Search Results (230)

Background/Objectives: Vaccination is a critical public health intervention, yet its global implementation is hindered by high production costs and cold-chain requirements. This review aims to evaluate plant-based systems as sustainable, cost-efficient alternatives for vaccine production. Methods: A comprehensive literature search was conducted across major databases (PubMed, Scopus, Web of Science). The peer-reviewed references were critically assessed, focusing on molecular expression strategies, phytochemical immunomodulators, and plant-mediated oral delivery. Results: Plant and microalgae systems effectively support nuclear, chloroplast, and transient expression of diverse antigens. Furthermore, specific plant-derived compounds were found to act as potent adjuvants and immunostimulants, enhancing the immunogenicity of vaccine formulations. Edible plant tissues also provide a viable platform for oral delivery, reducing the need for extensive purification and refrigerated logistics. Conclusions: Integrating recombinant expression technologies with bioactive plant metabolites offers a flexible and scalable foundation for next-generation vaccines. These biological platforms show promise for addressing some immunization challenges, particularly in low-resource settings. Full article

Ensuring the quality, reliability, and efficiency of cold chain logistics for thermolabile pharmaceutical products, particularly vaccines, remains a critical challenge in global health supply chains. These biologics require stringent temperature control throughout storage, transport, and distribution to preserve their efficacy. Persistent issues such as maintaining product integrity, accurately forecasting vaccine demand, and fostering trust among stakeholders often result in inefficiencies, waste, and public mistrust. This study proposes an intelligent digital management framework specifically designed for vaccine cold chains, integrating blockchain, the Internet of Things (IoT), and machine learning (ML) to address these challenges in a holistic and sustainable manner. The main innovation of the study lies in combining secure traceability, real-time cold chain monitoring, and predictive decision support within a unified vaccine cold chain management framework rather than treating these functions as isolated technological solutions. Using WHO immunization coverage data and vaccine-related review data, the framework supports vaccine demand forecasting through the Informer model and stakeholder trust assessment through BERT-based sentiment analysis. In the sentiment analysis task, the BERT model achieved ~80% accuracy on dominant sentiment classes, with a weighted F1-score of 0.6974, demonstrating strong performance on imbalanced datasets. By minimizing vaccine spoilage and enabling more accurate demand planning, the system reduces excess production and distribution, thus lowering resource consumption, carbon emissions, and financial waste. Moreover, trust-informed analytics support better alignment of supply with actual community needs, fostering equity and resilience in vaccine distribution. While this framework has been validated through simulations and experimental evaluation, further real-world testing is needed to assess long-term stability and stakeholder adoption. Nonetheless, it provides a scalable and adaptive foundation for advancing sustainability and transparency in pharmaceutical cold chains. Full article

Antarctica’s extreme cryospheric conditions impose severe thermodynamic constraints on the natural attenuation of hydrocarbon pollutants. Despite the Antarctic Treaty System’s protections, the footprint of human logistics has left persistent reservoirs of petroleum hydrocarbons that threaten endemic biodiversity. This review critically synthesizes the state-of-the-art in Antarctic bioremediation, moving beyond traditional culture-dependent studies to integrate recent multi-omics breakthroughs (2020–2025). We analyze the molecular mechanisms limiting bioavailability in frozen soils and highlight the adaptive strategies of psychrophilic consortia, including the modification of membrane fluidity and the expression of cold-active enzymes (e.g., RHDs, AlkB). Notably, we discuss emerging findings on novel long-chain alkane degradation genes (almA, ladA) identified in 2025, which challenge previous assumptions about recalcitrance. Furthermore, the review evaluates the engineering bottlenecks of in situ versus ex situ strategies, emphasizing the synergistic potential of bacterial–fungal co-cultures and the ecological necessity of “climate-smart” remediation to mitigate methane emissions from thawing permafrost. By bridging the gap between fundamental microbial genetics and applied field engineering, we propose a roadmap for the next generation of biotechnological solutions in the warming polar environment. Full article

This study examines the spatio-temporal evolution and restricting mechanisms of agricultural supply chain resilience in the Yangtze River Basin from a gradient perspective. An evaluation index system encompassing the dimensions of the supply side, demand side, circulation side, and support side was developed. The Entropy-Weighted TOPSIS method, kernel density estimation, and obstacle degree model were comprehensively applied to measure and dynamically analyze supply chain resilience across 11 provinces from 2013 to 2023. The findings reveal distinct spatio-temporal evolution patterns: while the overall resilience shows an upward trend, significant gradient disparities exist, with downstream areas exhibiting markedly higher resilience than the mid- and upstream regions. Regarding the restricting mechanisms, the circulation and support sides exhibit higher levels of obstacles, representing key constraints to resilience enhancement. Among these, express delivery volume, freight turnover, and local R&D personnel full-time equivalents are the core obstacle factors affecting resilience. Based on these findings, this study proposes targeted recommendations, including optimizing rural last-mile logistics, upgrading inter-provincial freight hubs, improving rail–water intermodal transport, and strengthening cold-chain infrastructure, as well as implementing differentiated regional strategies and establishing cross-regional coordination mechanisms. These recommendations aim to provide decision-making guidance for enhancing the risk-response capabilities of agricultural supply chains in the Yangtze River Basin and to promote balanced regional development. Full article

Amid tightening emission rules and growing cold-chain demand, ports face complex multi-objective scheduling under dual uncertainties in vessel arrivals and operations. This work develops a multi-objective chance-constrained stochastic MILP model for joint berth, QC, and OPS scheduling. Heavy-tailed operational delays are managed via chance constraints, converting Weibull distributions to time buffers, while convex formulations allow piecewise cargo damage penalties to be computed linearly. A reinforcement learning-based adaptive large neighborhood search (RL-ALNS) algorithm is proposed to solve this NP-hard continuous-time problem, integrating a spatiotemporal decoder and an MDP-based selector to ensure microgrid limits and efficiency. Simulations demonstrate RL-ALNS’s superior Pareto convergence versus conventional heuristics. The model cuts the 95th-percentile tail risk by 46.59% and actual costs by 24.44% under mild delays, compared to deterministic scheduling. Overall, it quantifies the non-linear cost–emission–reliability trade-off, providing a robust tool for port decision-making. Full article

The COVID-19 pandemic highlighted both the transformative potential of mRNA vaccines and the structural challenges associated with their supply chains. Unlike traditional vaccine platforms, mRNA vaccines depend on highly specialized raw materials, including plasmid DNA (pDNA), nucleotides, enzymes, and lipid nanoparticles (LNP), that are produced by a limited number of global suppliers. These dependencies, combined with platform-specific manufacturing processes and stringent cold chain requirements, introduce vulnerabilities across production, distribution, and regulatory oversight. This narrative review examines the distinctive features of mRNA vaccine supply chains and identifies key challenges and opportunities across three interconnected domains: manufacturing systems, logistics and distribution, and regulatory governance. Drawing on literature published between January 2021 and March 2026, the review synthesizes evidence on supply chain bottlenecks revealed during the COVID-19 pandemic, including upstream raw-material dependencies, limitations in manufacturing scale-up, cold chain constraints, and regulatory fragmentation. Particular attention is given to the implications of these challenges for low- and middle-income countries, where infrastructure, technical capacity, and regulatory resources may limit participation in mRNA vaccine production and deployment. The review also highlights emerging strategies to strengthen supply chain resilience, including diversification of input suppliers, development of regional manufacturing hubs, improvements in vaccine thermostability, regulatory harmonization initiatives, and the use of digital technologies for supply chain management. By integrating insights from manufacturing, logistics, and regulatory perspectives, this study contributes to a better understanding of the structural characteristics shaping mRNA vaccine supply chains and identifies priority areas for strengthening global preparedness for future health emergencies. Full article

High-stakes logistics, defined as supply chains where delays, quality loss, or noncompliance have serious human, safety, financial, or geopolitical consequences, are a prominent case of a broader reality: global supply chains are safety-, cost-, and time-critical socio-technical systems where forecasting quality, vendor coordination, and operational decisions shape service levels and stakeholder welfare. At the same time, decarbonization pressures and the growing use of AI for planning and control introduce new risks and trade-offs across energy, computation, and physical logistics. We develop a multi-agent framework that models supply chain system-of-systems dynamics drawing on (1) supply chain decision functions (shipment planning, sourcing and vendor management), (2) national energy-transition conditions that determine grid carbon intensity, and (3) carbon-aware computation accounting for AI-enabled decision support. Methodologically, we combine predictive analytics, unsupervised segmentation, and a carbon-cost-of-intelligence layer in a scenario-based assessment of how national energy-transition profiles–from Norway to India–affect the intensity of AI compute carbon, meaning the carbon emissions generated by the hardware and data centers required to train and run AI models. We introduce the carbon-adjusted supply chain performance (CASP) metric that integrates physical transport carbon, cold-chain overhead where applicable, and AI compute carbon into a per-package-type performance measure. Our analysis yields three actionable outputs for systems engineering and environmental management: carbon, service, and cost trade-off frontiers; governance levers (sourcing portfolio rules, buffers, and compute policies); and system-level early-warning indicators for disruption amplification. This study implements a tool-augmented multi-agent system (orchestrator, risk, and sourcing agents) using AWS bedrock and strands agents, where LLM-based agents orchestrate deterministic analytical engines through structured tool interfaces with adaptive query generation. Theoretically, we extend previous systems-of-systems and sustainable supply chain findings by formalizing package-type-specific carbon–service frontiers and by embedding AI compute carbon into a socio-technical resilience framework. Practically, the CASP benchmark, governance lever analysis, and multi-agent implementation provide decision-makers with concrete tools to compare carriers, routes, and compute strategies across countries while making transparent the trade-offs between service reliability and total carbon. Full article

Global citrus exports rely heavily on temperature-controlled logistics to safeguard fruit quality and minimise postharvest losses. Temperature management remains a critical factor governing citrus quality throughout export logistics. Yet the extent to which historical shipment temperature data can meaningfully predict fruit condition at arrival has never been systematically assessed. This study presents a comprehensive review of how historical temperature records have been used to assess citrus quality within export supply chains, highlighting the lack of longitudinal temperature–quality correlations in existing research. Using PRISMA 2020 guidelines and Kitchenham’s three-phase review framework, 35 relevant peer-reviewed articles published between 2013 and 2025 were analysed. Bibliometric mapping identified dominant research concentrations in experimental cold chain studies and simulation-based approaches, with emerging themes around digital twins and virtual cold chain technologies. The review shows that current research predominantly employs controlled experimental designs and computational simulations to quantify temperature-driven deterioration, including chilling injury, decay rate, and weight loss. Although real-time temperature monitoring in commercial shipments is emerging, temperature deviations are rarely assessed alongside direct quality metrics. Although several studies have examined shipment temperatures alongside arrival-quality outcomes, these analyses are generally limited in duration, scope, or sensor resolution. Consequently, rigorous, multi-year, longitudinal datasets that pair detailed shipment temperature histories with standardised fruit-quality assessments remain largely unavailable, constraining the empirical validation of temperature–quality relationships in real export conditions. This gap significantly limits predictive capability in real-world export contexts. The review highlights the urgent need for a coordinated, long-term data infrastructure that integrates temperature and quality measurements across global citrus supply chains. Establishing such datasets, particularly in major exporting regions such as South Africa, would enable more robust modelling of temperature impacts, support the optimisation of cold chain practices, and contribute to international food loss-reduction goals. Full article

Achieving sustainability in rural cold chain logistics requires resolving inherent conflicts among participating agents. This paper develops an evolutionary game theory framework to examine the dynamic interactions between government regulators, cold chain enterprises, and agricultural producers. The model identifies three evolutionarily stable strategies (ESS) under different policy environments. Numerical simulations, using parameters calibrated from industry data and survey results, quantify the impact of key policy variables: (1) Subsidy intensity has a diminishing marginal effect on green technology adoption, with an optimal range between 12–18% of project cost; (2) Monitoring probability exhibits a threshold effect, needing to exceed 60% to deter non-compliance effectively; (3) Farmer organization reduces system stabilization time by approximately 30%. Our results challenge the conventional focus on single-policy solutions and instead demonstrate the necessity of integrated approaches that simultaneously address economic viability, operational efficiency, and community engagement. These insights offer evidence-based guidance for designing multi-stakeholder governance mechanisms in resource-constrained rural settings. Full article

Urban short-haul cold-chain distribution operates under strict service constraints while facing increasing pressure to reduce carbon emissions under the dual-carbon goals. Existing emission-aware routing studies often treat carbon emissions as external constraints or ex post evaluation indicators, limiting their influence on operational decision making. This study addresses this gap by developing a cold-chain distribution network optimization model that integrates internal carbon pricing (ICP), enabling carbon emissions to be internalized as economic costs within routing and scheduling decisions. Using the student milk cold-chain distribution system serving 54 primary and secondary schools in Fuzhou as an empirical case, the model incorporates multiple cost components, including energy consumption, warehouse operation, carbon emissions, and low-load penalties, while embedding operational constraints such as vehicle capacity, delivery time windows, and minimum economic loading requirements. An improved genetic algorithm is applied to solve the model. Scenario analyses are conducted across carbon price variation and demand fluctuation. Results show that when the internal carbon price increases from 97.49 RMB/t to 2000 RMB/t, the total distribution cost rises from 3531.2 RMB to 4082.842 RMB, indicating that carbon costs become an increasingly important factor in operational decision making. The distribution network exhibits a core-route-dominated structure, with key routes remaining stable across carbon price scenarios, suggesting that the influence of ICP is primarily reflected through cost internalization rather than route substitution. Demand analysis further shows that a 10% demand reduction reduces costs through route consolidation, while a 20% reduction weakens load efficiency and reduces vehicle utilization without triggering low-load penalty costs. These findings demonstrate that integrating ICP into routing optimization provides an effective pathway for aligning operational decisions with low-carbon transition objectives in rigid-demand cold-chain distribution systems. Full article

Background: Immunobiologicals are thermolabile products that require strict storage and transportation conditions to maintain their immunogenic efficacy, particularly in countries where logistical and operational challenges are evident, such as Brazil. Methods: A holistic multiple case study, carried out in five regions of Brazil, in 2022, with 42 workers from different instances of the cold chain was conducted. As a source of evidence, data were collected through interviews and analysis of printed documents and analyzed using Thematic Content Analysis, using the analytical technique of cross-case synthesis. Results: The influence of geoclimatic diversity and transportation modes on immunobiological logistics was highlighted. Challenges and requirements were identified, as well as aspects of monitoring during transportation and distribution. Among the main challenges were long distances, poor road conditions, seasonality and the need to share vehicles due to the unavailability of exclusive transportation. Conversely, positive practices were highlighted, such as the use of air-conditioned vehicles, dataloggers and properly prepared thermal boxes. Conclusions: It is necessary to adopt mitigation strategies that consider regional inequalities and promote equity, through raising awareness among managers, investing in logistical infrastructure and expanding good practices in order to guarantee the universal and qualified distribution of immunobiologicals in the country. Full article

Cold vaccine delivery is often known as a high-cost logistic process, which forces many pharmaceutical manufacturers, particularly small- and medium-sized enterprises (SMEs), to subcontract logistics operations of vaccines to third-party logistics (3PL). It is clear that maintaining the traceability and trackability of vaccines in this dynamic collaborative environment is fundamental for guaranteeing the safety of product. However, the lack of a unified vaccine logistics platform holds back comprehensive supervision and traceability, posing significant challenges to the development of useful cold chain logistics systems. To address these challenges, in this study we propose a blockchain-enabled platform for the evaluation and selection of 3PL providers in vaccine supply chains. We leveraged consortium blockchain technology to guarantee data integrity, transparency, and decentralization, facilitating trust among four main players of vaccine supply chain. We utilized smart contracts as a main part of this platform, which are responsible for automating key operational processes, including 3PL evaluation, contract execution, and monitoring. In this respect, the Fuzzy Analytic Hierarchy Process (FAHP) engine is integrated into the proposed platform to enable a data-driven, multi-criteria decision-making framework for selecting the most suitable 3PL providers. We evaluated the proposed platform through case study and gas consumption analysis; the results of the case study validate high operational accuracy (93.21%), precision (90.23%), recall (94.50%), and an F1-score of 92.32% for the platform, which offers a robust solution to enhance accountability, reliability, and decision-making in vaccine distribution networks. Full article

The Vehicle Routing Problems with Time Windows (VRPTW) has remained a classic and continuously studied problem since its introduction. With the rapid growth of cold chain product distribution demands, VRP research has become increasingly important for guiding real-world scheduling decisions. However, most studies focus on further subdividing new scenarios and constraints, often overlooking fundamental real-world applications. This includes the impact of unknown road conditions on costs, rough cost modeling, and poor algorithm adaptability to high-dimensional cold chain constraints. To address these three issues, this paper proposes the Spatio-temporal dependency and road network distribution-based traffic forecasting model (STD-RND) to provide region-level traffic scheduling information. The model also constructs cost functions to quantify cargo spoilage, refrigeration, and carbon emissions. Finally, we introduce an Improved Hippo Optimization with Traffic Forecasting (IHTF) that incorporates traffic prediction to enhance the solution quality of the VRPTW in cold chain scenarios. To strengthen optimization performance and prevent premature convergence to local optima, we integrate several enhanced strategies, including chaotic mapping, dynamic Cauchy mutation, and an escape mechanism. Through a series of experiments on the Solomon dataset and simulation datasets based on real road networks, we demonstrate that the proposed algorithm shows consistent superiority and effectiveness. Full article

A considerable proportion of perishable goods, including fruits and vegetables, deteriorate prior to reaching customers. Inadequate refrigeration infrastructure, particularly in developing nations with arid climates and markets distant from agricultural sources, accounts for most of these losses. A food cold chain has three primary phases: pre-cooling, cold storage, and refrigerated transportation. All phases of the cold chain rely fundamentally on refrigeration to preserve perishable products at designated temperatures, relative humidity, and CO₂ concentrations, thus prolonging their shelf life. Solar-driven or aided refrigeration systems use solar energy to power cooling systems and preserve the food in the cold chain. These systems are especially beneficial in off-grid or developing areas for preserving perishable goods such as fruits, vegetables, and other food items, mitigating postharvest losses that can exceed 30–50% in areas with inconsistent energy supplies. Despite progress in efficiency and scalability, numerous research gaps remain across technological, economic, social, policy, and regional dimensions, including technical aspects, optimization, and integration. There is a need to enhance energy-efficient designs, particularly by managing solar intermittency to address non-uniform cooling, which leads to inconsistent ripening and spoilage, and by integrating sustainable refrigerants to mitigate environmental impact. Further development is necessary for micro-scale, transportable, or decentralized systems designed for small farms, while economic and financing obstacles include high upfront costs and limited financial accessibility. Substantial deficiencies exist in creating affordable models and funding channels for small-scale agriculturalists. Addressing these deficiencies could expedite adoption, thereby reducing global food loss and waste (accounting for 8–10% of GHG emissions) while improving food security. Future research must emphasize multidisciplinary methodologies that amalgamate engineering, economics, and social sciences to provide comprehensive solutions. Full article

Extreme hydro-meteorological events are intensifying under climate change, disproportionately disrupting last-mile healthcare in flood-prone geographies. In this study, flood-adaptive primary care clinics (FAPCCs) integrated with islandable smart microgrids and a rapid-deploy medical technology stack (MedTech) are developed and evaluated to ensure continuity of essential services (triage, maternal and child health, vaccination cold-chain, minor procedures, diagnostics, and telemedicine) during fluvial, pluvial, and coastal flooding. Evidence on resilient health facilities, microgrid architectures, distributed energy resources, and modular clinical systems is presented in a multi-layer systems design: (1) a modular, amphibious, and elevatable clinic chassis; (2) a photovoltaic–battery–diesel hybrid system with demand-aware energy management; (3) redundant connectivity long-term evolution/fifth-generation, satellite, and very high frequency; (4) a rapid-deploy MedTech kit including point-of-care diagnostics, low-temperature cold-chain, negative-pressure isolation, and sterilization modules; and (5) flood-aware logistics using unmanned aerial vehicle/unmanned surface vehicle. A mixed-integer linear programming sizing is formulated and dispatched with a continuity-of-care reliability metric that couples energy availability to clinical throughput. Simulation across three archetypal sites (peri-urban delta, inland riverine, coastal estuary) shows that FAPCCs achieve the service availability of higher than 99.5% across 7-day grid outage scenarios while reducing fuel use by 62–81% relative to diesel-only baselines, maintaining vaccine temperatures within 2–8 °C with <0.1% thermal excursion time, and sustaining telemedicine quality of service with <150 ms median uplink latency in hybrid networks. A life-cycle cost analysis indicates a 7.1–9.8 year discounted payback from fuel displacement and avoided service loss. Deployment playbooks and policy guidance are also proposed for Ministries of Health and Disaster Agencies in monsoon-impacted regions. Full article