Due to the lack of accurate data and complex parameterization,the prediction of groundwater depth is a chal-lenge for numerical models.Machine learning can effectively solve this issue and has been proven useful in th...Due to the lack of accurate data and complex parameterization,the prediction of groundwater depth is a chal-lenge for numerical models.Machine learning can effectively solve this issue and has been proven useful in the prediction of groundwater depth in many areas.In this study,two new models are applied to the prediction of groundwater depth in the Ningxia area,China.The two models combine the improved dung beetle optimizer(DBO)algorithm with two deep learning models:The Multi-head Attention-Convolution Neural Network-Long Short Term Memory networks(MH-CNN-LSTM)and the Multi-head Attention-Convolution Neural Network-Gated Recurrent Unit(MH-CNN-GRU).The models with DBO show better prediction performance,with larger R(correlation coefficient),RPD(residual prediction deviation),and lower RMSE(root-mean-square error).Com-pared with the models with the original DBO,the R and RPD of models with the improved DBO increase by over 1.5%,and the RMSE decreases by over 1.8%,indicating better prediction results.In addition,compared with the multiple linear regression model,a traditional statistical model,deep learning models have better prediction performance.展开更多
Soil improvement is one of the most important issues in geotechnical engineering practice.The wide application of traditional improvement techniques(cement/chemical materials)are limited due to damage ecological en-vi...Soil improvement is one of the most important issues in geotechnical engineering practice.The wide application of traditional improvement techniques(cement/chemical materials)are limited due to damage ecological en-vironment and intensify carbon emissions.However,the use of microbially induced calcium carbonate pre-cipitation(MICP)to obtain bio-cement is a novel technique with the potential to induce soil stability,providing a low-carbon,environment-friendly,and sustainable integrated solution for some geotechnical engineering pro-blems in the environment.This paper presents a comprehensive review of the latest progress in soil improvement based on the MICP strategy.It systematically summarizes and overviews the mineralization mechanism,influ-encing factors,improved methods,engineering characteristics,and current field application status of the MICP.Additionally,it also explores the limitations and correspondingly proposes prospective applications via the MICP approach for soil improvement.This review indicates that the utilization of different environmental calcium-based wastes in MICP and combination of materials and MICP are conducive to meeting engineering and market demand.Furthermore,we recommend and encourage global collaborative study and practice with a view to commercializing MICP technique in the future.The current review purports to provide insights for engineers and interdisciplinary researchers,and guidance for future engineering applications.展开更多
Carbon dioxide (CO_(2)) mineralization technology has attracted significant attention, due tothe synergistic terminal treatment of CO_(2) and industrial waste. The combined CO_(2) mineralizationprocess with steel ente...Carbon dioxide (CO_(2)) mineralization technology has attracted significant attention, due tothe synergistic terminal treatment of CO_(2) and industrial waste. The combined CO_(2) mineralizationprocess with steel enterprises is a promising route to simultaneously address CO_(2)emissions and SS treatment. Recently, a serial of the relevant work focus on a single type ofsteel slag (SS), and the understanding of CO_(2) absorption by mineralization of various SS isvery lacking.Meanwhile, it is urgent requirement for systematic summary and discussion onhow to make full use of the mineralized products produced after the mineralization of CO_(2)in SS. This review aims to investigate the progress of CO_(2) mineralization using SS, includingthe potential applications of mineralization products, as well as the environmental impactand risk assessment ofmineralization product applications. Currently, the application of SSmineralization products is primarily focused on their use as construction materials with loweconomic value. With usage of the mineralization products for ecological restoration (e.g.sandy soil remediation) was treated as an advanced route, but still remaining challenge infunctional materials preparation, and its technical economy and possible hazards need tobe further explored by long-term experimental tests.展开更多
Accurate short-term wind power forecast technique plays a crucial role in maintaining the safety and economic efficiency of smart grids.Although numerous studies have employed various methods to forecast wind power,th...Accurate short-term wind power forecast technique plays a crucial role in maintaining the safety and economic efficiency of smart grids.Although numerous studies have employed various methods to forecast wind power,there remains a research gap in leveraging swarm intelligence algorithms to optimize the hyperparameters of the Transformer model for wind power prediction.To improve the accuracy of short-term wind power forecast,this paper proposes a hybrid short-term wind power forecast approach named STL-IAOA-iTransformer,which is based on seasonal and trend decomposition using LOESS(STL)and iTransformer model optimized by improved arithmetic optimization algorithm(IAOA).First,to fully extract the power data features,STL is used to decompose the original data into components with less redundant information.The extracted components as well as the weather data are then input into iTransformer for short-term wind power forecast.The final predicted short-term wind power curve is obtained by combining the predicted components.To improve the model accuracy,IAOA is employed to optimize the hyperparameters of iTransformer.The proposed approach is validated using real-generation data from different seasons and different power stations inNorthwest China,and ablation experiments have been conducted.Furthermore,to validate the superiority of the proposed approach under different wind characteristics,real power generation data fromsouthwestChina are utilized for experiments.Thecomparative results with the other six state-of-the-art prediction models in experiments show that the proposed model well fits the true value of generation series and achieves high prediction accuracy.展开更多
Photosynthesis is one the most important chemical reaction in plants,and it is the ultimate energy source of any living organisms.The light and dark reactions are two essential phases of photosynthesis.Light reaction ...Photosynthesis is one the most important chemical reaction in plants,and it is the ultimate energy source of any living organisms.The light and dark reactions are two essential phases of photosynthesis.Light reaction harvests light energy to synthesize ATP and NADPH through an electron transport chain,and as well as giving out O_(2);dark reaction fixes CO_(2) into six carbon sugars by utilizing NADPH and energy from ATP.Subsequently,plants convert optical energy into chemical energy for maintaining growth and development through absorbing light energy.Here,firstly,we highlighted the biological importance of photosynthesis,and hormones and metabolites,photosynthetic and regulating enzymes,and signaling components that collectively regulate photosynthesis in tomato.Next,we reviewed the advances in tomato photosynthesis,including two aspects of genetic basis and genetic improvement.Numerous genes regulating tomato photosynthesis are gradually uncovered,and the interaction network among those genes remains to be constructed.Finally,the photosynthesis occurring in fruit of tomato and the relationship between photosynthesis in leaf and fruit were discussed.Leaves and fruits are photosynthate sources and sinks of tomato respectively,and interaction between photosynthesis in leaf and fruit exists.Additionally,future perspectives that needs to be addressed on tomato photosynthesis were proposed.展开更多
This study investigates the innovative reuse of sewage sludge with eco-friendly alkaline solutes to improve clayey soil without conventional cementitious binders.The unconfined compressive strength(UCS)was the main cr...This study investigates the innovative reuse of sewage sludge with eco-friendly alkaline solutes to improve clayey soil without conventional cementitious binders.The unconfined compressive strength(UCS)was the main criterion to assess the quality and effectiveness of the proposed solutions,as this test was performed to measure the strength of the stabilized clay by varying binders’dosages and curing times.Moreover,the direct shear test(DST)was used to investigate the Mohr-Coulomb parameters of the treated soil.Microstructure observations of the natural and treated soil were conducted using scanning electron microscope(SEM),energy-dispersive spectroscopy(EDS),and FTIR.Furthermore,toxicity characteristic leaching procedure(TCLP)tests were performed on the treated soil to investigate the leachability of metals.According to the results,using 2.5%of sewage sludge activated by NaOH and Na_(2)SiO_(3)increases the UCS values from 176 kPa to 1.46 MPa after 7 d and 56 d of curing,respectively.The results of the DST indicate that sewage sludge as a precursor increases cohesion and enhances frictional resistance,thereby improving the Mohr-Coulomb parameters of the stabilized soil.The SEM micrographs show that alkali-activated sewage sludge increases the integrity and reduces the cavity volumes in the stabilized soil.Moreover,TCLP tests revealed that the solubility of metals in the treated soil alkaliactivated by sewage sludge significantly decreased.This study suggests that using sewage sludge can replace cement and lime in ground improvement,improve the circular economy,and reduce the carbon footprint of construction projects.展开更多
Machine picking in cotton is an emerging practice in India,to solve the problems of labour shortages and production costs increasing.Cotton production has been declining in recent years;however,the high density planti...Machine picking in cotton is an emerging practice in India,to solve the problems of labour shortages and production costs increasing.Cotton production has been declining in recent years;however,the high density planting system(HDPS)offers a viable method to enhance productivity by increasing plant populations per unit area,optimizing resource utilization,and facilitating machine picking.Cotton is an indeterminate plant that produce excessive vegeta-tive growth in favorable soil fertility and moisture conditions,which posing challenges for efficient machine picking.To address this issue,the application of plant growth retardants(PGRs)is essential for controlling canopy architecture.PGRs reduce internode elongation,promote regulated branching,and increase plant compactness,making cotton plants better suited for machine picking.PGRs application also optimizes photosynthates distribution between veg-etative and reproductive growth,resulting in higher yields and improved fibre quality.The integration of HDPS and PGRs applications results in an optimal plant architecture for improving machine picking efficiency.However,the success of this integration is determined by some factors,including cotton variety,environmental conditions,and geographical variations.These approaches not only address yield stagnation and labour shortages but also help to establish more effective and sustainable cotton farming practices,resulting in higher cotton productivity.展开更多
To solve the problem of low detection accuracy for complex weld defects,the paper proposes a weld defects detection method based on improved YOLOv5s.To enhance the ability to focus on key information in feature maps,t...To solve the problem of low detection accuracy for complex weld defects,the paper proposes a weld defects detection method based on improved YOLOv5s.To enhance the ability to focus on key information in feature maps,the scSE attention mechanism is intro-duced into the backbone network of YOLOv5s.A Fusion-Block module and additional layers are added to the neck network of YOLOv5s to improve the effect of feature fusion,which is to meet the needs of complex object detection.To reduce the computation-al complexity of the model,the C3Ghost module is used to replace the CSP2_1 module in the neck network of YOLOv5s.The scSE-ASFF module is constructed and inserted between the neck network and the prediction end,which is to realize the fusion of features between the different layers.To address the issue of imbalanced sample quality in the dataset and improve the regression speed and accuracy of the loss function,the CIoU loss function in the YOLOv5s model is replaced with the Focal-EIoU loss function.Finally,ex-periments are conducted based on the collected weld defect dataset to verify the feasibility of the improved YOLOv5s for weld defects detection.The experimental results show that the precision and mAP of the improved YOLOv5s in detecting complex weld defects are as high as 83.4%and 76.1%,respectively,which are 2.5%and 7.6%higher than the traditional YOLOv5s model.The proposed weld defects detection method based on the improved YOLOv5s in this paper can effectively solve the problem of low weld defects detection accuracy.展开更多
This study tested the electrical conductivity and pressure sensitivity of lime⁃improved silty sand reinforced with Carbon Fiber Powder(CFP)as the conductive medium.The influence of CFP dosage,moisture content and curi...This study tested the electrical conductivity and pressure sensitivity of lime⁃improved silty sand reinforced with Carbon Fiber Powder(CFP)as the conductive medium.The influence of CFP dosage,moisture content and curing duration on the unconfined compressive strength,initial resistivity and pressure sensitivity of the improved soil was systematically analysed.The results showed that the unconfined compressive strength varied non⁃monotonically with increasing CFP dosage,reaching a peak at a dosage of 1.6%.Furthermore,the initial resistivity showed slight variations under different moisture conditions but eventually converged towards the conductive percolation threshold at a dosage of 2.4%.It is worth noting that CFP reinforced lime⁃improved silty sand(CRLS)exhibit a clear dynamic synchronization of strain with stress and resistivity rate of variation.The pressure sensitivity was optimized with CFP dosages ranging from 1.6%to 2.0%.Both insufficient and excessive dosages had a negative impact on pressure sensitivity.It is important to consider the weakening effect of high moisture content on the pressure sensitivity of the specimens in practical applications.展开更多
To improve the efficiency and accuracy of path planning for fan inspection tasks in thermal power plants,this paper proposes an intelligent inspection robot path planning scheme based on an improved A^(*)algorithm.The...To improve the efficiency and accuracy of path planning for fan inspection tasks in thermal power plants,this paper proposes an intelligent inspection robot path planning scheme based on an improved A^(*)algorithm.The inspection robot utilizes multiple sensors to monitor key parameters of the fans,such as vibration,noise,and bearing temperature,and upload the data to the monitoring center.The robot’s inspection path employs the improved A^(*)algorithm,incorporating obstacle penalty terms,path reconstruction,and smoothing optimization techniques,thereby achieving optimal path planning for the inspection robot in complex environments.Simulation results demonstrate that the improved A^(*)algorithm significantly outperforms the traditional A^(*)algorithm in terms of total path distance,smoothness,and detour rate,effectively improving the execution efficiency of inspection tasks.展开更多
Bacterial blight(BB),caused by Xanthomonas oryzae pathovar oryzae(Xoo),poses a significant threat to rice production,particularly in Asia and West Africa.Breeding resistance against BB in elite rice varieties is cruci...Bacterial blight(BB),caused by Xanthomonas oryzae pathovar oryzae(Xoo),poses a significant threat to rice production,particularly in Asia and West Africa.Breeding resistance against BB in elite rice varieties is crucial to advancing rice breeding program and supporting smallholder farmers.Transcription Activator-Like effectors(TALes)are key virulence factors in Xoo,with some targeting the susceptibility(S)genes such as the sugar transporter SWEET genes in rice.Among these,SWEET14 is an important S gene,with its promoter bound by the TALe TalC which exists across all sequenced African Xoo isolates.In the present study,we utilized CRISPR/Cas9-based cytidine and adenine base editors to alter the effector binding element(EBE)of TalC in the promoter of SWEET14 in rice cultivars Kitaake,IR24,and Zhonghua 11.Mutations with C to T changes in EBE led to reduced SWEET14 induction by TalC-containing Xoo strains,resulting in resistance to African Xoo isolates reliant on TalC for virulence.Conversely,A to G changes retained SWEET14 inducibility and susceptibility to Xoo in edited lines.Importantly,no off-target mutations were detected at predicted sites,and the edited lines exhibited no obvious defects in major agronomic traits in Kitaake.These results underscore the effectiveness of base editing systems for both molecular biology research and crop improvement endeavors.展开更多
When the maneuverability of a pursuer is not significantly higher than that of an evader,it will be difficult to intercept the evader with only one pursuer.Therefore,this article adopts a two-to-one differential game ...When the maneuverability of a pursuer is not significantly higher than that of an evader,it will be difficult to intercept the evader with only one pursuer.Therefore,this article adopts a two-to-one differential game strategy,the game of kind is generally considered to be angle-optimized,which allows unlimited turns,but these practices do not take into account the effect of acceleration,which does not correspond to the actual situation,thus,based on the angle-optimized,the acceleration optimization and the acceleration upper bound constraint are added into the game for consideration.A two-to-one differential game problem is proposed in the three-dimensional space,and an improved multi-objective grey wolf optimization(IMOGWO)algorithm is proposed to solve the optimal game point of this problem.With the equations that describe the relative motions between the pursuers and the evader in the three-dimensional space,a multi-objective function with constraints is given as the performance index to design an optimal strategy for the differential game.Then the optimal game point is solved by using the IMOGWO algorithm.It is proved based on Markov chains that with the IMOGWO,the Pareto solution set is the solution of the differential game.Finally,it is verified through simulations that the pursuers can capture the escapee,and via comparative experiments,it is shown that the IMOGWO algorithm performs well in terms of running time and memory usage.展开更多
Introducing B2 ordering can effectively improve the mechanical properties of lightweight refractory high-entropy alloys(LRHEAs).However,(Zr,Al)-enriched B2 precipitates generally reduce the ductility because their ord...Introducing B2 ordering can effectively improve the mechanical properties of lightweight refractory high-entropy alloys(LRHEAs).However,(Zr,Al)-enriched B2 precipitates generally reduce the ductility because their ordering characteristic is destroyed after dislocation shearing.Meanwhile,the local chemical order(LCO)cannot provide an adequate strengthening effect due to its small size.展开更多
Improving the quality of life for Earth's growing population is a complex task that requires the development of new technologies and materials. Perhaps the biggest challenge is access to clean and renewable energy...Improving the quality of life for Earth's growing population is a complex task that requires the development of new technologies and materials. Perhaps the biggest challenge is access to clean and renewable energy sources that can drive a sustainable future. Photovoltaics, today mainly represented by silicon-based solar cells, convert solar energy into electricity and is already an important component in the renewable energy portfolio.展开更多
An improved model based on you only look once version 8(YOLOv8)is proposed to solve the problem of low detection accuracy due to the diversity of object sizes in optical remote sensing images.Firstly,the feature pyram...An improved model based on you only look once version 8(YOLOv8)is proposed to solve the problem of low detection accuracy due to the diversity of object sizes in optical remote sensing images.Firstly,the feature pyramid network(FPN)structure of the original YOLOv8 mode is replaced by the generalized-FPN(GFPN)structure in GiraffeDet to realize the"cross-layer"and"cross-scale"adaptive feature fusion,to enrich the semantic information and spatial information on the feature map to improve the target detection ability of the model.Secondly,a pyramid-pool module of multi atrous spatial pyramid pooling(MASPP)is designed by using the idea of atrous convolution and feature pyramid structure to extract multi-scale features,so as to improve the processing ability of the model for multi-scale objects.The experimental results show that the detection accuracy of the improved YOLOv8 model on DIOR dataset is 92%and mean average precision(mAP)is 87.9%,respectively 3.5%and 1.7%higher than those of the original model.It is proved the detection and classification ability of the proposed model on multi-dimensional optical remote sensing target has been improved.展开更多
Liver transplantation(LT)has made significant progress in the treatment of end stage liver disease(ESLD).However,many patients still die from disease progression while awaiting transplantation.As the number of patient...Liver transplantation(LT)has made significant progress in the treatment of end stage liver disease(ESLD).However,many patients still die from disease progression while awaiting transplantation.As the number of patients on LT waiting lists is increasing,and the organ shortage crisis is obvious,various efforts have been made to increase the pool of available liver grafts[1].In addition to living donor liver transplantation(LDLT),improving the utilization rate of extended criteria donor(ECD)livers is an important way.However,under traditional cold storage,ECD livers are usually associated with a higher risk of ischemic biliary disease,early allograft dysfunction(EAD)or even primary nonfunction(PNF).The frequently described definition in the literature for ECD grafts generally includes elderly,steatotic,long cold ischemia time(CIT),grafts obtained from donation after circulatory death(DCD),split liver grafts,donors with increased risk of infectious disease transmission and prolonged donor intensive care unit stay[2].展开更多
In the first two months,a package of exist ing and incremental policies continued to take effect,industrial and service sectors grew rapidly,consumpt ion and investment continued to improve,employment was generally st...In the first two months,a package of exist ing and incremental policies continued to take effect,industrial and service sectors grew rapidly,consumpt ion and investment continued to improve,employment was generally stable,and new quality productive forces grew and thrived.The national economy got off to a steady start with new and positive development momentum.展开更多
Dryland regions face complex interactions between urbanization and ecological changes,where effective coordination is essential for enhancing sustainability and resilience.However,most studies concentrate on the natio...Dryland regions face complex interactions between urbanization and ecological changes,where effective coordination is essential for enhancing sustainability and resilience.However,most studies concentrate on the national or provincial scales,with insufficient research on county-level coordination,limiting the ability to provide targeted polifrom a precise perspective.This study addresses this gap by analyzing 39 counties within the Hohhot-Baotou-Ordos-Yulin Urban Agglomeration(HBOYUA),a typical dryland urban cluster in China.We use daytime and nighttime remote sensing images to track the spatio-temporal evolution of urbanization and ecological conditions from 1992 to 2023.A novel quantitative framework based on an improved coupling coordination degree(CCD)is proposed to assess their coordination relationship.The results reveal that:(1)Urbanization and ecological quality both exhibited fluctuating upward trends,with spatial heterogeneity increasing for urbanization and decreasing for the eco-environment.Regions with better ecological conditions had higher urbanization levels.(2)The overall coordinated level improved from imbalance(0.36)to low-level coordination(0.55),although its spatial distribution remained uneven,with central urban areas showing higher CCD than surrounding counties.(3)Socioeconomic factors exerted greater effects on CCD than natural factors,with GDP and land surface temperature(LST)playing a significant role in interaction analysis.(4)In western arid regions,urbanization did not necessarily harm ecosystems;instead,ecological conditions improved alongside urbanization.This research offers targeted and valuable references for county and city governments in resource allocation and sustainable development.The proposed methodology is also adaptable for urban resilience studies in other regions.展开更多
Dear Editor,This letter focuses on how an attacker can design suitable improved zero-dynamics (ZD) attack signal based on state estimates of target system. Improved ZD attack is to change zero dynamic gain matrix of a...Dear Editor,This letter focuses on how an attacker can design suitable improved zero-dynamics (ZD) attack signal based on state estimates of target system. Improved ZD attack is to change zero dynamic gain matrix of attack signal to a matrix with determinant greater than 1.展开更多
基金supported by the National Natural Science Foundation of China [grant numbers 42088101 and 42375048]。
文摘Due to the lack of accurate data and complex parameterization,the prediction of groundwater depth is a chal-lenge for numerical models.Machine learning can effectively solve this issue and has been proven useful in the prediction of groundwater depth in many areas.In this study,two new models are applied to the prediction of groundwater depth in the Ningxia area,China.The two models combine the improved dung beetle optimizer(DBO)algorithm with two deep learning models:The Multi-head Attention-Convolution Neural Network-Long Short Term Memory networks(MH-CNN-LSTM)and the Multi-head Attention-Convolution Neural Network-Gated Recurrent Unit(MH-CNN-GRU).The models with DBO show better prediction performance,with larger R(correlation coefficient),RPD(residual prediction deviation),and lower RMSE(root-mean-square error).Com-pared with the models with the original DBO,the R and RPD of models with the improved DBO increase by over 1.5%,and the RMSE decreases by over 1.8%,indicating better prediction results.In addition,compared with the multiple linear regression model,a traditional statistical model,deep learning models have better prediction performance.
基金funded by the National Natural Science Foundation of China(No.41962016)the Natural Science Foundation of NingXia(Nos.2023AAC02023,2023A1218,and 2021AAC02006).
文摘Soil improvement is one of the most important issues in geotechnical engineering practice.The wide application of traditional improvement techniques(cement/chemical materials)are limited due to damage ecological en-vironment and intensify carbon emissions.However,the use of microbially induced calcium carbonate pre-cipitation(MICP)to obtain bio-cement is a novel technique with the potential to induce soil stability,providing a low-carbon,environment-friendly,and sustainable integrated solution for some geotechnical engineering pro-blems in the environment.This paper presents a comprehensive review of the latest progress in soil improvement based on the MICP strategy.It systematically summarizes and overviews the mineralization mechanism,influ-encing factors,improved methods,engineering characteristics,and current field application status of the MICP.Additionally,it also explores the limitations and correspondingly proposes prospective applications via the MICP approach for soil improvement.This review indicates that the utilization of different environmental calcium-based wastes in MICP and combination of materials and MICP are conducive to meeting engineering and market demand.Furthermore,we recommend and encourage global collaborative study and practice with a view to commercializing MICP technique in the future.The current review purports to provide insights for engineers and interdisciplinary researchers,and guidance for future engineering applications.
基金supported by the National Key Research and Development Program(Nos.2023YFC3707101 and 2023YFF0614301)the Tsinghua University Initiative Scientific Research Program(No.2023Z02JMP001)the Linghang Project of School of Environment(No.025108011).
文摘Carbon dioxide (CO_(2)) mineralization technology has attracted significant attention, due tothe synergistic terminal treatment of CO_(2) and industrial waste. The combined CO_(2) mineralizationprocess with steel enterprises is a promising route to simultaneously address CO_(2)emissions and SS treatment. Recently, a serial of the relevant work focus on a single type ofsteel slag (SS), and the understanding of CO_(2) absorption by mineralization of various SS isvery lacking.Meanwhile, it is urgent requirement for systematic summary and discussion onhow to make full use of the mineralized products produced after the mineralization of CO_(2)in SS. This review aims to investigate the progress of CO_(2) mineralization using SS, includingthe potential applications of mineralization products, as well as the environmental impactand risk assessment ofmineralization product applications. Currently, the application of SSmineralization products is primarily focused on their use as construction materials with loweconomic value. With usage of the mineralization products for ecological restoration (e.g.sandy soil remediation) was treated as an advanced route, but still remaining challenge infunctional materials preparation, and its technical economy and possible hazards need tobe further explored by long-term experimental tests.
基金supported by Yunnan Provincial Basic Research Project(202401AT070344,202301AT070443)National Natural Science Foundation of China(62263014,52207105)+1 种基金Yunnan Lancang-Mekong International Electric Power Technology Joint Laboratory(202203AP140001)Major Science and Technology Projects in Yunnan Province(202402AG050006).
文摘Accurate short-term wind power forecast technique plays a crucial role in maintaining the safety and economic efficiency of smart grids.Although numerous studies have employed various methods to forecast wind power,there remains a research gap in leveraging swarm intelligence algorithms to optimize the hyperparameters of the Transformer model for wind power prediction.To improve the accuracy of short-term wind power forecast,this paper proposes a hybrid short-term wind power forecast approach named STL-IAOA-iTransformer,which is based on seasonal and trend decomposition using LOESS(STL)and iTransformer model optimized by improved arithmetic optimization algorithm(IAOA).First,to fully extract the power data features,STL is used to decompose the original data into components with less redundant information.The extracted components as well as the weather data are then input into iTransformer for short-term wind power forecast.The final predicted short-term wind power curve is obtained by combining the predicted components.To improve the model accuracy,IAOA is employed to optimize the hyperparameters of iTransformer.The proposed approach is validated using real-generation data from different seasons and different power stations inNorthwest China,and ablation experiments have been conducted.Furthermore,to validate the superiority of the proposed approach under different wind characteristics,real power generation data fromsouthwestChina are utilized for experiments.Thecomparative results with the other six state-of-the-art prediction models in experiments show that the proposed model well fits the true value of generation series and achieves high prediction accuracy.
基金supported by grants from the National Key Research&Development Plan(Grants Nos.2022YFF10030022022YFD1200502)+7 种基金National Natural Science Foundation of China(Grant Nos.3237269631991182)Wuhan Biological Breeding Major Project(Grant No.2022021302024852)Key Project of Hubei Hongshan Laboratory(2021hszd007)HZAU-AGIS Cooperation Fund(Grant No.SZYJY2023022)Funds for High Quality Development of Hubei Seed Industry(HBZY2023B004)Hubei Agriculture Research System(2023HBSTX4-06)Hubei Key Research&Development Plan(Grants Nos.2022BBA0066,2022BBA0062)。
文摘Photosynthesis is one the most important chemical reaction in plants,and it is the ultimate energy source of any living organisms.The light and dark reactions are two essential phases of photosynthesis.Light reaction harvests light energy to synthesize ATP and NADPH through an electron transport chain,and as well as giving out O_(2);dark reaction fixes CO_(2) into six carbon sugars by utilizing NADPH and energy from ATP.Subsequently,plants convert optical energy into chemical energy for maintaining growth and development through absorbing light energy.Here,firstly,we highlighted the biological importance of photosynthesis,and hormones and metabolites,photosynthetic and regulating enzymes,and signaling components that collectively regulate photosynthesis in tomato.Next,we reviewed the advances in tomato photosynthesis,including two aspects of genetic basis and genetic improvement.Numerous genes regulating tomato photosynthesis are gradually uncovered,and the interaction network among those genes remains to be constructed.Finally,the photosynthesis occurring in fruit of tomato and the relationship between photosynthesis in leaf and fruit were discussed.Leaves and fruits are photosynthate sources and sinks of tomato respectively,and interaction between photosynthesis in leaf and fruit exists.Additionally,future perspectives that needs to be addressed on tomato photosynthesis were proposed.
文摘This study investigates the innovative reuse of sewage sludge with eco-friendly alkaline solutes to improve clayey soil without conventional cementitious binders.The unconfined compressive strength(UCS)was the main criterion to assess the quality and effectiveness of the proposed solutions,as this test was performed to measure the strength of the stabilized clay by varying binders’dosages and curing times.Moreover,the direct shear test(DST)was used to investigate the Mohr-Coulomb parameters of the treated soil.Microstructure observations of the natural and treated soil were conducted using scanning electron microscope(SEM),energy-dispersive spectroscopy(EDS),and FTIR.Furthermore,toxicity characteristic leaching procedure(TCLP)tests were performed on the treated soil to investigate the leachability of metals.According to the results,using 2.5%of sewage sludge activated by NaOH and Na_(2)SiO_(3)increases the UCS values from 176 kPa to 1.46 MPa after 7 d and 56 d of curing,respectively.The results of the DST indicate that sewage sludge as a precursor increases cohesion and enhances frictional resistance,thereby improving the Mohr-Coulomb parameters of the stabilized soil.The SEM micrographs show that alkali-activated sewage sludge increases the integrity and reduces the cavity volumes in the stabilized soil.Moreover,TCLP tests revealed that the solubility of metals in the treated soil alkaliactivated by sewage sludge significantly decreased.This study suggests that using sewage sludge can replace cement and lime in ground improvement,improve the circular economy,and reduce the carbon footprint of construction projects.
文摘Machine picking in cotton is an emerging practice in India,to solve the problems of labour shortages and production costs increasing.Cotton production has been declining in recent years;however,the high density planting system(HDPS)offers a viable method to enhance productivity by increasing plant populations per unit area,optimizing resource utilization,and facilitating machine picking.Cotton is an indeterminate plant that produce excessive vegeta-tive growth in favorable soil fertility and moisture conditions,which posing challenges for efficient machine picking.To address this issue,the application of plant growth retardants(PGRs)is essential for controlling canopy architecture.PGRs reduce internode elongation,promote regulated branching,and increase plant compactness,making cotton plants better suited for machine picking.PGRs application also optimizes photosynthates distribution between veg-etative and reproductive growth,resulting in higher yields and improved fibre quality.The integration of HDPS and PGRs applications results in an optimal plant architecture for improving machine picking efficiency.However,the success of this integration is determined by some factors,including cotton variety,environmental conditions,and geographical variations.These approaches not only address yield stagnation and labour shortages but also help to establish more effective and sustainable cotton farming practices,resulting in higher cotton productivity.
基金supported by Postgraduate Research&Practice Innovation Program of Jiangsu Province(Grant No.KYCX24_4084).
文摘To solve the problem of low detection accuracy for complex weld defects,the paper proposes a weld defects detection method based on improved YOLOv5s.To enhance the ability to focus on key information in feature maps,the scSE attention mechanism is intro-duced into the backbone network of YOLOv5s.A Fusion-Block module and additional layers are added to the neck network of YOLOv5s to improve the effect of feature fusion,which is to meet the needs of complex object detection.To reduce the computation-al complexity of the model,the C3Ghost module is used to replace the CSP2_1 module in the neck network of YOLOv5s.The scSE-ASFF module is constructed and inserted between the neck network and the prediction end,which is to realize the fusion of features between the different layers.To address the issue of imbalanced sample quality in the dataset and improve the regression speed and accuracy of the loss function,the CIoU loss function in the YOLOv5s model is replaced with the Focal-EIoU loss function.Finally,ex-periments are conducted based on the collected weld defect dataset to verify the feasibility of the improved YOLOv5s for weld defects detection.The experimental results show that the precision and mAP of the improved YOLOv5s in detecting complex weld defects are as high as 83.4%and 76.1%,respectively,which are 2.5%and 7.6%higher than the traditional YOLOv5s model.The proposed weld defects detection method based on the improved YOLOv5s in this paper can effectively solve the problem of low weld defects detection accuracy.
基金Sponsored by Jilin Provincial Department of Education Scientific Research Project(Grant Nos.JJKH20190875KJ,JJKH20230348KJ).
文摘This study tested the electrical conductivity and pressure sensitivity of lime⁃improved silty sand reinforced with Carbon Fiber Powder(CFP)as the conductive medium.The influence of CFP dosage,moisture content and curing duration on the unconfined compressive strength,initial resistivity and pressure sensitivity of the improved soil was systematically analysed.The results showed that the unconfined compressive strength varied non⁃monotonically with increasing CFP dosage,reaching a peak at a dosage of 1.6%.Furthermore,the initial resistivity showed slight variations under different moisture conditions but eventually converged towards the conductive percolation threshold at a dosage of 2.4%.It is worth noting that CFP reinforced lime⁃improved silty sand(CRLS)exhibit a clear dynamic synchronization of strain with stress and resistivity rate of variation.The pressure sensitivity was optimized with CFP dosages ranging from 1.6%to 2.0%.Both insufficient and excessive dosages had a negative impact on pressure sensitivity.It is important to consider the weakening effect of high moisture content on the pressure sensitivity of the specimens in practical applications.
文摘To improve the efficiency and accuracy of path planning for fan inspection tasks in thermal power plants,this paper proposes an intelligent inspection robot path planning scheme based on an improved A^(*)algorithm.The inspection robot utilizes multiple sensors to monitor key parameters of the fans,such as vibration,noise,and bearing temperature,and upload the data to the monitoring center.The robot’s inspection path employs the improved A^(*)algorithm,incorporating obstacle penalty terms,path reconstruction,and smoothing optimization techniques,thereby achieving optimal path planning for the inspection robot in complex environments.Simulation results demonstrate that the improved A^(*)algorithm significantly outperforms the traditional A^(*)algorithm in terms of total path distance,smoothness,and detour rate,effectively improving the execution efficiency of inspection tasks.
基金supported by a sub-award to the University of Missouri from the Heinrich Heine University of Dusseldorf funded by the Bill&Melinda Gates Foundation(OPP1155704)(Bing Yang)and the China Scholar Council(Chenhao Li,as a joint Ph.D.student).
文摘Bacterial blight(BB),caused by Xanthomonas oryzae pathovar oryzae(Xoo),poses a significant threat to rice production,particularly in Asia and West Africa.Breeding resistance against BB in elite rice varieties is crucial to advancing rice breeding program and supporting smallholder farmers.Transcription Activator-Like effectors(TALes)are key virulence factors in Xoo,with some targeting the susceptibility(S)genes such as the sugar transporter SWEET genes in rice.Among these,SWEET14 is an important S gene,with its promoter bound by the TALe TalC which exists across all sequenced African Xoo isolates.In the present study,we utilized CRISPR/Cas9-based cytidine and adenine base editors to alter the effector binding element(EBE)of TalC in the promoter of SWEET14 in rice cultivars Kitaake,IR24,and Zhonghua 11.Mutations with C to T changes in EBE led to reduced SWEET14 induction by TalC-containing Xoo strains,resulting in resistance to African Xoo isolates reliant on TalC for virulence.Conversely,A to G changes retained SWEET14 inducibility and susceptibility to Xoo in edited lines.Importantly,no off-target mutations were detected at predicted sites,and the edited lines exhibited no obvious defects in major agronomic traits in Kitaake.These results underscore the effectiveness of base editing systems for both molecular biology research and crop improvement endeavors.
基金National Natural Science Foundation of China(NSFC61773142,NSFC62303136)。
文摘When the maneuverability of a pursuer is not significantly higher than that of an evader,it will be difficult to intercept the evader with only one pursuer.Therefore,this article adopts a two-to-one differential game strategy,the game of kind is generally considered to be angle-optimized,which allows unlimited turns,but these practices do not take into account the effect of acceleration,which does not correspond to the actual situation,thus,based on the angle-optimized,the acceleration optimization and the acceleration upper bound constraint are added into the game for consideration.A two-to-one differential game problem is proposed in the three-dimensional space,and an improved multi-objective grey wolf optimization(IMOGWO)algorithm is proposed to solve the optimal game point of this problem.With the equations that describe the relative motions between the pursuers and the evader in the three-dimensional space,a multi-objective function with constraints is given as the performance index to design an optimal strategy for the differential game.Then the optimal game point is solved by using the IMOGWO algorithm.It is proved based on Markov chains that with the IMOGWO,the Pareto solution set is the solution of the differential game.Finally,it is verified through simulations that the pursuers can capture the escapee,and via comparative experiments,it is shown that the IMOGWO algorithm performs well in terms of running time and memory usage.
基金supported by the National Natural Science Foundation of China(Nos.52171166 and U20A20231)the Natural Science Foundation of Hunan Province,China(Nos.2024JJ2060 and 2024JJ5406)+1 种基金the Key Laboratory of Materials in Dynamic Extremes of Sichuan Province(No.2023SCKT1102)the Postgraduate Scientific Research Innovation Project of National University of Defense Technology(No.XJJC2024065).
文摘Introducing B2 ordering can effectively improve the mechanical properties of lightweight refractory high-entropy alloys(LRHEAs).However,(Zr,Al)-enriched B2 precipitates generally reduce the ductility because their ordering characteristic is destroyed after dislocation shearing.Meanwhile,the local chemical order(LCO)cannot provide an adequate strengthening effect due to its small size.
基金financially supported by the National Science Foundation of China grant (62322407, 22279034, 52261145698, W2421103)Shanghai Science and Technology Innovation Action Plan (22ZR1418900, 24110714100)+1 种基金the Swedish Research Council (project grant no. 2020-04538)the Swedish Government Strategic Research Area in Materials Science on Functional Materials at Link?ping University (Faculty Grant SFO Mat LiU no. 2009 00971)。
文摘Improving the quality of life for Earth's growing population is a complex task that requires the development of new technologies and materials. Perhaps the biggest challenge is access to clean and renewable energy sources that can drive a sustainable future. Photovoltaics, today mainly represented by silicon-based solar cells, convert solar energy into electricity and is already an important component in the renewable energy portfolio.
基金supported by the National Natural Science Foundation of China(No.62241109)the Tianjin Science and Technology Commissioner Project(No.20YDTPJC01110)。
文摘An improved model based on you only look once version 8(YOLOv8)is proposed to solve the problem of low detection accuracy due to the diversity of object sizes in optical remote sensing images.Firstly,the feature pyramid network(FPN)structure of the original YOLOv8 mode is replaced by the generalized-FPN(GFPN)structure in GiraffeDet to realize the"cross-layer"and"cross-scale"adaptive feature fusion,to enrich the semantic information and spatial information on the feature map to improve the target detection ability of the model.Secondly,a pyramid-pool module of multi atrous spatial pyramid pooling(MASPP)is designed by using the idea of atrous convolution and feature pyramid structure to extract multi-scale features,so as to improve the processing ability of the model for multi-scale objects.The experimental results show that the detection accuracy of the improved YOLOv8 model on DIOR dataset is 92%and mean average precision(mAP)is 87.9%,respectively 3.5%and 1.7%higher than those of the original model.It is proved the detection and classification ability of the proposed model on multi-dimensional optical remote sensing target has been improved.
文摘Liver transplantation(LT)has made significant progress in the treatment of end stage liver disease(ESLD).However,many patients still die from disease progression while awaiting transplantation.As the number of patients on LT waiting lists is increasing,and the organ shortage crisis is obvious,various efforts have been made to increase the pool of available liver grafts[1].In addition to living donor liver transplantation(LDLT),improving the utilization rate of extended criteria donor(ECD)livers is an important way.However,under traditional cold storage,ECD livers are usually associated with a higher risk of ischemic biliary disease,early allograft dysfunction(EAD)or even primary nonfunction(PNF).The frequently described definition in the literature for ECD grafts generally includes elderly,steatotic,long cold ischemia time(CIT),grafts obtained from donation after circulatory death(DCD),split liver grafts,donors with increased risk of infectious disease transmission and prolonged donor intensive care unit stay[2].
文摘In the first two months,a package of exist ing and incremental policies continued to take effect,industrial and service sectors grew rapidly,consumpt ion and investment continued to improve,employment was generally stable,and new quality productive forces grew and thrived.The national economy got off to a steady start with new and positive development momentum.
基金National Natural Science Foundation of China,No.42330106。
文摘Dryland regions face complex interactions between urbanization and ecological changes,where effective coordination is essential for enhancing sustainability and resilience.However,most studies concentrate on the national or provincial scales,with insufficient research on county-level coordination,limiting the ability to provide targeted polifrom a precise perspective.This study addresses this gap by analyzing 39 counties within the Hohhot-Baotou-Ordos-Yulin Urban Agglomeration(HBOYUA),a typical dryland urban cluster in China.We use daytime and nighttime remote sensing images to track the spatio-temporal evolution of urbanization and ecological conditions from 1992 to 2023.A novel quantitative framework based on an improved coupling coordination degree(CCD)is proposed to assess their coordination relationship.The results reveal that:(1)Urbanization and ecological quality both exhibited fluctuating upward trends,with spatial heterogeneity increasing for urbanization and decreasing for the eco-environment.Regions with better ecological conditions had higher urbanization levels.(2)The overall coordinated level improved from imbalance(0.36)to low-level coordination(0.55),although its spatial distribution remained uneven,with central urban areas showing higher CCD than surrounding counties.(3)Socioeconomic factors exerted greater effects on CCD than natural factors,with GDP and land surface temperature(LST)playing a significant role in interaction analysis.(4)In western arid regions,urbanization did not necessarily harm ecosystems;instead,ecological conditions improved alongside urbanization.This research offers targeted and valuable references for county and city governments in resource allocation and sustainable development.The proposed methodology is also adaptable for urban resilience studies in other regions.
基金supported in part by the National Natural Science Foundation of China(61873106,62303109)Start-Up Research Fund of Southeast University(RF1028623002)Shenzhen Science and Technology Program(JCYJ20230807114609019)
文摘Dear Editor,This letter focuses on how an attacker can design suitable improved zero-dynamics (ZD) attack signal based on state estimates of target system. Improved ZD attack is to change zero dynamic gain matrix of attack signal to a matrix with determinant greater than 1.
