Search Results (104)

Mineral oil hydrocarbons (MOH), comprising saturated (MOSH) and aromatic (MOAH) compounds, are ubiquitous lipophilic contaminants. This review critically examines their occurrence, toxicology, analysis, contamination sources, and mitigation strategies in the olive oil sector. Emphasis is placed on analytical evolution, highlighting online LC-GC-FID and the EN ISO 20122:2024 standard, including advances in saponification and epoxidation to minimize biogenic interferences. Monitoring data reveal that virgin olive oils from the market can sometimes exceed the 2.0 mg/kg limit for the MOAH. Ten times higher levels are usually found in olive pomace oils (OPOs). In OPO, solvent extraction causes a significant reconcentration of hydrocarbons remaining on the solid matter after physical extraction and accumulating during the open-air storage of pomace. Conversely, for virgin oils, contamination can occur at multiple points along the supply chain, but harvesting emerged as the most important critical step, often due to accidental contact with lubricants, greases, or hydraulic fluids. Post-milling operations may also contribute to contamination. Mitigation strategies rely on Good Agricultural and Manufacturing Practices, focusing on the systematic replacement of technical-grade lubricants with food-grade alternatives. Additionally, olive washing can reduce initial MOSH content, while refining further lowers levels, particularly in lighter fractions. Full article

Natural rubber (NR) is essential to the medical, industrial, defense and transportation industries. Alternative rubber crops are needed to supplement increasing rubber demands which cannot be met by the tropical rubber tree, Hevea brasiliensis, and to protect supplies in the event of a rubber tree crop collapse, political strife or a pandemic disrupting global rubber supply chains. Taraxacum kok-saghyz, rubber dandelion, has high-molecular-weight NR, substantial rubber content and the ability to grow in temperate regions. It can also grow hydroponically or aeroponically in controlled environments. This work presents a scenario-based cost analysis of requirements to scale up hydroponic rubber dandelion to replace the 1 million metric tons of imported rubber consumed annually by United States manufacturers. Two scale-up scenarios were considered: a single-level, deep water culture greenhouse and an indoor, ten-level hydroponic vertical farm built in a warehouse. Fuel usage, operating costs, electricity consumption, beneficial insect applications, fertilizers, cooling, and more were included for each case. The costs of operation and construction were compared to the value of products to determine potential annual profit. Sensitivity analyses revealed several scenarios which would drastically improve the economics of the hydroponic facilities. A combination of multiple factors may allow economic feasibility. Hydroponic rubber dandelion production can be profitable on a small scale (up to 15 MT of TNR/year) provided leafy greens and inulin are included as coproducts. The validity of scaling up such a system to 100,000 MT TNR/year to meet 10% of US manufacturing requirements depends heavily on successful research-based gains in TNR concentration and root size, the difference in TNR price between a commodity price and a specialty NR, and upon whether or not tropical rubber tree NR is able to continue to provide a stable source of NR for the US. Full article

This study investigates the sustainability of competitiveness in the textile and apparel industry across Asia following the 2005 conclusion of the Agreement on Textiles and Apparel (ATC). It aims to evaluate how sectoral competitiveness is understood and maintained beyond cost savings alone. A systematic review of the literature was conducted using PRISMA 2020 guidelines, analyzing 48 peer-reviewed journal articles from reputable sources published between 2001 and 2024. The selection process involved multiple stages of screening and thematic categorization, focusing on individual country case studies, competitiveness measures, indicators, analytical frameworks, and methodological approaches. A Risk of Bias assessment was conducted using the Mixed Methods Appraisal Tool (MMAT) to evaluate the methodological quality of the included studies. The findings highlight seven strategic pillars for sustaining competitiveness in the textile and apparel industry: shifting toward higher value-added manufacturing; integration into Global Value Chains (GVCs); technological innovation; adaptability; supply chain collaboration and organizational networks; responsible manufacturing; and government support. Moreover, the review includes a Co-occurrence analysis of all seven pillars. The analysis shows that supply chain collaboration and organizational networks serve as central pillars, often combined with adaptability and technological innovation. These findings demonstrate that maintaining industrial competitiveness in the textile and apparel industry no longer depends solely on cost efficiency but increasingly relies on strategic capabilities, ecosystem collaboration, and institutional support. The study offers a comprehensive framework to enhance the long-term competitiveness of textile manufacturing, particularly in Asia, contributing to the broader literature on transforming industries to stay competitive. Full article

Against the backdrop of accelerated terrestrial hydrological cycling and the increasing concurrence of drought-heatwave compound extremes under global warming, regional land-atmosphere coupling has emerged as a central mechanism shaping climate feedbacks and trajectories of ecosystem carbon uptake. However, prior studies spanning climatic regimes, observational scales, and data sources have often yielded contradictory conclusions. Here, we challenge these fragmented perspectives by constructing an integrated LST-SM-ET-GPP chain that jointly represents land surface temperature, soil moisture, evapotranspiration, and gross primary productivity, thereby linking water availability, surface energy balance, and plant physiological processes within a unified framework. We synthesize a conceptual diagnostic roadmap for interpreting land-atmosphere coupling across observations and models. When ecosystems operate in humid, energy-limited environments, radiative and advective controls should be prioritized to diagnose system forcing. By contrast, as the system becomes water-depleted, attribution must shift to a nonlinear regime transition framework governed by a critical soil moisture threshold. This threshold mechanism implies that, once the system enters the moisture-limited regime, even modest declines in soil moisture can trigger a rapid weakening of evaporative cooling, substantially amplifying LST anomalies and strongly suppressing GPP. The competitive regulation of stomatal conductance by atmospheric demand (vapor pressure deficit, VPD) and terrestrial supply (rootzone soil moisture) further explains why the “dominant” controlling factor can dynamically reverse across hydrothermal states, timescales, and stages of extreme-event evolution. Notably, the steady-state coupling assumption may break down under flux “flooring” during extreme drought, or when structural buffering such as deep root water uptake is present, delineating strict applicability bounds for existing diagnostic frameworks. Finally, current assessments remain constrained by multiple uncertainties, particularly the lack of ET partitioning constraints, representativeness biases arising from clear-sky observations and sampling-depth limitations, and systematic errors in Earth system model simulations during the warm season. Full article

Shipping is urgently exploring alternative vessel energy sources across a wide range of options—from other fossil fuels to renewables—with a view to more sustainable ship propulsion. Based on processing of publicly available data, the authors discuss the prospects of the supply chains for 16 vessel power sources alternative to oil, comparing descriptive statistics across respective fuel supply chain key performance indicators (KPIs) to evaluate potentiality along with hidden vulnerabilities. While finding marked differences across calculated mean, standard deviation and coefficient of variation values, the authors do not preclude the development of parallel ship fuel supply chains, unlike the case of previous fuel transitions in shipping. To support this scenario, already formed in practice, they emphasize the enabling attributes of today’s world fleet in terms of total capacity and of size of each of the main shipping sectors which could eventually sustain nowadays multiple fuel supply chains. Concluding on limitations and challenges that such an energy-source multitude can create, the authors underline the need to consider in the Life-Cycle Assessment (LCA) of shipping fuels their total impact, including necessary ship hardware changes for a more thorough assessment of fuels’ impact across the entire shipping services’ supply chain. Full article

For nations heavily dependent on fossil-fuel exports, hydrogen is emerging as a promising solution to reduce carbon emissions while preserving economic stability and promoting countries’ energy independence. This research study examines hydrogen potential as a renewable energy source to facilitate the transition toward a sustainable economy with a special focus on Middle East and North Africa (MENA) countries. The analysis delves into policy frameworks, technological advancements, and infrastructure adaptations to build a reliable green hydrogen supply chain for a scalable and bankable future. The role played by other renewable energies like solar and wind, together with the risk related to the high demand for water resources to achieve the green hydrogen transition, has also been assessed. Furthermore, key challenges have been highlighted, including the repurposing of the existing pipelines into the energy networks, public–private partnerships to secure investment, and legislation requirements to encourage the adoption of novel hydrogen applications. In order to do that, a SWOT-PESTEL analysis has been carried out to identify the main decarbonization strategies for achieving a replicable framework. Moreover, a multi-criteria decision analysis was performed, applying 11 indicators across supply-side (e.g., solar/wind potential, LCOE, and water stress), demand-pull/logistics (e.g., maritime connectivity, steel production, and LNG export capacity), and risk/regulation dimensions (e.g., governance effectiveness, regulatory quality, and fossil rent dependence). The Analytic Hierarchy Process (AHP) was used for weighting, the entropy method for weighting variability (hybrid 50/50 combined weights), min–max normalization for costs, 5% Winsorization for outliers, and TOPSIS for aggregation following OECD-JRC composite indicator guidelines. Results have been validated through a multiple scenario analysis (base, supply-led, and risk-aware) and sensitivity testing via Dirichlet bootstrapping (5000 iterations) with ±20% weight perturbations. Six countries of the MENA region have been studied. The multi-criteria decision analysis outcomes rank Egypt (composite score 0.518), Algeria (0.482), and Oman (0.479) as the most suitable countries for large-scale green hydrogen and ammonia production/export, while Saudi Arabia, Qatar, and Kuwait achieved lower supply scores in the base case due to higher perceived risks. Full article

Background: Access to affordable essential medicines is critical for effective management of hypertension (HTN) and diabetes mellitus (DM). In Zimbabwe, frequent stock-outs in public facilities position private pharmacies as important alternative sources of these medicines. Aim: To assess availability, pricing, and stock-out levels of essential HTN and DM medicines in private retail pharmacies in Gweru Urban District, Zimbabwe. Methods: A cross-sectional survey was conducted in 40 registered private pharmacies. Data on medicine availability, retail prices, monthly stock-outs, and supply-chain factors were collected using a structured interviewer-administered questionnaire, stock cards, and observational checklists. Local prices were compared with international reference prices (IRPs). Chi-square analyses evaluated associations between pharmacy characteristics, medicine prices, availability, and stock-out durations. Results: Most tracer medicines for HTN and DM were available in ≥80% of pharmacies, with average stock-outs generally <3 days per month. Pharmacy characteristics were not significantly associated with availability or stock-outs. Medicines with <80% availability and those priced at ≥USD 5 were significantly associated with prolonged stock-outs of ≥7 days (p = 0.006 and p = 0.001, respectively). Local retail prices exceeded IRPs and public facility prices, suggesting potential affordability barriers in the context of an economic crisis, where most health expenditures are out-of-pocket. Key drivers of stock-outs included wholesaler shortages, delivery delays, limited procurement funds, and substitution with alternative medicines. Conclusions: While medicine availability and short-term stock-outs were generally favourable, high retail prices pose a major potential barrier to access. The cost burden is amplified by the common HTN-DM comorbidity, requiring multiple medications per person, thereby further increasing out-of-pocket expenses. High prices may limit adherence, reduce functional capacity, and negatively impact productivity. Policy interventions targeting pricing regulations and value-chain optimization are urgently needed to enhance equitable access to essential NCD medicines in urban Zimbabwe. Full article

The agri-food sector is a major contributor to global greenhouse gas emissions while facing increasing demand for food production driven by population growth. Transitioning towards sustainable and low-carbon agricultural systems is therefore critical. Green hydrogen, produced from renewable energy sources, holds significant promise as a clean energy carrier and chemical feedstock to decarbonize multiple stages of the agri-food supply chain. This systematic review is based on a structured analysis of peer-reviewed literature retrieved from Web of Science, Scopus, and Google Scholar, covering over 120 academic publications published between 2010 and 2025. This review provides a comprehensive overview of hydrogen’s current and prospective applications across agriculture and the food industry, highlighting opportunities to reduce fossil fuel dependence and greenhouse gas emissions. In agriculture, hydrogen-powered machinery, hydrogen-rich water treatments for crop enhancement, and the use of green hydrogen for sustainable fertilizer production are explored. Innovative waste-to-hydrogen strategies contribute to circular resource utilization within farming systems. In the food industry, hydrogen supports fat hydrogenation and modified atmosphere packaging to extend product shelf life and serves as a sustainable energy source for processing operations. The analysis indicates that near-term opportunities for green hydrogen deployment are concentrated in fertilizer production, food processing, and controlled-environment agriculture, while broader adoption in agricultural machinery remains constrained by cost, storage, and infrastructure limitations. Challenges such as scalability, economic viability, and infrastructure development are also discussed. Future research should prioritize field-scale demonstrations, technology-specific life-cycle and techno-economic assessments, and policy frameworks adapted to decentralized and rural agri-food contexts. The integration of hydrogen technologies offers a promising pathway to achieve carbon-neutral, resilient, and efficient agri-food systems that align with global sustainability goals and climate commitments. Full article

Remote Indigenous communities experience persistent inequities in access to fresh and nutritious foods due to the fragility of perishable food supply chains (PFSCs). Disruptions across procurement, transportation, storage, retail, and limited local production restrict access to perishable foods, contributing to food insecurity and diet-related health risks. This scoping literature review synthesizes evidence from 84 peer-reviewed, grey, and unpublished sources across fourteen countries to map PFSC management (PFSCM) challenges affecting food access in remote Indigenous communities worldwide and to synthesize reported practices implemented to address these challenges. PFSCM challenges were identified across all supply chain levels, and five categories of reported practices emerged: PFSC redesign strategies, forecasting and decision-support models, technological innovations, collaboration and coordination mechanisms, and targeted investments. These findings informed the development of a multi-scalar conceptual framework comprising seven interconnected PFSCM clusters that organize how reported practices are associated with multiple food access dimensions, including quantity, affordability, quality, safety, variety, and cultural acceptability. This review contributes an integrative, system-oriented synthesis of PFSCM research and provides a conceptual basis to support future scholarly inquiry, comparative inquiry, and policy-relevant discussion of food access and health equity in remote Indigenous communities. Full article

The proliferation of binary vulnerabilities in the software supply chain has become a critical security challenge. Existing vulnerability detection approaches—including dynamic analysis, static analysis, and decompilation-assisted analysis—all suffer from limitations such as insufficient coverage, high false-positive and false-negative rates, or poor compatibility. Although decompilation technology can serve as a bridge connecting binary-code and source-code vulnerability detection tools, current schemes suffer from inadequate semantic restoration quality and lack of tool compatibility. To address these issues, this paper proposes LLMVulDecompiler, a binary decompilation model based on fine-tuned large language models designed to generate high-precision decompiled code that integrates directly with source-code static analysis tools. We construct a dedicated training and evaluation dataset that covers multiple compiler optimization levels (e.g., O0–O3) and a diverse set of program functionalities. We adopt a two-stage fine-tuning strategy that involves first building foundational decompilation capabilities, then enhancing vulnerability-specific features. Additionally, we design a low-cost inference pipeline and establish multi-dimensional evaluation criteria, including restoration similarity, compilation success rate, and functional correctness. Experimental results show that the model significantly outperforms baseline models in terms of average edit distance, compilation success rate, and black-box test pass rate on the HumanEval-C benchmark. In tests on 12 real-world CVE (Common Vulnerabilities and Exposures) instances, the approach achieved a detection accuracy of 91.7%, with substantially reduced false-positive and false-negative rates. This study demonstrates the effectiveness of specialized fine-tuning of large language models for binary decompilation and vulnerability detection, offering a new pathway for binary security analysis. Full article

The transportation problem (TP) is a canonical linear programming model for minimizing the cost of distributing goods from multiple sources to multiple destinations. Classical TPs assume deterministic costs, supplies, and demands, whereas real supply chains are affected by volatility in fuel prices, inflation, disruptions, and weather, making such parameters uncertain. Fuzzy sets (FSs) and intuitionistic fuzzy sets (IFSs) have been widely used to handle vagueness; however, while Atanassov’s IFSs incorporate hesitation in addition to membership and non-membership, they remain limited to isotropic representations of uncertainty. This paper introduces an index-matrix interpretation for a two-stage three-dimensional transportation problem (2-S 3-D TP) defined under Elliptic Intuitionistic Fuzzy Quadruples (E-IFQs). Within this framework, transportation costs, supplies, and demands are represented as E-IFQs, allowing the modeling of anisotropic and correlated uncertainty along the membership and non-membership axes. The two-stage formulation extends previous intuitionistic fuzzy approaches by adding a temporal dimension and incorporating practical constraints such as cost thresholds and feasibility checks. The objective is to determine optimal producer–hub–buyer allocations that minimize the total E-IFQ cost while preserving consistency across all stages and time periods. A detailed case study on EV battery module distribution demonstrates the effectiveness of the proposed model. Compared with conventional fuzzy and intuitionistic fuzzy formulations, the 2-S 3-D E-IFTP yields more robust and precise decisions under complex, multidimensional uncertainty, offering improved interpretability and policy integration over time. Full article

Port berthing sites are regions of high interest for monitoring and optimizing port operations. Data sourced from the Automatic Identification System (AIS) can be superimposed on berths, enabling their real-time monitoring and revealing long-term utilization patterns. Ultimately, insights from multiple berths can uncover bottlenecks, and lead to the optimization of the underlying supply chain of the port and beyond. However, publicly available documentation of port berths, even when available, is frequently incomplete—e.g., there may be missing berths or inaccuracies such as incorrect boundary boxes—necessitating a more robust, data-driven approach to port berth localization. In this context, we propose an unsupervised spatial modeling method that leverages AIS data clustering and hyperparameter optimization to localize berthing sites. Trained on one month of freely available AIS data and evaluated across ports of varying sizes, our models significantly outperform competing methods, achieving a mean Bhattacharyya distance of 0.85 when comparing Gaussian Mixture Models trained on separate data splits, compared to 13.56 for the best existing method. Qualitative comparison with satellite images and existing berth labels further supports the superiority of our method, revealing more precise berth boundaries and improved spatial resolution across diverse port environments. Full article

Canthaxanthin is a significant carotenoid that is synthesized by specific microorganisms. It has multiple functions and has been utilized in food and feed supply chains. This research focused on improving canthaxanthin production by Paracoccus bogoriensis PH1, an orange-pigmented bacterium isolated from hot springs. Canthaxanthin production was optimized in flask-scale cultures by varying the pH, temperature, nutritional sources, aeration rates, and agitation techniques. Flask culture cultivation indicated that canthaxanthin production by this strain was influenced by pH stress mechanisms, resulting in the establishment of a two-stage pH control (pH-shift) technique to enhance cell mass and pigment production. The optimum flask conditions were refined for application in a 1 L bioreactor. An optimized cultivation procedure was established utilizing a Polypeptone Sucrose Yeast Extract (PPSYE) medium, with a pH transition from 7 to 11, incubation at 40 °C, agitation at 250 rpm, and aeration at 2 vvm for 48 h. This process resulted in a 3.12-fold increase in total carotenoid content and a 1.61-fold increase in canthaxanthin production, achieving 0.84 ± 0.06 mg/L compared to pre-optimized flask cultures in TSYEB medium (pH 7 at 37 °C, 72 h). Purified canthaxanthin from P. bogoriensis PH1 exhibited antioxidant activity in the ABTS assay. Full article

To address the limitations of traditional single-point detection methods in monitoring the sulfur content of ship fuel (FSC), which are inadequate in meeting the regulatory demands of high-traffic ports, this study proposes an integrated analytical approach based on artificial intelligence. This approach synthesizes multi-source heterogeneous data, including historical fuel testing records, Automatic Identification System (AIS) trajectory data, ship and operator profiles, technical specifications, fuel supply chain documentation, fundamental ship attributes and so on. Following rigorous data cleaning and preprocessing procedures, a refined dataset comprising 3046 records collected between 2017 and 2024 from the Port of Ningbo was utilized. Initially, multiple linear regression analysis was con-ducted to identify key factors influencing sulfur emissions, resulting in an R² value of 0.67. Based on these findings, a deep neural network model was developed using TensorFlow to enable real-time estimation of FSC and classification of compliance risk levels. The results indicate that the proposed method exhibits high estimated accuracy and robustness. An AI-based intelligent monitoring module, developed based on this research, has been integrated into the ship exhaust gas detection system at the Port of Ningbo. This module enables real-time analysis of inbound ships and intelligent identification of potentially non-compliant ships, thereby significantly improving the precision and efficiency of port regulatory operations. This study not only contributes to the theoretical framework for ship fuel compliance monitoring but also provides a practical and scalable technical solution for intelligent port governance. Full article

Rapid depletion of fossil fuel reserves forces the global energy sector to transition to sustainable energy sources. Specifically, distributed energy markets have emerged in the renewable energy sector in recent years, partly because blockchain technology is becoming a successful way to promote secure and transparent transactions. Using its decentralized structure, transparency, and even pseudonymity, blockchain is increasingly adopted worldwide for large-scale energy trading, peer-to-peer exchanges, project financing, supply chain management, and asset tracking. The research comprehensively analyzes blockchain applications across multiple fields related to energy, bibliographically evaluating their transformative potential. In addition, the study explores the architecture of various blockchain systems, assesses critical security and privacy challenges, and discusses how blockchain can enhance operational efficiency, transparency, and reliability in the energy sector. The paper’s findings provide a roadmap for future developments and the strategic adoption of blockchain technologies in the evolving energy landscape for an effective energy transition. Full article