The continuous extension of human life expectancy and the global trend of population aging have contributed to a marked increase in the incidence of musculoskeletal diseases,with fractures and osteoporosis being promi...The continuous extension of human life expectancy and the global trend of population aging have contributed to a marked increase in the incidence of musculoskeletal diseases,with fractures and osteoporosis being prominent examples.Consequently,promoting bone regeneration is a crucial medical challenge that demands immediate attention.As early as the mid-20th century,researchers revealed that electrical stimulation could effectively promote the healing and regeneration of bone tissue.This is achieved by mimicking the endogenous electric field within bone tissue,which influences cellular behavior and molecular mechanisms.In recent years,electroactive hydrogels responsive to electric field stimulation have been developed and applied to regulate cell functions at different stages of bone regeneration.This paper elaborates on the regulatory effects of electrical stimulation on MSCs,macrophages,and vascular endothelial cells during the process of bone regeneration.It also involves the activation of relevant ion channels and signaling pathways.Subsequently,it comprehensively reviews various electric-field-responsive hydrogels developed in recent years,covering aspects such as material selection,preparation methods,characteristics,and their applications in bone regeneration.Ultimately,it provides an objective summary of the existing deficiencies in hydrogel materials and research,and looks ahead to future development directions.展开更多
China ranked first worldwide in the production and export of electric bicycles.As an emerging market for electric bicycles,Malaysia holds significant potential for trade collabor ation with China in this sector.This s...China ranked first worldwide in the production and export of electric bicycles.As an emerging market for electric bicycles,Malaysia holds significant potential for trade collabor ation with China in this sector.This study presents a compar ative analysis of the national electric bicycle standards in China and Malaysia,offering technical insights from a standardization perspective.These insights aim to support Chinese enterprises in strategically positioning their technologies in the Malaysian market.The findings reveal significant differences in technical parameters,safety requirements,and testing methods,highlighting the need for tailored product adapt ation.展开更多
To advance the theoretical understanding,technological development,and field application of electric charge induction for monitoring rock deformation and failure,this study investigates the induced electric charge gen...To advance the theoretical understanding,technological development,and field application of electric charge induction for monitoring rock deformation and failure,this study investigates the induced electric charge generated during the deformation and failure of igneous rocks.The charge originates mainly from a combination of electrical polarization and triboelectric effects.Through laboratory experiments,we analyzed the time-frequency evolution of induced electric charge signals and identified relevant monitoring parameters.An online downhole electric charge induction monitoring system was developed and validated in the field.Experimental results show that the dominant frequency range of induced electric charge signals generated during igneous rock deformation and failure lies between 0 and 23 Hz,and a low-pass finite impulse response(FIR)filter effectively suppresses noise.Optimal sensor distances for monitoring cubic and cylindrical specimens were determined to be 17 mm and 13 mm,respectively.We proposed early warning indicators,including the maximum absolute value of the induced electric charge,the arithmetic mean value,the distribution dispersion coefficient,and the cumulative sum value.In field application,time-domain curves and spatial distribution charts of these warning indicators correspond well with changes in abutment stress ahead of the mining face,offering indirect insights into local stress evolution.This research provides technical and equipment support for the application of electric charge induction technology to monitoring and early warning of coal bursts.展开更多
Accurate short-term electricity price forecasts are essential for market participants to optimize bidding strategies,hedge risk and plan generation schedules.By leveraging advanced data analytics and machine learning ...Accurate short-term electricity price forecasts are essential for market participants to optimize bidding strategies,hedge risk and plan generation schedules.By leveraging advanced data analytics and machine learning methods,accurate and reliable price forecasts can be achieved.This study forecasts day-ahead prices in Türkiye’s electricity market using eXtreme Gradient Boosting(XGBoost).We benchmark XGBoost against four alternatives—Support Vector Machines(SVM),Long Short-Term Memory(LSTM),Random Forest(RF),and Gradient Boosting(GBM)—using 8760 hourly observations from 2023 provided by Energy Exchange Istanbul(EXIST).All models were trained on an identical chronological 80/20 train–test split,with hyperparameters tuned via 5-fold cross-validation on the training set.XGBoost achieved the best performance(Mean Absolute Error(MAE)=144.8 TRY/MWh,Root Mean Square Error(RMSE)=201.8 TRY/MWh,coefficient of determination(R^(2))=0.923)while training in 94 s.To enhance interpretability and identify key drivers,we employed Shapley Additive Explanations(SHAP),which highlighted a strong association between higher prices and increased natural-gas-based generation.The results provide a clear performance benchmark and practical guidance for selecting forecasting approaches in day-ahead electricity markets.展开更多
Conducting hydrogels have garnered significant interest in the field of wearable electronics.However,simultaneously achieving high transparency,high conductivity,strong adhesion,and self-healing ability within a short...Conducting hydrogels have garnered significant interest in the field of wearable electronics.However,simultaneously achieving high transparency,high conductivity,strong adhesion,and self-healing ability within a short time remains a major challenge.In this study,a multifunctional mussel-inspired hydrogel was synthesized in only 5 min,with polydopamine(PDA)-polypyrrole(Ppy)-polyaniline(PANi)and poly(vinyl alcohol)(PVA)nanoparticles incorporated into the polyacrylamide(PAM)network.The resulting hydrogel exhibited high transparency(about 90% light transmission in the range of 400-800 nm),high conductivity((95.4±0.4)×10^(-4)S/cm),tensile strength(32.60±1.03 k Pa),strain at break(904.46%±11.50%),and adhesive strength(30-60 k Pa).It also demonstrated rapid self-healing properties(about 48% strength recovery within 1h at 50℃)and water-dependent shape memory behavior.As a wearable strain sensor,the hydrogel successfully detected finger flexion,wrist movements,facial expression changes,and breathing with high sensitivity and stability.The calculated gauge factor(GF)was 7.44±0.31,which is higher than that of many previously reported hydrogels.Compared with previous oyster-inspired or Ppy-based hydrogels,our system showed a much shorter synthesis time,higher transparency,and enhanced multifunctionality.These findings highlight the potential of the proposed hydrogel for next-generation flexible electronics,e-skin,and biomedical monitoring devices.展开更多
With the rapid proliferation of electric vehicles,their charging loads pose new challenges to power grid stability and operational efficiency.To address this,this study employs a Monte Carlo simulation model to analyz...With the rapid proliferation of electric vehicles,their charging loads pose new challenges to power grid stability and operational efficiency.To address this,this study employs a Monte Carlo simulation model to analyze the charging load characteristics of six battery electric vehicle categories in Hebei Province,leveraging multi-source probabilistic distribution data under typical operational scenarios.The findings reveal that electric vehicle charging loads are primarily concentrated during midday and nighttime periods,with significant load fluctuations exerting substantial pressure on the grid.In response,this paper proposes strategic interventions including optimized charging infrastructure planning,time-of-use electricity pricing mechanisms,and smart charging technologies to balance grid loads.The results provide a theoretical foundation for electric vehicle load forecasting,smart grid dispatching,and vehicle-grid integration,thereby enhancing grid operational efficiency and sustainability.展开更多
Peroxymonosulfate(PMS)-based advanced oxidation processes(AOPs)are an effective way to remove emerging contaminants(ECs)from water.The catalytic process involving PMS is hindered by the suboptimal electron trans-fer e...Peroxymonosulfate(PMS)-based advanced oxidation processes(AOPs)are an effective way to remove emerging contaminants(ECs)from water.The catalytic process involving PMS is hindered by the suboptimal electron trans-fer efficiency of current catalysts,the further application of AOPs technology is limited.Here,it is proposed that the interfacial electric field can be controlled by bor(B)-doped FeNC catalysts,which shows significant advantages in the efficient generation,release and participation of reactive oxygen species(ROS)in the reaction.The super exchange interaction between Fe sites and N and B sites is realized through the directional transfer of electrons in the interfacial electric field,which ensures the high efficiency and stability of the PMS catalytic process.B doping increases the d orbitals distribution at Fermi level,which facilitates enhanced electron transition activity,thereby promoting the effective generation of (1)^O_(2).At the same time,orbital hybridization causes the center of the d band to move to a lower energy level,which not only contributes to the desorption process of (1)^O_(2),but also accelerates its release.In addition,B-doping also improved the adsorption capacity of organic pollutants and shortened the migration distance of ROS,thereby significantly improving the degradation efficiency of ECs.The B-doping strategy outlined offers a novel approach to the development of FeNC catalysts,it lays a theoretical foundation and offers technical insights for the integration of PMS/AOPs technology in the ECs management.展开更多
To achieve low-carbon regulation of electric vehicle(EV)charging loads under the“dual carbon”goals,this paper proposes a coordinated scheduling strategy that integrates dynamic carbon factor prediction and multiobje...To achieve low-carbon regulation of electric vehicle(EV)charging loads under the“dual carbon”goals,this paper proposes a coordinated scheduling strategy that integrates dynamic carbon factor prediction and multiobjective optimization.First,a dual-convolution enhanced improved Crossformer prediction model is constructed,which employs parallel 1×1 global and 3×3 local convolutionmodules(Integrated Convolution Block,ICB)formultiscale feature extraction,combinedwith anAdaptive Spectral Block(ASB)to enhance time-series fluctuationmodeling.Based on high-precision predictions,a carbon-electricity cost joint optimization model is further designed to balance economic,environmental,and grid-friendly objectives.The model’s superiority was validated through a case study using real-world data from a renewable-heavy grid.Simulation results show that the proposed multi-objective strategy demonstrated a superior balance compared to baseline and benchmark models,achieving a 15.8%reduction in carbon emissions and a 5.2%reduction in economic costs,while still providing a substantial 22.2%reduction in the peak-valley difference.Its balanced performance significantly outperformed both a single-objective strategy and a state-of-the-art Model Predictive Control(MPC)benchmark,highlighting the advantage of a global optimization approach.This study provides theoretical and technical pathways for dynamic carbon factor-driven EV charging optimization.展开更多
Tactile feedback is critical for human interaction with external information.Similarly,tactile feedback can enrich the user's sensations when using prosthesis.To explore a potential scheme for tactile feedback,thi...Tactile feedback is critical for human interaction with external information.Similarly,tactile feedback can enrich the user's sensations when using prosthesis.To explore a potential scheme for tactile feedback,this study applied a non-inva-sive Transcutaneous Electrical Nerve Stimulation(TENS)to elicit tactile sensations in the hand,which involved median nerve,ulnar nerve,and radial nerve.Ten able-bodied subjects(8 males,2 females)were recruited to participate in the study.An array of 4×2 electrodes was positioned on the medial aspect of the brachii muscle's short head in the upper arm,which is in proximity to the median nerve,ulnar nerve,and radial nerve.Different electrode pairs were randomly selected to elicit distinct sensations at various positions on the hand,and the subjects reported the sensory areas.Then,the sensory areas and sensory thresholds were confirmed through psychophysical methods.According to the experimental results,tactile sensations were elicited at different locations on the subjects'hand through TENS of different electrode pairs.All subjects reported extensive and detailed sensory areas in the fingers,palm,and dorsum,corresponding to the sensory innervation areas of different nerves.The study effectively demonstrated the ability of TENS in evoking tactile feedback in the hand,paving the way for future optimization and development of prosthetic hands.展开更多
The thermal and electrical conductivities of magnesium alloys are highly sensitive to composition and microstructure,with thermal conductivity varying by up to 20-fold across different as-cast alloy systems,making rap...The thermal and electrical conductivities of magnesium alloys are highly sensitive to composition and microstructure,with thermal conductivity varying by up to 20-fold across different as-cast alloy systems,making rapid and accurate prediction crucial for high-throughput screening and development of high-performance alloys.This study introduces a physics-informed symbolic regression approach that addresses the limitations of traditional methods,including the high computational cost of first-principles calculations and the poor interpretability of machine learning models.Comprehensive datasets comprising 1512 data points from 60 literature sources were analyzed,including thermal conductivity measurements from 52 alloy systems and electrical conductivity measurements from 36 systems.The derived symbolic regression model achieved Mean Absolute Percentage Errors(MAPEs)of 11.2%and 11.4%for thermal conductivity in low and high-component systems,respectively.When integrated with the Smith-Palmer equation,electrical conductivity predictions reached MAPEs of 15.6%and 16.4%.Independent validation on an entirely separate dataset of 554 data points from 53 additional literature sources,including 37 previously unseen alloy systems,confirmed model generalizability with MAPEs of 10.7%-15.2%.Shapley Additive Explanations(SHAP)analysis was employed to evaluate the relative importance of different features affecting conductivity,while equation decomposition quantified the contribution of individual functional terms.This methodology bridges data-driven prediction with mechanistic understanding,establishing a foundation for knowledge-based design of magnesium alloys with tailored transport properties.展开更多
Tilted metasurface nanostructures,with excellent physical properties and enormous application potential,pose an urgent need for manufacturing methods.Here,electric-field-driven generative-nanoimprinting technique is p...Tilted metasurface nanostructures,with excellent physical properties and enormous application potential,pose an urgent need for manufacturing methods.Here,electric-field-driven generative-nanoimprinting technique is proposed.The electric field applied between the template and the substrate drives the contact,tilting,filling,and holding processes.By accurately controlling the introduced included angle between the flexible template and the substrate,tilted nanostructures with a controllable angle are imprinted onto the substrate,although they are vertical on the template.By flexibly adjusting the electric field intensity and the included angle,large-area uniform-tilted,gradient-tilted,and high-angle-tilted nanostructures are fabricated.In contrast to traditional replication,the morphology of the nanoimprinting structure is extended to customized control.This work provides a cost-effective,efficient,and versatile technology for the fabrication of various large-area tilted metasurface structures.As an illustration,a tilted nanograting with a high coupling efficiency is fabricated and integrated into augmented reality displays,demonstrating superior imaging quality.展开更多
The increasing complexity of China’s electricity market creates substantial challenges for settlement automation,data consistency,and operational scalability.Existing provincial settlement systems are fragmented,lack...The increasing complexity of China’s electricity market creates substantial challenges for settlement automation,data consistency,and operational scalability.Existing provincial settlement systems are fragmented,lack a unified data structure,and depend heavily on manual intervention to process high-frequency and retroactive transactions.To address these limitations,a graph-based unified settlement framework is proposed to enhance automation,flexibility,and adaptability in electricity market settlements.A flexible attribute-graph model is employed to represent heterogeneousmulti-market data,enabling standardized integration,rapid querying,and seamless adaptation to evolving business requirements.An extensible operator library is designed to support configurable settlement rules,and a suite of modular tools—including dataset generation,formula configuration,billing templates,and task scheduling—facilitates end-to-end automated settlement processing.A robust refund-clearing mechanism is further incorporated,utilizing sandbox execution,data-version snapshots,dynamic lineage tracing,and real-time changecapture technologies to enable rapid and accurate recalculations under dynamic policy and data revisions.Case studies based on real-world data from regional Chinese markets validate the effectiveness of the proposed approach,demonstrating marked improvements in computational efficiency,system robustness,and automation.Moreover,enhanced settlement accuracy and high temporal granularity improve price-signal fidelity,promote cost-reflective tariffs,and incentivize energy-efficient and demand-responsive behavior among market participants.The method not only supports equitable and transparent market operations but also provides a generalizable,scalable foundation for modern electricity settlement platforms in increasingly complex and dynamic market environments.展开更多
To address the high costs and operational instability of distribution networks caused by the large-scale integration of distributed energy resources(DERs)(such as photovoltaic(PV)systems,wind turbines(WT),and energy s...To address the high costs and operational instability of distribution networks caused by the large-scale integration of distributed energy resources(DERs)(such as photovoltaic(PV)systems,wind turbines(WT),and energy storage(ES)devices),and the increased grid load fluctuations and safety risks due to uncoordinated electric vehicles(EVs)charging,this paper proposes a novel dual-scale hierarchical collaborative optimization strategy.This strategy decouples system-level economic dispatch from distributed EV agent control,effectively solving the resource coordination conflicts arising from the high computational complexity,poor scalability of existing centralized optimization,or the reliance on local information decision-making in fully decentralized frameworks.At the lower level,an EV charging and discharging model with a hybrid discrete-continuous action space is established,and optimized using an improved Parameterized Deep Q-Network(PDQN)algorithm,which directly handles mode selection and power regulation while embedding physical constraints to ensure safety.At the upper level,microgrid(MG)operators adopt a dynamic pricing strategy optimized through Deep Reinforcement Learning(DRL)to maximize economic benefits and achieve peak-valley shaving.Simulation results show that the proposed strategy outperforms traditional methods,reducing the total operating cost of the MG by 21.6%,decreasing the peak-to-valley load difference by 33.7%,reducing the number of voltage limit violations by 88.9%,and lowering the average electricity cost for EV users by 15.2%.This method brings a win-win result for operators and users,providing a reliable and efficient scheduling solution for distribution networks with high renewable energy penetration rates.展开更多
An in-built N^(+)pocket electrically doped tunnel field-effect transistor(ED-TFET)-based biosensor has been reported for the first time.The proposed device begins with a PN junction structure with a control gate(CG)an...An in-built N^(+)pocket electrically doped tunnel field-effect transistor(ED-TFET)-based biosensor has been reported for the first time.The proposed device begins with a PN junction structure with a control gate(CG)and two polarity gates(PG1 and PG2).Utilizing the polarity bias concept,a narrow N^(+)pocket is formed between the source and channel without the need for additional doping steps,achieved through biasing PG1 and PG2 at-1.2 V and 1.2 V,respectively.This method not only addresses issues related to doping control but also eliminates constraints associated with thermal budgets and simplifies the fabrication process compared to traditional TFETs.To facilitate biomolecule sensing within the device,a nanogap cavity is formed in the gate dielectric by selectively etching a section of the polarity gate dielectric layer toward the source side.The investigation into the presence of neutral and charged molecules within the cavities has been conducted by examining variations in the electrical properties of the proposed biosensor.Key characteristics assessed include drain current,energy band,and electric field distribution.The performance of the biosensor is measured using various metrics such as drain current(I_(DS)),subthreshold swing(SS),threshold voltage(V_(TH)),drain current ratio(I_(ON)/I_(OFF)).The proposed in-built N^(+)pocket ED-TFET-based biosensor reaches a peak sensitivity of 1.08×10~(13)for a neutral biomolecule in a completely filled nanogap with a dielectric constant of 12.Additionally,the effects of cavity geometry and different fill factors(FFs)on sensitivity are studied.展开更多
The electric double layer(EDL)at the electrochemical interface is crucial for ion transport,charge transfer,and surface reactions in aqueous rechargeable zinc batteries(ARZBs).However,Zn anodes routinely encounter per...The electric double layer(EDL)at the electrochemical interface is crucial for ion transport,charge transfer,and surface reactions in aqueous rechargeable zinc batteries(ARZBs).However,Zn anodes routinely encounter persistent dendrite growth and parasitic reactions,driven by the inhomogeneous charge distribution and water-dominated environment within the EDL.Compounding this,classical EDL theory,rooted in meanfield approximations,further fails to resolve molecular-scale interfacial dynamics under battery-operating conditions,limiting mechanistic insights.Herein,we established a multiscale theoretical calculation framework from single molecular characteristics to interfacial ion distribution,revealing the EDL’s structure and interactions between different ions and molecules,which helps us understand the parasitic processes in depth.Simulations demonstrate that water dipole and sulfate ion adsorption at the inner Helmholtz plane drives severe hydrogen evolution and by-product formation.Guided by these insights,we engineered a“water-poor and anion-expelled”EDL using 4,1’,6’-trichlorogalactosucrose(TGS)as an electrolyte additive.As a result,Zn||Zn symmetric cells with TGS exhibited stable cycling for over 4700 h under a current density of 1 mA cm^(−2),while NaV_(3)O_(8)·1.5H_(2)O-based full cells kept 90.4%of the initial specific capacity after 800 cycles at 5 A g^(−1).This work highlights the power of multiscale theoretical frameworks to unravel EDL complexities and guide high-performance ARZB design through integrated theory-experiment approaches.展开更多
Electrically controlled solid propellant(ECSP)offers multiple ignition and adjustable burning rate,serving as fuel for next-generation intelligent propulsion systems.To further enhance the combustion performance of EC...Electrically controlled solid propellant(ECSP)offers multiple ignition and adjustable burning rate,serving as fuel for next-generation intelligent propulsion systems.To further enhance the combustion performance of ECSP,a method utilizing electrochemical and thermal decomposition catalysts has been proposed.In this work,we investigated the combustion characteristics of hydroxylamine nitrate(HAN)-based ECSP incorporating cerium oxide(CeO_(2))and graphene oxide(GO)by using an electrically controlled combustion test system.Electrochemical impedance spectroscopy(EIS)and linear sweep voltammetry(LSV)were used to measure the electrical conductibility and overpotential of ECSP with various additives,and Tafel curves were calculated.Thermogravimetric analysis coupled with differential scanning calorimetry(TG-DSC)was employed to investigate the thermal decomposition behavior of ECSP.While the addition of CeO_(2) and GO reduced the conductivity of ECSP,both catalysts exhibited strong electrocatalytic properties and facilitated the thermal decomposition of ECSP.Between two catalysts,GO demonstrated superior electrochemical catalytic performance but weaker thermal decomposition catalytic ability than CeO_(2).The addition of catalysts significantly enhanced the combustion performance of HAN-based ECSP.Specifically,the ignition delay time was shortened by 10%~20%.CeO_(2) raised the burning rate by approximately 20%but GO exhibited a remarkable boost of 40%in burning rate at high voltage.The combination of GO and PVA produced a flame-retardant substance that negatively impacted the ignition delay of ECSP and resulted in a smaller increase in the burning rate of ECSP at low ignition voltages.展开更多
To elucidate the accelerated degradation mechanisms of metallic interconnects in operational solid oxide fuel cells,the oxidation behavior of FSS430 ferritic stainless steel under the coupling of simultaneous electric...To elucidate the accelerated degradation mechanisms of metallic interconnects in operational solid oxide fuel cells,the oxidation behavior of FSS430 ferritic stainless steel under the coupling of simultaneous electrical current and high-temperature exposure is investigated.Isothermal thermogravimetric analysis was employed to quantify oxidation kinetics,complemented by microstructural characterization using X-ray diffraction,scanning electron microscopy with energy-dispersive spectroscopy and transmission electron microscopy.Experimental results demonstrate that the applied current dramatically enhances oxidation rates,increasing specific mass gain from 0.25 mg/cm^(2)(0 A/cm^(2))to 5.20 mg/cm^(2)(0.2 A/cm^(2))and oxide scale thickness from 1.87 to 15.62μm after 200 h.This acceleration originates from current-induced electromigration forces that promote cationic transport through the oxide layer.The quantitative relationships between current density and oxidation parameters are established,enabling predictive modeling of interconnector degradation in solid oxide fuel cell(SOFC)systems.展开更多
The construction of spot electricity markets plays a pivotal role in power system reforms,where market clearing systems profoundly influence market efficiency and security.Current clearing systems predominantly adopt ...The construction of spot electricity markets plays a pivotal role in power system reforms,where market clearing systems profoundly influence market efficiency and security.Current clearing systems predominantly adopt a single-system architecture,with research focusing primarily on accelerating solution algorithms through techniques such as high-efficiency parallel solvers and staggered decomposition of mixed-integer programming models.Notably absent are systematic studies evaluating the adaptability of primary-backup clearing systems incontingency scenarios—a critical gap given redundant systems’expanding applications in operational environments.This paper proposes a comprehensive evaluation framework for analyzing dual-system adaptability,demonstrated through an in-depth case study of the Inner Mongolia power market.First,we establish the innovative“Dual-Active Heterogeneous”architecture that enables independent parallelized operation and fault-isolated redundancy.Subsequently,key performance indices are quantitatively evaluated across four critical dimensions:unit commitment decisions,generator output constraints,transmission section congestion patterns,and clearing price formation mechanisms.An integrated fuzzy evaluation methodology incorporating grey relational analysis is employed for objective indicator weighting,enabling systematic quantification of system superiority under specific grid operating states.Empirical results based on actual operational data from 200 generation units demonstrate the framework’s efficacy in guiding optimal system selection,with particularly strong performance observed during peak load periods.The proposed approach shows high generalization potential for other regional markets employing redundant clearing mechanisms—particularly those with increasing renewable penetration and associated uncertainty.展开更多
According to the China Association of Automobile Manufacturers (CAAM),China's auto industry reached record highs in 2025,with production and sales at 34.53 million and 34.4 million vehicles,respectively.This secur...According to the China Association of Automobile Manufacturers (CAAM),China's auto industry reached record highs in 2025,with production and sales at 34.53 million and 34.4 million vehicles,respectively.This secured China's position as the world's largest auto market for the 17th year in a row.展开更多
BACKGROUND:Individualized positive end-expiratory pressure(PEEP)titration is a crucial technique in mechanical ventilation therapy for acute respiratory distress syndrome(ARDS)patients with intra-abdominal hypertensio...BACKGROUND:Individualized positive end-expiratory pressure(PEEP)titration is a crucial technique in mechanical ventilation therapy for acute respiratory distress syndrome(ARDS)patients with intra-abdominal hypertension(IAH).This study aimed to evaluate the eff ectiveness of electrical impedance tomography(EIT)-guided PEEP titration in this population.METHODS:This prospective study enrolled 36 ARDS patients,including 22 patients with IAH and 14 without IAH.All the patients underwent EIT-guided PEEP titration at the intersection point between alveolar overdistension and collapse during a decremental PEEP trial.The changes in pulmonary ventilation distribution,respiratory mechanics and hemodynamics during the titration process were observed.RESULTS:After EIT-guided PEEP titration was performed,the PEEP,peak inspiratory pressure and plateau pressure increased significantly(P<0.05).Furthermore,no significant differences were observed in respiratory system compliance,tidal volume,driving pressure,or the 4*DP+RR index between the two groups(P>0.05).The mechanical power increased in the non-IAH(NIAH)group after PEEP titration(P<0.05).Ventilation in gravity-dependent lung regions significantly increased(P<0.05),and the oxygenation index(PaO2/FiO2)improved signifi cantly(P<0.05)in both groups.However,blood pressure,heart rate,respiratory rate,central venous pressure,and lactate levels did not signifi cantly change.In the IAH group,the PaO2/FiO2 ratio improved less than that in the NIAH group did(P<0.05).CONCLUSION:In our study,individualized PEEP titration guided by EIT improved oxygenation in ARDS patients with concomitant IAH without signifi cantly aff ecting hemodynamics.The presence of IAH may limit the improvement of oxygenation during EIT-guided PEEP titration.展开更多
基金supported by the National Science Foundation of China(No.82272491)。
文摘The continuous extension of human life expectancy and the global trend of population aging have contributed to a marked increase in the incidence of musculoskeletal diseases,with fractures and osteoporosis being prominent examples.Consequently,promoting bone regeneration is a crucial medical challenge that demands immediate attention.As early as the mid-20th century,researchers revealed that electrical stimulation could effectively promote the healing and regeneration of bone tissue.This is achieved by mimicking the endogenous electric field within bone tissue,which influences cellular behavior and molecular mechanisms.In recent years,electroactive hydrogels responsive to electric field stimulation have been developed and applied to regulate cell functions at different stages of bone regeneration.This paper elaborates on the regulatory effects of electrical stimulation on MSCs,macrophages,and vascular endothelial cells during the process of bone regeneration.It also involves the activation of relevant ion channels and signaling pathways.Subsequently,it comprehensively reviews various electric-field-responsive hydrogels developed in recent years,covering aspects such as material selection,preparation methods,characteristics,and their applications in bone regeneration.Ultimately,it provides an objective summary of the existing deficiencies in hydrogel materials and research,and looks ahead to future development directions.
文摘China ranked first worldwide in the production and export of electric bicycles.As an emerging market for electric bicycles,Malaysia holds significant potential for trade collabor ation with China in this sector.This study presents a compar ative analysis of the national electric bicycle standards in China and Malaysia,offering technical insights from a standardization perspective.These insights aim to support Chinese enterprises in strategically positioning their technologies in the Malaysian market.The findings reveal significant differences in technical parameters,safety requirements,and testing methods,highlighting the need for tailored product adapt ation.
基金supported by the National Key Research and Development Project of the National Natural Science Foundation of China(Grant No.2022YFC3004605)the National Natural Science Foundation of China Youth Science Fund(Grant No.52104087).
文摘To advance the theoretical understanding,technological development,and field application of electric charge induction for monitoring rock deformation and failure,this study investigates the induced electric charge generated during the deformation and failure of igneous rocks.The charge originates mainly from a combination of electrical polarization and triboelectric effects.Through laboratory experiments,we analyzed the time-frequency evolution of induced electric charge signals and identified relevant monitoring parameters.An online downhole electric charge induction monitoring system was developed and validated in the field.Experimental results show that the dominant frequency range of induced electric charge signals generated during igneous rock deformation and failure lies between 0 and 23 Hz,and a low-pass finite impulse response(FIR)filter effectively suppresses noise.Optimal sensor distances for monitoring cubic and cylindrical specimens were determined to be 17 mm and 13 mm,respectively.We proposed early warning indicators,including the maximum absolute value of the induced electric charge,the arithmetic mean value,the distribution dispersion coefficient,and the cumulative sum value.In field application,time-domain curves and spatial distribution charts of these warning indicators correspond well with changes in abutment stress ahead of the mining face,offering indirect insights into local stress evolution.This research provides technical and equipment support for the application of electric charge induction technology to monitoring and early warning of coal bursts.
文摘Accurate short-term electricity price forecasts are essential for market participants to optimize bidding strategies,hedge risk and plan generation schedules.By leveraging advanced data analytics and machine learning methods,accurate and reliable price forecasts can be achieved.This study forecasts day-ahead prices in Türkiye’s electricity market using eXtreme Gradient Boosting(XGBoost).We benchmark XGBoost against four alternatives—Support Vector Machines(SVM),Long Short-Term Memory(LSTM),Random Forest(RF),and Gradient Boosting(GBM)—using 8760 hourly observations from 2023 provided by Energy Exchange Istanbul(EXIST).All models were trained on an identical chronological 80/20 train–test split,with hyperparameters tuned via 5-fold cross-validation on the training set.XGBoost achieved the best performance(Mean Absolute Error(MAE)=144.8 TRY/MWh,Root Mean Square Error(RMSE)=201.8 TRY/MWh,coefficient of determination(R^(2))=0.923)while training in 94 s.To enhance interpretability and identify key drivers,we employed Shapley Additive Explanations(SHAP),which highlighted a strong association between higher prices and increased natural-gas-based generation.The results provide a clear performance benchmark and practical guidance for selecting forecasting approaches in day-ahead electricity markets.
文摘Conducting hydrogels have garnered significant interest in the field of wearable electronics.However,simultaneously achieving high transparency,high conductivity,strong adhesion,and self-healing ability within a short time remains a major challenge.In this study,a multifunctional mussel-inspired hydrogel was synthesized in only 5 min,with polydopamine(PDA)-polypyrrole(Ppy)-polyaniline(PANi)and poly(vinyl alcohol)(PVA)nanoparticles incorporated into the polyacrylamide(PAM)network.The resulting hydrogel exhibited high transparency(about 90% light transmission in the range of 400-800 nm),high conductivity((95.4±0.4)×10^(-4)S/cm),tensile strength(32.60±1.03 k Pa),strain at break(904.46%±11.50%),and adhesive strength(30-60 k Pa).It also demonstrated rapid self-healing properties(about 48% strength recovery within 1h at 50℃)and water-dependent shape memory behavior.As a wearable strain sensor,the hydrogel successfully detected finger flexion,wrist movements,facial expression changes,and breathing with high sensitivity and stability.The calculated gauge factor(GF)was 7.44±0.31,which is higher than that of many previously reported hydrogels.Compared with previous oyster-inspired or Ppy-based hydrogels,our system showed a much shorter synthesis time,higher transparency,and enhanced multifunctionality.These findings highlight the potential of the proposed hydrogel for next-generation flexible electronics,e-skin,and biomedical monitoring devices.
基金funded by Humanities and Social Sciences of Ministry of Education Planning Fund of China,grant number 21YJA790009National Natural Science Foundation of China,grant number 72140001.
文摘With the rapid proliferation of electric vehicles,their charging loads pose new challenges to power grid stability and operational efficiency.To address this,this study employs a Monte Carlo simulation model to analyze the charging load characteristics of six battery electric vehicle categories in Hebei Province,leveraging multi-source probabilistic distribution data under typical operational scenarios.The findings reveal that electric vehicle charging loads are primarily concentrated during midday and nighttime periods,with significant load fluctuations exerting substantial pressure on the grid.In response,this paper proposes strategic interventions including optimized charging infrastructure planning,time-of-use electricity pricing mechanisms,and smart charging technologies to balance grid loads.The results provide a theoretical foundation for electric vehicle load forecasting,smart grid dispatching,and vehicle-grid integration,thereby enhancing grid operational efficiency and sustainability.
基金supported by the National Natural Science Foundation of China(No.22278156)the Guangdong Special Support Program Project(No.2021JC060580)+1 种基金the Young Elite Scientists Sponsorship Program by CAST-Doctoral Student Special Plan,the China Scholarship Council Program(No.202406150148)the Natural Science Foundation of Guangdong Province(No.2023A1515011186).
文摘Peroxymonosulfate(PMS)-based advanced oxidation processes(AOPs)are an effective way to remove emerging contaminants(ECs)from water.The catalytic process involving PMS is hindered by the suboptimal electron trans-fer efficiency of current catalysts,the further application of AOPs technology is limited.Here,it is proposed that the interfacial electric field can be controlled by bor(B)-doped FeNC catalysts,which shows significant advantages in the efficient generation,release and participation of reactive oxygen species(ROS)in the reaction.The super exchange interaction between Fe sites and N and B sites is realized through the directional transfer of electrons in the interfacial electric field,which ensures the high efficiency and stability of the PMS catalytic process.B doping increases the d orbitals distribution at Fermi level,which facilitates enhanced electron transition activity,thereby promoting the effective generation of (1)^O_(2).At the same time,orbital hybridization causes the center of the d band to move to a lower energy level,which not only contributes to the desorption process of (1)^O_(2),but also accelerates its release.In addition,B-doping also improved the adsorption capacity of organic pollutants and shortened the migration distance of ROS,thereby significantly improving the degradation efficiency of ECs.The B-doping strategy outlined offers a novel approach to the development of FeNC catalysts,it lays a theoretical foundation and offers technical insights for the integration of PMS/AOPs technology in the ECs management.
基金Supported by State Grid Corporation of China Science and Technology Project:Research on Key Technologies for Intelligent Carbon Metrology in Vehicle-to-Grid Interaction(Project Number:B3018524000Q).
文摘To achieve low-carbon regulation of electric vehicle(EV)charging loads under the“dual carbon”goals,this paper proposes a coordinated scheduling strategy that integrates dynamic carbon factor prediction and multiobjective optimization.First,a dual-convolution enhanced improved Crossformer prediction model is constructed,which employs parallel 1×1 global and 3×3 local convolutionmodules(Integrated Convolution Block,ICB)formultiscale feature extraction,combinedwith anAdaptive Spectral Block(ASB)to enhance time-series fluctuationmodeling.Based on high-precision predictions,a carbon-electricity cost joint optimization model is further designed to balance economic,environmental,and grid-friendly objectives.The model’s superiority was validated through a case study using real-world data from a renewable-heavy grid.Simulation results show that the proposed multi-objective strategy demonstrated a superior balance compared to baseline and benchmark models,achieving a 15.8%reduction in carbon emissions and a 5.2%reduction in economic costs,while still providing a substantial 22.2%reduction in the peak-valley difference.Its balanced performance significantly outperformed both a single-objective strategy and a state-of-the-art Model Predictive Control(MPC)benchmark,highlighting the advantage of a global optimization approach.This study provides theoretical and technical pathways for dynamic carbon factor-driven EV charging optimization.
基金National Natural Science Foundation of China(Grant No.52525504)Emerging Frontiers Cultivation Program of Tianjin University Interdisciplinary Center.
文摘Tactile feedback is critical for human interaction with external information.Similarly,tactile feedback can enrich the user's sensations when using prosthesis.To explore a potential scheme for tactile feedback,this study applied a non-inva-sive Transcutaneous Electrical Nerve Stimulation(TENS)to elicit tactile sensations in the hand,which involved median nerve,ulnar nerve,and radial nerve.Ten able-bodied subjects(8 males,2 females)were recruited to participate in the study.An array of 4×2 electrodes was positioned on the medial aspect of the brachii muscle's short head in the upper arm,which is in proximity to the median nerve,ulnar nerve,and radial nerve.Different electrode pairs were randomly selected to elicit distinct sensations at various positions on the hand,and the subjects reported the sensory areas.Then,the sensory areas and sensory thresholds were confirmed through psychophysical methods.According to the experimental results,tactile sensations were elicited at different locations on the subjects'hand through TENS of different electrode pairs.All subjects reported extensive and detailed sensory areas in the fingers,palm,and dorsum,corresponding to the sensory innervation areas of different nerves.The study effectively demonstrated the ability of TENS in evoking tactile feedback in the hand,paving the way for future optimization and development of prosthetic hands.
基金supported by the National Key Research and Development Program of China(No.2023YFB3712401)the National Natural Science Foundation of China(No.52274301)+2 种基金the Aeronautical Science Foundation of China(No.2023Z0530S6005)Academician Workstation of Kunming University of Science and Technology(2024),Ningbo Yongjiang Talent-Introduction Program(No.2022A-023C)Zhejiang Phenomenological Materials Technology Co.,Ltd.,China.
文摘The thermal and electrical conductivities of magnesium alloys are highly sensitive to composition and microstructure,with thermal conductivity varying by up to 20-fold across different as-cast alloy systems,making rapid and accurate prediction crucial for high-throughput screening and development of high-performance alloys.This study introduces a physics-informed symbolic regression approach that addresses the limitations of traditional methods,including the high computational cost of first-principles calculations and the poor interpretability of machine learning models.Comprehensive datasets comprising 1512 data points from 60 literature sources were analyzed,including thermal conductivity measurements from 52 alloy systems and electrical conductivity measurements from 36 systems.The derived symbolic regression model achieved Mean Absolute Percentage Errors(MAPEs)of 11.2%and 11.4%for thermal conductivity in low and high-component systems,respectively.When integrated with the Smith-Palmer equation,electrical conductivity predictions reached MAPEs of 15.6%and 16.4%.Independent validation on an entirely separate dataset of 554 data points from 53 additional literature sources,including 37 previously unseen alloy systems,confirmed model generalizability with MAPEs of 10.7%-15.2%.Shapley Additive Explanations(SHAP)analysis was employed to evaluate the relative importance of different features affecting conductivity,while equation decomposition quantified the contribution of individual functional terms.This methodology bridges data-driven prediction with mechanistic understanding,establishing a foundation for knowledge-based design of magnesium alloys with tailored transport properties.
基金supported by National Natural Science Foundation of China(No.52025055 and 52275571)Basic Research Operation Fund of China(No.xzy012024024).
文摘Tilted metasurface nanostructures,with excellent physical properties and enormous application potential,pose an urgent need for manufacturing methods.Here,electric-field-driven generative-nanoimprinting technique is proposed.The electric field applied between the template and the substrate drives the contact,tilting,filling,and holding processes.By accurately controlling the introduced included angle between the flexible template and the substrate,tilted nanostructures with a controllable angle are imprinted onto the substrate,although they are vertical on the template.By flexibly adjusting the electric field intensity and the included angle,large-area uniform-tilted,gradient-tilted,and high-angle-tilted nanostructures are fabricated.In contrast to traditional replication,the morphology of the nanoimprinting structure is extended to customized control.This work provides a cost-effective,efficient,and versatile technology for the fabrication of various large-area tilted metasurface structures.As an illustration,a tilted nanograting with a high coupling efficiency is fabricated and integrated into augmented reality displays,demonstrating superior imaging quality.
基金funded by the Science and Technology Project of State Grid Corporation of China(5108-202355437A-3-2-ZN).
文摘The increasing complexity of China’s electricity market creates substantial challenges for settlement automation,data consistency,and operational scalability.Existing provincial settlement systems are fragmented,lack a unified data structure,and depend heavily on manual intervention to process high-frequency and retroactive transactions.To address these limitations,a graph-based unified settlement framework is proposed to enhance automation,flexibility,and adaptability in electricity market settlements.A flexible attribute-graph model is employed to represent heterogeneousmulti-market data,enabling standardized integration,rapid querying,and seamless adaptation to evolving business requirements.An extensible operator library is designed to support configurable settlement rules,and a suite of modular tools—including dataset generation,formula configuration,billing templates,and task scheduling—facilitates end-to-end automated settlement processing.A robust refund-clearing mechanism is further incorporated,utilizing sandbox execution,data-version snapshots,dynamic lineage tracing,and real-time changecapture technologies to enable rapid and accurate recalculations under dynamic policy and data revisions.Case studies based on real-world data from regional Chinese markets validate the effectiveness of the proposed approach,demonstrating marked improvements in computational efficiency,system robustness,and automation.Moreover,enhanced settlement accuracy and high temporal granularity improve price-signal fidelity,promote cost-reflective tariffs,and incentivize energy-efficient and demand-responsive behavior among market participants.The method not only supports equitable and transparent market operations but also provides a generalizable,scalable foundation for modern electricity settlement platforms in increasingly complex and dynamic market environments.
基金supported in part by the Research on Key Technologies for the Development of an Active Balancing Cooperative Control Systemfor Distribution Networks and the National Natural Science Foundation of China under Grant 521532240029,Grant 62303006.
文摘To address the high costs and operational instability of distribution networks caused by the large-scale integration of distributed energy resources(DERs)(such as photovoltaic(PV)systems,wind turbines(WT),and energy storage(ES)devices),and the increased grid load fluctuations and safety risks due to uncoordinated electric vehicles(EVs)charging,this paper proposes a novel dual-scale hierarchical collaborative optimization strategy.This strategy decouples system-level economic dispatch from distributed EV agent control,effectively solving the resource coordination conflicts arising from the high computational complexity,poor scalability of existing centralized optimization,or the reliance on local information decision-making in fully decentralized frameworks.At the lower level,an EV charging and discharging model with a hybrid discrete-continuous action space is established,and optimized using an improved Parameterized Deep Q-Network(PDQN)algorithm,which directly handles mode selection and power regulation while embedding physical constraints to ensure safety.At the upper level,microgrid(MG)operators adopt a dynamic pricing strategy optimized through Deep Reinforcement Learning(DRL)to maximize economic benefits and achieve peak-valley shaving.Simulation results show that the proposed strategy outperforms traditional methods,reducing the total operating cost of the MG by 21.6%,decreasing the peak-to-valley load difference by 33.7%,reducing the number of voltage limit violations by 88.9%,and lowering the average electricity cost for EV users by 15.2%.This method brings a win-win result for operators and users,providing a reliable and efficient scheduling solution for distribution networks with high renewable energy penetration rates.
基金Project supported by the Ministry of Education’s Supply and Demand Matching Employment and Education Project(Grant No.2024110776329)。
文摘An in-built N^(+)pocket electrically doped tunnel field-effect transistor(ED-TFET)-based biosensor has been reported for the first time.The proposed device begins with a PN junction structure with a control gate(CG)and two polarity gates(PG1 and PG2).Utilizing the polarity bias concept,a narrow N^(+)pocket is formed between the source and channel without the need for additional doping steps,achieved through biasing PG1 and PG2 at-1.2 V and 1.2 V,respectively.This method not only addresses issues related to doping control but also eliminates constraints associated with thermal budgets and simplifies the fabrication process compared to traditional TFETs.To facilitate biomolecule sensing within the device,a nanogap cavity is formed in the gate dielectric by selectively etching a section of the polarity gate dielectric layer toward the source side.The investigation into the presence of neutral and charged molecules within the cavities has been conducted by examining variations in the electrical properties of the proposed biosensor.Key characteristics assessed include drain current,energy band,and electric field distribution.The performance of the biosensor is measured using various metrics such as drain current(I_(DS)),subthreshold swing(SS),threshold voltage(V_(TH)),drain current ratio(I_(ON)/I_(OFF)).The proposed in-built N^(+)pocket ED-TFET-based biosensor reaches a peak sensitivity of 1.08×10~(13)for a neutral biomolecule in a completely filled nanogap with a dielectric constant of 12.Additionally,the effects of cavity geometry and different fill factors(FFs)on sensitivity are studied.
基金supported by the National Natural Science Foundation of China(52471240)the Natural Science Foundation of Zhejiang Province(LZ23B030003)+2 种基金the Fundamental Research Funds for the Central Universities(226-2024-00075)support from the Engineering and Physical Sciences Research Council(EPSRC,UK)RiR grant-RIR18221018-1EU COST CA23155。
文摘The electric double layer(EDL)at the electrochemical interface is crucial for ion transport,charge transfer,and surface reactions in aqueous rechargeable zinc batteries(ARZBs).However,Zn anodes routinely encounter persistent dendrite growth and parasitic reactions,driven by the inhomogeneous charge distribution and water-dominated environment within the EDL.Compounding this,classical EDL theory,rooted in meanfield approximations,further fails to resolve molecular-scale interfacial dynamics under battery-operating conditions,limiting mechanistic insights.Herein,we established a multiscale theoretical calculation framework from single molecular characteristics to interfacial ion distribution,revealing the EDL’s structure and interactions between different ions and molecules,which helps us understand the parasitic processes in depth.Simulations demonstrate that water dipole and sulfate ion adsorption at the inner Helmholtz plane drives severe hydrogen evolution and by-product formation.Guided by these insights,we engineered a“water-poor and anion-expelled”EDL using 4,1’,6’-trichlorogalactosucrose(TGS)as an electrolyte additive.As a result,Zn||Zn symmetric cells with TGS exhibited stable cycling for over 4700 h under a current density of 1 mA cm^(−2),while NaV_(3)O_(8)·1.5H_(2)O-based full cells kept 90.4%of the initial specific capacity after 800 cycles at 5 A g^(−1).This work highlights the power of multiscale theoretical frameworks to unravel EDL complexities and guide high-performance ARZB design through integrated theory-experiment approaches.
基金supported by the National Natural Science Foundation of China(Grant No.12074187).
文摘Electrically controlled solid propellant(ECSP)offers multiple ignition and adjustable burning rate,serving as fuel for next-generation intelligent propulsion systems.To further enhance the combustion performance of ECSP,a method utilizing electrochemical and thermal decomposition catalysts has been proposed.In this work,we investigated the combustion characteristics of hydroxylamine nitrate(HAN)-based ECSP incorporating cerium oxide(CeO_(2))and graphene oxide(GO)by using an electrically controlled combustion test system.Electrochemical impedance spectroscopy(EIS)and linear sweep voltammetry(LSV)were used to measure the electrical conductibility and overpotential of ECSP with various additives,and Tafel curves were calculated.Thermogravimetric analysis coupled with differential scanning calorimetry(TG-DSC)was employed to investigate the thermal decomposition behavior of ECSP.While the addition of CeO_(2) and GO reduced the conductivity of ECSP,both catalysts exhibited strong electrocatalytic properties and facilitated the thermal decomposition of ECSP.Between two catalysts,GO demonstrated superior electrochemical catalytic performance but weaker thermal decomposition catalytic ability than CeO_(2).The addition of catalysts significantly enhanced the combustion performance of HAN-based ECSP.Specifically,the ignition delay time was shortened by 10%~20%.CeO_(2) raised the burning rate by approximately 20%but GO exhibited a remarkable boost of 40%in burning rate at high voltage.The combination of GO and PVA produced a flame-retardant substance that negatively impacted the ignition delay of ECSP and resulted in a smaller increase in the burning rate of ECSP at low ignition voltages.
基金supported by Natural Science Foundation of Wuhan(2024040701010051)Natural Science Foundation of Hubei(2023AFB111)and National Natural Science Foundation of China(52401108).
文摘To elucidate the accelerated degradation mechanisms of metallic interconnects in operational solid oxide fuel cells,the oxidation behavior of FSS430 ferritic stainless steel under the coupling of simultaneous electrical current and high-temperature exposure is investigated.Isothermal thermogravimetric analysis was employed to quantify oxidation kinetics,complemented by microstructural characterization using X-ray diffraction,scanning electron microscopy with energy-dispersive spectroscopy and transmission electron microscopy.Experimental results demonstrate that the applied current dramatically enhances oxidation rates,increasing specific mass gain from 0.25 mg/cm^(2)(0 A/cm^(2))to 5.20 mg/cm^(2)(0.2 A/cm^(2))and oxide scale thickness from 1.87 to 15.62μm after 200 h.This acceleration originates from current-induced electromigration forces that promote cationic transport through the oxide layer.The quantitative relationships between current density and oxidation parameters are established,enabling predictive modeling of interconnector degradation in solid oxide fuel cell(SOFC)systems.
基金supported by NARI Relays Electric Co.,Ltd.under the Project“Research on Evaluation of Clearing Results and Switching Criteria for Primary-Backup Systems in Electricity SpotMarkets”(Project No.CGSQ240800443).
文摘The construction of spot electricity markets plays a pivotal role in power system reforms,where market clearing systems profoundly influence market efficiency and security.Current clearing systems predominantly adopt a single-system architecture,with research focusing primarily on accelerating solution algorithms through techniques such as high-efficiency parallel solvers and staggered decomposition of mixed-integer programming models.Notably absent are systematic studies evaluating the adaptability of primary-backup clearing systems incontingency scenarios—a critical gap given redundant systems’expanding applications in operational environments.This paper proposes a comprehensive evaluation framework for analyzing dual-system adaptability,demonstrated through an in-depth case study of the Inner Mongolia power market.First,we establish the innovative“Dual-Active Heterogeneous”architecture that enables independent parallelized operation and fault-isolated redundancy.Subsequently,key performance indices are quantitatively evaluated across four critical dimensions:unit commitment decisions,generator output constraints,transmission section congestion patterns,and clearing price formation mechanisms.An integrated fuzzy evaluation methodology incorporating grey relational analysis is employed for objective indicator weighting,enabling systematic quantification of system superiority under specific grid operating states.Empirical results based on actual operational data from 200 generation units demonstrate the framework’s efficacy in guiding optimal system selection,with particularly strong performance observed during peak load periods.The proposed approach shows high generalization potential for other regional markets employing redundant clearing mechanisms—particularly those with increasing renewable penetration and associated uncertainty.
文摘According to the China Association of Automobile Manufacturers (CAAM),China's auto industry reached record highs in 2025,with production and sales at 34.53 million and 34.4 million vehicles,respectively.This secured China's position as the world's largest auto market for the 17th year in a row.
基金PEEP titration in ARDS patients using EIT combined with lung ultrasound,Key Laboratory of Emergency Trauma Research,Ministry of Education (KLET-202201)airway clearance protocol in ICU mechanically ventilated patients based on electrical impedance imaging technology,Natural Science Foundation of Hunan Province (2024JJ9148)effects of end expiratory positive pressure on lung re-expansion in patients with ARDS and intra-abdominal hypertension monitored using lung ultrasound,Natural Science Foundation of Hunan Province (2023JJ60308)
文摘BACKGROUND:Individualized positive end-expiratory pressure(PEEP)titration is a crucial technique in mechanical ventilation therapy for acute respiratory distress syndrome(ARDS)patients with intra-abdominal hypertension(IAH).This study aimed to evaluate the eff ectiveness of electrical impedance tomography(EIT)-guided PEEP titration in this population.METHODS:This prospective study enrolled 36 ARDS patients,including 22 patients with IAH and 14 without IAH.All the patients underwent EIT-guided PEEP titration at the intersection point between alveolar overdistension and collapse during a decremental PEEP trial.The changes in pulmonary ventilation distribution,respiratory mechanics and hemodynamics during the titration process were observed.RESULTS:After EIT-guided PEEP titration was performed,the PEEP,peak inspiratory pressure and plateau pressure increased significantly(P<0.05).Furthermore,no significant differences were observed in respiratory system compliance,tidal volume,driving pressure,or the 4*DP+RR index between the two groups(P>0.05).The mechanical power increased in the non-IAH(NIAH)group after PEEP titration(P<0.05).Ventilation in gravity-dependent lung regions significantly increased(P<0.05),and the oxygenation index(PaO2/FiO2)improved signifi cantly(P<0.05)in both groups.However,blood pressure,heart rate,respiratory rate,central venous pressure,and lactate levels did not signifi cantly change.In the IAH group,the PaO2/FiO2 ratio improved less than that in the NIAH group did(P<0.05).CONCLUSION:In our study,individualized PEEP titration guided by EIT improved oxygenation in ARDS patients with concomitant IAH without signifi cantly aff ecting hemodynamics.The presence of IAH may limit the improvement of oxygenation during EIT-guided PEEP titration.
