Enhancing the efficiency of Rankine cycles is crucial for improving the performance of thermal power plants,as it directly impacts operational costs and emissions in light of energy transition goals.This study sets it...Enhancing the efficiency of Rankine cycles is crucial for improving the performance of thermal power plants,as it directly impacts operational costs and emissions in light of energy transition goals.This study sets itself apart from existing research by applying a novel optimization technique to a basic ideal Rankine cycle,focusing on a specific power plant that has not been previously analyzed.Currently,this cycle operates at 41%efficiency and a steam quality of 76%,constrained by fixed operational parameters.The primary objectives are to increase thermal efficiency beyond 46%and raise steam quality above 85%,while adhering to operational limits:a boiler pressure not exceeding 15 MPa,condenser pressure not dropping below 10 kPa,and turbine temperature not surpassing 500℃.This study utilizes numerical simulations to model the effects of varying boiler pressure(Pb)and condenser pressure(Pc)within the ranges of 12MPa<Pb<15 MPa and 5 kPa<Pc<10 kPa.By systematically adjusting these parameters,the proposed aimto identify optimal conditions that maximize efficiency and performance within specified constraints.The findings will provide valuable insights for power plant operators seeking to optimize performance under real-world conditions,contributing to more efficient and sustainable power generation.展开更多
With the objective of investigating the basis of phosphorus(P)utilization efficiency(PUE),physiological and morphological traits,two P-efficient and two P-inefficient rapeseed(Brassica napus L.)cultivars were compared...With the objective of investigating the basis of phosphorus(P)utilization efficiency(PUE),physiological and morphological traits,two P-efficient and two P-inefficient rapeseed(Brassica napus L.)cultivars were compared at the seedling stage.P-efficient cultivars showed root morphological adaptation,high P uptake activity,and greater phospholipid degradation under low P stress.Improving root morphological adaptation and reducing lipid-P allocation could allow increasing PUE in rapeseed seedlings.展开更多
This study takes the panel data of 278 prefecture-level cities in China from 2011 to 2022 as samples,constructs a super-efficiency SBM model to measure urban energy-environment efficiency,uses the entropy method to sy...This study takes the panel data of 278 prefecture-level cities in China from 2011 to 2022 as samples,constructs a super-efficiency SBM model to measure urban energy-environment efficiency,uses the entropy method to synthesize the digital economy composite index,and introduces the green innovation index as a mediating variable.Breaking through the traditional analysis framework in the empirical method:Firstly,through the fixed-effects model and mediating-effect test,it reveals the direct impact of the digital economy on energy-environment efficiency and the transmission path of green innovation.Secondly,it divides the eastern,central,and western regions and low-carbon pilot cities for heterogeneity tests to identify the moderating effect of policy intervention.Thirdly,it strengthens the robustness of the conclusions by replacing the super-efficiency CCR model,shortening the sample period,and performing winsorization.The study finds that the digital economy significantly improves energy-environment efficiency through green technology innovation.These conclusions provide an empirical basis for optimizing the layout of digital infrastructure and improving the regional collaborative emission-reduction mechanism.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
The increase in soil temperature associated with climate change has introduced considerable challenges to crop production.Split nitrogen application(SN)represents a potential strategy for improving crop nitrogen use e...The increase in soil temperature associated with climate change has introduced considerable challenges to crop production.Split nitrogen application(SN)represents a potential strategy for improving crop nitrogen use efficiency and enhancing crop stress resistance.Nevertheless,the precise interaction between soil warming(SW)and SN remains unclear.In order to ascertain the impact of SW on maize growth and whether SN can improve the tolerance of maize to SW,a two-year field experiment was conducted(2022-2023).The aim was to examine the influence of two SW ranges(MT,warming 1.40℃;HT,warming 2.75℃)and two nitrogen application methods(N1,one-time basal application of nitrogen fertilizer;N2,one third of base nitrogen fertilizer+two thirds of jointing stage supplemental nitrogen fertilizer)on maize root growth,photosynthetic characteristics,nitrogen use efficiency,and yield.The results demonstrated that SW impeded root growth and precipitated the premature aging of maize leaves following anthesis,particularly in the HT,which led to a notable reduction in maize yield.In comparison to N1,SN has been shown to increase root length density by 8.54%,root bleeding rate by 8.57%,and enhance root distribution ratio in the middle soil layers(20-60 cm).The interaction between SW and SN had a notable impact on maize growth and yield.The SN improved the absorption and utilization efficiency of nitrogen by promoting root development and downward canopy growth,thus improving the tolerance of maize to SW at the later stage of growth.In particular,the N2HT resulted in a 14.51%increase in the photosynthetic rate,a 18.58%increase in nitrogen absorption efficiency,and a 18.32%increase in maize yield compared with N1HT.It can be posited that the SN represents a viable nitrogen management measure with the potential to enhance maize tolerance to soil high-temperature stress.展开更多
Trochoidal milling is known for its advantages in machining difficult-to-machine materials as it facilitates chip removal and tool cooling.However,the conventional trochoidal tool path presents challenges such as lowe...Trochoidal milling is known for its advantages in machining difficult-to-machine materials as it facilitates chip removal and tool cooling.However,the conventional trochoidal tool path presents challenges such as lower machining efficiency and longer machining time due to its time-varying cutter-workpiece engagement angle and a high percentage of non-cutting tool paths.To address these issues,this paper introduces a parameter-variant trochoidal-like(PVTR)tool path planning method for chatter-free and high-efficiency milling.This method ensures a constant engagement angle for each tool path period by adjusting the trochoidal radius and step.Initially,the nonlinear equation for the PVTR toolpath is established.Then,a segmented recurrence method is proposed to plan tool paths based on the desired engagement angle.The impact of trochoidal tool path parameters on the engagement angle is analyzed and coupled this information with the milling stability model based on spindle speed and engagement angle to determine the desired engagement angle throughout the machining process.Finally,several experimental tests are carried out using the bull-nose end mill to validate the feasibility and effectiveness of the proposed method.展开更多
Although phase-change random-access memory(PCRAM)is a promising next-generation nonvolatile memory technology,challenges remain in terms of reducing energy consumption.This is primarily be-cause the high thermal condu...Although phase-change random-access memory(PCRAM)is a promising next-generation nonvolatile memory technology,challenges remain in terms of reducing energy consumption.This is primarily be-cause the high thermal conductivities of phase-change materials(PCMs)promote Joule heating dissi-pation.Repeated phase transitions also induce long-range atomic diffusion,limiting the durability.To address these challenges,phase-change heterostructure(PCH)devices that incorporate confinement sub-layers based on transition-metal dichalcogenide materials have been developed.In this study,we engi-neered a PCH device by integrating HfTe_(2),which has low thermal conductivity and excellent stability,into the PCM to realize PCRAM with enhanced thermal efficiency and structural stability.HEAT sim-ulations were conducted to validate the superior heat confinement in the programming region of the HfTe_(2)-based PCH device.Moreover,electrical measurements of the device demonstrated its outstanding performance,which was characterized by a low RESET current(∼1.6 mA),stable two-order ON/OFF ratio,and exceptional cycling endurance(∼2×10^(7)).The structural integrity of the HfTe_(2)confinement sub-layer was confirmed using X-ray photoelectron spectroscopy and transmission electron microscopy.The material properties,including electrical conductivity,cohesive energy,and electronegativity,substantiated these findings.Collectively,these results revealed that the HfTe_(2)-based PCH device can achieve significant improvements in performance and reliability compared with conventional PCRAM devices.展开更多
Ultra-low emission of nitrogen oxide(NO_(x))is an irreversible trend for the development of waste-to-energy industry.But traditional approaches to remove NO_(x) face significant challenge s,such as low denitration eff...Ultra-low emission of nitrogen oxide(NO_(x))is an irreversible trend for the development of waste-to-energy industry.But traditional approaches to remove NO_(x) face significant challenge s,such as low denitration efficiency,complex denitration system,and high investment and operating cost.Here we put forward a novel polymer non-catalytic reduction(PNCR)technology that utilized a new type of polymer agent to remove NO_(x),and the proposed PNCR technology was applied to the existing waste-to-energy plant to test the denitration performance.The PNCR technology demonstrated excellent denitration performance with a NO_(x) emission concentration of<100 mg/Nm^(3) and high denitration efficiency of>75%at the temperature range of 800-900℃,which showed the application feasibility even on the complex and unstable industrial operating conditions.In addition,PNCR and hybrid polymer/selective non-catalytic reduction(PNCR/SNCR)technology possessed remarkable economic advantages including low investment fee and low operating cost of<10 CNY per ton of municipal solid waste(MSW)compared with selective catalytic reduction(SCR)technology.The excellent denitration performance of PNCR technology forebodes a broad industrial application prospect in the field of flue gas cleaning for waste-to-energy plants.展开更多
Trap-assisted charge recombination is one of the primary limitationsof restricting the performance of organic solar cells. However, effectivelyreducing the presence of traps in the photoactive layer remains challengin...Trap-assisted charge recombination is one of the primary limitationsof restricting the performance of organic solar cells. However, effectivelyreducing the presence of traps in the photoactive layer remains challenging.Herein, wide bandgap polymer donor PTzBI-dF is demonstrated as an effectivemodulator for enhancing the crystallinity of the bulk heterojunction active layerscomposed of D18 derivatives blended with Y6, leading to dense and orderedmolecular packings, and thus, improves photoluminescence quenching properties.As a result, the photovoltaic devices exhibit reduced trap-assisted charge recombinationlosses, achieving an optimized power conversion efficiency of over 19%.Besides the efficiency enhancement, the devices comprised of PTzBI-dF as athird component simultaneously attain decreased current leakage, improved chargecarrier mobilities, and suppressed bimolecular charge recombination, leading toreduced energy losses. The advanced crystalline structures induced by PTzBI-dFand its characteristics, such as well-aligned energy level, and complementaryabsorption spectra, are ascribed to the promising performance improvements.Our findings suggest that donor phase engineering is a feasible approach to tuning the molecular packings in the active layer, providingguidelines for designing effective morphology modulators for high-performance organic solar cells.展开更多
In this paper,a wideband true time delay line for X-band is designed to overcome the beam dispersion problem in a high-resolution spaceborne synthetic aperture radar phased array antenna system.The delay line loads th...In this paper,a wideband true time delay line for X-band is designed to overcome the beam dispersion problem in a high-resolution spaceborne synthetic aperture radar phased array antenna system.The delay line loads the electromagnetic bandgap structure on the upper surface of the substrate integrated waveguide.This is equivalent to including an additional inductance-capacitance for energy storage,which realizes the slow-wave effect.A microstrip line-SIW tapered transition structure is introduced to achieve a low loss and a large bandwidth.In the frequency band between 8-12 GHz,the measured results show that the delay multiplier of the delay line reaches 4 times,i.e.,delay line’s delay time is 4 times larger than 50Ωmicrostrip line with same length.Furthermore,the delay fluctuation,i.e.,the difference between the maximum and minimum delay as a percentage of the standard delay is only 2.5%,the insertion loss is less than-2.5 dB,and the return loss is less than-15 dB.Compared with the existing delay lines,the proposed delay line has the advantages of high delay efficiency,low delay error,wide bandwidth and low loss,which has good practical value and application prospects.展开更多
In order to accurately forecast the main engine fuel consumption and reduce the Energy Efficiency Operational Indicator(EEOI)of merchant ships in polar ice areas,the energy transfer relationship between ship-machine-p...In order to accurately forecast the main engine fuel consumption and reduce the Energy Efficiency Operational Indicator(EEOI)of merchant ships in polar ice areas,the energy transfer relationship between ship-machine-propeller is studied by analyzing the complex force situation during ship navigation and building a MATLAB/Simulink simulation platform based on multi-environmental resistance,propeller efficiency,main engine power,fuel consumption,fuel consumption rate and EEOI calculation module.Considering the environmental factors of wind,wave and ice,the route is divided into sections,the calculation of main engine power,main engine fuel consumption and EEOI for each section is completed,and the speed design is optimized based on the simulation model for each section.Under the requirements of the voyage plan,the optimization results show that the energy efficiency operation index of the whole route is reduced by 3.114%and the fuel consumption is reduced by 9.17 t.展开更多
Feed efficiency(FE)is a crucial economic trait that significantly impacts profitability in intensive sheep production,and can be evaluated by the residual feed intake(RFI)and feed conversion ratio(FCR).However,the und...Feed efficiency(FE)is a crucial economic trait that significantly impacts profitability in intensive sheep production,and can be evaluated by the residual feed intake(RFI)and feed conversion ratio(FCR).However,the underlying genetic mechanisms that underlie FE-related traits in sheep are not fully understood.Herein,we measured the FE-related traits of 1,280 Hu sheep and conducted the phenotype statistics and correlation analysis,the result showcase that there was a large variation for FE-related traits,and RFI was significant positive correlation with average daily feed intake(ADFI)and FCR.Moreover,a genome-wide association study(GWAS)was conducted using whole-genome resequencing data to investigate the genetic associations of ADFI,FCR and RFI.For ADFI and FCR traits,2 and one single nucleotide polymorphisms(SNPs)exceeded the genome-wide significance threshold,whereas ten and 5 SNPs exceeded the suggestive significance threshold.For RFI traits,only 4 SNPs exceeded the suggestive significance threshold.Finally,a total of 8 genes(LOC101121953,LOC101110202,CTNNA3,IZUMO3,PPM1E,YIPF7,ZSCAN12and LOC105603808)were identified as potential candidate genes for FE-related traits.Simultaneously,we further analyzed the effects of 2 candidate SNPs associated with RFI on growth and FE traits in enlarged experimental population,the results demonstrated that these 2 SNPs was not significantly associated with growth traits(P>0.05),but significantly related to RFI traits(P<0.05).These findings will provide valuable reference data and key genetic variants that can be used to effectively select feed-efficient individual in sheep breeding programs.展开更多
AI’s(artificial intelligence)groundbreaking impact on energy optimization and efficiency across various fields is growing,minimizing costs,increasing environmental sustainability,and improving energy resource managem...AI’s(artificial intelligence)groundbreaking impact on energy optimization and efficiency across various fields is growing,minimizing costs,increasing environmental sustainability,and improving energy resource management.As the global energy demand is predicted to rise,traditional energy management methods are proved to be inefficient,calling for new,innovative AI-driven solutions.This research unfolds the revolutionary impact of AI in energy optimization,focusing on its modern approaches,most significantly,predictive maintenance and analytics.A notable achievement is reflected by Stem Inc.,whose AI-powered energy storage system reduced its electricity costs by 60%,through predictive analytics of demand-based battery charging and discharging.Additionally,the study also investigates the logic behind AI’s energy optimization methods and AI’s role in crucial sectors like oil extraction,solar energy maintenance,and smart buildings,showcasing its flexibility across various fields.Finally,the study also uncovers a groundbreaking solution to improve AI’s role in energy optimization.Ultimately,this paper highlights the significance of AI in energy optimization and efficiency in the 21st century,the current methods used,and its projected growth and potential in the future.展开更多
Blockchain Technology(BT)has emerged as a transformative solution for improving the efficacy,security,and transparency of supply chain intelligence.Traditional Supply Chain Management(SCM)systems frequently have probl...Blockchain Technology(BT)has emerged as a transformative solution for improving the efficacy,security,and transparency of supply chain intelligence.Traditional Supply Chain Management(SCM)systems frequently have problems such as data silos,a lack of visibility in real time,fraudulent activities,and inefficiencies in tracking and traceability.Blockchain’s decentralized and irreversible ledger offers a solid foundation for dealing with these issues;it facilitates trust,security,and the sharing of data in real-time among all parties involved.Through an examination of critical technologies,methodology,and applications,this paper delves deeply into computer modeling based-blockchain framework within supply chain intelligence.The effect of BT on SCM is evaluated by reviewing current research and practical applications in the field.As part of the process,we delved through the research on blockchain-based supply chain models,smart contracts,Decentralized Applications(DApps),and how they connect to other cutting-edge innovations like Artificial Intelligence(AI)and the Internet of Things(IoT).To quantify blockchain’s performance,the study introduces analytical models for efficiency improvement,security enhancement,and scalability,enabling computational assessment and simulation of supply chain scenarios.These models provide a structured approach to predicting system performance under varying parameters.According to the results,BT increases efficiency by automating transactions using smart contracts,increases security by using cryptographic techniques,and improves transparency in the supply chain by providing immutable records.Regulatory concerns,challenges with interoperability,and scalability all work against broad adoption.To fully automate and intelligently integrate blockchain with AI and the IoT,additional research is needed to address blockchain’s current limitations and realize its potential for supply chain intelligence.展开更多
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
The rapid expansion of the Internet of Things(IoT)has led to the widespread adoption of sensor networks,with Long-Range Wide-Area Networks(LoRaWANs)emerging as a key technology due to their ability to support long-ran...The rapid expansion of the Internet of Things(IoT)has led to the widespread adoption of sensor networks,with Long-Range Wide-Area Networks(LoRaWANs)emerging as a key technology due to their ability to support long-range communication while minimizing power consumption.However,optimizing network performance and energy efficiency in dynamic,large-scale IoT environments remains a significant challenge.Traditional methods,such as the Adaptive Data Rate(ADR)algorithm,often fail to adapt effectively to rapidly changing network conditions and environmental factors.This study introduces a hybrid approach that leverages Deep Learning(DL)techniques,namely Long Short-Term Memory(LSTM)networks,and Machine Learning(ML)techniques,namely Artificial Neural Networks(ANNs),to optimize key network parameters such as Signal-to-Noise Ratio(SNR)and Received Signal Strength Indicator(RSSI).LSTM-ANN model trained on the“LoRaWAN Path Loss Dataset including Environmental Variables”from Medellín,Colombia,and the model demonstrated exceptional predictive accuracy,achieving an R2 score of 0.999,Mean Squared Error(MSE)of 0.041,Root Mean Squared Error(RMSE)of 0.203,and Mean Absolute Error(MAE)of 0.167,significantly outperforming traditional regression-based approaches.These findings highlight the potential of combining advanced ML and DL techniques to address the limitations of traditional optimization strategies in LoRaWAN.By providing a scalable and adaptive solution for large-scale IoT deployments,this work lays the foundation for real-world implementation,emphasizing the need for continuous learning frameworks to further enhance energy efficiency and network resilience in dynamic environments.展开更多
This study analyzes the energy impact of applying green roofs on flat roofs of existing buildings,assessing their potential to reduce the demand for non-renewable primary energy for heating and cooling.Through dynamic...This study analyzes the energy impact of applying green roofs on flat roofs of existing buildings,assessing their potential to reduce the demand for non-renewable primary energy for heating and cooling.Through dynamic numerical simulations conducted on two real buildings located near Florence,Italy,and modeled in 130 different European locations,with a particular focus on the Mediterranean climate,it was possible to quantify the energy benefits derived from the application of green roofs on existing structures.The results show that,while the effect on heating is limited,with an average reduction in energy demand of only a few percentage points,the impact on cooling is significantly more pronounced,with average savings of 20%in non-renewable primary energy,particularly in Mediterranean climates with high CDD(cooling degree days)values.The study confirms that green roofs can be an effective solution to improve the energy efficiency of existing buildings with flat roofs in the Mediterranean climate,in line with European goals for reducing CO₂emissions and promoting renewable energy.展开更多
Background Intestinal oxidative stress serves as an endogenous host defense against the gut microbiota by increas-ing energy expenditure and therefore decreasing feed efficiency(FE).Several systems coordinately regula...Background Intestinal oxidative stress serves as an endogenous host defense against the gut microbiota by increas-ing energy expenditure and therefore decreasing feed efficiency(FE).Several systems coordinately regulate redox bal-ance,including the mitochondrial respiratory chain,nicotinamide adenine dinucleotide phosphate(NADPH)oxidase,and different antioxidants.However,it remains unclear which redox balance compartments in the intestine are crucial for determining FE.Results In this study,we first screened the key targets of different metabolites and redox balance-related gene expression in broiler ceca.We then constructed a mouse colitis model to explore malic acid(MA)ability to allevi-ate intestinal inflammation.We further used controlled release technology to coat MA and investigated its effects on the intestinal redox status and FE in vivo.Finally,we examined the underlying mechanism by which MA modulated redox status using a porcine intestinal epithelial cell jejunum 2(IPEC-J2)cell model in vitro.Our results demonstrated that the MA/malic enzyme 3(ME3)pathway may play an important role in reducing oxidative stress in the broiler cecum.In addition,colon infusion of MA attenuated inflammatory phenotypes in the dextran sulfate sodium salt(DSS)induced mouse colitis model.Then,dietary supplementation with controlled-release MA pellet(MAP)reduced the feed to gain(F/G)ratio and promoted chicken growth,with reduced oxidative stress and increased bacterial diver-sity.Finally,the in vitro IPEC-J2 cell model revealed that ME3 mediated the effect of MA on cellular oxidative stress.Conclusion In summary,our study firstly revealed the important role of the MA/ME3 system in the hindgut of broiler chickens for improving intestinal health and FE,which may also be crucial for the implications of colon inflammation associated diseases.展开更多
This study investigates the traction performance and efficiency of a conical friction continuously variable trans-mission.A new mathematical model was developed and validated through experimental measurements using a ...This study investigates the traction performance and efficiency of a conical friction continuously variable trans-mission.A new mathematical model was developed and validated through experimental measurements using a custom-built test rig to predict these parameters accurately.The results showed a close correlation between the-oretical predictions and experimental data.Key findings include the impact of load on efficiency and the model’s ability to predict performance under various operating conditions.The study provides detailed insights into the dynamics of conical friction variator and demonstrates the model’s effectiveness in predicting real-world behav-ior.The developed model can assist in selecting optimal parameters during the design phase and can be applied to other developing variator systems to achieve maximum efficiency.展开更多
The Elongator complex is conserved in a wide range of species and plays crucial roles in diverse cellular processes.We have previously shown that the Elongator protein PoElp3 was involved in the asexual development,pa...The Elongator complex is conserved in a wide range of species and plays crucial roles in diverse cellular processes.We have previously shown that the Elongator protein PoElp3 was involved in the asexual development,pathogenicity,and autophagy of the rice blast fungus.In this study,we further revealed that PoElp3 functions via tRNA-mediated protein integrity.Phenotypic analyses revealed that overexpression of two of the tRNAs,tK(UUU)and tQ(UUG)could rescue the defects inΔPoelp3 strain.TMT-based proteomic and transcriptional analyses demonstrated that 386 proteins were down-regulated inΔPoelp3 strain compared with wild type strain Guy11,in a transcription-independent manner.Codon usage assays revealed an enrichment of Glutamine CAA-biased mRNA in the 386 proteins compared with the 70-15 genome.In addition to those reported previously,we also found that PoErp9,a sphingolipid C9-methyltransferase,was down-regulated in theΔPoelp3strain.Through an ILV2-specific integration of PoERP9-GFP into the wild type andΔPoelp3 strain,we were able to show that PoErp9 was positively regulated by PoElp3 translationally but not transcriptionally.Functional analyses revealed that PoErp9 was involved in the fungal growth,conidial development,pathogenicity,and TORrelated autophagy homeostasis in Pyricularia oryzae.Taken together,our results suggested that PoElp3 acts through the tRNA-mediated translational efficiency to regulate asexual development,pathogenicity,sphingolipid metabolism,and autophagy in the rice blast fungus.展开更多
文摘Enhancing the efficiency of Rankine cycles is crucial for improving the performance of thermal power plants,as it directly impacts operational costs and emissions in light of energy transition goals.This study sets itself apart from existing research by applying a novel optimization technique to a basic ideal Rankine cycle,focusing on a specific power plant that has not been previously analyzed.Currently,this cycle operates at 41%efficiency and a steam quality of 76%,constrained by fixed operational parameters.The primary objectives are to increase thermal efficiency beyond 46%and raise steam quality above 85%,while adhering to operational limits:a boiler pressure not exceeding 15 MPa,condenser pressure not dropping below 10 kPa,and turbine temperature not surpassing 500℃.This study utilizes numerical simulations to model the effects of varying boiler pressure(Pb)and condenser pressure(Pc)within the ranges of 12MPa<Pb<15 MPa and 5 kPa<Pc<10 kPa.By systematically adjusting these parameters,the proposed aimto identify optimal conditions that maximize efficiency and performance within specified constraints.The findings will provide valuable insights for power plant operators seeking to optimize performance under real-world conditions,contributing to more efficient and sustainable power generation.
基金supported by the National Key Research and Development Program of China(2024YFD2301200)National Nature Science Foundation of China(32172662).
文摘With the objective of investigating the basis of phosphorus(P)utilization efficiency(PUE),physiological and morphological traits,two P-efficient and two P-inefficient rapeseed(Brassica napus L.)cultivars were compared at the seedling stage.P-efficient cultivars showed root morphological adaptation,high P uptake activity,and greater phospholipid degradation under low P stress.Improving root morphological adaptation and reducing lipid-P allocation could allow increasing PUE in rapeseed seedlings.
文摘This study takes the panel data of 278 prefecture-level cities in China from 2011 to 2022 as samples,constructs a super-efficiency SBM model to measure urban energy-environment efficiency,uses the entropy method to synthesize the digital economy composite index,and introduces the green innovation index as a mediating variable.Breaking through the traditional analysis framework in the empirical method:Firstly,through the fixed-effects model and mediating-effect test,it reveals the direct impact of the digital economy on energy-environment efficiency and the transmission path of green innovation.Secondly,it divides the eastern,central,and western regions and low-carbon pilot cities for heterogeneity tests to identify the moderating effect of policy intervention.Thirdly,it strengthens the robustness of the conclusions by replacing the super-efficiency CCR model,shortening the sample period,and performing winsorization.The study finds that the digital economy significantly improves energy-environment efficiency through green technology innovation.These conclusions provide an empirical basis for optimizing the layout of digital infrastructure and improving the regional collaborative emission-reduction mechanism.
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 Natural Science Fund of China(31771724)the Key Research and Development Project of Shaanxi Province(2024NC-ZDCYL-01-10).
文摘The increase in soil temperature associated with climate change has introduced considerable challenges to crop production.Split nitrogen application(SN)represents a potential strategy for improving crop nitrogen use efficiency and enhancing crop stress resistance.Nevertheless,the precise interaction between soil warming(SW)and SN remains unclear.In order to ascertain the impact of SW on maize growth and whether SN can improve the tolerance of maize to SW,a two-year field experiment was conducted(2022-2023).The aim was to examine the influence of two SW ranges(MT,warming 1.40℃;HT,warming 2.75℃)and two nitrogen application methods(N1,one-time basal application of nitrogen fertilizer;N2,one third of base nitrogen fertilizer+two thirds of jointing stage supplemental nitrogen fertilizer)on maize root growth,photosynthetic characteristics,nitrogen use efficiency,and yield.The results demonstrated that SW impeded root growth and precipitated the premature aging of maize leaves following anthesis,particularly in the HT,which led to a notable reduction in maize yield.In comparison to N1,SN has been shown to increase root length density by 8.54%,root bleeding rate by 8.57%,and enhance root distribution ratio in the middle soil layers(20-60 cm).The interaction between SW and SN had a notable impact on maize growth and yield.The SN improved the absorption and utilization efficiency of nitrogen by promoting root development and downward canopy growth,thus improving the tolerance of maize to SW at the later stage of growth.In particular,the N2HT resulted in a 14.51%increase in the photosynthetic rate,a 18.58%increase in nitrogen absorption efficiency,and a 18.32%increase in maize yield compared with N1HT.It can be posited that the SN represents a viable nitrogen management measure with the potential to enhance maize tolerance to soil high-temperature stress.
基金supported by the National Natural Science Foundation of China(Grant Nos.U22A20202 and 52275477).
文摘Trochoidal milling is known for its advantages in machining difficult-to-machine materials as it facilitates chip removal and tool cooling.However,the conventional trochoidal tool path presents challenges such as lower machining efficiency and longer machining time due to its time-varying cutter-workpiece engagement angle and a high percentage of non-cutting tool paths.To address these issues,this paper introduces a parameter-variant trochoidal-like(PVTR)tool path planning method for chatter-free and high-efficiency milling.This method ensures a constant engagement angle for each tool path period by adjusting the trochoidal radius and step.Initially,the nonlinear equation for the PVTR toolpath is established.Then,a segmented recurrence method is proposed to plan tool paths based on the desired engagement angle.The impact of trochoidal tool path parameters on the engagement angle is analyzed and coupled this information with the milling stability model based on spindle speed and engagement angle to determine the desired engagement angle throughout the machining process.Finally,several experimental tests are carried out using the bull-nose end mill to validate the feasibility and effectiveness of the proposed method.
基金financially supported by a National Research Foundation of Korea(NRF)grant funded by the Korean government(No.2016R1A3B1908249,RS202400407199).
文摘Although phase-change random-access memory(PCRAM)is a promising next-generation nonvolatile memory technology,challenges remain in terms of reducing energy consumption.This is primarily be-cause the high thermal conductivities of phase-change materials(PCMs)promote Joule heating dissi-pation.Repeated phase transitions also induce long-range atomic diffusion,limiting the durability.To address these challenges,phase-change heterostructure(PCH)devices that incorporate confinement sub-layers based on transition-metal dichalcogenide materials have been developed.In this study,we engi-neered a PCH device by integrating HfTe_(2),which has low thermal conductivity and excellent stability,into the PCM to realize PCRAM with enhanced thermal efficiency and structural stability.HEAT sim-ulations were conducted to validate the superior heat confinement in the programming region of the HfTe_(2)-based PCH device.Moreover,electrical measurements of the device demonstrated its outstanding performance,which was characterized by a low RESET current(∼1.6 mA),stable two-order ON/OFF ratio,and exceptional cycling endurance(∼2×10^(7)).The structural integrity of the HfTe_(2)confinement sub-layer was confirmed using X-ray photoelectron spectroscopy and transmission electron microscopy.The material properties,including electrical conductivity,cohesive energy,and electronegativity,substantiated these findings.Collectively,these results revealed that the HfTe_(2)-based PCH device can achieve significant improvements in performance and reliability compared with conventional PCRAM devices.
基金supported by the National Natural Science Foundation of China(No.92367107)。
文摘Ultra-low emission of nitrogen oxide(NO_(x))is an irreversible trend for the development of waste-to-energy industry.But traditional approaches to remove NO_(x) face significant challenge s,such as low denitration efficiency,complex denitration system,and high investment and operating cost.Here we put forward a novel polymer non-catalytic reduction(PNCR)technology that utilized a new type of polymer agent to remove NO_(x),and the proposed PNCR technology was applied to the existing waste-to-energy plant to test the denitration performance.The PNCR technology demonstrated excellent denitration performance with a NO_(x) emission concentration of<100 mg/Nm^(3) and high denitration efficiency of>75%at the temperature range of 800-900℃,which showed the application feasibility even on the complex and unstable industrial operating conditions.In addition,PNCR and hybrid polymer/selective non-catalytic reduction(PNCR/SNCR)technology possessed remarkable economic advantages including low investment fee and low operating cost of<10 CNY per ton of municipal solid waste(MSW)compared with selective catalytic reduction(SCR)technology.The excellent denitration performance of PNCR technology forebodes a broad industrial application prospect in the field of flue gas cleaning for waste-to-energy plants.
基金support from the National Natural Science Foundation of China(62275057)the Guangxi Natural Science Foundation(2023GXNSFFA026004 and 2022GXNSFDA035066)+2 种基金the Innovation Project of Guangxi Graduate Education(YCBZ2024034)Natural Science Foundation of Ningbo under grant(2022J149)Natural Science Foundation of Ningbo under grant(2022A-230-G)
文摘Trap-assisted charge recombination is one of the primary limitationsof restricting the performance of organic solar cells. However, effectivelyreducing the presence of traps in the photoactive layer remains challenging.Herein, wide bandgap polymer donor PTzBI-dF is demonstrated as an effectivemodulator for enhancing the crystallinity of the bulk heterojunction active layerscomposed of D18 derivatives blended with Y6, leading to dense and orderedmolecular packings, and thus, improves photoluminescence quenching properties.As a result, the photovoltaic devices exhibit reduced trap-assisted charge recombinationlosses, achieving an optimized power conversion efficiency of over 19%.Besides the efficiency enhancement, the devices comprised of PTzBI-dF as athird component simultaneously attain decreased current leakage, improved chargecarrier mobilities, and suppressed bimolecular charge recombination, leading toreduced energy losses. The advanced crystalline structures induced by PTzBI-dFand its characteristics, such as well-aligned energy level, and complementaryabsorption spectra, are ascribed to the promising performance improvements.Our findings suggest that donor phase engineering is a feasible approach to tuning the molecular packings in the active layer, providingguidelines for designing effective morphology modulators for high-performance organic solar cells.
基金Supported by the National Natural Science Foundation of China(61971401)。
文摘In this paper,a wideband true time delay line for X-band is designed to overcome the beam dispersion problem in a high-resolution spaceborne synthetic aperture radar phased array antenna system.The delay line loads the electromagnetic bandgap structure on the upper surface of the substrate integrated waveguide.This is equivalent to including an additional inductance-capacitance for energy storage,which realizes the slow-wave effect.A microstrip line-SIW tapered transition structure is introduced to achieve a low loss and a large bandwidth.In the frequency band between 8-12 GHz,the measured results show that the delay multiplier of the delay line reaches 4 times,i.e.,delay line’s delay time is 4 times larger than 50Ωmicrostrip line with same length.Furthermore,the delay fluctuation,i.e.,the difference between the maximum and minimum delay as a percentage of the standard delay is only 2.5%,the insertion loss is less than-2.5 dB,and the return loss is less than-15 dB.Compared with the existing delay lines,the proposed delay line has the advantages of high delay efficiency,low delay error,wide bandwidth and low loss,which has good practical value and application prospects.
文摘In order to accurately forecast the main engine fuel consumption and reduce the Energy Efficiency Operational Indicator(EEOI)of merchant ships in polar ice areas,the energy transfer relationship between ship-machine-propeller is studied by analyzing the complex force situation during ship navigation and building a MATLAB/Simulink simulation platform based on multi-environmental resistance,propeller efficiency,main engine power,fuel consumption,fuel consumption rate and EEOI calculation module.Considering the environmental factors of wind,wave and ice,the route is divided into sections,the calculation of main engine power,main engine fuel consumption and EEOI for each section is completed,and the speed design is optimized based on the simulation model for each section.Under the requirements of the voyage plan,the optimization results show that the energy efficiency operation index of the whole route is reduced by 3.114%and the fuel consumption is reduced by 9.17 t.
基金supported by the National Key R&D Program of China(2021YFD1300901)the National Key R&D Young Scientists Project of China(2022YFD1302000)+1 种基金the Education Department of Gansu Province:Outstanding Postgraduate“Innovation Star”,China(2022CXZX-086)the Major Science and Technology Project of Gansu Province,China(22ZD6NC069)。
文摘Feed efficiency(FE)is a crucial economic trait that significantly impacts profitability in intensive sheep production,and can be evaluated by the residual feed intake(RFI)and feed conversion ratio(FCR).However,the underlying genetic mechanisms that underlie FE-related traits in sheep are not fully understood.Herein,we measured the FE-related traits of 1,280 Hu sheep and conducted the phenotype statistics and correlation analysis,the result showcase that there was a large variation for FE-related traits,and RFI was significant positive correlation with average daily feed intake(ADFI)and FCR.Moreover,a genome-wide association study(GWAS)was conducted using whole-genome resequencing data to investigate the genetic associations of ADFI,FCR and RFI.For ADFI and FCR traits,2 and one single nucleotide polymorphisms(SNPs)exceeded the genome-wide significance threshold,whereas ten and 5 SNPs exceeded the suggestive significance threshold.For RFI traits,only 4 SNPs exceeded the suggestive significance threshold.Finally,a total of 8 genes(LOC101121953,LOC101110202,CTNNA3,IZUMO3,PPM1E,YIPF7,ZSCAN12and LOC105603808)were identified as potential candidate genes for FE-related traits.Simultaneously,we further analyzed the effects of 2 candidate SNPs associated with RFI on growth and FE traits in enlarged experimental population,the results demonstrated that these 2 SNPs was not significantly associated with growth traits(P>0.05),but significantly related to RFI traits(P<0.05).These findings will provide valuable reference data and key genetic variants that can be used to effectively select feed-efficient individual in sheep breeding programs.
文摘AI’s(artificial intelligence)groundbreaking impact on energy optimization and efficiency across various fields is growing,minimizing costs,increasing environmental sustainability,and improving energy resource management.As the global energy demand is predicted to rise,traditional energy management methods are proved to be inefficient,calling for new,innovative AI-driven solutions.This research unfolds the revolutionary impact of AI in energy optimization,focusing on its modern approaches,most significantly,predictive maintenance and analytics.A notable achievement is reflected by Stem Inc.,whose AI-powered energy storage system reduced its electricity costs by 60%,through predictive analytics of demand-based battery charging and discharging.Additionally,the study also investigates the logic behind AI’s energy optimization methods and AI’s role in crucial sectors like oil extraction,solar energy maintenance,and smart buildings,showcasing its flexibility across various fields.Finally,the study also uncovers a groundbreaking solution to improve AI’s role in energy optimization.Ultimately,this paper highlights the significance of AI in energy optimization and efficiency in the 21st century,the current methods used,and its projected growth and potential in the future.
基金supported by Princess Nourah bint Abdulrahman University Researchers Supporting Project Number(PNURSP2025R97)Princess Nourah bint Abdulrahman University,Riyadh,Saudi Arabia。
文摘Blockchain Technology(BT)has emerged as a transformative solution for improving the efficacy,security,and transparency of supply chain intelligence.Traditional Supply Chain Management(SCM)systems frequently have problems such as data silos,a lack of visibility in real time,fraudulent activities,and inefficiencies in tracking and traceability.Blockchain’s decentralized and irreversible ledger offers a solid foundation for dealing with these issues;it facilitates trust,security,and the sharing of data in real-time among all parties involved.Through an examination of critical technologies,methodology,and applications,this paper delves deeply into computer modeling based-blockchain framework within supply chain intelligence.The effect of BT on SCM is evaluated by reviewing current research and practical applications in the field.As part of the process,we delved through the research on blockchain-based supply chain models,smart contracts,Decentralized Applications(DApps),and how they connect to other cutting-edge innovations like Artificial Intelligence(AI)and the Internet of Things(IoT).To quantify blockchain’s performance,the study introduces analytical models for efficiency improvement,security enhancement,and scalability,enabling computational assessment and simulation of supply chain scenarios.These models provide a structured approach to predicting system performance under varying parameters.According to the results,BT increases efficiency by automating transactions using smart contracts,increases security by using cryptographic techniques,and improves transparency in the supply chain by providing immutable records.Regulatory concerns,challenges with interoperability,and scalability all work against broad adoption.To fully automate and intelligently integrate blockchain with AI and the IoT,additional research is needed to address blockchain’s current limitations and realize its potential for supply chain intelligence.
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funded by King Saud University Researchers Supporting Project Number(RSPD2025R1007),King Saud University,Riyadh,Saudi Arabia.
文摘The rapid expansion of the Internet of Things(IoT)has led to the widespread adoption of sensor networks,with Long-Range Wide-Area Networks(LoRaWANs)emerging as a key technology due to their ability to support long-range communication while minimizing power consumption.However,optimizing network performance and energy efficiency in dynamic,large-scale IoT environments remains a significant challenge.Traditional methods,such as the Adaptive Data Rate(ADR)algorithm,often fail to adapt effectively to rapidly changing network conditions and environmental factors.This study introduces a hybrid approach that leverages Deep Learning(DL)techniques,namely Long Short-Term Memory(LSTM)networks,and Machine Learning(ML)techniques,namely Artificial Neural Networks(ANNs),to optimize key network parameters such as Signal-to-Noise Ratio(SNR)and Received Signal Strength Indicator(RSSI).LSTM-ANN model trained on the“LoRaWAN Path Loss Dataset including Environmental Variables”from Medellín,Colombia,and the model demonstrated exceptional predictive accuracy,achieving an R2 score of 0.999,Mean Squared Error(MSE)of 0.041,Root Mean Squared Error(RMSE)of 0.203,and Mean Absolute Error(MAE)of 0.167,significantly outperforming traditional regression-based approaches.These findings highlight the potential of combining advanced ML and DL techniques to address the limitations of traditional optimization strategies in LoRaWAN.By providing a scalable and adaptive solution for large-scale IoT deployments,this work lays the foundation for real-world implementation,emphasizing the need for continuous learning frameworks to further enhance energy efficiency and network resilience in dynamic environments.
文摘This study analyzes the energy impact of applying green roofs on flat roofs of existing buildings,assessing their potential to reduce the demand for non-renewable primary energy for heating and cooling.Through dynamic numerical simulations conducted on two real buildings located near Florence,Italy,and modeled in 130 different European locations,with a particular focus on the Mediterranean climate,it was possible to quantify the energy benefits derived from the application of green roofs on existing structures.The results show that,while the effect on heating is limited,with an average reduction in energy demand of only a few percentage points,the impact on cooling is significantly more pronounced,with average savings of 20%in non-renewable primary energy,particularly in Mediterranean climates with high CDD(cooling degree days)values.The study confirms that green roofs can be an effective solution to improve the energy efficiency of existing buildings with flat roofs in the Mediterranean climate,in line with European goals for reducing CO₂emissions and promoting renewable energy.
基金supported by the local innovative and research teams project of Guangdong province(2019BT02N630)national key research and development program(2022YFD1300401)+2 种基金Double first-class discipline promoting project(2023B10564001)National Natural Science Foundation of China(32272954)Natural Science Foundation of Guangdong Province,China(2024A1515013131).
文摘Background Intestinal oxidative stress serves as an endogenous host defense against the gut microbiota by increas-ing energy expenditure and therefore decreasing feed efficiency(FE).Several systems coordinately regulate redox bal-ance,including the mitochondrial respiratory chain,nicotinamide adenine dinucleotide phosphate(NADPH)oxidase,and different antioxidants.However,it remains unclear which redox balance compartments in the intestine are crucial for determining FE.Results In this study,we first screened the key targets of different metabolites and redox balance-related gene expression in broiler ceca.We then constructed a mouse colitis model to explore malic acid(MA)ability to allevi-ate intestinal inflammation.We further used controlled release technology to coat MA and investigated its effects on the intestinal redox status and FE in vivo.Finally,we examined the underlying mechanism by which MA modulated redox status using a porcine intestinal epithelial cell jejunum 2(IPEC-J2)cell model in vitro.Our results demonstrated that the MA/malic enzyme 3(ME3)pathway may play an important role in reducing oxidative stress in the broiler cecum.In addition,colon infusion of MA attenuated inflammatory phenotypes in the dextran sulfate sodium salt(DSS)induced mouse colitis model.Then,dietary supplementation with controlled-release MA pellet(MAP)reduced the feed to gain(F/G)ratio and promoted chicken growth,with reduced oxidative stress and increased bacterial diver-sity.Finally,the in vitro IPEC-J2 cell model revealed that ME3 mediated the effect of MA on cellular oxidative stress.Conclusion In summary,our study firstly revealed the important role of the MA/ME3 system in the hindgut of broiler chickens for improving intestinal health and FE,which may also be crucial for the implications of colon inflammation associated diseases.
基金supported by the Czech Technical University in Prague(Grant no.SGS23/108/OHK2/2T/12).
文摘This study investigates the traction performance and efficiency of a conical friction continuously variable trans-mission.A new mathematical model was developed and validated through experimental measurements using a custom-built test rig to predict these parameters accurately.The results showed a close correlation between the-oretical predictions and experimental data.Key findings include the impact of load on efficiency and the model’s ability to predict performance under various operating conditions.The study provides detailed insights into the dynamics of conical friction variator and demonstrates the model’s effectiveness in predicting real-world behav-ior.The developed model can assist in selecting optimal parameters during the design phase and can be applied to other developing variator systems to achieve maximum efficiency.
基金supported by National Natural Science Foundation of China(32172365 and 32272513)the Central Guidance on Local Science and Technology Development Fund of Fujian Province,China(2022L3088)the Innovative Research Funding of Fujian Agriculture and Forestry University,China(CXZX2020153D)。
文摘The Elongator complex is conserved in a wide range of species and plays crucial roles in diverse cellular processes.We have previously shown that the Elongator protein PoElp3 was involved in the asexual development,pathogenicity,and autophagy of the rice blast fungus.In this study,we further revealed that PoElp3 functions via tRNA-mediated protein integrity.Phenotypic analyses revealed that overexpression of two of the tRNAs,tK(UUU)and tQ(UUG)could rescue the defects inΔPoelp3 strain.TMT-based proteomic and transcriptional analyses demonstrated that 386 proteins were down-regulated inΔPoelp3 strain compared with wild type strain Guy11,in a transcription-independent manner.Codon usage assays revealed an enrichment of Glutamine CAA-biased mRNA in the 386 proteins compared with the 70-15 genome.In addition to those reported previously,we also found that PoErp9,a sphingolipid C9-methyltransferase,was down-regulated in theΔPoelp3strain.Through an ILV2-specific integration of PoERP9-GFP into the wild type andΔPoelp3 strain,we were able to show that PoErp9 was positively regulated by PoElp3 translationally but not transcriptionally.Functional analyses revealed that PoErp9 was involved in the fungal growth,conidial development,pathogenicity,and TORrelated autophagy homeostasis in Pyricularia oryzae.Taken together,our results suggested that PoElp3 acts through the tRNA-mediated translational efficiency to regulate asexual development,pathogenicity,sphingolipid metabolism,and autophagy in the rice blast fungus.
