Search Results (850)

Seafood plays a key role in a healthy diet due to its high content of essential nutrients. However, its global trade and complex supply chains expose it to frequent mislabeling and food fraud. This study investigates Italian consumers’ willingness to pay (WTP) for traceable seafood products, exploring how blockchain technology (BT) can enhance transparency and economic sustainability in the fish supply chain. An online questionnaire, administered in 2022 and 2024, gathered responses from a diverse demographic, focusing on four representative seafood species: farmed sea bass, striped venus clams, giant red shrimp, and albacore tuna. Results indicate that most respondents—primarily with higher education levels—value traceability and are willing to pay a premium for certified, traceable seafood. The study models the economic feasibility of implementing BT at both national and regional levels and finds that the consumer’s WTP exceeds the additional costs incurred by adopting BT. These findings support the viability of traceability systems in improving food safety and sustainability, while reinforcing consumer trust. The results also underscore the importance of providing clear information at the point of purchase, particularly regarding species, origin, and production methods—factors critical to informed seafood choices and advancing more sustainable consumer behavior in Italy. Full article

As the world is technologically advancing, the integration of FSO communication in
non-terrestrial platforms is transforming the landscape of global connectivity. By enabling
high-data-rate inter-satellite links, secure UAV–ground channels, and efficient HAPS
backhaul, FSO technology is paving the way for sustainable 6G non-terrestrial networks.
However, the stringent requirement for precise line-of-sight (LoS) alignment between
the optical transmitter and receivers poses a hindrance in practical deployment. As
non-terrestrial missions require continuous movement across the mission area, the platform
is subject to vibrations, dynamic motion, and environmental disturbances. This makes
maintaining the LoS between the transceivers difficult. While fine-pointing mechanisms
such as fast steering mirrors and adaptive optics are effective for microradian angular
corrections, they rely heavily on an initial coarse alignment to maintain the LoS. Coarse
pointing modules or gimbals serve as the primary mechanical interface for steering
and stabilizing the optical beam over wide angular ranges. This survey presents a
comprehensive analysis of coarse pointing and gimbal modules that are being used in
FSO communication systems for non-terrestrial platforms. The paper classifies gimbal
architectures based on actuation type, degrees of freedom, and stabilization strategies.
Key design trade-offs are examined, including angular precision, mechanical inertia,
bandwidth, and power consumption, which directly impact system responsiveness and
tracking accuracy. This paper also highlights emerging trends such as AI-driven pointing
prediction and lightweight gimbal design for SWap-constrained platforms. The final part
of the paper discusses open challenges and research directions in developing scalable and
resilient coarse pointing systems for aerial FSO networks Full article

The integration of SLAM with Gaussian splatting presents a significant challenge: achieving compatibility between real-time performance and high-quality rendering. This paper introduces a novel SLAM system named SFGS-SLAM (SuperFeats Gaussian Splatting SLAM), restructured from tracking to mapping, to address this issue. A new keypoint detection network is designed and characterized by fewer parameters than existing networks such as SuperFeats, resulting in faster processing speeds. This keypoint detection network is augmented with a global factor graph incorporating the GICP (Generalized Iterative Closest Point) odometry, reprojection-error factors and loop-closure constraints to minimize drift. It is integrated with the Gaussian splatting as the mapping part. By leveraging the reprojection error, the proposed system further reduces odometry error and improves rendering quality without compromising speed. It is worth noting that SFGS-SLAM is primarily designed for static indoor environments and does not explicitly model or suppress dynamic disturbances. Comprehensive experiments were conducted on various datasets to evaluate the performance of our system. Extensive experiments on indoor and synthetic datasets show that SFGS-SLAM achieves accuracy comparable to state-of-the-art SLAM while running in real time. SuperFeats reduces matching latency by over 50%, and joint optimization significantly improves global consistency. Our results demonstrate the practicality of combining lightweight feature matching with dense Gaussian mapping, highlighting trade-offs between speed and accuracy. Full article

Reliable individual detection under dense and cluttered conditions is a prerequisite for automated monitoring in modern poultry systems. We propose CF-DETR, an end-to-end detector that builds on RT-DETR and is tailored to chicken face detection in production-like environments. CF-DETR advances three technical directions: Dynamic Inception Depthwise Convolution (DIDC) expands directional and multi-scale receptive fields while remaining lightweight, Polar Embedded Multi-Scale Encoder (PEMD) restores global context and fuses multi-scale information to compensate for lost high-frequency details, and a Matchability Aware Loss (MAL) aligns predicted confidence with localization quality to accelerate convergence and improve discrimination. On a comprehensive broiler dataset, CF-DETR achieves a mean average precision at IoU 0.50 of 96.9% and a mean average precision (IoU 0.50–0.95) of 62.8%. Compared to the RT-DETR baseline, CF-DETR reduces trainable parameters by 33.2% and lowers FLOPs by 23.0% while achieving 81.4 frames per second. Ablation studies confirm that each module contributes to performance gains and that the combined design materially enhances robustness to occlusion and background clutter. Owing to its lightweight design, CF-DETR is well-suited for deployment in real-time smart farming monitoring systems. These results indicate that CF-DETR delivers an improved trade-off between detection performance and computational cost for real-time visual monitoring in intensive poultry production. Full article

Crude oil and grain, as two pivotal global commodities, exhibit significant price co-movement that profoundly affects national economic stability and food security. From the perspective of systems theory, the energy and grain markets do not exist in isolation but rather form a highly coupled complex system, characterized by nonlinear feedback, cross-market risk contagion, and cascading effects. This study systematically investigates the transmission mechanisms from international crude oil prices to the domestic prices of Chinese four major grains, employing the DY spillover index, Vector Error Correction Model (VECM), and a mediation effect framework. The empirical findings reveal three key insights. First, rising international crude oil prices significantly strengthen the pass-through of global grain prices to domestic markets, while simultaneously weakening the effectiveness of domestic price stabilization policies. Second, higher crude oil prices amplify international-to-domestic price spillovers by increasing maritime freight costs, a key channel in global grain trade logistics. Third, elevated oil prices stimulate demand for renewable biofuels, including biodiesel and ethanol, thereby boosting international demand for corn and soybeans and intensifying the transmission of price fluctuations in these commodities to the domestic market. These findings reveal the key pathways through which shocks in the energy market affect food security and highlight the necessity of studying the “energy–food” coupling mechanism within a systems framework, enabling a more comprehensive understanding of cross-market risk transmission. Full article

Identifying suitable areas for ecosystem services (ES) development is essential for balancing economic growth with environmental sustainability in ecologically fragile regions. However, existing studies often neglect integrating future climate and socioeconomic drivers into ES optimization, hindering the design of robust strategies for sustainable resource management. In this study, we propose a novel framework integrating the System Dynamics (SD) model, the Patch-based Land Use Simulation (PLUS) model, the Integrated Valuation of Ecosystem Services and Trade-offs (InVEST) model, and the Dynamic Bayesian Network (DBN) to optimize ES patterns in the Sanjiangyuan region under three climate scenarios (SSP126, SSP245, and SSP585) from 2030 to 2060. Our results show the following: (1) Ecological land (forest) expanded by 0.86% under SSP126, but declined by 11.54% under SSP585 due to unsustainable land use intensification. (2) SSP126 emerged as the optimal scenario for ES sustainability, increasing carbon storage and sequestration, habitat quality, and water conservation by 3.2%, 1%, and 1.4%, respectively, compared to SSP585. (3) The central part of the Sanjiangyuan region, characterized by gentle topography and adequate rainfall, was identified as a priority zone for ES development. This study provides a transferable framework for aligning ecological conservation with low-carbon transitions in global biodiversity hotspots. Full article

To address the challenges of insufficient response speed and robustness in optical attitude control systems under highly dynamic disturbances and internal uncertainties, a composite control strategy is proposed in this study. By integrating the proposed piecewise sliding control (P-SMC) with the improved active disturbance rejection control (ADRC), this strategy achieves complementary performance, which can not only suppress the disturbance but also converge to a bounded region fast. Under highly dynamic disturbances, the improved extended state observer (ESO) based on the EKF achieves rapid response with amplified state observations, and the Nonlinear State Error Feedback (NLSEF) generates a compensation signal to actively reject disturbances. Simultaneously, the robust sliding mode control (SMC) suppresses the effects of system nonlinearity and uncertainty. To address chattering and overshoot of the conventional SMC, this study proposes a novel P-SMC law which applies distinct reaching functions across different error bands. Furthermore, the key parameters of the composite scheme are globally optimized using the particle swarm optimization (PSO) algorithm to achieve Pareto-optimal trade-offs between tracking accuracy and disturbance rejection robustness. Finally, MATLAB simulation experiments validate the effectiveness of the proposed strategy under diverse representative disturbances. The results demonstrate improved performance in terms of response speed, overshoot, settling time and control input signals smoothness compared to conventional control algorithms (ADRC, C-ADRC, T-SMC-ADRC). The proposed strategy enhances the stability and robustness of optical attitude control system against internal uncertainties of system and sensor measurement noise. It achieves bounded-error steady-state tracking against random multi-source disturbances while preserving high real-time responsiveness and efficiency. Full article

Growing global supply chain uncertainties significantly threaten China’s forage import security. The evolving characteristics of the global forage trade network directly impact the stability of China’s supply. This study constructs a directed, weighted trade network based on global forage products trade data (2000–2024). Using complex network analysis methods, it systematically analyzes the network’s topological structure and evolutionary patterns, with a focus on their impact on China’s import security. The study addresses the following questions: What evolutionary patterns does the global forage trade network exhibit in terms of its topological structure? How does the evolution of this network impact the import security of forage products in China, specifically regarding supply chain stability and risk resilience? The research findings indicate the following: (1) From 2000 to 2024, the total volume of global forage products trade increased by 48.17%, primarily driven by forage products excluding alfalfa meal and pellets, which accounted for an average of 82.04% of volume annually. Additionally, the number of participating countries grew by 21.95%. (2) The global forage products trade network follows a power–law distribution, characterized by increasing network density, a clustering coefficient that initially declines and then rises, and a shortening of the average path length. (3) The core structure of the global forage products trade network shows an evolutionary trend of diffusion from core nodes in North America, Oceania, and Asia to multiple core nodes, including those in North America, Oceania, Europe, Africa, and Asia. (4) China’s forage products trade network displays distinct phase characteristics; however, imports face significant risks from high supply chain dependency and exposure to international price fluctuations. Based on these conclusions, it is recommended that China actively expands trade relations with potential product-exporting countries in Africa, encouraging enterprises to “go global.” Additionally, China should establish a three-dimensional supply chain security system, comprising maritime, land, and storage components, to enhance risk resistance and import safety. Full article

Aflatoxin (AF) contamination in pistachios remains a critical food safety and trade challenge, given the potent carcinogenicity of AF-B₁ and the nut’s high susceptibility to Aspergillus infection throughout production and storage. Traditional decontamination methods such as roasting, irradiation, ozonation, and acid/alkaline treatments can reduce AF levels but often degrade sensory and nutritional quality, implying the need for more sustainable approaches. In recent years, innovative nonthermal interventions, including pulsed light, cold plasma, nanomaterial-based adsorbents, and bioactive coatings, have demonstrated significant potential to decrease fungal growth and AF accumulation while preserving product quality. Biosensing technologies such as electrochemical immunosensors, aptamer-based systems, and optical or imaging tools are advancing rapid, portable, and sensitive detection capabilities. Combining these experimental strategies with artificial intelligence (AI) and machine learning (ML) models can increasingly be applied to integrate spectral, sensor, and imaging data for predicting fungal development and AF risk in real time. This review brings together progress in nonthermal reduction strategies, biosensing innovations, and data-driven approaches, presenting a comprehensive perspective on emerging tools that could transform pistachio safety management and strengthen compliance with global regulatory standards. Full article

This benchmarking study situates Jordan’s trade indicators relative to comparators (Egypt, Lebanon, Saudi Arabia, and the United Arab Emirates) with descriptive analysis. Using indicators for port competitiveness, geopolitical stability, logistics infrastructure, and trade facilitation within a Modified Input–Process–Output framework, based on secondary data from conventional international indicators (“Fund for Peace Fragile States Index,” “Institute for Economics & Peace Global Peace Index,” “OECD Trade Facilitation Indicators,” “UN Comtrade Trade Volume Records, 2022–2023,” “UN Conference on Trade and Development Port Performance Scorecard,” and “World Bank Logistics Performance Index”). The outcomes of this analysis demonstrate that Jordan’s strengths in terms of institutional quality and geopolitical stability are countermanded by relatively poor digital technology adoption and governance of ports, and homogeneity in exports. Using M-IPO model and SWOT analysis, it was identified that specific actions are needed to improve Jordan’s trade performance, especially as a hub for regional logistics, including investment and facilitation of digital system adoption, commensurate infrastructure, and flexibility in governance. Full article

Türkiye’s role in the global lemon trade was evaluated using the Constant Market Share (CMS) method to assess changes in export competitiveness across major destination markets. The CMS framework decomposes export performance into three components—market share effect, commodity composition effect, and commodity adaptation effect—which, respectively, represent competitiveness, product–market alignment, and structural responsiveness. Trade data for the ten largest importing countries, representing over 80% of Türkiye’s lemon exports, were analyzed to identify the drivers of export growth and structural change. Results show a sharp decline in competitiveness during the COVID-19 disruption, followed by a partial recovery in markets such as Iraq, Poland, Russia, and Azerbaijan. Persistent structural rigidities were identified in several Eastern European and Gulf markets, indicating limited responsiveness to shifting import demand. The findings highlight the need for flexible production systems, improved alignment of export structures with market requirements, and strategic partnerships to sustain long-term competitiveness in the global citrus sector. Full article

This work presents the design and simulation of a time-interleaved successive approximation register (SAR) analog-to-digital converter (ADC) implemented in GlobalFoundries’ 22 nm Fully Depleted Silicon-on-Insulator (FD-SOI) CMOS process. Motivated by the increasing demand for high-speed electrical links in data center and AI/ML applications, the proposed ADC architecture targets medium-resolution, high-throughput conversion with optimized power and area efficiency. The design leverages asynchronous SAR operation, bootstrapped sampling switches, and a hybrid binary/non-binary capacitive digital-to-analog converter (DAC) to achieve robust performance across process, voltage, and temperature (PVT) variations. System-level modeling using channel operating margin (COM) methodology guided the specification of key circuit blocks, enabling efficient trade-offs between resolution, speed, and power. Post-layout simulations demonstrated effective number of bits (ENOB) performance consistent with system requirements, while Monte Carlo analysis confirmed the statistical yield. The converter achieved competitive figures of merit compared to state-of-the-art designs, as benchmarked against the Murmann ADC survey. This work highlights critical design considerations for scalable mixed-signal architectures in advanced CMOS nodes and lays the foundation for future integration in high-speed SerDes systems. Full article

This paper presents a comprehensive analysis of the border city of Jilong in Tibet, China, within the wider context of the global south and the transformation of China’s interior frontier in recent decades. It examines the transformation process of Jilong, identifies the driving factors of its development, and investigates the implementation and impact of relevant policies. Employing a longitudinal case study method, semi-structured interviews, and multi-source data analysis (including policy documents, statistical bulletins, and field notes), this research examines Jilong’s transformation trajectory, the factors behind this change, and policy implementation outcomes. The findings reveal that Jilong has undergone a significant transition from a traditional border trade point to a national strategic hub. Industrial diversification, infrastructure modernization, and governance innovation are recognized as central to this transformation. Additionally, the study also finds challenges such as ecological vulnerability, geological disaster risk, and the necessity for enhancement in cross-border collaboration mechanisms, proposing measures like green development, customs facilitation, and a system for both importing and cultivating local talent. This research emphasizes the transformation of border cities from a complex interplay of national strategy, external shocks, and local initiative. It accordingly advocates for an integrated development model, which combines policy empowerment, resilient infrastructure, cultivation of distinctive industries, and refined border governance. This study adds to research on border cities in the Global South and provides insights for supporting sustainable development in similar cities located in strategic corridors. Full article

Fisheries and aquaculture are crucial for global food security, supporting over 60 million livelihoods worldwide, predominantly in developing countries. This paper presents a perspective on the socioeconomic impacts of the expanding seafood trade and aquaculture growth on dependent communities, emphasizing their interconnected effects on livelihoods, poverty alleviation, and equitable development. While aquaculture can increase fish supply and stabilize markets, it requires strategic policies and sustainable management to prevent negative consequences such as habitat degradation and resource competition, particularly for small-scale fishers. The concept of pro-poor aquaculture is vital for ensuring fair access and benefits, though challenges persist in resource access, market dynamics, and regulatory gaps. Despite economic gains, the global seafood trade raises concerns about diverting nutritious food from local consumption and threatening food sovereignty, highlighting the need for policies that balance trade interests with domestic food security and equitable access. To address these issues, integrated policy frameworks are essential. These should promote sustainable management, equitable resource access and support for local markets, finally fostering a more equitable, resilient, and sustainable aquatic food system for all stakeholders. Full article

In the technology-assisted review (TAR) area, most research has focused on ranking effectiveness and active learning strategies within individual topics, often assuming unconstrained review effort. However, real-world applications such as legal discovery or medical systematic reviews are frequently subject to global screening budgets. In this paper, we revisit the CLEF eHealth TAR shared tasks (2017–2019) through the lens of budget-aware evaluation. We first reproduce and verify the official participant results, organizing them into a unified dataset for comparative analysis. Then, we introduce and assess four intuitive budget allocation strategies—even, proportional, inverse proportional, and threshold-capped greedy—to explore how review effort can be efficiently distributed across topics. To evaluate systems under resource constraints, we propose two cost-aware metrics: relevant found per cost unit (RFCU) and utility gain at budget (UG@B). These complement traditional recall by explicitly modeling efficiency and trade-offs between true and false positives. Our results show that different allocation strategies optimize different metrics: even and inverse proportional allocation favor recall, while proportional and capped strategies better maximize RFCU. UG@B remains relatively stable across strategies, reflecting its balanced formulation. A correlation analysis reveals that RFCU and UG@B offer distinct perspectives from recall, with varying alignment across years. Together, these findings underscore the importance of aligning evaluation metrics and allocation strategies with screening goals. We release all data and code to support reproducibility and future research on cost-sensitive TAR. Full article