The methods of network attacks have become increasingly sophisticated,rendering traditional cybersecurity defense mechanisms insufficient to address novel and complex threats effectively.In recent years,artificial int...The methods of network attacks have become increasingly sophisticated,rendering traditional cybersecurity defense mechanisms insufficient to address novel and complex threats effectively.In recent years,artificial intelligence has achieved significant progress in the field of network security.However,many challenges and issues remain,particularly regarding the interpretability of deep learning and ensemble learning algorithms.To address the challenge of enhancing the interpretability of network attack prediction models,this paper proposes a method that combines Light Gradient Boosting Machine(LGBM)and SHapley Additive exPlanations(SHAP).LGBM is employed to model anomalous fluctuations in various network indicators,enabling the rapid and accurate identification and prediction of potential network attack types,thereby facilitating the implementation of timely defense measures,the model achieved an accuracy of 0.977,precision of 0.985,recall of 0.975,and an F1 score of 0.979,demonstrating better performance compared to other models in the domain of network attack prediction.SHAP is utilized to analyze the black-box decision-making process of the model,providing interpretability by quantifying the contribution of each feature to the prediction results and elucidating the relationships between features.The experimental results demonstrate that the network attack predictionmodel based on LGBM exhibits superior accuracy and outstanding predictive capabilities.Moreover,the SHAP-based interpretability analysis significantly improves the model’s transparency and interpretability.展开更多
In the context of global COVID-19 epidemic preparedness,the extensive use of disposable surgical masks(DSM)may lead to its emergence as a main new source of microplastics in the environment.Nowadays,DSMs have become a...In the context of global COVID-19 epidemic preparedness,the extensive use of disposable surgical masks(DSM)may lead to its emergence as a main new source of microplastics in the environment.Nowadays,DSMs have become a non-negligible source of plastic waste in aquatic environment,however,less research has been done on DSM after biofilm colonization in freshwater environment.The study investigated the microbial community of DSM-associated biofilms by 16S rRNA gene sequencing.Analysis of the microbial community in the middle and inner/outer layers of the DSM showed that the middle layer was different from the remaining two layers and that potential pathogens were enriched only in the middle layer of the DSM.Herein,we focused on the middle layer and explored the characterization properties and extracellular polymeric substances(EPS)components changes during biofilm formation.The results showed that the EPS components varied with the biofilm incubation time.As the formation of biofilm,the protein(PN)and polysaccharide(PS)in EPS showed an overall increasing trend,and the growth of PS was well synchronized with PN.Three fluorescent components of EPS were determined by the three-dimensional excitation emission matrix(3D-EEM),including humic acid-like,fulvic acid-like,and aromatic protein-like components.The percentage of fluorescent components varied with increasing biofilm development time and then stabilized.Fourier transform infrared spectroscopy(FTIR)characterization results elucidated the emergence of oxygen-containing functional groups during biofilm formation.Moreover,the hydrophilicity increased with biofilm development.In conclusion,the environmental behavior and ecological risks of DSM in aquatic environment deserve urgent attention in future studies.展开更多
A cable-driven redundant manipulator(CDRM)characterized by redundant degrees of freedom and a lightweight,slender design can perform tasks in confined and restricted spaces efficiently.However,the complex multistage c...A cable-driven redundant manipulator(CDRM)characterized by redundant degrees of freedom and a lightweight,slender design can perform tasks in confined and restricted spaces efficiently.However,the complex multistage coupling between drive cables and passive joints in CDRM leads to a challenging dynamic model with difficult parameter identification,complicating the efforts to achieve accurate modeling and control.To address these challenges,this paper proposes a dynamic modeling and adaptive control approach tailored for CDRM systems.A multilevel kinematic model of the cable-driven redundant manipulator is presented,and a screw theory is employed to represent the cable tension and cable contact forces as spatial wrenches,which are equivalently mapped to joint torque using the principle of virtual work.This approach simplifies the mapping process while maintaining the integrity of the dynamic model.A recursive method is used to compute cable tension section-by-section for enhancing the efficiency of inverse dynamics calculations and meeting the high-frequency demands of the controller,thereby avoiding large matrix operations.An adaptive control method is proposed building on this foundation,which involves the design of a dynamic parameter adaptive controller in the joint space to simplify the linearization process of the dynamic equations along with a closed-loop controller that incorporates motor parameters in the driving space.This approach improves the control accuracy and dynamic performance of the CDRM under dynamic uncertainties.The accuracy and computational efficiency of the dynamic model are validated through simulations,and the effectiveness of the proposed control method is demonstrated through control tests.This paper presents a dynamic modeling and adaptive control approach for CDRM to enhance accuracy and performance under dynamic uncertainties.展开更多
Rice productivity faces critical sustainability challenges from stagnating yields and inefficient fertilizer use,particularly in intensive agricultural regions like the Yangtze River Delta(YRD)of China.Controlled-rele...Rice productivity faces critical sustainability challenges from stagnating yields and inefficient fertilizer use,particularly in intensive agricultural regions like the Yangtze River Delta(YRD)of China.Controlled-release blended fertilizers(CRBF),which synchronize nutrient release with crop demand,represent a promising strategy to enhance rice productivity.Here,we conducted an eight-year(2017–2024)field study across 25 representative sites in the YRD to evaluate CRBF’s effects,complemented by a regional extrapolation analysis.Our findings showed that,relative to conventional fertilization,CRBF increased rice yield by 4.9%,primarily by increasing the number of effective panicles(5%)and plant biomass(5.2%–11.3%).Notably,this yield benefit rose to 5.3%when CRBF was applied via deep placement,which was attributed to greater root biomass(13.1%–29.2%)and higher soil NH_(4)^(+)-N availability(24.3%–43.6%),thereby enhancing N uptake.Furthermore,initial soil organic matter was identified as the predominant modulator of CRBF effectiveness.Regional extrapolation projected that applying CRBF could enhance rice yield by 4.0%across the YRD,with deep placement providing an additional 2.1%gain.In conclusion,our study demonstrates that adopting CRBF,particularly with deep placement,is a robust and effective strategy to sustainably boost rice productivity in intensive rice cultivation systems.展开更多
Real-time semantic segmentation tasks place stringent demands on network inference speed,often requiring a reduction in network depth to decrease computational load.However,shallow networks tend to exhibit degradation...Real-time semantic segmentation tasks place stringent demands on network inference speed,often requiring a reduction in network depth to decrease computational load.However,shallow networks tend to exhibit degradation in feature extraction completeness and inference accuracy.Therefore,balancing high performance with real-time requirements has become a critical issue in the study of real-time semantic segmentation.To address these challenges,this paper proposes a lightweight bilateral dual-residual network.By introducing a novel residual structure combined with feature extraction and fusion modules,the proposed network significantly enhances representational capacity while reducing computational costs.Specifically,an improved compound residual structure is designed to optimize the efficiency of information propagation and feature extraction.Furthermore,the proposed feature extraction and fusion module enables the network to better capture multi-scale information in images,improving the ability to detect both detailed and global semantic features.Experimental results on the publicly available Cityscapes dataset demonstrate that the proposed lightweight dual-branch network achieves outstanding performance while maintaining low computational complexity.In particular,the network achieved a mean Intersection over Union(mIoU)of 78.4%on the Cityscapes validation set,surpassing many existing semantic segmentation models.Additionally,in terms of inference speed,the network reached 74.5 frames per second when tested on an NVIDIA GeForce RTX 3090 GPU,significantly improving real-time performance.展开更多
In a wind turbine,the rolling bearing is the critical component.However,it has a high failure rate.Therefore,the failure analysis and fault diagnosis of wind power rolling bearings are very important to ensure the hig...In a wind turbine,the rolling bearing is the critical component.However,it has a high failure rate.Therefore,the failure analysis and fault diagnosis of wind power rolling bearings are very important to ensure the high reliability and safety of wind power equipment.In this study,the failure form and the corresponding reason for the failure are discussed firstly.Then,the natural frequency and the characteristic frequency are analyzed.The Empirical Mode Decomposition(EMD)algorithm is used to extract the characteristics of the vibration signal of the rolling bearing.Moreover,the eigenmode function is obtained and then filtered by the kurtosis criterion.Consequently,the relationship between the actual fault frequency spectrum and the theoretical fault frequency can be obtained.Then the fault analysis is performed.To enhance the accuracy of fault diagnosis,based on the previous feature extraction and the time-frequency domain feature extraction of the data after EMD decomposition processing,four different classifiers are added to diagnose and classify the fault status of rolling bearings and compare them with four different classifiers.展开更多
Bread wheat provides an essential fraction of the daily calorific intake for humanity.Due to its huge and complex genome,progress in studying on the wheat genome is substantially trailed behind those of the other two ...Bread wheat provides an essential fraction of the daily calorific intake for humanity.Due to its huge and complex genome,progress in studying on the wheat genome is substantially trailed behind those of the other two major crops,rice and maize,for at least a decade.With rapid advances in genome assembling and reduced cost of high-throughput sequencing,emerging de novo genome assemblies of wheat and whole-genome sequencing data are leading to a paradigm shift in wheat research.Here,we review recent progress in dissecting the complex genome and germplasm evolution of wheat since the release of the first high-quality wheat genome.New insights have been gained in the evolution of wheat germplasm during domestication and modern breeding progress,genomic variations at multiple scales contributing to the diversity of wheat germplasm,and complex transcriptional and epigenetic regulations of functional genes in polyploid wheat.Genomics databases and bioinformatics tools meeting the urgent needs of wheat ge-nomics research are also summarized.The ever-increasing omics data,along with advanced tools and well-structured databases,are expected to accelerate deciphering the germplasm and gene resources in wheat for future breeding advances.展开更多
The problem of effluent total nitrogen(TN)at most of the wastewater treatment plants(WWTPs)in China is important for meeting the related water quality standards,even under the condition of high energy consumption.To a...The problem of effluent total nitrogen(TN)at most of the wastewater treatment plants(WWTPs)in China is important for meeting the related water quality standards,even under the condition of high energy consumption.To achieve better prediction and control of effluent TN concentration,an efficient prediction model,based on controllable operation parameters,was constructed in a sequencing batch reactor process.Compared with previous models,this model has two main characteristics:①Superficial gas velocity and anoxic time are controllable operation parameters and are selected as the main input parameters instead of dissolved oxygen to improve the model controllability,and②the model prediction accuracy is improved on the basis of a feedforward neural network(FFNN)with algorithm optimization.The results demonstrated that the FFNN model was efficiently optimized by scaled conjugate gradient,and the performance was excellent compared with other models in terms of the correlation coefficient(R).The optimized FFNN model could provide an accurate prediction of effluent TN based on influent water parameters and key control parameters.This study revealed the possible application of the optimized FFNN model for the efficient removal of pollutants and lower energy consumption at most of the WWTPs.展开更多
HZSM-5/MCM-41 molecular sieve (H-ZM) catalysts with well-defined micro/mesoporous structures were synthesized and showed high performance for selective synthesis of triacetin via the esterification reaction of glycero...HZSM-5/MCM-41 molecular sieve (H-ZM) catalysts with well-defined micro/mesoporous structures were synthesized and showed high performance for selective synthesis of triacetin via the esterification reaction of glycerol with acetic acid. The conversion of glycerol was demonstrated to be 100% and the triacetin selectivity was over 91%, which can be attributed to the synergistic effect regarding suitable acidic property, excellent diffusion efficiency and good stability derived from the combined advantages of microporous molecular sieve HZSM-5 and mesoporous molecular sieve MCM-41.展开更多
Heterojunction fabrication is one of the most effective strategies for enhancing the photocatalytic performance of semiconductor photocatalysts. Here, TiO2（B）/anatase nanowires with interfacial heterostructures were...Heterojunction fabrication is one of the most effective strategies for enhancing the photocatalytic performance of semiconductor photocatalysts. Here, TiO2（B）/anatase nanowires with interfacial heterostructures were prepared through a three-step synthesis method, including hydrothermal treatment, H＋ exchange, and annealing. The phase structures of the nanowires in the bulk and on the surface during the annealing process were monitored by XRD and UV-Raman spectroscopy, respectively. SEM and TEM results indicate that the TiO2（B） nanowires partially collapse and transform into anatase during the annealing process and the heterophase junction structure is formed simultaneously. On the basis of the phase structure together with morphology data, a phase-transformation mechanism was proposed. Photocatalytic activity was evaluated by hydrogen production and pollutant-degradation assays. The optimized structure of the photocatalyst contains 24% TiO2（B） in the bulk and 100% anatase on the surface. The charge-carrier behavior during the photocatalytic process was investigated by photocurrent, electrochemical impedance spectroscopy（EIS）, and photoluminescence（PL） spectroscopy, which revealed that the heterophase-junction structure in the bulk was responsible for the highly efficient charge separation and transportation, etc.; the anatase on the surface took control of the high surface-reaction activity.展开更多
Direct epitaxial growthⅢ–Ⅴquantum dot(QD)structures on CMOS-compatible silicon substrates is considered as one of the most promising approaches to achieve low-cost and high-yield Si-based lasers for silicon photoni...Direct epitaxial growthⅢ–Ⅴquantum dot(QD)structures on CMOS-compatible silicon substrates is considered as one of the most promising approaches to achieve low-cost and high-yield Si-based lasers for silicon photonic integration.However,epitaxial growth ofⅢ–Ⅴmaterials on Si encounters the following three major challenges:high density of threading dislocations,antiphase boundaries and thermal cracks,which significantly degrade the crystal quality and potential device performance.In this review,we will focus on some recent results related to InAs/GaAs quantum dot lasers on Si(001)substrates byⅢ–Ⅴ/Ⅳhybrid epitaxial growth via(111)-faceted Si hollow structures.Moreover,by using the step-graded epitaxial growth process the emission wavelength of InAs QDs can be extended from O-band to C/L-band.High-performance InAs/GaAs QD microdisk lasers with sub-milliwatts threshold on Si(001)substrates are fabricated and characterized.The above results pave a promising path towards the on-chip lasers for optical interconnect applications.展开更多
The spread of severe acute respiratory syndrome coronavirus 2(SARS-CoV-2) from cold-chain foods to frontline workers poses a serious public health threat during the current global pandemic. There is an urgent need to ...The spread of severe acute respiratory syndrome coronavirus 2(SARS-CoV-2) from cold-chain foods to frontline workers poses a serious public health threat during the current global pandemic. There is an urgent need to design concise approaches for effective virus inactivation under different physicochemical conditions to reduce the risk of contagion through viral contaminated surfaces of cold-chain foods. By employing a time course of electron beam exposure to a high titer of SARS-CoV-2 at cold-chain temperatures, a radiation dose of 2 kGy was demonstrated to reduce the viral titer from 10^(4.5)to 0 median tissue culture infectious dose(TCID_(50))/mL. Next,using human coronavirus OC43(HCoV-OC43) as a suitable SARS-CoV-2 surrogate, 3 kGy of high-energy electron radiation was defined as the inactivation dose for a titer reduction of more than 4 log units on tested packaging materials. Furthermore, quantitative reverse transcription PCR(RT-qPCR) was used to test three viral genes,namely, E, N, and ORF1ab. There was a strong correlation between TCID50and RT-qPCR for SARS-CoV-2detection. However, RT-qPCR could not differentiate between the infectivity of the radiation-inactivated and nonirradiated control viruses. As the defined radiation dose for effective viral inactivation fell far below the upper safe dose limit for food processing, our results provide a basis for designing radiation-based approaches for the decontamination of SARS-CoV-2 in frozen food products. We further demonstrate that cell-based virus assays are essential to evaluate the SARS-CoV-2 inactivation efficiency for the decontaminating strategies.展开更多
Ⅲ-Ⅴ quantum dot(QD) lasers monolithically grown on CMOS-compatible Si substrates are considered as essential components for integrated silicon photonic circuits.However,epitaxial growth of Ⅲ-Ⅴ materials on Si subs...Ⅲ-Ⅴ quantum dot(QD) lasers monolithically grown on CMOS-compatible Si substrates are considered as essential components for integrated silicon photonic circuits.However,epitaxial growth of Ⅲ-Ⅴ materials on Si substrates encounters three obstacles:mismatch defects,antiphase boundaries(APBs),and thermal cracks.We study the evolution of the structures on U-shaped trench-patterned Si(001) substrates with various trench orientations by homoepitaxy and the subsequent heteroepitaxial growth of GaAs film.The results show that the formation of(111)-faceted hollow structures on patterned Si(001) substrates with trenches oriented along [110] direction can effectively reduce the defect density and thermal stress in the GaAs/Si epilayers.The(111)-faceted silicon hollow structure can act as a promising platform for the direct growth of Ⅲ-Ⅴ materials for silicon based optoelectronic applications.展开更多
Surface cracks are commonly observed in coatings and films.When structures with coatings are subject to stretching,opening mode cracks are likely to form on the surface,which may further lead to other forms of damage,...Surface cracks are commonly observed in coatings and films.When structures with coatings are subject to stretching,opening mode cracks are likely to form on the surface,which may further lead to other forms of damage,such as interfacial delamination and substrate damage.Possible crack forms include cracks extending towards the interface and channeling across the film.In this paper,a two-dimensional numerical model is proposed to obtain the structural strain energy at arbitrary crack lengths for bilayer structures under uniaxial tension.The energy release rate and structural stress intensity factors can be obtained accordingly,and the effects of geometry and material features on fracture characteristics are investigated,with most crack patterns being confirmed as unstable.The proposed model can also facilitate the analysis of the stress distribution in periodic crack patterns of films.The results from the numerical model are compared with those obtained by the finite element method(FEM),and the accuracy of the theoretical results is demonstrated.展开更多
Full-spectrum phosphor-converted white-light-emitting diodes(pc-WLED)are emerging as a mainstream technology in semiconductor lighting.Nevertheless,high-performance blue phosphor which can be excited efficiently by a ...Full-spectrum phosphor-converted white-light-emitting diodes(pc-WLED)are emerging as a mainstream technology in semiconductor lighting.Nevertheless,high-performance blue phosphor which can be excited efficiently by a 400 nm NUV diode chip is still lacking.Herein,we present a blue-emitting Na_(3)KMg_(7)(PO_(4))6:Eu^(2+)phosphor synthesized by the solid-reaction method.Particularly,we find that the using of Li_(2)CO_(3)as flux can significantly improve the crystal quality and thus the emission efficiency of the phosphor.Meanwhile,the excitation peak of the phosphor shifts from 365 to 400 nm,which is pivotal for efficient NUV(400 nm)diode chip excitation.The practical Eu^(2+)concentration is also enhanced by using Li_(2)CO_(3)as flux,and the absorption efficiency is greatly increased.This phosphor exhibits superior PL thermal stability,namely retains 94%integrated photoluminescence intensity at 150℃of that at 25℃.As a result,the optimized phosphor shows an emission band peaked at 437 nm with a bandwidth of 40 nm and a high external photoluminescence quantum yield of 51.7%.Finally,a pc-WLED was fabricated by using NKMPO:Eu^(2+)blue,Sr_(2)SiO_(4):Eu^(2+)green,CaAlSiN_(3):Eu^(2+)red phosphors,and a 400 nm NUV diode chip.It shows a high color rendering index of R_(a)=96.4 and a correlated color temperature of 4358 K.These results prove that NKMPO:Eu^(2+)is a promising blue phosphor for full-spectrum WLED based on NUV diode chips.展开更多
From the end of 2019 until now,the Coronavirus Disease 2019(COVID-19)has been rampaging around the world,posing a great threat to people's lives and health,as well as a serious impact on economic development.Consi...From the end of 2019 until now,the Coronavirus Disease 2019(COVID-19)has been rampaging around the world,posing a great threat to people's lives and health,as well as a serious impact on economic development.Considering the severely infectious nature of COVID-19,the diagnosis of COVID-19 has become crucial.Identification through the use of Computed Tomography(CT)images is an efficient and quick means.Therefore,scientific researchers have proposed numerous segmentation methods to improve the diagnosis of CT images.In this paper,we propose a reinforcement learning-based golden jackal optimization algorithm,which is named QLGJO,to segment CT images in furtherance of the diagnosis of COVID-19.Reinforcement learning is combined for the first time with meta-heuristics in segmentation problem.This strategy can effectively overcome the disadvantage that the original algorithm tends to fall into local optimum.In addition,one hybrid model and three different mutation strategies were applied to the update part of the algorithm in order to enrich the diversity of the population.Two experiments were carried out to test the performance of the proposed algorithm.First,compare QLGJO with other advanced meta-heuristics using the IEEE CEC2022 benchmark functions.Secondly,QLGJO was experimentally evaluated on CT images of COVID-19 using the Otsu method and compared with several well-known meta-heuristics.It is shown that QLGJO is very competitive in benchmark function and image segmentation experiments compared with other advanced meta-heuristics.Furthermore,the source code of the QLGJO is publicly available at https://github.com/Vang-z/QLGJO.展开更多
基金supported by the National Natural Science Foundation of China Project(No.62302540)please visit their website at https://www.nsfc.gov.cn/(accessed on 18 June 2024).
文摘The methods of network attacks have become increasingly sophisticated,rendering traditional cybersecurity defense mechanisms insufficient to address novel and complex threats effectively.In recent years,artificial intelligence has achieved significant progress in the field of network security.However,many challenges and issues remain,particularly regarding the interpretability of deep learning and ensemble learning algorithms.To address the challenge of enhancing the interpretability of network attack prediction models,this paper proposes a method that combines Light Gradient Boosting Machine(LGBM)and SHapley Additive exPlanations(SHAP).LGBM is employed to model anomalous fluctuations in various network indicators,enabling the rapid and accurate identification and prediction of potential network attack types,thereby facilitating the implementation of timely defense measures,the model achieved an accuracy of 0.977,precision of 0.985,recall of 0.975,and an F1 score of 0.979,demonstrating better performance compared to other models in the domain of network attack prediction.SHAP is utilized to analyze the black-box decision-making process of the model,providing interpretability by quantifying the contribution of each feature to the prediction results and elucidating the relationships between features.The experimental results demonstrate that the network attack predictionmodel based on LGBM exhibits superior accuracy and outstanding predictive capabilities.Moreover,the SHAP-based interpretability analysis significantly improves the model’s transparency and interpretability.
基金Supported by the Natural Science Foundation of Shandong Province(Nos.ZR2022MD115,ZR202111160067)。
文摘In the context of global COVID-19 epidemic preparedness,the extensive use of disposable surgical masks(DSM)may lead to its emergence as a main new source of microplastics in the environment.Nowadays,DSMs have become a non-negligible source of plastic waste in aquatic environment,however,less research has been done on DSM after biofilm colonization in freshwater environment.The study investigated the microbial community of DSM-associated biofilms by 16S rRNA gene sequencing.Analysis of the microbial community in the middle and inner/outer layers of the DSM showed that the middle layer was different from the remaining two layers and that potential pathogens were enriched only in the middle layer of the DSM.Herein,we focused on the middle layer and explored the characterization properties and extracellular polymeric substances(EPS)components changes during biofilm formation.The results showed that the EPS components varied with the biofilm incubation time.As the formation of biofilm,the protein(PN)and polysaccharide(PS)in EPS showed an overall increasing trend,and the growth of PS was well synchronized with PN.Three fluorescent components of EPS were determined by the three-dimensional excitation emission matrix(3D-EEM),including humic acid-like,fulvic acid-like,and aromatic protein-like components.The percentage of fluorescent components varied with increasing biofilm development time and then stabilized.Fourier transform infrared spectroscopy(FTIR)characterization results elucidated the emergence of oxygen-containing functional groups during biofilm formation.Moreover,the hydrophilicity increased with biofilm development.In conclusion,the environmental behavior and ecological risks of DSM in aquatic environment deserve urgent attention in future studies.
基金Supported by National Natural Science Foundation of China(Grant No.52405040)Research Project of State Key Laboratory of Mechanical System and Vibration(Grant No.MSV202514)。
文摘A cable-driven redundant manipulator(CDRM)characterized by redundant degrees of freedom and a lightweight,slender design can perform tasks in confined and restricted spaces efficiently.However,the complex multistage coupling between drive cables and passive joints in CDRM leads to a challenging dynamic model with difficult parameter identification,complicating the efforts to achieve accurate modeling and control.To address these challenges,this paper proposes a dynamic modeling and adaptive control approach tailored for CDRM systems.A multilevel kinematic model of the cable-driven redundant manipulator is presented,and a screw theory is employed to represent the cable tension and cable contact forces as spatial wrenches,which are equivalently mapped to joint torque using the principle of virtual work.This approach simplifies the mapping process while maintaining the integrity of the dynamic model.A recursive method is used to compute cable tension section-by-section for enhancing the efficiency of inverse dynamics calculations and meeting the high-frequency demands of the controller,thereby avoiding large matrix operations.An adaptive control method is proposed building on this foundation,which involves the design of a dynamic parameter adaptive controller in the joint space to simplify the linearization process of the dynamic equations along with a closed-loop controller that incorporates motor parameters in the driving space.This approach improves the control accuracy and dynamic performance of the CDRM under dynamic uncertainties.The accuracy and computational efficiency of the dynamic model are validated through simulations,and the effectiveness of the proposed control method is demonstrated through control tests.This paper presents a dynamic modeling and adaptive control approach for CDRM to enhance accuracy and performance under dynamic uncertainties.
基金supported by the National Key Research and Development Program of China(2023YFD2301300)the National Natural Science Foundation of China(U24A20402,32301354).
文摘Rice productivity faces critical sustainability challenges from stagnating yields and inefficient fertilizer use,particularly in intensive agricultural regions like the Yangtze River Delta(YRD)of China.Controlled-release blended fertilizers(CRBF),which synchronize nutrient release with crop demand,represent a promising strategy to enhance rice productivity.Here,we conducted an eight-year(2017–2024)field study across 25 representative sites in the YRD to evaluate CRBF’s effects,complemented by a regional extrapolation analysis.Our findings showed that,relative to conventional fertilization,CRBF increased rice yield by 4.9%,primarily by increasing the number of effective panicles(5%)and plant biomass(5.2%–11.3%).Notably,this yield benefit rose to 5.3%when CRBF was applied via deep placement,which was attributed to greater root biomass(13.1%–29.2%)and higher soil NH_(4)^(+)-N availability(24.3%–43.6%),thereby enhancing N uptake.Furthermore,initial soil organic matter was identified as the predominant modulator of CRBF effectiveness.Regional extrapolation projected that applying CRBF could enhance rice yield by 4.0%across the YRD,with deep placement providing an additional 2.1%gain.In conclusion,our study demonstrates that adopting CRBF,particularly with deep placement,is a robust and effective strategy to sustainably boost rice productivity in intensive rice cultivation systems.
文摘Real-time semantic segmentation tasks place stringent demands on network inference speed,often requiring a reduction in network depth to decrease computational load.However,shallow networks tend to exhibit degradation in feature extraction completeness and inference accuracy.Therefore,balancing high performance with real-time requirements has become a critical issue in the study of real-time semantic segmentation.To address these challenges,this paper proposes a lightweight bilateral dual-residual network.By introducing a novel residual structure combined with feature extraction and fusion modules,the proposed network significantly enhances representational capacity while reducing computational costs.Specifically,an improved compound residual structure is designed to optimize the efficiency of information propagation and feature extraction.Furthermore,the proposed feature extraction and fusion module enables the network to better capture multi-scale information in images,improving the ability to detect both detailed and global semantic features.Experimental results on the publicly available Cityscapes dataset demonstrate that the proposed lightweight dual-branch network achieves outstanding performance while maintaining low computational complexity.In particular,the network achieved a mean Intersection over Union(mIoU)of 78.4%on the Cityscapes validation set,surpassing many existing semantic segmentation models.Additionally,in terms of inference speed,the network reached 74.5 frames per second when tested on an NVIDIA GeForce RTX 3090 GPU,significantly improving real-time performance.
基金the Guangdong Basic and Applied Basic Research Foundation(Grant No.2021A1515012070)the Sichuan Science and Technology Program(Grant Nos.2021YFS0336 and 2019YJ0712)+1 种基金the Fundamental Research Funds for the Central Universities(Grant No.ZYGX2019J035)the Sichuan Science and Technology Innovation Seedling Project Funding Project(Grant No.2020023)are gratefully acknowledged.
文摘In a wind turbine,the rolling bearing is the critical component.However,it has a high failure rate.Therefore,the failure analysis and fault diagnosis of wind power rolling bearings are very important to ensure the high reliability and safety of wind power equipment.In this study,the failure form and the corresponding reason for the failure are discussed firstly.Then,the natural frequency and the characteristic frequency are analyzed.The Empirical Mode Decomposition(EMD)algorithm is used to extract the characteristics of the vibration signal of the rolling bearing.Moreover,the eigenmode function is obtained and then filtered by the kurtosis criterion.Consequently,the relationship between the actual fault frequency spectrum and the theoretical fault frequency can be obtained.Then the fault analysis is performed.To enhance the accuracy of fault diagnosis,based on the previous feature extraction and the time-frequency domain feature extraction of the data after EMD decomposition processing,four different classifiers are added to diagnose and classify the fault status of rolling bearings and compare them with four different classifiers.
基金supported by the National Natural Science Foundation of China(32272124,31991210)and the 2115 Talent Development Program.
文摘Bread wheat provides an essential fraction of the daily calorific intake for humanity.Due to its huge and complex genome,progress in studying on the wheat genome is substantially trailed behind those of the other two major crops,rice and maize,for at least a decade.With rapid advances in genome assembling and reduced cost of high-throughput sequencing,emerging de novo genome assemblies of wheat and whole-genome sequencing data are leading to a paradigm shift in wheat research.Here,we review recent progress in dissecting the complex genome and germplasm evolution of wheat since the release of the first high-quality wheat genome.New insights have been gained in the evolution of wheat germplasm during domestication and modern breeding progress,genomic variations at multiple scales contributing to the diversity of wheat germplasm,and complex transcriptional and epigenetic regulations of functional genes in polyploid wheat.Genomics databases and bioinformatics tools meeting the urgent needs of wheat ge-nomics research are also summarized.The ever-increasing omics data,along with advanced tools and well-structured databases,are expected to accelerate deciphering the germplasm and gene resources in wheat for future breeding advances.
基金This work was funded by the Major Science and Technology Program for Water Pollution Control and Treatment(2017ZX07201003)the National Natural Science Foundation of China(51961125101)the Science and Technology Project of Zhejiang Province(2018C03003).
文摘The problem of effluent total nitrogen(TN)at most of the wastewater treatment plants(WWTPs)in China is important for meeting the related water quality standards,even under the condition of high energy consumption.To achieve better prediction and control of effluent TN concentration,an efficient prediction model,based on controllable operation parameters,was constructed in a sequencing batch reactor process.Compared with previous models,this model has two main characteristics:①Superficial gas velocity and anoxic time are controllable operation parameters and are selected as the main input parameters instead of dissolved oxygen to improve the model controllability,and②the model prediction accuracy is improved on the basis of a feedforward neural network(FFNN)with algorithm optimization.The results demonstrated that the FFNN model was efficiently optimized by scaled conjugate gradient,and the performance was excellent compared with other models in terms of the correlation coefficient(R).The optimized FFNN model could provide an accurate prediction of effluent TN based on influent water parameters and key control parameters.This study revealed the possible application of the optimized FFNN model for the efficient removal of pollutants and lower energy consumption at most of the WWTPs.
基金Supported by the National Natural Science Foundation of China(21620102007)the Natural Science Foundation for High Education of Jiangsu Province(17KJB530011)+1 种基金the Science and Technology Innovation Foundation of Yangzhou University(2017CXJ015)the Priority Academic Program Development of Jiangsu Higher Education Institutions(PAPD)
文摘HZSM-5/MCM-41 molecular sieve (H-ZM) catalysts with well-defined micro/mesoporous structures were synthesized and showed high performance for selective synthesis of triacetin via the esterification reaction of glycerol with acetic acid. The conversion of glycerol was demonstrated to be 100% and the triacetin selectivity was over 91%, which can be attributed to the synergistic effect regarding suitable acidic property, excellent diffusion efficiency and good stability derived from the combined advantages of microporous molecular sieve HZSM-5 and mesoporous molecular sieve MCM-41.
基金supported by the National Natural Science Foundation of China(21603134)Young Talent Fund of University Association for Science and Technology in Shaanxi,China(20150104)+1 种基金Natural Science Basic Research Plan in Shaanxi Province of China(2016JQ2023)the Fundamental Research Funds for the Central Universities(GK201603032)~~
文摘Heterojunction fabrication is one of the most effective strategies for enhancing the photocatalytic performance of semiconductor photocatalysts. Here, TiO2（B）/anatase nanowires with interfacial heterostructures were prepared through a three-step synthesis method, including hydrothermal treatment, H＋ exchange, and annealing. The phase structures of the nanowires in the bulk and on the surface during the annealing process were monitored by XRD and UV-Raman spectroscopy, respectively. SEM and TEM results indicate that the TiO2（B） nanowires partially collapse and transform into anatase during the annealing process and the heterophase junction structure is formed simultaneously. On the basis of the phase structure together with morphology data, a phase-transformation mechanism was proposed. Photocatalytic activity was evaluated by hydrogen production and pollutant-degradation assays. The optimized structure of the photocatalyst contains 24% TiO2（B） in the bulk and 100% anatase on the surface. The charge-carrier behavior during the photocatalytic process was investigated by photocurrent, electrochemical impedance spectroscopy（EIS）, and photoluminescence（PL） spectroscopy, which revealed that the heterophase-junction structure in the bulk was responsible for the highly efficient charge separation and transportation, etc.; the anatase on the surface took control of the high surface-reaction activity.
基金financial support was provided by the National Natural Science Foundation of China (Nos. 61635011, 11574356, 11434010, 61804177 and 11804382)National Key Research and Development Program of China (Nos. 2016YFA0300600 and 2016YFA0301700)+1 种基金Key Research Program of Frontier Sciences, CAS (No. QYZDB-SSW-JSC009)Ting Wang was supported by the Youth Innovation Promotion Association of CAS (No. 2018011)
文摘Direct epitaxial growthⅢ–Ⅴquantum dot(QD)structures on CMOS-compatible silicon substrates is considered as one of the most promising approaches to achieve low-cost and high-yield Si-based lasers for silicon photonic integration.However,epitaxial growth ofⅢ–Ⅴmaterials on Si encounters the following three major challenges:high density of threading dislocations,antiphase boundaries and thermal cracks,which significantly degrade the crystal quality and potential device performance.In this review,we will focus on some recent results related to InAs/GaAs quantum dot lasers on Si(001)substrates byⅢ–Ⅴ/Ⅳhybrid epitaxial growth via(111)-faceted Si hollow structures.Moreover,by using the step-graded epitaxial growth process the emission wavelength of InAs QDs can be extended from O-band to C/L-band.High-performance InAs/GaAs QD microdisk lasers with sub-milliwatts threshold on Si(001)substrates are fabricated and characterized.The above results pave a promising path towards the on-chip lasers for optical interconnect applications.
基金supported by a grant from the Strategic Priority Research Program of the Chinese Academy of Sciences (XDB29040000)the Industrial innovation team grant from Foshan Industrial Technology Research Institute, Chinese Academy of Sciences+1 种基金the National Natural Science Foundation of China (32070163, 81761128002, 81871297)the China ATOMIC energy authority, Foshan High-level Hospital construction DengFeng plan and Guangdong Province biomedical innovation platform construction project tumor immunobiotherapy
文摘The spread of severe acute respiratory syndrome coronavirus 2(SARS-CoV-2) from cold-chain foods to frontline workers poses a serious public health threat during the current global pandemic. There is an urgent need to design concise approaches for effective virus inactivation under different physicochemical conditions to reduce the risk of contagion through viral contaminated surfaces of cold-chain foods. By employing a time course of electron beam exposure to a high titer of SARS-CoV-2 at cold-chain temperatures, a radiation dose of 2 kGy was demonstrated to reduce the viral titer from 10^(4.5)to 0 median tissue culture infectious dose(TCID_(50))/mL. Next,using human coronavirus OC43(HCoV-OC43) as a suitable SARS-CoV-2 surrogate, 3 kGy of high-energy electron radiation was defined as the inactivation dose for a titer reduction of more than 4 log units on tested packaging materials. Furthermore, quantitative reverse transcription PCR(RT-qPCR) was used to test three viral genes,namely, E, N, and ORF1ab. There was a strong correlation between TCID50and RT-qPCR for SARS-CoV-2detection. However, RT-qPCR could not differentiate between the infectivity of the radiation-inactivated and nonirradiated control viruses. As the defined radiation dose for effective viral inactivation fell far below the upper safe dose limit for food processing, our results provide a basis for designing radiation-based approaches for the decontamination of SARS-CoV-2 in frozen food products. We further demonstrate that cell-based virus assays are essential to evaluate the SARS-CoV-2 inactivation efficiency for the decontaminating strategies.
基金the National Natural Science Foundation of China under Grant Nos.61635011,61975230,61804177,11434041 and 11574356the National Key Research and Development Program of China(2016YFA0300600 and 2016YFA0301700)+1 种基金the Key Research Program of Frontier Sciences,CAS(No.QYZDB-SSW-JSC009)Ting Wang is supported by the Youth Innovation Promotion Association of CAS(No.2018011).
文摘Ⅲ-Ⅴ quantum dot(QD) lasers monolithically grown on CMOS-compatible Si substrates are considered as essential components for integrated silicon photonic circuits.However,epitaxial growth of Ⅲ-Ⅴ materials on Si substrates encounters three obstacles:mismatch defects,antiphase boundaries(APBs),and thermal cracks.We study the evolution of the structures on U-shaped trench-patterned Si(001) substrates with various trench orientations by homoepitaxy and the subsequent heteroepitaxial growth of GaAs film.The results show that the formation of(111)-faceted hollow structures on patterned Si(001) substrates with trenches oriented along [110] direction can effectively reduce the defect density and thermal stress in the GaAs/Si epilayers.The(111)-faceted silicon hollow structure can act as a promising platform for the direct growth of Ⅲ-Ⅴ materials for silicon based optoelectronic applications.
基金Project supported by the National Natural Science Foundation of China(Nos.12172027 and 11572022)。
文摘Surface cracks are commonly observed in coatings and films.When structures with coatings are subject to stretching,opening mode cracks are likely to form on the surface,which may further lead to other forms of damage,such as interfacial delamination and substrate damage.Possible crack forms include cracks extending towards the interface and channeling across the film.In this paper,a two-dimensional numerical model is proposed to obtain the structural strain energy at arbitrary crack lengths for bilayer structures under uniaxial tension.The energy release rate and structural stress intensity factors can be obtained accordingly,and the effects of geometry and material features on fracture characteristics are investigated,with most crack patterns being confirmed as unstable.The proposed model can also facilitate the analysis of the stress distribution in periodic crack patterns of films.The results from the numerical model are compared with those obtained by the finite element method(FEM),and the accuracy of the theoretical results is demonstrated.
基金Project supported by the National Natural Science Foundation of China(11974351)。
文摘Full-spectrum phosphor-converted white-light-emitting diodes(pc-WLED)are emerging as a mainstream technology in semiconductor lighting.Nevertheless,high-performance blue phosphor which can be excited efficiently by a 400 nm NUV diode chip is still lacking.Herein,we present a blue-emitting Na_(3)KMg_(7)(PO_(4))6:Eu^(2+)phosphor synthesized by the solid-reaction method.Particularly,we find that the using of Li_(2)CO_(3)as flux can significantly improve the crystal quality and thus the emission efficiency of the phosphor.Meanwhile,the excitation peak of the phosphor shifts from 365 to 400 nm,which is pivotal for efficient NUV(400 nm)diode chip excitation.The practical Eu^(2+)concentration is also enhanced by using Li_(2)CO_(3)as flux,and the absorption efficiency is greatly increased.This phosphor exhibits superior PL thermal stability,namely retains 94%integrated photoluminescence intensity at 150℃of that at 25℃.As a result,the optimized phosphor shows an emission band peaked at 437 nm with a bandwidth of 40 nm and a high external photoluminescence quantum yield of 51.7%.Finally,a pc-WLED was fabricated by using NKMPO:Eu^(2+)blue,Sr_(2)SiO_(4):Eu^(2+)green,CaAlSiN_(3):Eu^(2+)red phosphors,and a 400 nm NUV diode chip.It shows a high color rendering index of R_(a)=96.4 and a correlated color temperature of 4358 K.These results prove that NKMPO:Eu^(2+)is a promising blue phosphor for full-spectrum WLED based on NUV diode chips.
基金supported by the National Natural Science Foundation of China[grant numbers 21466008]the Guangxi Natural Science Foundation,China[grant numbers 2019GXNSFAA185017]+1 种基金the Scientific Research Project of Guangxi Minzu University[grant numbers 2021MDKJ004]the Innovation Project of Guangxi Graduate Education[grant numbers YCSW2022255].
文摘From the end of 2019 until now,the Coronavirus Disease 2019(COVID-19)has been rampaging around the world,posing a great threat to people's lives and health,as well as a serious impact on economic development.Considering the severely infectious nature of COVID-19,the diagnosis of COVID-19 has become crucial.Identification through the use of Computed Tomography(CT)images is an efficient and quick means.Therefore,scientific researchers have proposed numerous segmentation methods to improve the diagnosis of CT images.In this paper,we propose a reinforcement learning-based golden jackal optimization algorithm,which is named QLGJO,to segment CT images in furtherance of the diagnosis of COVID-19.Reinforcement learning is combined for the first time with meta-heuristics in segmentation problem.This strategy can effectively overcome the disadvantage that the original algorithm tends to fall into local optimum.In addition,one hybrid model and three different mutation strategies were applied to the update part of the algorithm in order to enrich the diversity of the population.Two experiments were carried out to test the performance of the proposed algorithm.First,compare QLGJO with other advanced meta-heuristics using the IEEE CEC2022 benchmark functions.Secondly,QLGJO was experimentally evaluated on CT images of COVID-19 using the Otsu method and compared with several well-known meta-heuristics.It is shown that QLGJO is very competitive in benchmark function and image segmentation experiments compared with other advanced meta-heuristics.Furthermore,the source code of the QLGJO is publicly available at https://github.com/Vang-z/QLGJO.
