use upstream of, within, and downstream of the former impoundment. A wide range of geomorphic and engineering assessment tools were applied to help manage sediment-related risks associated with the removal of two dams from the Elwha River in Washington State and the release of roughly 21 million m³ of sediment. Each of these tools had its strengths and weaknesses, which are explored here. The processes of sediment erosion, transport and deposition were complex. No one model was able to fully simulate all these with the accuracy necessary for predicting the magnitude and timing of coarse and fine sediment release from the reservoir. Collectively, however, the model outputs provided enough information to guide the adaptive sediment management process during dam removal. When the complexity of the morphodynamic responses to dam removal and the associated risks exceeded the capacity of any one tool to adequately assess, synoptic forecasting proved useful. The lessons learned on the Elwha have provided insights into how to use a variety of modeling techniques to address sediment management issues as dam removal scale, complexity and risk increase. Full article

White Spot Syndrome Virus (WSSV) remains one of the most devastating pathogens in global shrimp aquaculture, causing massive economic losses annually. This study employed comparative transcriptomics to elucidate the molecular basis of the differential resistance to WSSV between the highly susceptible Pacific white shrimp (Litopenaeus vannamei) and the remarkably resistant oriental river prawn (Macrobrachium nipponense). Our analysis of gill, hepatopancreas, and muscle tissues at 24 h post-infection revealed fundamentally distinct defense strategies. The resistant M. nipponense employs a unique “proactive homeostatic reinforcement” strategy, characterized by significant enrichment of pathways central to cellular homeostasis, including signal transduction, cellular processes, and transport/catabolism. This approach, supported by coordinated up-regulation of heat shock proteins and structural genes, enables effective viral control without triggering excessive immune activation. In contrast, susceptible L. vannamei displays either widespread metabolic dysregulation leading to systemic collapse in moribund individuals or dependency on specific immune pathways (Toll-like receptor signaling and apoptosis) in survivors. Through comparative KEGG analysis, we identified heat shock protein 70 kDa (HSP70, K03283) as a key conserved gene and functionally validated its critical role in antiviral defense using RNA interference. Knockdown of HSP70 in M. nipponense significantly increased cumulative mortality and viral load, confirming its essential protective function. These findings provide novel insights into crustacean antiviral immunity and identify promising genetic targets for breeding WSSV-resistant shrimp strains, offering sustainable solutions for disease management in aquaculture. Full article

Against the backdrop of China’s dual-carbon goals, traditional road transportation has relatively high carbon emissions and is in urgent need of a low-carbon transition. The intermittency of photovoltaic (PV) power generation and the stochastic nature of electric vehicle (EV) charging demand introduce significant uncertainty for PV-energy storage-charging systems in highway service areas. Existing approaches often struggle to balance economic efficiency and reliability. This study develops a min-max-min robust optimization model for a full-route PV-energy storage-charging system. A box uncertainty set is used to characterize uncertainties in PV output and EV load, and a tunable uncertainty parameter is introduced to regulate risk. The model is solved using a column-and-constraint generation (C&CG) algorithm that decomposes the problem into a master problem and a subproblem. Strong duality, combined with a big-M formulation, enables an alternating iterative solution between the master problem and the subproblem. Simulation results demonstrate that the proposed algorithm attains the optimal solution and, relative to deterministic optimization, achieves a desirable trade-off between economic performance and robustness. Full article