Search Results (504)

To address the challenges of relying on experience for vehicle allocation in concrete transportation for dam construction—as well as the difficulty in coordinating vehicle capacity, loading/unloading capabilities, and system queuing status—this study focuses on a closed-loop transportation system comprising “batching plant—transport route—pouring area” and develops a vehicle allocation model based on a BCMP (Baskett–Chandy–Muntz–Palacios) closed-loop queuing network. The loading process at the mixing plant and the unloading process at the silo yard are modeled as finite-service nodes, while the transportation of loaded vehicles and the return of empty vehicles are modeled as infinite-service nodes. The Buzen convolution algorithm is used to solve for the system’s steady-state performance. With the number of vehicles N and the silo yard diversion ratio p as joint decision variables, the feasible region for vehicle configuration and recommended solutions are determined subject to constraints on silo yard feed demand and node utilization. The results of the case study show that, using reference operating condition S0 as a benchmark, a decrease in the loading efficiency of the batching plant increased the recommended number of vehicles by 28.57%; a simultaneous increase in the unloading efficiency of the dual-bin system reduced the recommended number of vehicles by 42.86%; enhanced coordination between the loading and unloading systems reduced the recommended number of vehicles by 50.00% and decreased the expected queuing time per cycle by 97.26%; furthermore, the system bottleneck shifted as loading and unloading capacities changed. Further independent validation was conducted using discrete-event simulation (DES); the maximum relative error between BCMP and DES in terms of system throughput, expected queuing wait time per cycle, and maximum node utilization was less than 1.5%. Sensitivity analysis indicates that concrete pouring demand and unloading capacity at the bin area are key factors affecting vehicle allocation. When demand increases or unloading capacity decreases beyond the system’s capacity limits, simply adding more vehicles does not result in a feasible solution. The study demonstrates that the proposed method can quantitatively reveal the relationships among vehicle fleet size, traffic diversion at the bin area, loading and unloading capacity, and queueing conditions, thereby providing a decision-making basis for the coordinated allocation of vehicles and loading/unloading resources in concrete construction for dams. Full article

Continuous operation is increasingly expected of Internet of Things (IoT) and wireless sensor network (WSN) nodes, yet practical solar front ends must account for source variability, intermediate storage, conversion losses, sensing overhead, and battery-management constraints. This article develops and evaluates a discrete, two-stage photovoltaic front end for such nodes: a perturb-and-observe (P&O) buck stage tracks the maximum power point of a 20 W Solarland SLP020-12U module (rated 17.2 V, 1.16 A) and feeds an intermediate storage bus, while a PI-compensated SEPIC stage regulates the IoT rail to 3.2 V independently of that bus voltage. Closed-loop MATLAB/Simulink simulations are reported at 1000, 800, and 600 W/m². The reported conversion figures originate from an idealized switching model and should therefore be interpreted as simulation-only values rather than measured prototype efficiency. A low-cost Arduino-based prototype confirms correct switching behavior and a 20.0048 kHz PWM signal, but the available captures lack synchronized, calibrated input/output power logging; consequently, no hardware efficiency, MPPT tracking efficiency, regulation error, ripple, or settling-time figure is claimed. The revised manuscript makes this simulation-to-hardware boundary explicit, adds the power cost of sensing and data conversion to the loss discussion, strengthens the battery-management and deployment caveats, and defines the measurements required for full quantitative validation. Full article

Metal-bearing tailings, slimes, metallurgical residues, spent catalysts, ashes, sludges, batteries, and electronic wastes are increasingly important secondary resources, but recovery is constrained by low and variable grades, fine particles, complex phase associations, passivation, and impurity-sensitive downstream processing. Hydrodynamic cavitation (HC) can modify selected flowsheet functions through interfacial renewal, localized mechanical action, gas–liquid transfer, fine-bubble generation, particle conditioning, and phase dispersion. The evidence was critically appraised across three independent dimensions: system relevance, causal attribution, and endpoint completeness. Application-level evidence is most developed for transport intensification in selected scheelite, uranium-bearing, and refractory-gold systems; particle conditioning and washing; spent-catalyst coating liberation; metal-bearing sludge treatment; copper cementation; and preparation of liquid emulsion membranes. Representative secondary-feed studies report conditioning, preconcentration, mobilization, and downstream separation responses, but complete feed-to-product recovery with controlled liquid and solid loops remains uncommon. Evidence is especially limited for battery black mass, electronic wastes, rare-earth-bearing residues, complex slags, metallurgical dusts, and multi-metal streams. HC is therefore most credible as a targeted module applied to a verified process limitation. A flowsheet advantage is established only when local gains persist through product recovery without offsetting increases in chemical use, water demand, energy consumption, equipment wear, or residual-stream burden. Full article

In molten salt reactors, multiphase transport of fission products produces nonuniform nuclide inventories throughout the primary loop, thereby affecting subsequent decay heat evolution. Although fission product transport has been widely studied, its influence on post-shutdown wall-deposited decay heat remains insufficiently characterized. Here, the bubble transport capability of the Thorium Fission Products Migration Code (ThorFPMC) was extended using a drift-flux model to investigate the effects of operating void fraction on the magnitude, spatial distribution, nuclide composition, and subsequent evolution of wall-deposited decay heat under an idealized post-drainage condition. Results showed that, for the baseline bubble diameter of 0.508 mm, the initial wall-deposited decay heat decreased from 41.33 to 6.63 kW as the operating void fraction increased, corresponding to an 84.0% reduction; bubble diameter sensitivity calculations preserved the same monotonic trend. The source remained strongly nonuniform, with the heat exchanger consistently dominant, while increasing the void fraction reduced the core fraction and increased the relative external-loop contribution. Nuclide contributions evolved from a broad early distribution to long-term dominance by ⁹⁵Nb and ¹⁰³Ru, with precursor feeding shaping several important daughter nuclides. These results link operating period multiphase transport to component-resolved residual decay heat sources and provide a basis for operating-condition-dependent source terms in shutdown thermal and system analyses. Full article

Cucurbitacins are highly oxygenated tetracyclic triterpenoids characterized by intense bitterness, substantial structural diversity, and important consequences for plant–herbivore interactions. Although best known from Cucurbitaceae, cucurbitacins and related cucurbitane-type metabolites also occur in phylogenetically distant herbaceous and woody plants. Genetic and biochemical studies have validated several core biosynthetic steps, including cucurbitadienol formation by oxidosqualene cyclases and subsequent modification by cytochrome P450 monooxygenases, acyltransferases, and glycosyltransferases. Tissue-preferential basic helix–loop–helix transcription factors constitute the best-characterized regulatory layer, whereas the evidence supporting accessory regulators, transporters, and environmental responses varies from functional validation to transcriptomic or genomic prediction. From the plant perspective, cucurbitacins deter feeding or impair performance in many generalist and non-adapted herbivores. By contrast, their use as host-recognition cues and feeding stimulants by specialist diabroticite beetles reflects evolved herbivore adaptations involving perception, tolerance, metabolism, or sequestration rather than a second defensive function of the plant trait. Herbivore-induced cucurbitacin accumulation has been demonstrated in particular systems, although its regulatory mechanisms and ecological generality remain unresolved. Unlike previous reviews centered primarily on cucurbitacin chemistry, pharmacological activity, or individual biosynthetic pathways, this review integrates evidence-graded pathway reconstruction and molecular regulation with taxonomic distribution, insect adaptation, domestication, and agroecological consequences. Mechanistically, this review traces how scaffold formation, oxidative tailoring, conjugation, tissue-specific regulation, and transport give rise to contrasting ecological outcomes through herbivore-specific perception, tolerance, metabolism, and sequestration. We conclude that uniformly increasing or eliminating cucurbitacins is unlikely to provide broadly effective crop resistance because either direction may favor a different herbivore group. Future priorities include functional validation of candidate genes, spatially resolved metabolite analysis, comparative investigation of non-cucurbit lineages, and field evaluation involving generalist and specialist herbivores, crop quality, and non-target organisms. These advances will support context-specific fruit-quality improvement, behavioral pest control, and integrated pest management strategies rather than cucurbitacin manipulation as a stand-alone resistance approach. Full article

Citric acid-based leaching is gaining attention as an environmentally friendly alternative to conventional sulfuric acid-based processes for recycling spent lithium-ion batteries (LIBs), but it generates sodium citrate (Na₃Cit)-rich wastewater that is difficult to treat using conventional technologies. Bipolar membrane (BM) electrodialysis (BMED), particularly a two-compartment BM/cation-exchange membrane (CEM) configuration, offers a simple and energy-efficient solution for simultaneously recovering acids and bases from such wastewater without external reagents, enabling a closed-loop resource-circulation approach that remains largely unexplored for this specific waste stream. This system was applied to treat Na₃Cit wastewater generated from citric acid-based spent LIB leaching, and the recovery feasibility and process performance of citric acid and NaOH were evaluated. The effects of feed concentration, current density, initial base concentration, and initial base volume on NaOH recovery, current efficiency, and energy consumption were investigated. Under the optimal conditions (1.00 M Na₃Cit, 300 A/m², 0.1 M NaOH, 1.25 L), a NaOH recovery of 93.93%, current efficiency of 92.55%, and energy consumption of 0.65 kWh/kg were achieved. This study demonstrates that Na₃Cit wastewater can be treated via BMED without external reagents, yielding high-purity NaOH, whereas the recovered acid stream contains residual unreacted Na₃Cit, and its direct reuse in the leaching process requires further verification. These findings provide a fundamental basis for developing BMED-based resource-circular processes. Full article

Colorectal cancer, especially the microsatellite-stable subtype, which accounts for 85% to 95% of cases, resists immune checkpoint inhibitors largely due to metabolic reprogramming in the tumor microenvironment. Lactate has evolved from a waste product into a central immunosuppressive regulator. Oncogenic KRAS and BRAF mutations drive aerobic glycolysis, causing glucose deprivation and massive lactate accumulation in the tumor microenvironment. Lactate suppresses immunity through three parallel mechanisms. It signals via GPR81 to recruit polymorphonuclear myeloid-derived suppressor cells (PMN-MDSCs) and inhibit T-cell function. It contributes to histone H3K18 lactylation, which silences effector genes including IFN-γ and GZMB while upregulating PD-L1 expression. It also acidifies the microenvironment to pH 6.0–6.5, directly impairing NK and T-cell activity. Concurrent lipid abundance stabilizes the MCT4 lactate exporter, forming a bidirectional feed-forward loop that amplifies lactate effects. Spatial metabolic heterogeneity creates distinct immune battlefields, with a supportive ‘metabolic oasis’—a concept proposed in this review—at the invasive front and a deeply immunosuppressive core. Thus, lactate acts as an epigenetic and signaling hub that bridges oncogenic mutations, metabolic competition and immune evasion. Targeting lactate metabolism through LDHA or MCT4 inhibition, modulation of histone lactylation, or disruption of lactate-lipid crosstalk, when combined with classical immune checkpoint blockade and guided by spatial biomarkers, offers a promising strategy to overcome immunotherapy resistance in this challenging subtype. Full article

Cooperative adaptive cruise control (CACC) platoons rely on Vehicle-to-Vehicle communication and GPS to maintain sub-second headways, creating cyberattack surfaces underrepresented in standard surrogate-safety metrics. We built a fully equation-based, Routh–Hurwitz- and Lp-string-stability-verified simulation of a ten-follower (eleven-vehicle, including the leader) CACC platoon (point-mass dynamics, actuator lag, PD spacing control) and subjected it to a two-channel GPS-spoofing attack corrupting both the attacked vehicle’s control loop and its broadcast position; velocity and acceleration broadcasts, and the CACC feed-forward term they drive, are left uncorrupted, so the reported boundaries are conditional on this restricted, single-channel threat model and should be read as a lower bound on attack severity rather than a worst case. Across a 64-cell severity–duration grid (2–20 m, 1–10 s; h = 0.6 s), minimum time-to-collision fell from 31.7 s to a simulated collision in 6/64 cells (9.4%), driven more by magnitude than duration; the disturbance decays sharply after the first hop rather than cascading down the platoon, so the resulting risk is local, not cascading. A 48-cell headway grid showed h ≥ 0.7 s eliminated all collisions at the originally tested attack duration (3/8 → 0/8 at fixed severity), a result that held under two alternative controller-gain sets tested for sensitivity and was largely, though not universally, robust to a substantially stiffer third set. A position sweep found risk invariant across nine of ten platoon positions. Batch-computed first-hop propagation and tail-to-origin amplification ratios showed the disturbance transiently amplifies (ratio > 1) at its first hop in a third of tested attacks despite decaying three orders of magnitude by the platoon’s tail, a behavior distinct from the front-injected Lp string stability verified separately. Peak root-mean-squared jerk stayed within the comfortable range (≤1 m/s³) in every tested cell, including collisions, showing collision and comfort risk are governed by different parameters. Embedding a representative detection and elastic-control layer alongside headway optimization eliminated collisions within the tested range and remained robust at three times that severity, where headway alone failed; because the detector’s residual is computed directly from the true offset magnitude and detector failure is not modeled, this joint-defense result is illustrative rather than a validated-detector-calibrated estimate. These results give a reproducible, quantified basis for headway- and detection-based mitigation policy in connected-vehicle platoons. Full article

The sustainable development of the ceramics industry is severely impeded by its intensive energy consumption and the concomitant deficits in cooling and freshwater resources. To address these bottlenecks, this study proposes an integrated ejector refrigeration (ER)–humidification–dehumidification (HDH) hybrid system, harnessing ceramic waste heat as the driving energy source to improve overall energy efficiency. A thermodynamic model was developed to analyze the heat transfer characteristics of the ER-HDH system. Comprehensive investigation focuses on the influences of key operating parameters on refrigeration performance, desalination output and overall system efficiency. The results demonstrate that the proposed ER–HDH hybrid system facilitates the efficient thermodynamic cascading of waste heat from both flue gas and internal thermodynamic processes, achieving a high energy utilization factor (EUF) of 0.64 and an exergy efficiency η_Ex of 15.7%. The freshwater yield significantly outperforms that of a standalone HDH system, with the gain output ratio (GOR) more than tripling. The system performance is optimized under elevated generator and evaporator temperatures (T_g and T_e), coupled with a reduced condenser temperature T_c. Across their respective tested ranges, the EUF increases by averages of 19.1%, 45.1% and 38.9%. Furthermore, raising the feed seawater temperature T_{sw_in} significantly elevates the moist air humidity ratio, which in turn drives substantial enhancements in GOR and EUF, by over 83.2% and 58.1%, respectively. T_e and T_{sw_in} should be prioritized to enhance refrigeration and freshwater productions, respectively, while T_c serves as the key determinant for maximizing η_Ex. This study introduces an open dual-cascade ER-HDH system for mid/low-grade flue gas utilization and elucidates the distinct thermodynamic mechanisms governing subsystem interactions, and it addresses a critical knowledge gap in prevalent closed-loop solar-driven ER-HDH systems. Full article

Stockpiles and run-of-mine (ROM) pads are critical control points between mine production and processing plant feed. The grade, quality mix, and variability of material delivered to the crusher and mill are largely determined by how these structures are designed, built, and reclaimed. Despite the operational significance of stockpile management, the field remains fragmented across five distinct research streams—physical blending theory, stockpile state modelling, reclaim sequencing and equipment scheduling, plant-feed and stockpile blending optimization, and sensor-driven reconciliation and closed-loop control—with limited integration between them. This paper presents a systematic review of 27 sources published between 1976 and 2025, including peer-reviewed journal articles, conference papers, a preprint, a book, and one industry publication. The literature search was conducted in May 2025 using Scopus, Web of Science, and Google Scholar, with records screened by title/abstract and full text for direct relevance to stockpile reclamation or grade blending in mining operations. A structured coverage matrix identifies that studies combining high spatial fidelity with strong optimization rigor are consistently absent from the literature, and that uncertainty handling and sensor-driven or real-time capability remain substantially underdeveloped. Six research gaps are identified and prioritized by practical significance, implementation readiness, and literature maturity. The four most operationally critical gaps concern: spatially explicit reclaim scheduling under live ROM-pad constraints; tractable multi-attribute blending formulations for polymetallic operations; uncertainty propagation to plant-feed predictions; and field-scale closed-loop validation. The review provides a structured development roadmap for ROM-pad optimization frameworks and identifies the specific integration challenges that must be addressed to move the field from static stockpile monitoring toward adaptive, sensor-updated decision support. Full article

Rare earth elements (REEs) are critical for advanced manufacturing and clean energy, yet their separation remains extremely challenging due to the nearly identical ionic radii of adjacent lanthanides. Conventional solvent extraction, ion exchange, and precipitation methods are limited by their high reagent consumption, slow kinetics, poor selectivity, and environmental burdens. Nanofiltration (NF) offers a green and efficient alternative—operating in the aqueous phase with low energy demand and continuous high throughput. This review systematically summarizes NF-based REE separation. We first elucidate the fundamental mechanisms (size exclusion, Donnan exclusion, dielectric exclusion, and complexation enhancement), and discuss how lanthanide hydration chemistry underpins these synergistic effects. Membrane materials, from commercial to biomimetic, are critically surveyed, with an emphasis on strategies to overcome the trade-off between permeability and selectivity. The impacts of operating conditions and solution chemistry are analyzed, and NF applications ranging from single REE systems to real leachates are assessed. A comparative evaluation positions NF against conventional technologies. Key challenges remain: poor adjacent REE selectivity, membrane fouling, performance loss at high salinity, chemical instability, and a gap between model and real feeds. Future directions include designing high-selectivity membranes, integrating machine learning optimization, establishing standardized protocols, and realizing closed-loop process integration. Full article

The model predictive current control (MPCC) of an interior permanent magnet synchronous machine (IPMSM) requires an accurate motor parameter model to predict future currents and achieve high control performance. However, the inductance parameters of an IPMSM are easily affected by factors such as magnetic field saturation, leading to large current prediction errors, high current ripple, and poor stability. Therefore, an MPCC strategy for an IPMSM based on parameter adaptive feedback correction is proposed. First, based on the mathematical model of the IPMSM in the synchronous rotary coordinate, the cross-coupling relationship between the dq-axis inductance deviations and the current prediction error is derived to form an explicit prediction error model. Then, the influence of the d-axis and q-axis inductance parameter deviations of the IPMSM on the current prediction error is discussed in detail. Next, based on the established mathematical model of the prediction error, the recursive least squares scheme is adopted to identify the d-axis and q-axis deviations of the inductance parameters online. Finally, unlike conventional open-loop RLS correction, a PI-based closed-loop correction loop is designed that feeds the prediction error back to adjust the inductance deviations, thereby forcing the prediction error toward zero while inherently compensating for inverter dead-time effects. Simulations and experiments were conducted, and the results show that the proposed scheme greatly improves the accuracy of current prediction and inductance parameter estimation, and enhances robustness against parameter mismatch and dead-time disturbances. The key novelty lies in the PI-feedback-driven RLS closed-loop structure that simultaneously achieves error elimination and dead-time compensation. Full article

Enteric methane measurement from ruminant livestock faces fundamental trade-offs between accuracy and operational feasibility. Existing methods quantify methane after eructation and atmospheric dilution, limiting temporal resolution and confounding biological signals with environmental variables. We present the Smart Cannula-mounted Optical Unit for Trace methane (SCOUT), an autonomous system for continuous in vivo monitoring of ruminal headspace methane concentrations. SCOUT uses a closed-loop gas recirculation circuit that samples the headspace continuously without venting gas to the atmosphere and mounts onto a standard cannula plug without degrading its seal integrity. SCOUT was deployed on cannulated Simmental heifers under contrasting dietary treatments. Headspace concentrations were two to three orders of magnitude above concurrent ambient sniffer readings, providing substantially greater signal resolution for characterizing methane dynamics. High-frequency monitoring revealed concentration changes associated with postural transitions and feeding on timescales inaccessible to ambient methods. Cross-platform comparison with ambient sniffers showed that eructation events produced the expected inverse concentration signature, supporting the validity of the in vivo concentration signal. These results demonstrate that the rumen headspace contains continuous, biologically interpretable methane signals that SCOUT can reliably access, establishing the measurement infrastructure necessary for developing concentration-to-flux models that would support precision phenotyping, emission proxy calibration, and mitigation strategy evaluation. Full article

A standard verification-based knowledge graph question answering (KGQA) pipeline retains a reasoning path only when retrieved evidence supports it. Requiring evidence makes large language model (LLM) output easier to audit and reduces unsupported answers. The verifier’s two outcomes are not equally informative: acceptance provides strong evidence, whereas rejection on an incomplete graph may indicate either an incorrect path or a missing proof. A one-pass pipeline discards both cases and loses the information contained in the failure. We introduce GRACE (Graph Reasoning with Adaptive Controller and Evidence), which feeds rejection back into retrieval and restores accept–reject symmetry in the search. GRACE assigns a failure type to each rejected path. Its reflective feedback loop (RFL) revises subsequent retrieval, whereas hypothetical bridging (HB) admits budgeted and penalized virtual edges for plausible missing links. A virtual edge remains marked as a hypothesis rather than a verified triple; the bridge budget bounds answer-level hallucination exposure, and the marking makes that exposure observable. With a fixed open-source LLM backbone, GRACE improves KG-grounded reasoning on WebQSP and ComplexWebQuestions. Diagnostic results indicate that RFL and HB recover different types of failure. Full article

This paper presents a hardware–software co-design framework for real-time super-resolution (SR) of low-quality video on resource-constrained edge platforms. At its core is a compact residual network obtained by once-for-all (OFA) neural architecture search over the Residual Channel Attention Network (RCAN) design space, trained conventionally and then optimized with quantization-aware training (QAT) for deployment on an integer-only deep-learning processing unit (DPU). Loop tiling and data-flow scheduling are applied within a custom high-level synthesis (HLS) pre-processing pipeline that feeds the DPU, and a per-directive ablation isolates the contribution of each optimization to post-route resource usage and timing. Deployed on a Kria KV260 board with a $128\times 128$ network input, the INT8 network sustains $96.37$ FPS at the ×2 scale at a measured board power of $5.38$ W, corresponding to $6.32$ Mpixel/s of reconstructed output at $1.17$ Mpixel/J, within 63.2% of the device LUT budget and with timing closed at 275 MHz. Relative to the FP32 model, INT8 quantization costs $0.274$ dB of peak signal-to-noise ratio (PSNR) on Set5, $0.172$ dB on Set14, $0.116$ dB on B100, and $0.146$ dB on Urban100, a loss dominated (81–90%) by activation rather than weight quantization. On a held-out UAV subset drawn from VisDrone2019, which is the operating domain the system targets, the network reconstructs at $25.94$ dB and $0.748$ SSIM. These results show that a twenty-three-layer residual SR network can be deployed within a 5.38 W envelope on a low-cost integer-only edge FPGA, making the approach suitable for autonomous systems, robotics, and airborne surveillance. Full article