Search Results (952)

This study focuses on the mechanical behavior of iron ore failings as base materials for roads. It is the first to systematically integrate freeze–thaw static load tests, SHPB dynamic tests, PFC discrete element microscopic simulation, and road stability analysis, to reveal the coupling mechanism of freeze–thaw, confining pressure and loading rate in cold environments, and to clarify the critical threshold of porosity and the safe threshold of failing content, as well as the intrinsic relationship between force chain evolution and macroscopic strength degradation. Firstly, a two-dimensional particle flow model of iron ore failing aggregates (150 mm × 150 mm, 11,530 particles) was constructed using PFC2D 2025 software, and the optimal microscopic parameters such as normal stiffness of 350 N/m and tangential stiffness of 175 N/m were determined (the error between simulation and experimental peak strength is less than 2.5%). The study revealed a negative correlation between high loading rate, local dense force chain and overall strength reduction. The initial porosity critical threshold is 0.23, and the optimal control range is 0.18–0.23 (this threshold varies with particle gradation). Secondly, taking iron ore failings from Lanzhou Daiquiri County, Sichuan Province, as the object, the static mechanical degradation law under freeze–thaw cycles (porosity from 7.5% to 9.5%, elastic modulus decreased by 52.3%, peak strength decayed by 13.0%) was clarified. The three-dimensional coupling effect of freeze–thaw times, confining pressure, and loading rate was investigated. The loading rate was also revealed (the average strength increased by 15% due to confining pressure, and the dynamic strength dropped to 110.2 MPa after 50 freeze–thaw cycles). Finally, the stability of the iron failing roadbed was analyzed, and it was found that the tailing content and safety factor FS(x) decreased linearly, the correction coefficient k(x) increased linearly, and the critical content was 66.67% (FS = 1.3), reaching the specification threshold. The poor tailing gradation led to insufficient stability, and stabilization agents were needed for improvement. This study did not investigate the long-term freeze–thaw durability, dissolution risks, and optimal dosage of the stabilizer, and thus has certain limitations. Full article

This field study examined extant aquatic food production and marketing in the three coastal states of Lagos, Ogun, and Ondo before IMTA across 15 Local Government Areas (LGAs)/Local Council Development Areas (LCDAs). Marketing mix practices in coastal aquatic food systems were explored through a structured, qualitative assessment using a multi-value chain perspective. Monthly sales volumes most frequently fell within the range of 1–5 tonnes. The local market was dominant, with some sales in the international markets. Respondents asserted that post-harvest processing was diverse, and some were satisfied with the technology available to preserve their products. Cold storage practices across coastal states were hindered by unreliable power supply. Zero-level channel distribution dominated among traders, with over 90% relying on word-of-mouth (WOM) to promote their products. Consumers showed a strong preference for the quality of local products and expressed openness to incorporating seaweed into their purchases. Health benefits, taste, and other reasons for purchase decisions varied significantly across the state χ² (df = 8, n = 300) = 92.39, p < 0.001. These findings provide a baseline for IMTA in Nigeria, highlighting existing strengths, market dynamics, and infrastructure gaps that must be addressed to support sustainable integration. Full article

Inspired by the hovering, diving, and cooperative hunting behaviors of the pied kingfisher, the Pied Kingfisher Optimizer (PKO) has demonstrated competitive performance in optimization tasks. However, it exhibits several phase-specific limitations, including uneven population distribution caused by random initialization, insufficient use of historical information during exploration, over-reliance on the global best during exploitation, and weakly guided perturbation in the symbiosis phase. To address these issues, this study proposes an Improved Pied Kingfisher Optimizer (IPKO), which incorporates biologically inspired adaptive strategies. Drawing inspiration from the kingfisher’s diverse perching, gaze adjustment during hovering, evasive diving after failed strikes, and territory shifting based on flock position, four mechanisms are developed. Specifically, sine chaotic opposition-based initialization enhances population diversity; adaptive directional search regulates the exploration–exploitation balance; stochastic perturbation-based information fusion improves the ability to escape local optima; and centroid-based adaptive boundary handling strengthens constraint adaptability. The performance of IPKO is evaluated on the CEC2017 benchmark suite (10, 30, 50, and 100 dimensions) and two real-world engineering problems. Experimental results show that IPKO achieves superior overall performance compared with eleven state-of-the-art algorithms, with statistical significance confirmed by the Friedman test and Holm’s post-hoc procedure. Ablation studies further verify the contribution of each strategy. In engineering applications such as cold chain logistics and dynamic multi-UAV cooperative path planning, the IPKO algorithm demonstrates superior solution quality, robustness, and constraint-handling capability compared with competing algorithms. These results demonstrate that IPKO is a robust and effective bio-inspired optimization approach for solving complex, high-dimensional constrained engineering problems. Full article

A novel method was developed for the rapid determination of five biogenic amines (BAs)—histamine (HIS), tyramine (TYR), cadaverine (CAD), spermidine (SPD), and spermine (SPM) in cold-chain fish by portable ion trap mass spectrometry with nano-electrospray(nESI) ionization. Samples were homogenized and extracted with aqueous solution containing 1% (v/v) formic acid and 80% (v/v) acetonitrile. With HIS-d4 as an internal standard, the sample solutions were directly injected with the nESI injection device and detected by a portable ion trap mass spectrometer at MS/MS detection mode. The results showed good linearity in the invested range of 0.2 (or 0.5)–10 μg mL⁻¹ with R² > 0.992, The limit of detection (LODs) and limits of quantification (LOQs) for HIS were less than 1.5 mg/kg and 4.0 mg/kg, respectively; the LOD and LOQ for other four BAs were less than 4.0 mg/kg and 12.5 mg/kg, respectively. Recoveries at three fortified levels ranged from 84.26% to 106.6% with relative standard deviations between 4.56% and 13.84%. With the safety limits of HIS as the concentrations of concern, this method demonstrated excellent performance when applied to the eligibility fast screening of HIS in cold-chain fish. The study provided a valuable methodological reference for the rapid detection of BAs in food. Full article

The quality of glutinous rice flour (GRF) plays a critical role in determining the processing suitability of Tangyuan, a traditional Chinese glutinous rice-based food. This study systematically characterized the physicochemical, pasting, textural and digestive properties of twelve representative GRFs, as well as the cooking behaviors of the resulting product of Tangyuan. The results revealed that different GRFs displayed varied protein, total starch and amylopectin contents. The microstructure of Tangyuan exhibited three main types: robust and dense (e.g., H1 and H3), porous and soft (e.g., S1 and S4), and fragmented and disrupted (e.g., S2 and S3) networks. Rheological and pasting profiling revealed that doughs with extreme rigidity (G′ > 10⁴ Pa) and high setback values exhibited rapid retrogradation, leading to severe frost cracking during cold-chain storage. Tangyuan with moderate G′, loss tangent (tan δ) below 0.35, and balanced peak viscosities provided optimal viscoelasticity for both mechanical machinability and freeze–thaw stability. Furthermore, S5 with naturally high resistant starch contents significantly attenuated the hydrolysis index, successfully shifting Tangyuan from a high-glycemic to a medium-glycemic profile. The results provide valuable insights into the screening of raw glutinous rice flour from different origins, offering theoretical guidance for the standardized production of freeze–thaw-stable and low-glycemic functional Tangyuan. Full article

Reliable potato quality monitoring during postharvest handling requires compact sensing systems that can acquire chemically relevant information while operating on irregular tuber surfaces. In this study, a Flexible Spectral Sensing Gripper (FSSG) was developed by integrating a low-cost 12-channel visible/near-infrared (Vis/NIR) spectral sensor array, electronic components, and an ESP32-S microcontroller onto a flexible printed circuit (FPC) substrate encapsulated with PDMS. By embedding the sensing units into the grasping interface, the FSSG enables conformal, multi-point spectral acquisition during potato handling, reducing optical-coupling uncertainty associated with unstable contact. Spectral reflectance data were collected from potato tubers, and dry matter content (DMC) and starch content (SC) were determined by standard chemical analysis as reference values. Multiple linear regression (MLR) and partial least squares regression (PLSR) models were compared under Norm, SNV, MSC, SNV-Norm, and MSC-Norm preprocessing conditions, and support vector machine (SVM) classification was used to distinguish healthy and artificially induced deteriorated samples. Normalization combined with MLR provided the best performance among the evaluated regression approaches, achieving cross-validation coefficients of determination ($R_{CV}^2$) of 0.847 and 0.817 and RPD values of 2.557 and 2.345 for DMC and SC, respectively. The SVM model achieved 98.67% accuracy for healthy versus artificially induced deteriorated potato samples. Overall, the FSSG demonstrates the value of combining gripper-integrated spectral sensing with interpretable chemometric modeling for potato quality screening. The FSSG enables real-time non-destructive quality prediction and disease-detected classification of potatoes, improves sorting accuracy and production efficiency, and provides general sensing solutions for controlled-environment agriculture, cold-chain logistics, and value-added processing of agricultural products. Full article

The decoupling of physical loading configurations from dynamic temperature control in cold-chain logistics exposes supply chains to severe thermal compliance risks and exponential cost penalties. To address this structural gap, this study formulated the Cold Chain Unitization Loading Optimization Problem (CCULP). We propose a mixed-integer linear programming (MILP) model that integrates continuous-time heat-transfer dynamics—including door-opening impulse disturbances—and Q10-driven quality-decay kinetics as endogenous constraints within the hierarchical assignment of perishable goods to insulated containers, pallets, and vehicles. By treating container thermal resistance as a core decision variable, the model operationalizes a “prevention-first” economic strategy. To solve this NP-hard problem, we developed a Temperature-Aware Heuristic Algorithm (TAHA) that embeds a forward-Euler temperature simulation loop directly into the combinatorial search. Computational experiments on instances up to 100 SKU types demonstrate that TAHA achieves near-optimal solutions (within 0.7% of the MILP proven optimum) while converging 63 times faster than a genetic algorithm benchmark. Moreover, compared with traditional geometry-centric heuristics, TAHA’s proactive container-polarization strategy effectively eliminates the “penalty cliff,” yielding up to a 25.9% reduction in total system cost on Large-scale instances, almost entirely attributable to the elimination of temperature-violation penalties. Sensitivity analyses further confirm TAHA’s robustness under extreme environmental stress (e.g., 40 °C ambient temperatures) and frequent logistical disturbances, offering an integrated framework for proactive risk mitigation and for reducing food loss in sustainable temperature-controlled distribution. Full article

As representatives of early-flowering herbaceous peony types, certain cultivars known as the ‘Coral’ series are highly prized in the global cut flowers market for their unique dynamic color transitions from orange-red (amber) to creamy yellow during the florescence and senescence periods. Despite their strong growth vigor and high commercial value, these cultivars face critical postharvest preservation challenges, most notably rapid petal abscission and short vase life. Previous studies have confirmed that postharvest quality deterioration of these peony cut flowers, including undesired color fading and accelerated senescence of petals, is closely associated with ethylene and ROS accumulation. To address these development impediments, systematic optimization of the entire industrial chain is essential. Proposed countermeasures include preharvest regulation of environmental conditions and cultivation practices to establish a foundation for quality formation, as well as postharvest strategies such as precise harvest timing, anti-ethylene treatments, and full cold-chain logistics. Meanwhile, simplifying the distribution system and optimizing terminal vase preservation techniques are also crucial to maintain postharvest quality. In the long term, promoting sustainable development of the global cut-flower industry will require breeding new germplasm with low ethylene sensitivity from a global perspective, continuously optimizing agronomic practices to overcome year-round supply constraints, and accelerating the application of intelligent technologies such as the Internet of Things (IoT) in full chain quality management. Full article

In complex multi-criteria decision-making scenarios, the inherent ambiguity of evaluation data and the frequent unavailability of complete attribute weight information pose significant challenges for domain experts. To address these methodological limitations, this study proposes a novel TOPSIS-based decision-making framework that integrates optimization algorithms with probabilistic linguistic term sets (PLTSs). Specifically, a distance measurement optimization model is constructed to objectively resolve the issue of incomplete attribute weight information. This mathematical approach enables the seamless fusion of qualitative expert judgments with quantitative metrics, effectively managing uncertainty and information deficiency in the decision-making process. To validate the practical viability and superiority of the proposed methodology, it is applied to an empirical case study of supplier selection in the cold chain logistics sector for fresh and perishable commodities. The evaluation encompasses three core dimensions: (i) environmental sustainability and energy efficiency, (ii) quality assurance and operational control, and (iii) supply chain collaboration and resilience. Empirical findings demonstrate that the proposed methodological framework substantially strengthens the robustness and reliability of selection outcomes under information-deficient conditions. Relative to conventional approaches, the developed framework demonstrates superior mathematical adaptability and effectively captures decision distortions, thereby offering rigorous theoretical contributions to decision-making under uncertainty and providing actionable practical guidance for complex supply chain evaluations. Full article

The Agricultural Energy Internet (AEI) represents an emerging systemic paradigm driven by the convergence of intelligent agriculture and rural energy transformation. It is not a simple extension of agricultural informatization or rural electrification; rather, it redefines agricultural processes—such as irrigation, greenhouse environmental control, supplementary lighting, cold-chain logistics, and agricultural machinery—as perceptible, computable, and schedulable energy-related processes, thereby enabling the deep integration of agriculture, energy, environmental management, and intelligent decision-making. This review systematically examines the evolutionary trajectory of AEI, from early agricultural digitalization and Internet of Things (IoT)-based monitoring to edge intelligence and digital twin technologies, and ultimately to the coordinated optimization of agriculture–energy–environment systems. A comprehensive technical framework is established, encompassing physical energy coupling, multi-source sensing and actuation, interconnection and interoperability, edge–cloud collaborative control, data governance, digital twin modeling, artificial intelligence-enabled optimization, and application-oriented decision-making. The review further highlights that high-quality data governance, edge–cloud collaboration, and digital twin calibration are critical enablers of the transition from visualization-oriented management to closed-loop intelligent operation. In addition, this study clarifies the complementary relationship between agricultural informatization and electrification: the former provides capabilities for perception, prediction, optimization, and coordination, whereas the latter provides a controllable execution chain. Together, they constitute the foundation of a cyber-physical agricultural energy system. Finally, frontier research directions are identified, including high-temperature solid oxide electrolysis for hydrogen production, edge AI–IoT-enabled closed-loop agricultural operation, and privacy, security, and trust mechanisms in federated edge intelligence. The findings suggest that AEI can serve as a strategic technological framework for supporting the next generation of smart agriculture toward low-carbon, resilient, and collaborative operation. Full article

Empathetic dialogue systems built upon large language models overwhelmingly adopt a monolithic inference paradigm that processes emotion perception, causal reasoning, memory retrieval, and response planning within a single forward pass without architecturally enforced intermediate representations, forfeiting intermediate-state transparency and long-horizon personalization. Drawing on neuroscientific and cognitive–psychological evidence that human empathy is functionally dissociable, we present MOSAIC (Multi-agent Orchestration with Structured Affective memory for Interpretable empathiC dialogue), a training-free framework that operationalizes empathetic dialogue as a four-stage cognitive pipeline: affective perception, causal appraisal, episodic memory retrieval, and response synthesis. Three innovations distinguish MOSAIC from prior work: (1) a cognitively motivated modular architecture whose functionally dissociable stages enable post hoc failure attribution through logged intermediate states; (2) a hierarchical three-tier emotional memory—perceptual, semantic, and episodic—coupled with adaptive three-dimensional retrieval over emotion, situation, and coping-strategy cues; and (3) a heterogeneous model orchestration strategy coordinating open-source and API-accessible models through role-specific chain-of-thought prompts, requiring no task-specific fine-tuning. We note that the EmpatheticDialogues evaluation pre-populates the memory store with 200 training-split episodes prior to test-set interaction, a data-access asymmetry relative to single-model baselines that must be borne in mind when interpreting comparative results. Experiments on EmpatheticDialogues and ESConv show that MOSAIC achieves a 76.4% weighted F1 and an empathy score of 3.87 (on a 1–5 Likert scale) and that it improves over single-model, training-free baselines on aggregate empathy and—most prominently—on human-rated personalization (3.67 vs. 3.24 against Claude-3.5 five-shot, $d=0.48$). We caution that the comparison against training-free baselines is not data access-controlled (see the cold-start discussion in Methods); the personalization advantage, supported by the ablation without the Event Agent, is the result we treat as the primary practical contribution of this work. Full article

With the rapid development of software-defined radio (SDR) technology, a digital, software-reconfigurable, and flexible solution is provided for microwave radiometers, particularly suitable for atmospheric water vapor and oxygen detection with wideband, multi-channel requirements, significantly improving system efficiency. Meanwhile, digitization helps improve channel consistency and address nonlinearity issues, while the digital zero-balancing mechanism implemented through adaptive integration is more suitable for digital platforms. This paper proposes a digital Dicke-type radiometer system based on an SDR platform, using Xilinx RFSoC XCZU47DR (AMD, San Jose, CA, USA) as the core hardware to achieve single-chip integration of RF signal sampling, digital local oscillator generation, and signal processing. The system implements a 46-channel channelized receiver (23 channels each for K-band and V-band) on an FPGA using a polyphase filter bank. The prototype filters achieve 70 dB stopband attenuation and 0.5 dB passband ripple, with each polyphase branch requiring only 25 coefficients, significantly reducing hardware resource consumption. An adaptive integration method is proposed, where an adaptive switch controller dynamically adjusts the hot source injection time ratio by calculating the power difference between adjacent integration periods, enabling the Dicke zero-balancing mechanism to operate entirely in the digital domain. Furthermore, a complete hardware transfer model is established for three signal branches (antenna, hot source, and matched load), and full-chain calibration of all 46 channels is performed using a liquid nitrogen cold source, with calibration reliability verified through blackbody measurements. Experimental results demonstrate brightness temperature consistency better than 0.7 K, with a sensitivity of less than 0.15 K for the K-band and less than 0.21 K for the V-band at 1 s integration time. Full article

Broccoli (Brassica oleracea var. italica) is highly nutritious, rich in vitamin C, glucosinolates, and minerals. However, its high postharvest respiratory rate leads to rapid quality deterioration, particularly chlorophyll degradation and yellowing under ambient conditions. In China, the lack of timely pre-cooling facilities exacerbates postharvest losses. Therefore, developing safe, effective and low-cost preservation methods for broccoli during transportation is of great practical importance. In this study, RNA sequencing was employed to analyze the effects of preharvest 1-methylcyclopropene (1-MCP) and postharvest pre-cooling combined with cold treatments on gene expression in broccoli. Transcriptome analysis revealed that both treatments significantly upregulated or maintained key genes involved in chlorophyll biosynthesis (e.g., Glutamyl-tRNA reductase (GluTR), porphobilinogen deaminase (PBGD), magnesium chelatase (MgCh)) and downregulated chlorophyll degradation-related genes (e.g., Chlorophyllase (CLH), pheophytinase (PPH), pheophorbide a oxygenase (PaO)), resulting in enhanced chlorophyll retention. Furthermore, chlorophyllide a oxygenase (CAO) was upregulated, while chlorophyll b reductase (CBR) was downregulated, suggesting modulation of the chlorophyll cycle. These findings elucidate the molecular mechanisms by which 1-MCP and pre-cooling combined with cold regulate chlorophyll metabolism, providing new insights into the gene regulatory network underlying the postharvest quality maintenance in broccoli. Full article

Background: Studies of fish supply chain efficiency often rely on price spreads or frontier-based measures, which do not fully capture actor-level coordination performance in heterogeneous, informal supply chains. This study addresses this gap by developing a composite Market Efficiency Index (MEI) that integrates financial performance, operational quality, service equity, and relational governance. Methods: The MEI, a multidimensional alternative to frontier-based measures, was developed and applied to data collected from 250 supply chain actors in Sri Lanka. Results: The results show a clear efficiency gradient along the supply chain, with fishers scoring the lowest (MEI = 0.44), intermediaries moderate (MEI = 0.54), and retailers the highest (MEI = 0.67), yielding an overall system efficiency of 0.55 and relational governance emerging as the weakest system-level dimension. These results indicate persistent structural differences in value distribution and in how well the fish supply chain functions as a cohesive network, driven by liquidity constraints, information asymmetry, and weak cold-chain infrastructure. Conclusions: A multidimensional supply chain assessment provides a more effective basis for diagnosing coordination constraints and enables targeted digital interventions that offer feasible pathways to improve transparency, liquidity, and inclusiveness in smallholder-dominated fish supply chains. Full article

Mitochondrial proteostasis in neurons relies on the coordinated expression, targeting, and import of a predominantly nuclear-encoded proteome to meet high metabolic demands. Here, we identify the RNA-binding protein cold shock domain containing E1 (CSDE1) as a TOM20-associated factor linked to mitochondrial protein-encoding mRNAs in sensory neurons. CSDE1 immunoprecipitation followed by sequencing from naïve dorsal root ganglion tissue revealed association with nuclear-encoded mitochondrial mRNAs enriched for inner membrane/matrix and oxidative phosphorylation pathways. A subset of CSDE1 localized to mitochondria and associated with the outer mitochondrial membrane import receptor TOM20 via its N-terminal region in an RNA-independent manner. In cultured sensory neurons, CSDE1 depletion reduced the mitochondrial-fraction abundance of representative nuclear-encoded electron transport chain mRNAs and decreased the abundance of selected mitochondrial proteins in the mitochondrial fraction. CSDE1 depletion reduced TMRM-positive mitochondrial puncta density along sensory neurites, without significantly increasing MitoSOX-detectable mitochondrial superoxide signals under either basal or oxidative challenge conditions. These findings identify CSDE1 as a TOM20-associated RNA-binding protein linked to mitochondrial protein-encoding transcripts in sensory neurons and support a model in which CSDE1 contributes to mitochondria-associated post-transcriptional regulation. Full article