Wireless Body Area Network(WBAN)is essential for continuous health monitoring.However,they face energy efficiency challenges due to the low power consumption of sensor nodes.Current WBAN routing protocols face limitat...Wireless Body Area Network(WBAN)is essential for continuous health monitoring.However,they face energy efficiency challenges due to the low power consumption of sensor nodes.Current WBAN routing protocols face limitations in strategically minimizing energy consumption during the retrieval of vital health parameters.Efficient network traffic management remains a challenge,with existing approaches often resulting in increased delay and reduced throughput.Additionally,insufficient attention has been paid to enhancing channel capacity to maintain signal strength and mitigate fading effects under dynamic and robust operating scenarios.Several routing strategies and procedures have been developed to effectively reduce communication-related energy consumption based on the selection of relay nodes.The relay node selection is essential for data transmission in WBAN.This paper introduces an Adaptive Relay-Assisted Protocol(ARAP)for WBAN,a hybrid routing protocol designed to optimize energy use and Quality of Service(QoS)metrics such as network longevity,latency,throughput,and residual energy.ARAP employs neutrosophic relay node selection techniques,including the Analytic Hierarchy Process(AHP)and Technique for Order Preference by Similarity to Ideal Solution(TOPSIS)to optimally resolve data and decision-making uncertainties.The protocol was compared with existing protocols such as Low-Energy Adaptive Clustering Hierarchy(LEACH),Modified-Adaptive Threshold Testing and Evaluation Methodology for Performance Testing(M-ATTEMPT),Wireless Adaptive Sampling Protocol(WASP),and Tree-Based Multicast Quality of Service(TMQoS).The comparative results show that the ARAP significantly outperformed these protocols in terms of network longevity and energy efficiency.ARAP has lower communication cost,better throughput,reduced delay,increased network lifetime,and enhanced residual energy.The simulation results indicate that the proposed approach performed better than the conventional methods,with 68%,62%,25%,and 50%improvements in network longevity,residual energy,throughput,and latency,respectively.This significantly improves the functional lifespan of WBAN and makes them promising candidates for sophisticated health monitoring systems.展开更多
Environmental problems are intensifying due to the rapid growth of the population,industry,and urban infrastructure.This expansion has resulted in increased air and water pollution,intensified urban heat island effect...Environmental problems are intensifying due to the rapid growth of the population,industry,and urban infrastructure.This expansion has resulted in increased air and water pollution,intensified urban heat island effects,and greater runoff from parks and other green spaces.Addressing these challenges requires prioritizing green infrastructure and other sustainable urban development strategies.This study introduces a novel Integrated Decision Support System that combines Pythagorean Fuzzy Sets with the Advanced Alternative Ranking Order Method allowing for Two-Step Normalization(AAROM-TN),enhanced by a dual weighting strategy.The weighting approach integrates the Criteria Importance Through Intercriteria Correlation(CRITIC)method with the Criteria Importance through Means and Standard Deviation(CIMAS)technique.The originality of the proposed framework lies in its ability to objectively quantify criteria importance using CRITIC,incorporate decision-makers’preferences through CIMAS,and capture the uncertainty and hesitation inherent in human judgment via Pythagorean Fuzzy Sets.A case study evaluating green infrastructure alternatives in metropolitan regions demonstrates the applicability and effectiveness of the framework.A sensitivity analysis is conducted to examine how variations in criteria weights affect the rankings and to evaluate the robustness of the results.Furthermore,a comparative analysis highlights the practical and financial implications of each alternative by assessing their respective strengths and weaknesses.展开更多
With the increasing complexity of industrial automation,planetary gearboxes play a vital role in largescale equipment transmission systems,directly impacting operational efficiency and safety.Traditional maintenance s...With the increasing complexity of industrial automation,planetary gearboxes play a vital role in largescale equipment transmission systems,directly impacting operational efficiency and safety.Traditional maintenance strategies often struggle to accurately predict the degradation process of equipment,leading to excessive maintenance costs or potential failure risks.However,existing prediction methods based on statistical models are difficult to adapt to nonlinear degradation processes.To address these challenges,this study proposes a novel condition-based maintenance framework for planetary gearboxes.A comprehensive full-lifecycle degradation experiment was conducted to collect raw vibration signals,which were then processed using a temporal convolutional network autoencoder with multi-scale perception capability to extract deep temporal degradation features,enabling the collaborative extraction of longperiod meshing frequencies and short-term impact features from the vibration signals.Kernel principal component analysis was employed to fuse and normalize these features,enhancing the characterization of degradation progression.A nonlinear Wiener process was used to model the degradation trajectory,with a threshold decay function introduced to dynamically adjust maintenance strategies,and model parameters optimized through maximum likelihood estimation.Meanwhile,the maintenance strategy was optimized to minimize costs per unit time,determining the optimal maintenance timing and preventive maintenance threshold.The comprehensive indicator of degradation trends extracted by this method reaches 0.756,which is 41.2%higher than that of traditional time-domain features;the dynamic threshold strategy reduces the maintenance cost per unit time to 55.56,which is 8.9%better than that of the static threshold optimization.Experimental results demonstrate significant reductions in maintenance costs while enhancing system reliability and safety.This study realizes the organic integration of deep learning and reliability theory in the maintenance of planetary gearboxes,provides an interpretable solution for the predictive maintenance of complex mechanical systems,and promotes the development of condition-based maintenance strategies for planetary gearboxes.展开更多
Shock waves in the nozzle during supersonic separation under different conditions can disrupt the flow field’s thermodynamic equilibrium.While it contributes to the recovery of pressure energy,it also leads to the di...Shock waves in the nozzle during supersonic separation under different conditions can disrupt the flow field’s thermodynamic equilibrium.While it contributes to the recovery of pressure energy,it also leads to the dissipation of mechanical energy.This study aimed to investigate the effects of changes in back pressure on the shock wave position and its subsequent impact on the refrigeration performance of nozzles.A mathematical model for the supersonic gas in a nozzle was established and evaluated via experiments.The results show that when the back pressure is less than 0.2 MPa,no shock wave is generated in the nozzle,and high refrigeration and liquefaction efficiency can be ensured while effective pressure recovery is achieved.When the back pressure(pb)is increased from 0.3 to 0.6 MPa,the refrigeration efficiency of the nozzle decreases,and the shock wave position(x shock)is advanced from 157 to 118 mm.The maximum Mach number(Ma)that can be reached by the fluid in the nozzle is reduced from 1.97 to 1.27.When the back pressure is increased from 0.2 to 0.6 MPa,the minimum temperature is increased by 55.18 K.When the back pressure is greater than 0.3 MPa,the Mach number upstream of the shock wave is reduced from 1.97 to 1.27,the shock wave intensity is weakened,and the thickness of the boundary layer separation caused by the shock wave is also decreased accordingly.Therefore,to ensure refrigeration efficiency,measures should be taken to control the back pressure within a reasonable range.展开更多
Evaluating the effectivenes s of forest restoration projects is crucial for designing adaptive restoration strategies.However,existing studies have primarily focused on ecological outcomes while overlooking cost input...Evaluating the effectivenes s of forest restoration projects is crucial for designing adaptive restoration strategies.However,existing studies have primarily focused on ecological outcomes while overlooking cost inputs.This gap can lead to increased uncertainties in restoration planning.Here we investigated forest dynamics in China's Upper Yangtze River Basin(UYRB)using kernel Normalized Difference Vegetation Index(kNDVI),Leaf Area Index(LAI),Gross Primary Productivity(GPP),Ku-band Vegetation Optical Depth(Ku-VOD)time series and climate data from1982 to 2020.Subsequently,we employed a residual trend analysis integrating temporal effects to determine the relative contributions of climate change and human activities to forest dynamics before and after the implementation of forest restoration engineering in 1998.Additionally,we developed an Afforestation Efficiency Index(AEI)to quantitatively assess the cost efficiency of afforestation projects.Results indicated that forest in the UYRB showed sustained increases during 1982-2020,with most areas experiencing greater growth after 1998 than before.Temporal effects of climatic factors influenced over 42.7%of the forest,and incorporating time-lag and cumulative effects enhanced climate-based explanations of forest variations by 1.61-24.73%.Human activities emerged as the dominant driver of forest dynamics post 1998,whereas climate variables predominated before this period.The cost-effectiveness of forest restoration projects in the UYRB typically ranges from moderate to high,with higher success predominantly observed in the northeastern and eastern counties,while the central,western,and northwestern counties mainly showed relatively low efficiency.These findings stress the need for assessing forest restoration outcomes from both ecological and cost perspectives,and can offer valuable insights for optimizing the layout of forest restoration initiatives in the UYRB.展开更多
The goal of the present work is to demonstrate the potential of Artificial Neural Network(ANN)-driven Genetic Algorithm(GA)methods for energy efficiency and economic performance optimization of energy efficiency measu...The goal of the present work is to demonstrate the potential of Artificial Neural Network(ANN)-driven Genetic Algorithm(GA)methods for energy efficiency and economic performance optimization of energy efficiency measures in a multi-family house building in Greece.The energy efficiency measures include different heating/cooling systems(such as low-temperature and high-temperature heat pumps,natural gas boilers,split units),building envelope components for floor,walls,roof and windows of variable heat transfer coefficients,the installation of solar thermal collectors and PVs.The calculations of the building loads and investment and operating and maintenance costs of the measures are based on the methodology defined in Directive 2010/31/EU,while economic assumptions are based on EN 15459-1 standard.Typically,multi-objective optimization of energy efficiency measures often requires the simulation of very large numbers of cases involving numerous possible combinations,resulting in intense computational load.The results of the study indicate that ANN-driven GA methods can be used as an alternative,valuable tool for reliably predicting the optimal measures which minimize primary energy consumption and life cycle cost of the building with greatly reduced computational requirements.Through GA methods,the computational time needed for obtaining the optimal solutions is reduced by 96.4%-96.8%.展开更多
A nonfused ring electron acceptor(NFREA),designated as TT-Ph-C6,has been synthesized with the aim of enhancing the power conversion efficiency(PCE)of organic solar cells(OSCs).By integrating asymmetric phenylalkylamin...A nonfused ring electron acceptor(NFREA),designated as TT-Ph-C6,has been synthesized with the aim of enhancing the power conversion efficiency(PCE)of organic solar cells(OSCs).By integrating asymmetric phenylalkylamino side groups,TT-Ph-C6 demonstrates excellent solubility and its crystal structure exhibits compact packing structures with a three-dimensional molecular stacking network.These structural attributes markedly promote exciton diffusion and charge carrier mobility,particularly advantageous for the fabrication of thick-film devices.TT-Ph-C6-based devices have attained a PCE of 18.01%at a film thickness of 100 nm,and even at a film thickness of 300 nm,the PCE remains at 14.64%,surpassing that of devices based on 2BTh-2F.These remarkable properties position TT-Ph-C6 as a highly promising NFREA material for boosting the efficiency of OSCs.展开更多
Hard carbon is a vital anode material for sodium-ion batteries;however,the nonuniform growth of solid electrolyte interphase(SEI)film substantially diminishes its initial coulombic efficiency(ICE)and cycle life.The ch...Hard carbon is a vital anode material for sodium-ion batteries;however,the nonuniform growth of solid electrolyte interphase(SEI)film substantially diminishes its initial coulombic efficiency(ICE)and cycle life.The chemical and morphological properties of surface highly influence the electrode/electrolyte interfacial reactions.In this study,we have tuned orbital hybridization states forming an interface enriched with sp^(2) hybridized carbon(sp^(2)-C),which decreases the binding energy to solvent molecules and inhibits excessive solvent decomposition during SEI formation.Benefiting from successfully constructed inorganic-rich SEI,the ICE increased to 91%and sodium storage capacity reached 346 mAh/g.Besides,the capacity retention rate was 90.7%after 700 cycles at 1 A/g higher than pristine electrode(83.8%).展开更多
A series of blue and blue‑green Ir(Ⅲ)complexes has been investigated theoretically to explore their electronic structures,photophysical properties,efficiency roll‑off effect,and thermal activation delayed fluorescenc...A series of blue and blue‑green Ir(Ⅲ)complexes has been investigated theoretically to explore their electronic structures,photophysical properties,efficiency roll‑off effect,and thermal activation delayed fluorescence(TADF)properties.All calculations were performed using density functional theory(DFT)and time‑dependent density functional theory(TDDFT).Calculations for electronic structures,frontier molecular orbital characteristics(which determine the efficiency roll‑off effect of the complexes),and photophysical properties were conducted using the Gaussian 09 software package.The calculation of spin‑orbit coupling matrix elements<T|HSOC|S>,which determine the TADF properties of the complexes,was performed using the ORCA software package.The calculation results show that the auxiliary ligand tetraphenylimidodiphosphinate(tpip),a strong electron‑withdrawing group,can mitigate the efficiency roll‑off effect of the complex.Furthermore,TADF is observed in one of the designed complexes,(F_(3)Phppy)_(2)Ir(tpip),where F_(3)Phppy=2‑[4‑(2,4,6‑trifluorophenyl)phenyl]pyridine.展开更多
Coordinating light and nitrogen(N)distribution within a canopy is essential for improving rice yield and resource use efficiency.However,limited research has examined light and N distribution in response to planting d...Coordinating light and nitrogen(N)distribution within a canopy is essential for improving rice yield and resource use efficiency.However,limited research has examined light and N distribution in response to planting density and N rate,and their relationships with grain yield,radiation use efficiency(RUE),and N use efficiency for grain production(NUEg)in rice.A two-year field experiment was conducted with two hybrid varieties under three N levels,0 kg ha^(-1)(N1),90 kg ha^(-1)(N2)and 180 kg ha^(-1)(N3),and two planting densities,22.2 hills m-2(D1)and 33.3 hills m^(-2)(D2).Results showed 3.4%higher yield and 4.4%higher NUEg under N2D2 compared with N3D1.The extinction coefficient for N(K_(N))and light(K_(L))and their ratio(K_(N)/K_(L))at heading stage were significantly influenced by N rate,planting density,and their interaction.K_(N)decreased with the increase of N input or planting density.Compared to N1,K_(N)decreased by 43.5 and 58.8%under N2 and N3,respectively,while K_(N)under D2 decreased by 16.0%compared to D1.Higher K_(L)and K_(N)/K_(L)values occurred under low N rates,with opposite trends under high N rates.Increased planting density led to decreased K_(L)and K_(N)/K_(L)values.N2D2 demonstrated higher K_(L)and K_(N),and thus comparable K_(N)/K_(L),compared to N3D1.Correlation analysis revealed K_(L)negatively correlated with RUE,while K_(N)and K_(N)/K_(L)positively correlated with NUEg.These findings indicate that increasing planting density under reduced N input could maintain rice yield while enhancing resource use efficiency through regulation of canopy light and N distribution.展开更多
Transforming urban spatial structures to promote green and low-carbon development is an effective strategy.Although prior studies have examined the impact of urban polycentricity on carbon emissions and economic devel...Transforming urban spatial structures to promote green and low-carbon development is an effective strategy.Although prior studies have examined the impact of urban polycentricity on carbon emissions and economic development,research on its role in the synergistic relationship between these factors regarding carbon emission efficiency is limited.Furthermore,existing literature often overlooks nonlinear effects and interactions with other urban variables.This paper analyzed data from 295 Chinese cities in 2020,calculating urban population polycentricity,population dispersion indices,and carbon emission efficiency.Utilizing local spatial autocorrelation tools,we reveal interactions among urban population polycentricity,dispersion,carbon emissions,and carbon emission efficiency.We then employ a gradient boosting decision tree model(GBDT)to explore nonlinear and synergistic effects of polycentric urbanization.Key findings include:1)polycentric urbanization in Chinese cities exhibits significant spatial differentiation characteristics.The Polycentricity index is relatively high in economically developed eastern coastal regions with an overall low level,carbon emissions are concentrated in industrialized north-central cities and some Yangtze River Delta hubs,and carbon emission efficiency is the highest in the Yangtze River Delta while relatively low in Northeast China;there are significant spatially heterogeneous interaction characteristics among population polycentricity,population dispersion,carbon emissions,and carbon emission efficiency.2)Urban population polycentricity contributes 9.42%to total carbon emissions and 6.24%to carbon emission efficiency.3)The polycentricity index has a nonlinear impact on carbon emissions and carbon emission efficiency:no significant effect when below 0.50 or above 0.55,increased carbon emissions in 0.50-0.53,and reduced carbon emissions with improved efficiency in 0.53-0.55.4)The polycentricity index has an interaction effect with other variables;specifically,when the polycentricity index is between 0.53 and 0.55,its interaction with urban gross domestic product(GDP),urban population,urban built-up area,green coverage rate in built-up areas,urban technological expenditure,and the proportion of the output value of the secondary industry will reduce carbon emissions and improve carbon emission efficiency.These findings enhance the understanding of urban spatial structures and carbon emissions,providing valuable insights for policymakers in developing green and low-carbon strategies.展开更多
A high-sensitivity,low-noise single photon avalanche diode(SPAD)detector was presented based on a 180 nm BCD process.The proposed device utilizes a p-implant layer/high-voltage n-well(HVNW)junction to form a deep aval...A high-sensitivity,low-noise single photon avalanche diode(SPAD)detector was presented based on a 180 nm BCD process.The proposed device utilizes a p-implant layer/high-voltage n-well(HVNW)junction to form a deep avalanche multiplication region for near-infrared(NIR)sensitivity enhancement.By optimizing the device size and electric field of the guard ring,the fill factor(FF)is significantly improved,further increasing photon detection efficiency(PDE).To solve the dark noise caused by the increasing active diameter,a field polysilicon gate structure connected to the p+anode was investigated,effectively suppressing dark count noise by 76.6%.It is experimentally shown that when the active diameter increases from 5 to 10μm,the FF is significantly improved from 20.7%to 39.1%,and thus the peak PDE also rises from 13.3%to 25.8%.At an excess bias voltage of 5 V,a NIR photon detection probability(PDP)of 6.8%at 905 nm,a dark count rate(DCR)of 2.12 cps/μm^(2),an afterpulsing probability(AP)of 1.2%,and a timing jitter of 216 ps are achieved,demonstrating excellent single photon detection performance.展开更多
Emerging and powerful genome editing tools,particularly CRISPR/Cas9,are facilitating functional genomics research and accelerating crop improvement(Jiang et al.2021;Cao et al.2023;Chen C et al.2023;Liu et al.2023a).Ho...Emerging and powerful genome editing tools,particularly CRISPR/Cas9,are facilitating functional genomics research and accelerating crop improvement(Jiang et al.2021;Cao et al.2023;Chen C et al.2023;Liu et al.2023a).However,the detection and screening of transgenic lines remain major bottlenecks,being time-consuming,labor-intensive,and inefficient during transformation and subsequent mutation identification.A simple and efficient visual marker system plays a critical role in addressing these challenges.Recent studies demonstrated that the GmW1 and RUBY reporter systems were used to obtain visual transgenic soybean(Glycine max) plants(Chen L et al.2023;Chen et al.2024).展开更多
To solve the problems of abnormal larger, abnormal lower or even negative of target yield and fertilizing amount recommended by part of non-typical fertilizer effect equations using agricultural experiments and statis...To solve the problems of abnormal larger, abnormal lower or even negative of target yield and fertilizing amount recommended by part of non-typical fertilizer effect equations using agricultural experiments and statistical analysis software,Yangzhou analyzer（2.2）, regression analysis of Excel, which objected to local actual production, the study adopted the principle and method of basic knowledge and the frequency of using probability theory, and carried out statistical analysis on the rape field fertilizer experiment data by frequency analysis method, the rape yield after optimizing fertilizing amount was 1 732.4 kg/hm^2, the ranges of N, P and K optimal combinations were： N=210.36-149.64 kg/hm^2,P2O5=81.89-58.11 kg/hm^2, K2O=81.89-58.11 kg/hm^2,which was consistent with local actual production. This study was based on frequency analysis, using weighted average method to determine the production combinations of different yield objectives, hereinto, the combinations with high yield, high frequency of occurrence（dependable crop） and fertilizer-saving were viewed as the optimizing production measures, and they had the merits of increasing fertilization decision-making information, reducing or avoiding the risk of small probability event. The results of this study can solve the problem of abnormal values fertilizing amount and target yield recommended by non-typical fertilizer effect function, which did not accord with local actual production, caused by Yangzhou analyzer（2.2）, regression analysis of Excel, and DPS statistical analysis software. For the fertilizer effect function equation established by regression analysis which did not reach significance level using variance analysis, whether the method can be adapted to for carrying out fertilization decision-making, recommending optimization combinations of N, P and K fertilizers and yield under optimized fertilizing amount should be further researched in future working practice.展开更多
The critical role of patient-reported outcome measures(PROMs)in enhancing clinical decision-making and promoting patient-centered care has gained a profound significance in scientific research.PROMs encapsulate a pati...The critical role of patient-reported outcome measures(PROMs)in enhancing clinical decision-making and promoting patient-centered care has gained a profound significance in scientific research.PROMs encapsulate a patient's health status directly from their perspective,encompassing various domains such as symptom severity,functional status,and overall quality of life.By integrating PROMs into routine clinical practice and research,healthcare providers can achieve a more nuanced understanding of patient experiences and tailor treatments accordingly.The deployment of PROMs supports dynamic patient-provider interactions,fostering better patient engagement and adherence to tre-atment plans.Moreover,PROMs are pivotal in clinical settings for monitoring disease progression and treatment efficacy,particularly in chronic and mental health conditions.However,challenges in implementing PROMs include data collection and management,integration into existing health systems,and acceptance by patients and providers.Overcoming these barriers necessitates technological advancements,policy development,and continuous education to enhance the acceptability and effectiveness of PROMs.The paper concludes with recommendations for future research and policy-making aimed at optimizing the use and impact of PROMs across healthcare settings.展开更多
The growing need for sustainable energy solutions,driven by rising energy shortages,environmental concerns,and the depletion of conventional energy sources,has led to a significant focus on renewable energy.Solar ener...The growing need for sustainable energy solutions,driven by rising energy shortages,environmental concerns,and the depletion of conventional energy sources,has led to a significant focus on renewable energy.Solar energy,among the various renewable sources,is particularly appealing due to its abundant availability.However,the efficiency of commercial solar photovoltaic(PV)modules is hindered by several factors,notably their conversion efficiency,which averages around 19%.This efficiency can further decline to 10%–16%due to temperature increases during peak sunlight hours.This study investigates the cooling of PV modules by applying water to their front surface through Computational fluid dynamics(CFD).The study aimed to determine the optimal conditions for cooling the PV module by analyzing the interplay between water film thickness,Reynolds number,and their effects on temperature reduction and heat transfer.The CFD analysis revealed that the most effective cooling condition occurred with a 5 mm thick water film and a Reynolds number of 10.These specific parameters were found to maximize the heat transfer and temperature reduction efficiency.This finding is crucial for the development of practical and efficient cooling systems for PV modules,potentially leading to improved performance and longevity of solar panels.Alternative cooling fluids or advanced cooling techniques that might offer even better efficiency or practical benefits.展开更多
To solve problems of poor security guarantee and insufficient training efficiency in the conventional reinforcement learning methods for decision-making,this study proposes a hybrid framework to combine deep reinforce...To solve problems of poor security guarantee and insufficient training efficiency in the conventional reinforcement learning methods for decision-making,this study proposes a hybrid framework to combine deep reinforcement learning with rule-based decision-making methods.A risk assessment model for lane-change maneuvers considering uncertain predictions of surrounding vehicles is established as a safety filter to improve learning efficiency while correcting dangerous actions for safety enhancement.On this basis,a Risk-fused DDQN is constructed utilizing the model-based risk assessment and supervision mechanism.The proposed reinforcement learning algorithm sets up a separate experience buffer for dangerous trials and punishes such actions,which is shown to improve the sampling efficiency and training outcomes.Compared with conventional DDQN methods,the proposed algorithm improves the convergence value of cumulated reward by 7.6%and 2.2%in the two constructed scenarios in the simulation study and reduces the number of training episodes by 52.2%and 66.8%respectively.The success rate of lane change is improved by 57.3%while the time headway is increased at least by 16.5%in real vehicle tests,which confirms the higher training efficiency,scenario adaptability,and security of the proposed Risk-fused DDQN.展开更多
Water use efficiency(WUE),as a pivotal indicator of the coupling degree within the carbon–water cycle of ecosystems,holds considerable importance in assessment of the carbon–water balance within terrestrial ecosyste...Water use efficiency(WUE),as a pivotal indicator of the coupling degree within the carbon–water cycle of ecosystems,holds considerable importance in assessment of the carbon–water balance within terrestrial ecosystems.However,in the context of global warming,WUE evolution and its primary drivers on the Tibetan Plateau remain unclear.This study employed the ensemble empirical mode decomposition method and the random forest algorithm to decipher the nonlinear trends and drivers of WUE on the Tibetan Plateau in 2001–2020.Results indicated an annual mean WUE of 0.8088 gC/mm·m^(2)across the plateau,with a spatial gradient reflecting decrease from the southeast toward the northwest.Areas manifesting monotonous trends of increase or decrease in WUE accounted for 23.64%and 9.69%of the total,respectively.Remarkably,66.67%of the region exhibited trend reversals,i.e.,39.94%of the area of the Tibetan Plateau showed transition from a trend of increase to a trend of decrease,and 26.73%of the area demonstrated a shift from a trend of decrease to a trend of increase.Environmental factors accounted for 70.79%of the variability in WUE.The leaf area index and temperature served as the major driving forces of WUE variation.展开更多
Due to the numerous variables to take into account as well as the inherent ambiguity and uncertainty,evaluating educational institutions can be difficult.The concept of a possibility Pythagorean fuzzy hypersoft set(pP...Due to the numerous variables to take into account as well as the inherent ambiguity and uncertainty,evaluating educational institutions can be difficult.The concept of a possibility Pythagorean fuzzy hypersoft set(pPyFHSS)is more flexible in this regard than other theoretical fuzzy set-like models,even though some attempts have been made in the literature to address such uncertainties.This study investigates the elementary notions of pPyFHSS including its set-theoretic operations union,intersection,complement,OR-and AND-operations.Some results related to these operations are also modified for pPyFHSS.Additionally,the similarity measures between pPyFHSSs are formulated with the assistance of numerical examples and results.Lastly,an intelligent decision-assisted mechanism is developed with the proposal of a robust algorithm based on similarity measures for solving multi-attribute decision-making(MADM)problems.A case study that helps the decision-makers assess the best educational institution is discussed to validate the suggested system.The algorithmic results are compared with the most pertinent model to evaluate the adaptability of pPyFHSS,as it generalizes the classical possibility fuzzy set-like theoretical models.Similarly,while considering significant evaluating factors,the flexibility of pPyFHSS is observed through structural comparison.展开更多
The mechanism of hydrate-based desalination is that water molecules would transfer to the hydrate phase during gas hydrate formation process,while the salt ions would be conversely concentrated in the unreacted saltwa...The mechanism of hydrate-based desalination is that water molecules would transfer to the hydrate phase during gas hydrate formation process,while the salt ions would be conversely concentrated in the unreacted saltwater.However,the salt concentration of hydrate decomposed water and the desalination degree of hydrate phase are still unclear.The biggest challenge is how to effectively separate the hydrate phase and the remaining unreacted salt water,and then decompose the hydrate phase to measure the salt concentration of hydrate melt water.This work developed an apparatus and pressure-driven filtration method to efficiently separate the hydrate phase and the remaining unreacted saltwater.On this basis,the single hydrate phase was obtained,then it was dissociated and the salt concentration of hydrate melt water was measured.The experimental results demonstrate that when the initial salt mass concentration is 0.3% to 8.0%,the salt removal efficiency for NaCl solution is 15.9% to 29.8%by forming CO_(2) hydrate,while for CaCl_(2) solution is 28.9%to 45.5%.The solute CaCl_(2) is easier to be removed than solute NaCl.In addition,the salt removal efficiency for forming CO_(2) hydrate is higher than that for forming methane hydrate.The multi-stage desalination can continuously decrease the salt concentration of hydrate dissociated water,and the salt removal efficiency per stage is around 20%.展开更多
文摘Wireless Body Area Network(WBAN)is essential for continuous health monitoring.However,they face energy efficiency challenges due to the low power consumption of sensor nodes.Current WBAN routing protocols face limitations in strategically minimizing energy consumption during the retrieval of vital health parameters.Efficient network traffic management remains a challenge,with existing approaches often resulting in increased delay and reduced throughput.Additionally,insufficient attention has been paid to enhancing channel capacity to maintain signal strength and mitigate fading effects under dynamic and robust operating scenarios.Several routing strategies and procedures have been developed to effectively reduce communication-related energy consumption based on the selection of relay nodes.The relay node selection is essential for data transmission in WBAN.This paper introduces an Adaptive Relay-Assisted Protocol(ARAP)for WBAN,a hybrid routing protocol designed to optimize energy use and Quality of Service(QoS)metrics such as network longevity,latency,throughput,and residual energy.ARAP employs neutrosophic relay node selection techniques,including the Analytic Hierarchy Process(AHP)and Technique for Order Preference by Similarity to Ideal Solution(TOPSIS)to optimally resolve data and decision-making uncertainties.The protocol was compared with existing protocols such as Low-Energy Adaptive Clustering Hierarchy(LEACH),Modified-Adaptive Threshold Testing and Evaluation Methodology for Performance Testing(M-ATTEMPT),Wireless Adaptive Sampling Protocol(WASP),and Tree-Based Multicast Quality of Service(TMQoS).The comparative results show that the ARAP significantly outperformed these protocols in terms of network longevity and energy efficiency.ARAP has lower communication cost,better throughput,reduced delay,increased network lifetime,and enhanced residual energy.The simulation results indicate that the proposed approach performed better than the conventional methods,with 68%,62%,25%,and 50%improvements in network longevity,residual energy,throughput,and latency,respectively.This significantly improves the functional lifespan of WBAN and makes them promising candidates for sophisticated health monitoring systems.
基金supported by the Princess Nourah bint Abdulrahman University Researchers Supporting Project number(PNURSP2026R259)Princess Nourah bint Abdulrahman University,Riyadh,Saudi Arabia.Ashit Kumar Dutta would like to thank AlMaarefa University for supporting this research under project number MHIRSP2025017.
文摘Environmental problems are intensifying due to the rapid growth of the population,industry,and urban infrastructure.This expansion has resulted in increased air and water pollution,intensified urban heat island effects,and greater runoff from parks and other green spaces.Addressing these challenges requires prioritizing green infrastructure and other sustainable urban development strategies.This study introduces a novel Integrated Decision Support System that combines Pythagorean Fuzzy Sets with the Advanced Alternative Ranking Order Method allowing for Two-Step Normalization(AAROM-TN),enhanced by a dual weighting strategy.The weighting approach integrates the Criteria Importance Through Intercriteria Correlation(CRITIC)method with the Criteria Importance through Means and Standard Deviation(CIMAS)technique.The originality of the proposed framework lies in its ability to objectively quantify criteria importance using CRITIC,incorporate decision-makers’preferences through CIMAS,and capture the uncertainty and hesitation inherent in human judgment via Pythagorean Fuzzy Sets.A case study evaluating green infrastructure alternatives in metropolitan regions demonstrates the applicability and effectiveness of the framework.A sensitivity analysis is conducted to examine how variations in criteria weights affect the rankings and to evaluate the robustness of the results.Furthermore,a comparative analysis highlights the practical and financial implications of each alternative by assessing their respective strengths and weaknesses.
基金funded by scientific research projects under Grant JY2024B011.
文摘With the increasing complexity of industrial automation,planetary gearboxes play a vital role in largescale equipment transmission systems,directly impacting operational efficiency and safety.Traditional maintenance strategies often struggle to accurately predict the degradation process of equipment,leading to excessive maintenance costs or potential failure risks.However,existing prediction methods based on statistical models are difficult to adapt to nonlinear degradation processes.To address these challenges,this study proposes a novel condition-based maintenance framework for planetary gearboxes.A comprehensive full-lifecycle degradation experiment was conducted to collect raw vibration signals,which were then processed using a temporal convolutional network autoencoder with multi-scale perception capability to extract deep temporal degradation features,enabling the collaborative extraction of longperiod meshing frequencies and short-term impact features from the vibration signals.Kernel principal component analysis was employed to fuse and normalize these features,enhancing the characterization of degradation progression.A nonlinear Wiener process was used to model the degradation trajectory,with a threshold decay function introduced to dynamically adjust maintenance strategies,and model parameters optimized through maximum likelihood estimation.Meanwhile,the maintenance strategy was optimized to minimize costs per unit time,determining the optimal maintenance timing and preventive maintenance threshold.The comprehensive indicator of degradation trends extracted by this method reaches 0.756,which is 41.2%higher than that of traditional time-domain features;the dynamic threshold strategy reduces the maintenance cost per unit time to 55.56,which is 8.9%better than that of the static threshold optimization.Experimental results demonstrate significant reductions in maintenance costs while enhancing system reliability and safety.This study realizes the organic integration of deep learning and reliability theory in the maintenance of planetary gearboxes,provides an interpretable solution for the predictive maintenance of complex mechanical systems,and promotes the development of condition-based maintenance strategies for planetary gearboxes.
基金supported by the National Science and Technology Major Project of China(2025ZD1406703)the Open Fund of Key Laboratory of Oil&Gas Equipment,Ministry of Education(Southwest Petroleum University)(Grant No.OGE20230206).
文摘Shock waves in the nozzle during supersonic separation under different conditions can disrupt the flow field’s thermodynamic equilibrium.While it contributes to the recovery of pressure energy,it also leads to the dissipation of mechanical energy.This study aimed to investigate the effects of changes in back pressure on the shock wave position and its subsequent impact on the refrigeration performance of nozzles.A mathematical model for the supersonic gas in a nozzle was established and evaluated via experiments.The results show that when the back pressure is less than 0.2 MPa,no shock wave is generated in the nozzle,and high refrigeration and liquefaction efficiency can be ensured while effective pressure recovery is achieved.When the back pressure(pb)is increased from 0.3 to 0.6 MPa,the refrigeration efficiency of the nozzle decreases,and the shock wave position(x shock)is advanced from 157 to 118 mm.The maximum Mach number(Ma)that can be reached by the fluid in the nozzle is reduced from 1.97 to 1.27.When the back pressure is increased from 0.2 to 0.6 MPa,the minimum temperature is increased by 55.18 K.When the back pressure is greater than 0.3 MPa,the Mach number upstream of the shock wave is reduced from 1.97 to 1.27,the shock wave intensity is weakened,and the thickness of the boundary layer separation caused by the shock wave is also decreased accordingly.Therefore,to ensure refrigeration efficiency,measures should be taken to control the back pressure within a reasonable range.
基金supported by the National Natural Science Foundation of China(42071238)the Jiuzhaigou Post-Disaster Restoration and Reconstruction Program(5132202020000046)+1 种基金the Second Tibetan Plateau Scientific Expedition and Research Program(STEP)the Ministry of Science and Technology of the People's Republic of China(2019QZKK0402)。
文摘Evaluating the effectivenes s of forest restoration projects is crucial for designing adaptive restoration strategies.However,existing studies have primarily focused on ecological outcomes while overlooking cost inputs.This gap can lead to increased uncertainties in restoration planning.Here we investigated forest dynamics in China's Upper Yangtze River Basin(UYRB)using kernel Normalized Difference Vegetation Index(kNDVI),Leaf Area Index(LAI),Gross Primary Productivity(GPP),Ku-band Vegetation Optical Depth(Ku-VOD)time series and climate data from1982 to 2020.Subsequently,we employed a residual trend analysis integrating temporal effects to determine the relative contributions of climate change and human activities to forest dynamics before and after the implementation of forest restoration engineering in 1998.Additionally,we developed an Afforestation Efficiency Index(AEI)to quantitatively assess the cost efficiency of afforestation projects.Results indicated that forest in the UYRB showed sustained increases during 1982-2020,with most areas experiencing greater growth after 1998 than before.Temporal effects of climatic factors influenced over 42.7%of the forest,and incorporating time-lag and cumulative effects enhanced climate-based explanations of forest variations by 1.61-24.73%.Human activities emerged as the dominant driver of forest dynamics post 1998,whereas climate variables predominated before this period.The cost-effectiveness of forest restoration projects in the UYRB typically ranges from moderate to high,with higher success predominantly observed in the northeastern and eastern counties,while the central,western,and northwestern counties mainly showed relatively low efficiency.These findings stress the need for assessing forest restoration outcomes from both ecological and cost perspectives,and can offer valuable insights for optimizing the layout of forest restoration initiatives in the UYRB.
文摘The goal of the present work is to demonstrate the potential of Artificial Neural Network(ANN)-driven Genetic Algorithm(GA)methods for energy efficiency and economic performance optimization of energy efficiency measures in a multi-family house building in Greece.The energy efficiency measures include different heating/cooling systems(such as low-temperature and high-temperature heat pumps,natural gas boilers,split units),building envelope components for floor,walls,roof and windows of variable heat transfer coefficients,the installation of solar thermal collectors and PVs.The calculations of the building loads and investment and operating and maintenance costs of the measures are based on the methodology defined in Directive 2010/31/EU,while economic assumptions are based on EN 15459-1 standard.Typically,multi-objective optimization of energy efficiency measures often requires the simulation of very large numbers of cases involving numerous possible combinations,resulting in intense computational load.The results of the study indicate that ANN-driven GA methods can be used as an alternative,valuable tool for reliably predicting the optimal measures which minimize primary energy consumption and life cycle cost of the building with greatly reduced computational requirements.Through GA methods,the computational time needed for obtaining the optimal solutions is reduced by 96.4%-96.8%.
基金Financial support from the National Natural Science Foundation of China(22375024,21975031,21734009,51933001,22109080,and 52173174)the Natural Science Foundation of Shandong Province(No.ZR2022YQ45)+2 种基金the Taishan Scholars Program(Nos.tstp20221121 and tsqnz20221134)The Beijing Natural Science Foundation(No.2244073)supported by State Key Laboratory of Bio-Fibers and Eco-Textiles(Qingdao University)(RZ2200002821)is acknowledged.
文摘A nonfused ring electron acceptor(NFREA),designated as TT-Ph-C6,has been synthesized with the aim of enhancing the power conversion efficiency(PCE)of organic solar cells(OSCs).By integrating asymmetric phenylalkylamino side groups,TT-Ph-C6 demonstrates excellent solubility and its crystal structure exhibits compact packing structures with a three-dimensional molecular stacking network.These structural attributes markedly promote exciton diffusion and charge carrier mobility,particularly advantageous for the fabrication of thick-film devices.TT-Ph-C6-based devices have attained a PCE of 18.01%at a film thickness of 100 nm,and even at a film thickness of 300 nm,the PCE remains at 14.64%,surpassing that of devices based on 2BTh-2F.These remarkable properties position TT-Ph-C6 as a highly promising NFREA material for boosting the efficiency of OSCs.
基金support from the Heilongjiang Province"Double First Class"Discipline Collaborative Innovation Project(No.LJGXCG2023-061).
文摘Hard carbon is a vital anode material for sodium-ion batteries;however,the nonuniform growth of solid electrolyte interphase(SEI)film substantially diminishes its initial coulombic efficiency(ICE)and cycle life.The chemical and morphological properties of surface highly influence the electrode/electrolyte interfacial reactions.In this study,we have tuned orbital hybridization states forming an interface enriched with sp^(2) hybridized carbon(sp^(2)-C),which decreases the binding energy to solvent molecules and inhibits excessive solvent decomposition during SEI formation.Benefiting from successfully constructed inorganic-rich SEI,the ICE increased to 91%and sodium storage capacity reached 346 mAh/g.Besides,the capacity retention rate was 90.7%after 700 cycles at 1 A/g higher than pristine electrode(83.8%).
文摘A series of blue and blue‑green Ir(Ⅲ)complexes has been investigated theoretically to explore their electronic structures,photophysical properties,efficiency roll‑off effect,and thermal activation delayed fluorescence(TADF)properties.All calculations were performed using density functional theory(DFT)and time‑dependent density functional theory(TDDFT).Calculations for electronic structures,frontier molecular orbital characteristics(which determine the efficiency roll‑off effect of the complexes),and photophysical properties were conducted using the Gaussian 09 software package.The calculation of spin‑orbit coupling matrix elements<T|HSOC|S>,which determine the TADF properties of the complexes,was performed using the ORCA software package.The calculation results show that the auxiliary ligand tetraphenylimidodiphosphinate(tpip),a strong electron‑withdrawing group,can mitigate the efficiency roll‑off effect of the complex.Furthermore,TADF is observed in one of the designed complexes,(F_(3)Phppy)_(2)Ir(tpip),where F_(3)Phppy=2‑[4‑(2,4,6‑trifluorophenyl)phenyl]pyridine.
基金supported by the Hubei Provincial Science and Technology Project,China(2025CSA039)the National Natural Science Foundation of China(32001467)。
文摘Coordinating light and nitrogen(N)distribution within a canopy is essential for improving rice yield and resource use efficiency.However,limited research has examined light and N distribution in response to planting density and N rate,and their relationships with grain yield,radiation use efficiency(RUE),and N use efficiency for grain production(NUEg)in rice.A two-year field experiment was conducted with two hybrid varieties under three N levels,0 kg ha^(-1)(N1),90 kg ha^(-1)(N2)and 180 kg ha^(-1)(N3),and two planting densities,22.2 hills m-2(D1)and 33.3 hills m^(-2)(D2).Results showed 3.4%higher yield and 4.4%higher NUEg under N2D2 compared with N3D1.The extinction coefficient for N(K_(N))and light(K_(L))and their ratio(K_(N)/K_(L))at heading stage were significantly influenced by N rate,planting density,and their interaction.K_(N)decreased with the increase of N input or planting density.Compared to N1,K_(N)decreased by 43.5 and 58.8%under N2 and N3,respectively,while K_(N)under D2 decreased by 16.0%compared to D1.Higher K_(L)and K_(N)/K_(L)values occurred under low N rates,with opposite trends under high N rates.Increased planting density led to decreased K_(L)and K_(N)/K_(L)values.N2D2 demonstrated higher K_(L)and K_(N),and thus comparable K_(N)/K_(L),compared to N3D1.Correlation analysis revealed K_(L)negatively correlated with RUE,while K_(N)and K_(N)/K_(L)positively correlated with NUEg.These findings indicate that increasing planting density under reduced N input could maintain rice yield while enhancing resource use efficiency through regulation of canopy light and N distribution.
基金Under the auspices of National Natural Science Foundation of China(No.42571300)。
文摘Transforming urban spatial structures to promote green and low-carbon development is an effective strategy.Although prior studies have examined the impact of urban polycentricity on carbon emissions and economic development,research on its role in the synergistic relationship between these factors regarding carbon emission efficiency is limited.Furthermore,existing literature often overlooks nonlinear effects and interactions with other urban variables.This paper analyzed data from 295 Chinese cities in 2020,calculating urban population polycentricity,population dispersion indices,and carbon emission efficiency.Utilizing local spatial autocorrelation tools,we reveal interactions among urban population polycentricity,dispersion,carbon emissions,and carbon emission efficiency.We then employ a gradient boosting decision tree model(GBDT)to explore nonlinear and synergistic effects of polycentric urbanization.Key findings include:1)polycentric urbanization in Chinese cities exhibits significant spatial differentiation characteristics.The Polycentricity index is relatively high in economically developed eastern coastal regions with an overall low level,carbon emissions are concentrated in industrialized north-central cities and some Yangtze River Delta hubs,and carbon emission efficiency is the highest in the Yangtze River Delta while relatively low in Northeast China;there are significant spatially heterogeneous interaction characteristics among population polycentricity,population dispersion,carbon emissions,and carbon emission efficiency.2)Urban population polycentricity contributes 9.42%to total carbon emissions and 6.24%to carbon emission efficiency.3)The polycentricity index has a nonlinear impact on carbon emissions and carbon emission efficiency:no significant effect when below 0.50 or above 0.55,increased carbon emissions in 0.50-0.53,and reduced carbon emissions with improved efficiency in 0.53-0.55.4)The polycentricity index has an interaction effect with other variables;specifically,when the polycentricity index is between 0.53 and 0.55,its interaction with urban gross domestic product(GDP),urban population,urban built-up area,green coverage rate in built-up areas,urban technological expenditure,and the proportion of the output value of the secondary industry will reduce carbon emissions and improve carbon emission efficiency.These findings enhance the understanding of urban spatial structures and carbon emissions,providing valuable insights for policymakers in developing green and low-carbon strategies.
基金supported by the National Natural Science Foundation of China under Grant 62171233the Natural Science Foundation of China,Jiangsu Province under Grant BK20241891the Jiangsu Province Graduate Research and Practice Innovation Plan under Grants SJCX24_0313 and KYCX24_1169。
文摘A high-sensitivity,low-noise single photon avalanche diode(SPAD)detector was presented based on a 180 nm BCD process.The proposed device utilizes a p-implant layer/high-voltage n-well(HVNW)junction to form a deep avalanche multiplication region for near-infrared(NIR)sensitivity enhancement.By optimizing the device size and electric field of the guard ring,the fill factor(FF)is significantly improved,further increasing photon detection efficiency(PDE).To solve the dark noise caused by the increasing active diameter,a field polysilicon gate structure connected to the p+anode was investigated,effectively suppressing dark count noise by 76.6%.It is experimentally shown that when the active diameter increases from 5 to 10μm,the FF is significantly improved from 20.7%to 39.1%,and thus the peak PDE also rises from 13.3%to 25.8%.At an excess bias voltage of 5 V,a NIR photon detection probability(PDP)of 6.8%at 905 nm,a dark count rate(DCR)of 2.12 cps/μm^(2),an afterpulsing probability(AP)of 1.2%,and a timing jitter of 216 ps are achieved,demonstrating excellent single photon detection performance.
基金supported by the Jilin Science and Technology Development Program,China (20240602032RC)the Jilin Agricultural Science and Technology Innovation Project,China (CXGC2024ZD001)+1 种基金the Jilin Agricultural Science and Technology Innovation Project,China (CXGC2024ZY012)the Jilin Province Development and Reform Commission-Project for Improving the Independent Innovation Capacity of Major Grain Crops,China (2024C002)。
文摘Emerging and powerful genome editing tools,particularly CRISPR/Cas9,are facilitating functional genomics research and accelerating crop improvement(Jiang et al.2021;Cao et al.2023;Chen C et al.2023;Liu et al.2023a).However,the detection and screening of transgenic lines remain major bottlenecks,being time-consuming,labor-intensive,and inefficient during transformation and subsequent mutation identification.A simple and efficient visual marker system plays a critical role in addressing these challenges.Recent studies demonstrated that the GmW1 and RUBY reporter systems were used to obtain visual transgenic soybean(Glycine max) plants(Chen L et al.2023;Chen et al.2024).
基金Supported by Fiscal Subsidy Project Fund of National Soil Testing and Formulated Fertilization(Yun Cai Nong[2009]2045)~~
文摘To solve the problems of abnormal larger, abnormal lower or even negative of target yield and fertilizing amount recommended by part of non-typical fertilizer effect equations using agricultural experiments and statistical analysis software,Yangzhou analyzer（2.2）, regression analysis of Excel, which objected to local actual production, the study adopted the principle and method of basic knowledge and the frequency of using probability theory, and carried out statistical analysis on the rape field fertilizer experiment data by frequency analysis method, the rape yield after optimizing fertilizing amount was 1 732.4 kg/hm^2, the ranges of N, P and K optimal combinations were： N=210.36-149.64 kg/hm^2,P2O5=81.89-58.11 kg/hm^2, K2O=81.89-58.11 kg/hm^2,which was consistent with local actual production. This study was based on frequency analysis, using weighted average method to determine the production combinations of different yield objectives, hereinto, the combinations with high yield, high frequency of occurrence（dependable crop） and fertilizer-saving were viewed as the optimizing production measures, and they had the merits of increasing fertilization decision-making information, reducing or avoiding the risk of small probability event. The results of this study can solve the problem of abnormal values fertilizing amount and target yield recommended by non-typical fertilizer effect function, which did not accord with local actual production, caused by Yangzhou analyzer（2.2）, regression analysis of Excel, and DPS statistical analysis software. For the fertilizer effect function equation established by regression analysis which did not reach significance level using variance analysis, whether the method can be adapted to for carrying out fertilization decision-making, recommending optimization combinations of N, P and K fertilizers and yield under optimized fertilizing amount should be further researched in future working practice.
文摘The critical role of patient-reported outcome measures(PROMs)in enhancing clinical decision-making and promoting patient-centered care has gained a profound significance in scientific research.PROMs encapsulate a patient's health status directly from their perspective,encompassing various domains such as symptom severity,functional status,and overall quality of life.By integrating PROMs into routine clinical practice and research,healthcare providers can achieve a more nuanced understanding of patient experiences and tailor treatments accordingly.The deployment of PROMs supports dynamic patient-provider interactions,fostering better patient engagement and adherence to tre-atment plans.Moreover,PROMs are pivotal in clinical settings for monitoring disease progression and treatment efficacy,particularly in chronic and mental health conditions.However,challenges in implementing PROMs include data collection and management,integration into existing health systems,and acceptance by patients and providers.Overcoming these barriers necessitates technological advancements,policy development,and continuous education to enhance the acceptability and effectiveness of PROMs.The paper concludes with recommendations for future research and policy-making aimed at optimizing the use and impact of PROMs across healthcare settings.
文摘The growing need for sustainable energy solutions,driven by rising energy shortages,environmental concerns,and the depletion of conventional energy sources,has led to a significant focus on renewable energy.Solar energy,among the various renewable sources,is particularly appealing due to its abundant availability.However,the efficiency of commercial solar photovoltaic(PV)modules is hindered by several factors,notably their conversion efficiency,which averages around 19%.This efficiency can further decline to 10%–16%due to temperature increases during peak sunlight hours.This study investigates the cooling of PV modules by applying water to their front surface through Computational fluid dynamics(CFD).The study aimed to determine the optimal conditions for cooling the PV module by analyzing the interplay between water film thickness,Reynolds number,and their effects on temperature reduction and heat transfer.The CFD analysis revealed that the most effective cooling condition occurred with a 5 mm thick water film and a Reynolds number of 10.These specific parameters were found to maximize the heat transfer and temperature reduction efficiency.This finding is crucial for the development of practical and efficient cooling systems for PV modules,potentially leading to improved performance and longevity of solar panels.Alternative cooling fluids or advanced cooling techniques that might offer even better efficiency or practical benefits.
基金Supported by National Key Research and Development Program of China(Grant No.2022YFE0117100)National Science Foundation of China(Grant No.52102468,52325212)Fundamental Research Funds for the Central Universities。
文摘To solve problems of poor security guarantee and insufficient training efficiency in the conventional reinforcement learning methods for decision-making,this study proposes a hybrid framework to combine deep reinforcement learning with rule-based decision-making methods.A risk assessment model for lane-change maneuvers considering uncertain predictions of surrounding vehicles is established as a safety filter to improve learning efficiency while correcting dangerous actions for safety enhancement.On this basis,a Risk-fused DDQN is constructed utilizing the model-based risk assessment and supervision mechanism.The proposed reinforcement learning algorithm sets up a separate experience buffer for dangerous trials and punishes such actions,which is shown to improve the sampling efficiency and training outcomes.Compared with conventional DDQN methods,the proposed algorithm improves the convergence value of cumulated reward by 7.6%and 2.2%in the two constructed scenarios in the simulation study and reduces the number of training episodes by 52.2%and 66.8%respectively.The success rate of lane change is improved by 57.3%while the time headway is increased at least by 16.5%in real vehicle tests,which confirms the higher training efficiency,scenario adaptability,and security of the proposed Risk-fused DDQN.
基金National Nonprofit Institute Research Grant of CAF,No.CAFYBB2018ZA004,No.CAFYBB2023ZA009Fengyun Application Pioneering Project,No.FY-APP-ZX-2023.02。
文摘Water use efficiency(WUE),as a pivotal indicator of the coupling degree within the carbon–water cycle of ecosystems,holds considerable importance in assessment of the carbon–water balance within terrestrial ecosystems.However,in the context of global warming,WUE evolution and its primary drivers on the Tibetan Plateau remain unclear.This study employed the ensemble empirical mode decomposition method and the random forest algorithm to decipher the nonlinear trends and drivers of WUE on the Tibetan Plateau in 2001–2020.Results indicated an annual mean WUE of 0.8088 gC/mm·m^(2)across the plateau,with a spatial gradient reflecting decrease from the southeast toward the northwest.Areas manifesting monotonous trends of increase or decrease in WUE accounted for 23.64%and 9.69%of the total,respectively.Remarkably,66.67%of the region exhibited trend reversals,i.e.,39.94%of the area of the Tibetan Plateau showed transition from a trend of increase to a trend of decrease,and 26.73%of the area demonstrated a shift from a trend of decrease to a trend of increase.Environmental factors accounted for 70.79%of the variability in WUE.The leaf area index and temperature served as the major driving forces of WUE variation.
基金supported by the Deanship of Graduate Studies and Scientific Research at Qassim University(QU-APC-2024-9/1).
文摘Due to the numerous variables to take into account as well as the inherent ambiguity and uncertainty,evaluating educational institutions can be difficult.The concept of a possibility Pythagorean fuzzy hypersoft set(pPyFHSS)is more flexible in this regard than other theoretical fuzzy set-like models,even though some attempts have been made in the literature to address such uncertainties.This study investigates the elementary notions of pPyFHSS including its set-theoretic operations union,intersection,complement,OR-and AND-operations.Some results related to these operations are also modified for pPyFHSS.Additionally,the similarity measures between pPyFHSSs are formulated with the assistance of numerical examples and results.Lastly,an intelligent decision-assisted mechanism is developed with the proposal of a robust algorithm based on similarity measures for solving multi-attribute decision-making(MADM)problems.A case study that helps the decision-makers assess the best educational institution is discussed to validate the suggested system.The algorithmic results are compared with the most pertinent model to evaluate the adaptability of pPyFHSS,as it generalizes the classical possibility fuzzy set-like theoretical models.Similarly,while considering significant evaluating factors,the flexibility of pPyFHSS is observed through structural comparison.
基金The financial support from the National Natural Science Foundation of China(22127812,22278433,22178379)the National Key Research and Development Program of China(2021YFC2800902)are gratefully acknowledged。
文摘The mechanism of hydrate-based desalination is that water molecules would transfer to the hydrate phase during gas hydrate formation process,while the salt ions would be conversely concentrated in the unreacted saltwater.However,the salt concentration of hydrate decomposed water and the desalination degree of hydrate phase are still unclear.The biggest challenge is how to effectively separate the hydrate phase and the remaining unreacted salt water,and then decompose the hydrate phase to measure the salt concentration of hydrate melt water.This work developed an apparatus and pressure-driven filtration method to efficiently separate the hydrate phase and the remaining unreacted saltwater.On this basis,the single hydrate phase was obtained,then it was dissociated and the salt concentration of hydrate melt water was measured.The experimental results demonstrate that when the initial salt mass concentration is 0.3% to 8.0%,the salt removal efficiency for NaCl solution is 15.9% to 29.8%by forming CO_(2) hydrate,while for CaCl_(2) solution is 28.9%to 45.5%.The solute CaCl_(2) is easier to be removed than solute NaCl.In addition,the salt removal efficiency for forming CO_(2) hydrate is higher than that for forming methane hydrate.The multi-stage desalination can continuously decrease the salt concentration of hydrate dissociated water,and the salt removal efficiency per stage is around 20%.
