Search Results (751)

Grid-connected photovoltaic–battery energy storage–electric vehicle (PV-BESS-EV) charging stations require supervisory energy management that can coordinate tariff response, carbon-intensity signals, peak constraints, storage utilization, and converter-level operability within a transparent evidential framework. This study develops a bounded-reference rule-based supervisory energy management system (RB-SEMS) that preserves lower-level local converter controllers while generating operating modes and saturated reference commands for BESS power, grid exchange, and EV charging limits. A dual-time-scale evaluation framework is established by combining short-time switching/control simulations for dynamic traceability and SOC-sensitive protection with 24 h, 15 min EMS-level energy-balance simulations for cost, carbon, peak, PV utilization, EV service, and storage throughput assessment. Selected daily reference-injection cases are retained as copied-model diagnostic checks rather than as full-day switching-level validation. Under the D4-LSOC condition, RB-SEMS reduces the reported post-startup DC-bus deviation from 46.13 V to 40.60 V and the filtered BESS peak from 269.18 kW to 84.42 kW. In the E1-TOU scenario, E1-TOU-cost reduces daily total cost from 623.57 CNY to 564.05 CNY, lowers peak-period grid import from 183.75 kWh to 126.75 kWh, and increases local PV utilization from 71.13% to 78.71%; E1-PC66 further reduces the maximum 15 min grid import from 77.88 kW to 66.00 kW. Under the prescribed E2-PCC scenario, E2-CP reduces the calculated grid-related CO₂ emissions from 550.29 kg to 500.42 kg, whereas the price-only diagnostic increases them to 572.29 kg. Same-metric PV-SC and MILP comparisons, tested-range sensitivity analysis, and a throughput-based degradation proxy clarify that RB-SEMS is an interpretable supervisory baseline for cost–carbon–peak–cycling trade-off analysis rather than a cost-optimal controller or regionally validated proof of carbon reduction. Full article

Urban–rural integration (URI) represents a pivotal pathway to realizing sustainable development within urban–rural spatial systems. It is of paramount importance in addressing the challenge of reconciling ecological conservation with high-quality development in the Yellow River Basin. Leveraging panel data from 78 cities in the Yellow River Basin spanning the years 2006–2023, this research constructs an evaluation index system that encompasses five dimensions: population, economy, society, ecology, and space. Through the comprehensive application of kernel density estimation, exploratory spatiotemporal data analysis, and panel quantile regression models, a systematic analysis of the spatiotemporal evolution patterns and transition mechanisms of URI is conducted. The results disclose that URI in the Yellow River Basin demonstrates a trend of “overall enhancement with regional disparities”. From 2006 to 2023, the URI of the basin witnessed an average annual growth rate of 2.86%. Spatially, it presented distinct features: high-level agglomeration in the lower reaches, accelerating-growth path dependency accompanied by internal divergence in the middle reaches, and balanced yet low-level development in the upper reaches. The local spatial evolution of URI follows a pattern characterized as “predominant stability and limited transitions”. In detail, high-level regions sustain their advantages, low-level regions encounter obstacles in achieving breakthroughs, and the spillover effects between adjacent regions remain relatively restricted. The driving mechanisms exhibit significant “phase-spatial” dual heterogeneity, with four distinct patterns identified. In light of these findings, policy recommendations are put forward, including the establishment of a multi-scale, coordinated spatial governance system. Full article

Countermovement jump (CMJ) analysis is widely used to assess lower limb neuromuscular function, but commercial force plates often suffer from high cost, closed algorithms, and lack of bilateral independent measurement. This study developed and evaluated a dual channel strain gauge force plate system featuring open architecture and hardware-triggered video synchronization. The system consists of two physically isolated plates, each with four full bridge strain beams, a precision analog front end, and a 2000 Hz acquisition unit. A microcontroller-based hardware trigger synchronizes force data with video capture. Custom host software implements adaptive jump phase recognition and calculates peak force (PF), concentric impulse, jump height, rate of force development (RFD), and asymmetry index (ASI). Validation included static mass measurements in 14 participants, low-load static calibration (5.0–30.0 kg), free-fall impulse validation (7.00 to 31.32 N·s), 240 fps high-speed video cross validation of flight time, ecological-validity comparison with published AMTI-based force-plate data, and 48 h test–retest reliability assessment. Static mass measurement showed a mean absolute percentage error (MAPE) of 1.01% and a coefficient of determination (R²) of 0.9992, while low-load testing confirmed excellent linearity (R² > 0.996) and minimal absolute error (mean absolute error = 0.34 kg) at lighter weights. Dynamic impulse validation yielded R² > 0.997 and MAPE < 3%. Flight time agreement with high-speed video was within ±10 ms. Test–retest reliability was excellent for concentric impulse (intraclass correlation coefficient (ICC) = 0.997) and jump height (ICC = 0.987), and good for PF (ICC = 0.962) and rate of force development at 100 ms (RFD_100ms) (ICC = 0.883). The physically isolated dual-plate architecture effectively captured bilateral force differences, although the ASI demonstrated moderate reliability (ICC = 0.748), likely reflecting the inherent biological variability in bilateral coordination. The ecological-validity comparison further indicated that the macroscopic kinetic outputs of the proposed system fell within the expected physiological and biomechanical ranges reported for adult CMJ testing. Overall, these findings support the study hypothesis that the proposed dual-channel force plate system provides a valid, reliable, and cost-effective solution for synchronized bilateral CMJ kinetic assessment in sports performance monitoring and biomechanical research, while offering improved accessibility through an open-source and transparent analysis framework with a hardware cost below 500 USD. Full article

This paper designs a statistical channel state information-based pinching antenna system for short-packet communication (SPC). To maximize the average maximal achievable rate (MAR) under physical collision-avoidance constraints, we formulate a highly non-convex geometry optimization problem, which is solved by our proposed novel phase-domain proximal policy optimization (PPO) framework. Unlike conventional coordinate-based approaches, the agent operates in a dual-component trigonometric phase domain, and the generated phase actions are mapped to feasible antenna positions via a customized phase-domain action mapping, which fundamentally avoids the $0/2\pi$ phase discontinuity and ensures stable learning. To evaluate the reliability of SPC, we derive a tractable statistical characterization of the received signal-to-noise ratio based on a mixture Gamma approximation over spatially correlated Rician fading channels, leading to a closed-form approximation for the average block error rate (BLER). A bisection search algorithm is further developed to minimize the required blocklength under the target reliability constraint. Simulation results demonstrate that the proposed phase-domain PPO scheme significantly outperforms the conventional algorithms in terms of average MAR, average BLER, and blocklength efficiency, with the performance gain becoming more pronounced as the number of antennas per waveguide increases. Full article

Multi-terminal voltage-source-converter-based HVDC (VSC-MTDC) systems are increasingly used to integrate renewable energy and interconnect asynchronous AC grids, but conventional fixed-coefficient droop control cannot simultaneously limit DC-voltage deviations, reduce operating losses, and preserve converter power margins during operating-point switching. This paper hypothesizes that a rule-based fuzzy adjustment of the droop slope can provide smooth multi-objective coordination without inter-station communication. A dual Mamdani fuzzy controller is developed: one controller adjusts the weighting between loss-oriented and power-margin-oriented droop coefficients according to converter power margin, while the other introduces a voltage-deviation correction according to DC-bus voltage. The controller is implemented and verified in a five-terminal MMC-based VSC-MTDC model built in PSCAD/EMTDC, where simulation data are generated under heavy-load, light-load, and power-reference switching scenarios using specified line and converter parameters. Compared with conventional droop control, the proposed strategy improves power-margin utilization, reduces operating-point discontinuities, and raises the minimum DC voltage from 370.2 kV to 381.4 kV in the severe switching case. The results confirm that fuzzy-slope droop control can achieve smoother operating-point switching and better coordinated optimization among voltage stability, operating loss, and converter reserve margin. Full article

In this work, we report an example of tuning the photophysical properties of a polypyridine ruthenium(II) complex via the coordination of a second cation. A new ruthenium(II) complex contains a thiacrown-ether fragment that allows selective binding of additional metal cations (Ba²⁺, Cd²⁺, Pb²⁺), leading to pronounced changes in the optical and electronic properties of the bimetallic system. Spectroscopic and electrochemical studies reveal that the monoruthenium precursor displays dual excitation pathways involving either intraligand charge transfer (ILCT) or triplet metal-to-ligand charge transfer (³MLCT) excited states. Upon coordination of a second metal ion, the ILCT channel is suppressed, and only the ³MLCT state remains emissive, resulting in a significant increase in phosphorescence quantum yields (up to 22.6% in degassed solutions) for the bimetallic derivative. Time-resolved emission studies confirm the conversion from biexponential to monoexponential luminescence decay upon complexation. Electrochemical analysis and density functional theory (DFT) calculations support the hypothesis that cation binding alters the electron density distribution within the chromophore, stabilizing the MLCT pathway. These results demonstrate that incorporation of a second cation provides an effective strategy to control excited-state dynamics in ruthenium complexes, offering opportunities for the rational design of photosensitizers and photofunctional materials. Full article

To measure the cross-view spacing between adjacent fastener bolts in railway turnouts, this study develops a dual-DLP-sensor structured-light measurement system without overlapping fields of view. A bridge-type calibration device is used to rapidly update the extrinsic parameters of the two DLP sensors. In a unified coordinate frame, the system integrates two-dimensional region-of-interest candidate generation, local three-dimensional geometric fitting, cross-view pairing, and measurement validity assessment to output bolt-spacing results. Experiments were conducted on 23 pairs of adjacent bolts with 15 repeated measurements using two DLP sensors. Under normal conditions, the mean absolute error, root mean square error, and average standard deviation were 0.261 mm, 0.290 mm, and 0.062 mm, respectively. Compared with fixed extrinsic parameters without updating, the bridge-based extrinsic update reduced the mean absolute error from 1.500 mm to 0.261 mm. The results indicate that the proposed task-driven dual-DLP-sensor measurement system can achieve stable cross-view spacing measurement with explicit validity criteria under non-overlapping fields of view, repeated deployment, and varying on-site data quality. Full article

In embodied-intelligence Industrial Internet of Things (IIoT), multi-AGV intelligent warehousing requires continuous processing of latency-sensitive tasks, such as environmental perception, inventory monitoring, and anomaly detection. Due to limited onboard computing capability and energy capacity, purely local execution can hardly satisfy real-time requirements, whereas fully cloud-based processing may incur excessive transmission delay and backhaul overhead. To address this issue, this paper investigates the joint optimization of AGV service-point migration and task offloading under a cloud-edge-end collaborative architecture. Considering the impact of service-point selection on wireless access, MEC resources, movement delay, and energy consumption, as well as the effect of offloading decisions on transmission, computation, and AGV-side energy cost, a dual-time-scale optimization model is formulated to minimize the long-term accumulated system delay while satisfying task latency and AGV energy constraints. To solve the resulting mixed discrete problem, a DPSO-MAPPO algorithm is proposed, where DPSO searches service-point plans satisfying movement and conflict constraints at the slow time scale, and MAPPO learns coordinated multi-AGV offloading policies at the fast time scale. The delay and energy feedback further enables coordination between the two types of decisions. Simulation results show that the proposed algorithm converges stably, reduces system delay by 13.55% compared with benchmark algorithms, and improves total energy consumption and energy-violation control. Full article

The large-scale integration of distributed photovoltaics (DPVs) into the distribution network exacerbates voltage fluctuations and substantially increases network losses. To improve the voltage quality and economic efficiency of distribution networks, a Volt/Var optimization (VVO) model is established. Coordinating multiple heterogeneous devices, the model aims to minimize the total voltage deviation, the total network losses, and the regulation cost of discrete equipment simultaneously. Considering multi-constraint coupling characteristics, a quantitative method is proposed to evaluate the reactive power regulation potential of DPVs under intricate operating conditions. Then, the multi-strategy integrated rime optimization algorithm (MSIRIME) is utilized for the model solution. Fuch chaotic mapping generates uniformly distributed and ergodic initial populations. A dual-branch search mechanism combining the snow ablation optimizer with the rime optimization significantly enhances global exploration capabilities. The guided learning strategy balances exploration and exploitation for high-dimensional VVO, preventing local optima. Case tests on a modified IEEE 33-bus system demonstrate that the proposed model exhibits excellent effectiveness and robustness. Moreover, MSIRIME exhibits better optimization performance than some classic and recently proposed strategies, reducing the average network losses and voltage deviation over 30 independent runs by at least 5.87% and 52.22%, respectively, relative to those of the compared methods. Full article

Plants must continuously balance the trade-offs between growth and defense, a constraint that is exacerbated by biotic and abiotic stresses, particularly when they occur together. Ethylene (ET) serves as a central, integrative regulatory node controlling this by linking developmental programs to stress-responsive signaling networks. Advances at the molecular and systems levels have revealed that ET mediates the redistribution of metabolic resources via coordinated regulation of its synthesis, perception, and downstream signaling. The ETR (Ethylene Receptor)-CTR1 (Constitutive Triple Response 1)-EIN2 (Ethylene Insensitive 2)-EIN3(Ethylene Insensitive 3) signaling module lies at the core of this network, integrating multiple hormonal pathways. Through dynamic crosstalk with jasmonic acid (JA), salicylic acid (SA), abscisic acid (ABA), auxin (AUX), and gibberellins (GA), ET enables the fine-tuned coordination of growth inhibition, immune activation, and stress acclimation in response to environmental fluctuations. Processes such as induced systemic resistance, programmed cell death, and architectural plasticity further reinforce this regulatory framework, with ethylene-responsive transcription factors, including ERFs (ethylene responsive factor gene family) and WRKYs, acting as critical convergence points. Emerging insights into ACC (1-aminocyclopropane-1-carboxylic acid)-dependent signaling, chromatin remodeling, and tissue-specific regulation expand the functional scope of ET beyond traditional hormone paradigms. At the same time, the ability of pathogens to manipulate ET signaling underscores its dual role in both promoting immunity and facilitating susceptibility. By integrating molecular, physiological, and ecological perspectives, this review highlights ET as a central coordinator of plant stress resilience and growth optimization, providing a unifying framework for understanding how plants adapt to complex and dynamic environments. Full article

Identifying superior salt-tolerant germplasm and resistance genes is crucial, as wheat (Triticum aestivum L.) seedlings are highly vulnerable to salt stress. Here, using an optimized 150 mM NaCl treatment, we screened 137 Chinese wheat accessions via an organ-specific method. Phenotyping analysis revealed extensive organ-specific divergence, with 48.91% of accessions displaying inconsistent performance between shoot and root length. We then performed comparative transcriptomics on three representative phenotypes at the seedling stage: Gaoyou 2018, representing the salt dual-sensitive group; Huapei 5, representing the salt dual-tolerant group; and Jimai 60, representing the divergent group with higher tolerance in shoots rather than in roots. Analysis of overlapping differentially expressed genes (DEGs) across all three accessions revealed a basal stress response—characterized by induced osmotic defense and suppressed primary growth—exemplifying a classical growth–defense trade-off. Genotype-specific DEG profiling demonstrated that the divergent Jimai 60 maintains its shoot advantage by reinforcing physical barriers and inhibiting apoptosis. Conversely, transcriptomic profiling implies that the systemically tolerant Huapei 5 maintains coordinated shoot and root tolerance at the seedling stage by strongly activating below-ground Na⁺ homeostasis (efflux and compartmentalization) while simultaneously down-regulating non-essential immune responses to optimize defense energy reallocation. Collectively, our findings provide novel insights into the organ-differentiated salt tolerance of wheat, offering well-characterized elite germplasm and compelling genetic targets for future molecular breeding. Full article

The association between digital economy (DE) and manufacturing transformation (MT) is conditioned by regional structural characteristics, yet little is known about how this association varies within provinces that are peripheral at the national scale. This study examines Yunnan Province, China, as a dual-peripheral context, where regions are simultaneously distant from national economic cores and internally structured along a pronounced core–intermediate–periphery gradient. Using prefecture-level panel data from 16 cities over 2011–2023, the analysis shows that the positive association between DE and MT is spatially attenuated along this gradient. Furthermore, three key regional factors—transportation infrastructure, industrial agglomeration, and technological talent—correspond to distinct spatial conditioning patterns. Transportation infrastructure exhibits an extensible but spatially bounded pattern, industrial agglomeration is most strongly associated with intermediate prefectures, and technological talent displays a highly concentrated pattern within the provincial core. These differentiated patterns indicate that internally differentiated peripheral structures are associated with different forms of spatial conditioning in the observed DE–MT association, rather than producing a uniform spatial pattern. Based on these findings, region-specific strategies targeting connectivity, industrial coordination, and talent development are recommended to support inclusive and context-sensitive manufacturing transformation. The study provides an analytically transferable perspective by highlighting how different regional conditions may correspond to different spatial reaches of digital–manufacturing transformation within peripheral systems. Full article

Against the backdrop of the dual-carbon goals and the Digital China initiative, the urgent need for enterprises to pursue green innovation and transformation is evident. Supply chain digitalization serves as a critical enabler for enterprises to achieve a low-carbon industrial transformation and high-quality development through the effective coordination of data resources across the entire chain. This study examines A-share listed companies from 2012 to 2023, leveraging the 2018 Supply Chain Innovation and Application Pilot Policy to construct a quasi-natural experiment. Employing a difference-in-differences approach with multiple mediation effects, it investigates the impact of supply chain digitalization on corporate green innovation and its transmission mechanisms. Findings reveal that supply chain digitalization significantly enhances corporate green innovation levels, with this effect being more pronounced in substantive innovation, western regions, and firms with high customer concentration. Mechanism tests reveal that supply chain digitalization promotes green innovation not only through independent pathways of enhancing information transparency and improving ESG performance but also via a chained mediation effect: “supply chain digitalization → information transparency → ESG performance → green innovation”. This study enriches theoretical research on the relationship between supply chain digitalization and green innovation from the dual perspectives of information and governance, offering insights for government initiatives to advance data sharing, implement differentiated policies, and establish green governance systems. Full article

Multi-manipulator cooperative systems are widely deployed in industrial assembly, intelligent manufacturing and other fields, but collision safety and efficient motion coordination during coordinated operation remain key challenges. In this paper, a novel cooperative control strategy based on relative velocity information is derived to guarantee collision-free maneuvers for multiple m-degree-of-freedom (m-DOF) manipulator systems with general Lagrangian dynamics. One key advantage is that it ensures reliable safety while achieving smoother avoidance maneuvers, reduced interference with objective tasks, lower energy consumption, and improved task efficiency; notably, the avoidance control depends not only on the relative distance between manipulators but also on their relative motion, making it less conservative as manipulators avoid unnecessary spreading during collision avoidance. Another is that it integrates collision avoidance, disturbance attenuation, and deadlock elimination into a unified closed-form control law, which yields a closed-form solution and is easy to implement in engineering practice. Theoretically, this paper adopts the generalized Lyapunov stability theory to rigorously prove the asymptotic convergence and persistent collision-free property. Finally, simulation results on a dual two-DOF manipulator system further verify the effectiveness and reliability of the proposed control strategy. Full article

Spanish–English bilingual learners in U.S. dual language and bilingual education programs develop Spanish orthographic competence while receiving literacy instruction across two writing systems that differ in phonological transparency, orthographic depth, and grammatical marking. This study examined experts’ perceptions of the clarity, instructional coherence, pedagogical relevance, applicability, and refinement priorities of a pedagogical framework for Spanish orthographic development in contexts where Spanish is used as a language of instruction and literacy. The framework conceptualizes Spanish orthographic decision-making as the coordinated activation of phonological mapping, orthographic–grammatical reasoning, and visual–lexical retrieval within biliteracy development. Using a qualitative evaluative design, the study analyzed open-ended questionnaire and interview data from 44 experts in bilingual education and Spanish literacy-related fields. Findings show broad convergence regarding the framework’s clarity, instructional coherence, and relevance for bilingual contexts. Participants emphasized pre-dictation preparation, explicit metalinguistic analysis, visual-memory activation and retrieval routines, and cross-linguistic comparison between Spanish and English. They also identified refinement priorities, including classroom-ready examples, clearer articulation of error and autocorrection, and stronger integration with reading, writing, and oracy practices. This study positions Spanish orthographic instruction as a cognitively guided biliteracy practice and identifies design principles for strengthening orthographic, metalinguistic, and cross-linguistic instruction in bilingual programs. Full article