Search Results (2,372)

China has emerged as one of the most influential actors in South–South scientific cooperation, progressively integrating agricultural innovation, technology transfer, and sustainable development into its international engagement strategy, with tropical agriculture positioned as a strategic domain in its relations with Latin America. However, despite China’s growing role as a driver of agricultural research collaboration, the specific mechanisms through which its institutions transfer knowledge and strengthen local scientific capacities in the Latin American region remain insufficiently studied, particularly in the case of Ecuador. This study adopted a qualitative scoping review methodology following PRISMA-ScR guidelines, screening 9199 records across Scopus, Web of Science, and SciELO, of which 61 documents were retained for thematic analysis. Results show that Chinese cooperation has evolved through three distinct phases: an initial phase centered on agricultural investment and resource-oriented cooperation (2000–2010); a second phase (2010–2018) characterized by the initial institutionalization of scientific and technological cooperation through bilateral agreements, joint action plans, researcher training, and institutional exchanges; and a third phase (2018–present), marked by the deliberate integration of science, technology, and innovation as central pillars of China’s engagement with Latin America, including long-term collaborative research, joint laboratories, scientific networks, and initiatives led by institutions such as the Chinese Academy of Tropical Agricultural Sciences (CATAS). In Ecuador, CATAS’s partnership with the National Institute of Agricultural Research (INIAP) illustrates China’s capacity to build joint research platforms, though sustained impact depends on long-term institutionalization, continuous financing, and transparent governance over genetic resources. The findings underscore China’s expanding support in shaping South–South agricultural cooperation and innovation, and the conditions required to translate this support force into durable, mutually beneficial scientific outcomes. From a public policy perspective, China and Ecuador could strengthen their international agricultural cooperation framework through long-term mechanisms supporting strategic scientific partnerships between the two countries, including multi-year joint research programs, dedicated funding instruments, researcher mobility, and institutional mechanisms for transparent governance of genetic resources and jointly generated intellectual property. Full article

Multi-energy virtual power plants (VPPs) aggregate electricity, heating, and natural gas resources to provide flexible regulation services to the external power grid. Their operational flexibility, however, cannot be accurately characterized using equipment capacities or single-period energy balances alone, because district heating and natural gas networks introduce heat transport delays, pipeline thermal storage, pressure dynamics, and linepack effects. This paper proposes an operational flexibility boundary assessment method for electricity–heating–gas VPPs based on a dynamic energy circuit model (ECM). The frequency-domain ECM converts heating-network temperature dynamics and gas-network pressure dynamics into algebraic constraints, which are integrated with electric-network and multi-energy coupling-device constraints. The net exchange power at the point of common coupling (PCC) is used as the external flexibility interface, and the period-wise upper and lower boundaries are determined subject to network and device constraints, terminal-state recovery requirements, and an economic feasibility limit. Case studies on an electricity–heating–gas VPP demonstrate that the dynamic ECM captures the intertemporal regulation capability provided by pipeline thermal storage and gas-network linepack. Compared with the static model, the dynamic ECM exhibits consistently greater downward flexibility and comparable or lower upward flexibility in several periods, thereby correcting the underestimation of electrical absorption capability and the optimistic estimation of power-export capability caused by the static approximation. The economic feasibility constraint further excludes high-cost boundary schedules, yielding a technically feasible and economically acceptable flexibility range. Full article

The implementation of circular solutions instead of single-use plastic requires a stronger alliance between science and the private sector, which could be achieved by means of knowledge and strategy co-creation. To investigate their benefits, this study applies common-pool resource theory in serious game design. While other serious games focused on the circular economy exist, none of them consider different modes of knowledge acquisition. To test the game’s potential, we used a convenience sample of 188 biology and geography students (researchers-to-be) from Jagiellonian University. Each of the 20 groups was divided into playing the roles of science and business actors. Two versions of the game were assessed—one with separation and one with personnel exchange. The results of the games were analyzed in relation to the structure of the shared social values as a differentiating co-factor. Science–business collaboration and environmental attitudes were evaluated using pre- and post-questionnaires. Results suggest that the successful resolution of the presented common-pool resource dilemma correlates with the introduced collaboration (p = 0.004, t value = 3.400, df = 1) and the Self-Transcendence values (p = 0.001, t value = 4.329, df = 1). We observed desirable changes in participants’ attitudes after the game (p = 0.000, χ² = 18.810, df = 1). Further investigation into gaming as a science communication tool and its long-term effects is recommended to facilitate the implementation of knowledge co-creation principles in practice. Full article

Traditional particle swarm optimization (PSO) easily falls into premature convergence, while differential evolution (DE) is highly sensitive to fixed control parameters. Existing PSO-DE hybrid frameworks suffer from static population sizes and insufficient cross-population information exchange. This paper proposes PSO-DE-ADP, a hybrid optimizer with sinusoidal adaptive parameters, elite-guided mutation, ring neighborhood-weighted PSO and fitness-driven dynamic dual-population allocation. Four complementary mechanisms are integrated: (i) sine-wave perturbation superimposed on linear decay adaptively adjusts PSO inertia weight, acceleration factors and DE scaling/crossover coefficients to balance search stages; (ii) global elite individuals are embedded into DE mutation to reduce blind random search; (iii) ring topology with weighted learning realizes bidirectional information interaction between PSO and DE subpopulations; (iv) the proportion of PSO/DE individuals is dynamically adjusted according to elite ratio to allocate computing resources. Experiments adopt the CEC2017 30-dimensional benchmark with 30 test functions covering unimodal, multimodal, hybrid and composite landscapes. Compared with 8 state-of-the-art metaheuristics, PSO-DE-ADP achieves the lowest Friedman rank (1.08 vs. 2.23–4.90 for PSO variants; 1.53 vs. 2.07–5.00 for non-PSO algorithms). Ablation tests prove each component significantly boosts accuracy; The algorithm only costs 0.172 s average runtime, superior to all competitors. Statistical Wilcoxon and Friedman tests verify its significant superiority. Future work extends this method to multi-objective, constrained and real engineering optimization tasks. Full article

Assessing the soil quality of coastal reclamation areas is fundamental to alleviating land resource scarcity in coastal cities and ensuring food security. However, it remains unclear how to evaluate soil quality in reclaimed areas and identify factors driving its variation. In this study, paddy soils from four typical reclaimed coastal areas in China (Yueqing, YQ; Longgang, LG; Rui’an, RA; Longwan, LW) were investigated to construct a minimum data set via principal component analysis and to calculate soil quality indices (SQIs). YQ had higher contents of soil organic carbon (SOC: 22.82 g kg⁻¹), total nitrogen (TN: 0.14 g kg⁻¹), total water-soluble salts (TWS: 3.09 g kg⁻¹), cation exchange capacity (CEC: 21.77 cmol(+) kg⁻¹), and available Fe (44.23 mg kg⁻¹), Mn (36.63 mg kg⁻¹), Cu (30.31 mg kg⁻¹), and Zn (8.79 mg kg⁻¹) than the other sites. RA exhibited significantly higher activities of β-glucosidase (BG: 32.79 nmol g⁻¹ h⁻¹), xylanase (XYL: 5.88 nmol g⁻¹ h⁻¹), N-acetyl-β-D-glucosaminidase (NAG: 18.00 nmol g⁻¹ h⁻¹), leucine aminopeptidase (LAP: 27.01 nmol g⁻¹ h⁻¹), and acid phosphatase (PHOS: 54.50 nmol g⁻¹ h⁻¹) than the other sites (p < 0.05). LW had the greatest bacterial and fungal abundances, whereas LW displayed the highest fungal diversity. RA showed the highest SQI (SQIw: 0.49; SQIa: 0.48), followed by LW (SQIw: 0.47; SQIa: 0.47), LG (SQIw: 0.43; SQIa: 0.41), and YQ (SQIw: 0.38; SQIa: 0.41). Random forest analysis indicated that soil enzyme activities (XYL, NAG, BG, CB, PHOS), nutrients (TN, SOC, AN), fungal abundance and diversity, and TWS were key SQI predictors (Welch ANOVA p = 0.016), with XYL being the strongest predictor (p < 0.05). Collectively, soil quality in coastal reclamation areas is co-regulated by microbial metabolic activity, nutrients, and salinity, with soil enzyme activity serving as an important indicator for its assessment, thereby deepening the understanding of soil quality dynamics within these areas and enabling their sustainable management. However, the microbial mechanisms underlying these patterns across broader environmental gradients remain to be explored. Full article

This study aims to investigate the perspectives of aquaculture producers in the Western Mediterranean Region (operating in Antalya, Burdur, and Isparta provinces) on climate change, examine the impacts of climate change on regional aquaculture, and develop solution proposals. Within the scope of this objective, the socioeconomic and demographic characteristics of the aquaculture producers in the Western Mediterranean Region, along with their knowledge levels regarding climate change, were obtained through a questionnaire technique. The results indicate that producers, who are predominantly engaged in rainbow trout aquaculture, are under severe economic pressure due to high-exchange-rate-driven input costs and the abolition of government subsidies. While all participants (100%) perceived that climate change has decreased production tonnage, the most prominent impact of the climate crisis is perceived as drought and the decline of water resources, with a response rate of 37.2%. Multivariable analysis further showed that aquaculture experience and satisfaction with aquaculture income were significantly associated with producers’ future outlook, highlighting the importance of socioeconomic factors in shaping perceived sectoral vulnerability. Due to both rising costs and environmental risks, 50% of the producers view the future of the sector pessimistically and do not recommend this profession to future generations. Consequently, these results emphasize the critical need for integrated land and water resource management policies, alongside targeted climate adaptation strategies, to ensure the long-term socio-ecological sustainability of forest inland aquaculture in the region. Full article

The Internet of Vehicles (IoV) relies on frequent vehicle-to-roadside-unit (RSU) access over open wireless channels, making efficient authentication and key establishment essential. In many existing authentication and key agreement (AKA) schemes, a target RSU receives and processes a request before an invalid sender is rejected, which can waste roadside computation under dense invalid-request traffic. This paper presents EDAKA-IoV, an elliptic-curve-cryptography-based AKA scheme that separates admission filtering from end-to-end session-key establishment. A trusted authority (TA) performs Lightweight Polynomial-based Pre-Verification (LPPV) to discard invalid authentication requests before they reach the target RSU, while the vehicle and RSU establish the final session key. A current–pending dual-state mechanism prevents permanent de-synchronization during dynamic pseudo-identity renewal without adding another communication round. Formal analysis under an eCK-style model, ProVerif verification, and heuristic analysis evaluate session-key secrecy, injective mutual authentication, privacy, and resistance to the considered attacks. Optional offline precomputation moves two fixed-base scalar multiplications outside the online phase and reduces the non-polynomial online computation component by approximately 48.8%. With fixed-length compressed point encoding, the authentication exchange requires 2336 bits. The workload analysis shows that the RSU-side processing reduction is proportional to the invalid-request ratio, while the TA still performs record lookup, hashing, and degree-dependent polynomial evaluation for every received request. EDAKA-IoV therefore provides a balanced authentication solution for resource-sensitive IoV deployments. Full article

The Weibei Plain, characterized by its complex stratified aquifer system and extensive brine resources, faces severe groundwater salinization. Unraveling the precise evolutionary mechanisms of diverse hydrochemical types across varying depths and geomorphological zones remains a significant challenge. This study synthesizes a multi-batch hydrochemical dataset with multi-isotopic tracers (δ²H, δ¹⁸O, δ¹¹B, δ⁸¹Br, δ³⁷Cl) to establish a comprehensive groundwater evolutionary model from the piedmont plain to the coastal marine plain. The results indicate distinct hydrochemical zonation governed by geographic geomorphology and historical marine transgressions. Salinization in transitional waters is primarily driven by physical mixing and reverse cation exchange rather than extreme evaporative fractionation. Crucially, isotopic mass balance definitively reveals that deep brine (depth > 60 m) originates not from modern seawater intrusion, but from the extreme surface evaporation of ancient paleo-seawater. This paleo-brine underwent profound isotopic exchange during its gravity-driven downward migration, evidenced by intense clay mineral adsorption (yielding extreme δ¹¹B enrichment up to 64.42‰) and secondary evaporite dissolution. Furthermore, the regional cone of depression formed by intensive brine extraction has profoundly altered deep hydrodynamics, inducing overflow and membrane ultrafiltration across massively thick clay aquitards. This process distinctly drives the isotopic fractionation observed in deep brackish waters. The analysis process in this study combines the isotope method with the regional geomorphological zoning, which can provide a reference for the analysis of groundwater evolution characteristics in other coastal aquifers. Full article

This study examines the long-run relationship between terms of trade (TOT) and real fishing-sector GDP in a small open economy, focusing on the Peruvian case. Despite the strategic importance of fisheries for exports, employment and foreign exchange generation, the extent to which external price conditions are associated with fishing-sector performance remains insufficiently explored in sector-level research. Building on the notion that TOT summarise opportunities and constraints arising from the international environment, the paper evaluates whether persistent external conditions are linked to the long-run trajectory of the fishing sector. The analysis employs the Johansen cointegration approach and a bivariate Vector Error Correction Model (VECM) using quarterly data for the period 2001–2025. Seasonal effects are incorporated through quarterly dummy variables, while robustness is assessed by controlling for extreme El Niño–Southern Oscillation (ENSO) episodes and the COVID-19 pandemic. The results reveal the existence of a unique long-run equilibrium relationship between TOT and fishing-sector GDP. The error-correction mechanism indicates that deviations from equilibrium are actively corrected over time, whereas the adjustment coefficient for TOT is statistically insignificant. Robustness tests further show that El Niño episodes are negatively and significantly associated with short-run sectoral performance, while no statistically significant association is detected for La Niña. The COVID-19 control does not materially alter the long-run relationship identified by the model. The findings contribute sector-level evidence for a resource-dependent economy and suggest that long-run equilibrium and sectoral adjustment dynamics are important elements for understanding the long-run behaviour of the fishing sector. Full article

The coordinated operation of interconnected multi-carrier energy hubs is a key enabler of cost-efficient and flexible energy management in modern smart cities. This paper develops a comprehensive optimization framework for the day-ahead scheduling of interconnected energy hubs in residential and commercial sectors. The problem is formulated as a mixed-integer linear programming (MILP) model that jointly manages electricity, natural gas, and thermal energy flows. To enhance operational flexibility, the proposed model incorporates demand response programs for both electrical and thermal loads, multiple energy storage technologies, and electric vehicles with vehicle-to-grid (V2G) capability. Six operating scenarios are defined to assess the impact of different resources and coordination levels, ranging from independent hub operation to fully integrated interconnected scheduling. Simulation results show that coordinated operation of the energy hubs, supported by flexible loads, storage systems, and electric vehicles, can significantly reduce total daily operating costs compared with conventional standalone configurations. The findings confirm that energy exchange among hubs, combined with demand-side flexibility and EV participation, improves both economic performance and system efficiency. The proposed framework offers a scalable scheduling approach for future integrated multi-energy systems. Full article

Background: In liver transplantation, maintaining donor organ viability is a critical factor determining transplant outcomes. The aim of this study was to evaluate liver metabolic activity under ex vivo perfusion in the presence of magnetite magnetic nanoparticles using mathematical modeling. Methods: Ex vivo liver perfusion was performed with nanoparticles added to the perfusate; the concentration of nanoparticles in the inflowing and outflowing perfusate was determined by mass spectrometry. A stoichiometric model of hepatic metabolic fluxes was constructed, and the distribution of energy resources was assessed using the Zipf–Pareto law and its linear approximation, the Zipf–Pareto–Mandelbrot distribution. Results: It was shown that nanoparticle uptake by the liver increased from 26.5% to 54.4% over the course of perfusion. The introduction of magnetic nanocomposites altered metabolic fluxes, including glycolysis, the respiratory chain, and oxygen exchange across the surface, leading to redistribution of energy resources within liver cells. Zipf–Pareto analysis showed that energy was optimally distributed among all metabolic fluxes both in the control condition and in the presence of nanoparticles. Conclusions: Magnetic nanoparticles alter liver metabolic activity, but the functional state of the organ remains intact. Full article

On edge devices, convolutional neural network (CNN) inference is bottlenecked mainly by memory bandwidth, owing to the frequent memory accesses to feature maps and parameters. To address this challenge, we propose a memory-efficient hardware accelerator for depthwise separable convolution that minimizes off-chip memory traffic and parameter storage. The proposed architecture employs three key techniques: (1) a 64-bit run-length coding (RLC) packet compression that exploits feature-map sparsity after ReLU, (2) a mixed-precision scheme that represents feature maps and weights at different precisions, and (3) separated depthwise and pointwise convolution units. In particular, feature maps are transferred in RLC-compressed form, which reduces the amount of data exchanged with the host. The compressed data are decoded row by row, so the on-chip buffers hold only the rows required for computation rather than a complete feature map. In software simulation on ImageNet, the mixed-precision scheme reduced the parameter storage by 49.22% at a cost of 6.24 percentage points (pp) in Top-1 accuracy, and the RLC reduced the data by up to 56.07% in the deeper layers. Implemented on a Xilinx ZCU-104 FPGA, the proposed accelerator performs the depthwise separable convolution with a small number of logic resources and on-chip memory, confirming its feasibility for resource-constrained edge devices. Full article

Liquid Air Energy Storage (LAES) is a promising large-scale storage technology for supporting the sustainable integration of intermittent renewable electricity into power grids, particularly when electricity storage is combined with waste-heat valorization, cryogenic cold recovery, and reduced exergy degradation. In this thermodynamic sense, the present study proposes a sustainability-oriented framework for the comparative and parametric exergetic analysis of LAES systems, integrating the liquefaction and discharge stages within a unified analysis. The assessment focuses on thermodynamic resource efficiency and exergy performance rather than on a complete economic, environmental, or life-cycle evaluation. The objective is to identify the components and operating parameters that most strongly influence performance and to quantify the reductions in exergy destruction and losses achieved through configuration changes and parameter variation. Three Linde–Hampson-based liquefaction configurations are compared, including arrangements with external and intermediate auxiliary pre-cooling. Improved heat-exchanger integration and temperature matching increase the structural liquefaction exergetic indicator from 7.95% in the baseline configuration to 19.28% in the two-RHX configuration. The discharge stage is assessed parametrically with respect to cryogenic pumping pressure, turbine inlet temperature, and expansion architecture. Single-stage and two-stage adiabatic expansions are compared with an ideal isothermal benchmark. The adiabatic configurations provide mechanical-work recovery together with recoverable cooling potential, whereas the isothermal case gives the highest work-recovery benchmark. Under the reference conditions, using the aggregated compressor representation adopted for the main parametric analysis, the two-stage adiabatic configuration reaches a global exergetic efficiency of 15.92% for the improved Linde–Hampson-based chain and 24.87% for the selected Claude–Heylandt reference block. Full article

Integrated electricity–gas–heat systems require coordinated scheduling while limiting data sharing and representing network constraints. This paper develops a day-ahead model incorporating reactive power, voltage magnitudes, network losses, demand response, and CHP/P2G coupling. Piecewise linearization and second-order cone relaxation reformulate the model as a mixed-integer second-order cone program, while a hierarchical ATC–ADMM method coordinates the electricity–heat and natural gas subsystems by exchanging coupling variables. Residual checks verify approximation accuracy and original equation feasibility. In the test system, ATC–ADMM reached consensus within five iterations, with a total-cost deviation of 0.0075% from centralized optimization, whereas ATC did not converge within 500 iterations. Coordinated operation reduced the total cost by 1.13%, and Shapley allocation benefited both subsystems. Increasing demand-side flexibility from 5% to 9% reduced the total cost by 0.88% and wind curtailment from 6.02% to 4.86%; increasing reactive compensation from 40% to 60% reduced the total cost by 0.41% and wind curtailment to 5.70%. The results reveal non-monotonic penalty-update effects and diminishing marginal benefits of flexibility resources, providing guidance for parameter selection and capacity allocation. Full article

Unmanned Aerial Vehicles (UAVs) have experienced rapid development due to their advantages of low cost, high efficiency, flexibility, reliability, and strong environmental adaptability. To fully leverage the potential of UAV swarms in multi-task scenarios, optimizing task allocation has become a crucial direction to enhance the efficiency of UAV swarms. While existing task allocation methods have achieved promising results, frequent inter-UAV information exchange can impose substantial communication overhead in distributed UAV swarms, particularly in resource-constrained applications such as emergency rescue and mountainous operations. In this context, to reduce inter-UAV interactions while maintaining the solution quality of task allocation, this paper first analyzes the factors affecting communication interactions between UAVs. Based on this analysis, we utilize historical bidding information to infer other UAVs’ positions and employ estimation strategies to resolve task conflicts, thereby reducing communication iterations. Furthermore, we propose a bidding-based grouping method to eliminate ineffective communication interactions. Finally, we introduce a network simplification algorithm based on reducing the number of triangular network topologies to optimize the communication network structure. Simulation results demonstrate that the proposed algorithm significantly reduces inter-UAV interactions while preserving the number of allocated tasks, with a maximum observed increase of only approximately 8% in task waiting time across the evaluated simulation settings. Full article