WE observe that the response speed of a linear timeinvariant system to a step reference input depends not only on the system parameters but also on the magnitude of the step input.Based on this observation,we demonstr...WE observe that the response speed of a linear timeinvariant system to a step reference input depends not only on the system parameters but also on the magnitude of the step input.Based on this observation,we demonstrate a method to schedule the magnitude of the reference input to achieve a faster response.展开更多
Low heat input welding is widely used in the industry.The microstructure and toughness of the welded joints under low heat input conditions have received less attention than those under high heat input.The impact toug...Low heat input welding is widely used in the industry.The microstructure and toughness of the welded joints under low heat input conditions have received less attention than those under high heat input.The impact toughness,microstructure and failure mechanisms of the coarse-grain heat-affected zone(CGHAZ)in a micro-alloyed steel were investigated by welding thermal simulation with the heat input ranging from 15 to 65 kJ/cm.The impact toughness of CGHAZ is highly sensitive to variations in low heat input.The failure mechanisms were discussed from the viewpoints of micro-voids formation and micro-cracks propagation.The micro-voids are preferred to be formed and grow at soft phase of grain boundary ferrite(GBF).At the heat inputs no more than 22 kJ/cm,martensite was dominantly formed,and the micro-cracks initiated from the GBF were propagated into the grain interiors,leading to the brittle fracture and low toughness.When the heat input was increased to 31.2 kJ/cm,granular bainite became the dominant constitute,causing cracks to deflect away from GBF and propagate into prior austenite grains.The high density high-angle and low-angle grain boundaries and the presence of retained austenite,effectively restricted the crack propagation,resulting in ductile fracture behavior and enhanced toughness.High heat input(62.3 kJ/cm)promoted coarse GBF formation,providing continuous paths for microcrack propagation.This direct intergranular crack progression caused brittle fracture and low toughness.Industrial cold cracking in the CGHAZ can thus be controlled by heat input optimization to maximize toughness.展开更多
This study integrates explicit input enhancement into comparative continuation writing,defined as a task in which learners produce a continuation by comparing their own expression with an input text,aligning with its ...This study integrates explicit input enhancement into comparative continuation writing,defined as a task in which learners produce a continuation by comparing their own expression with an input text,aligning with its discourse structure and linguistic features,while developing their own ideas.It aims to examine whether English as a Foreign Language(EFL)learners in China exhibit differences in discourse competence and writing performance when completing comparative continuation writing combined with different input enhancement techniques,and whether the alignment effect occurs at the discourse level.Sixty first-year Chinese senior middle school students were divided into four groups:three groups engaged in comparative continuation writing with varying input enhancement,achieved by combining different techniques,while a control group performed a designated-topic writing task.The results revealed that three comparative continuation writing groups outperformed the designated-topic writing group in discourse competence,particularly in the use of temporal connectives.However,differences and some inconsistencies were observed among the comparative continuation writing groups across individual indices.The study highlights effective ways to incorporate comparative continuation writing into English instruction and demonstrates how explicit input enhancement can complement the task,simultaneously activating the alignment effect proposed by the xu-argument and enhancing discourse competence in writing.展开更多
In this paper,we study the issue of controlling a rotating flexible body-beam system(RFBBS)which consists of a tip mass attached to the free-end and a rigid disk attached to the clamped-end of an Euler-Bernoulli beam....In this paper,we study the issue of controlling a rotating flexible body-beam system(RFBBS)which consists of a tip mass attached to the free-end and a rigid disk attached to the clamped-end of an Euler-Bernoulli beam.The boundary control input is affected by both unknown disturbance and nonlinear input backlash.First,the input backlash is considered as desired control input combined with a nonlinear input error,converting it to an external disturbance,and then,the control signal is designed through the energy-based control method.Next,the closed-loop system’s stability is analysed through Lyapunov direct method.Finally,the efficacy of the proposed control scheme is tested through numerical simulations utilizing the finite difference method.展开更多
With the expansion of peanut planting area year by year,film mulching cultivation has become increasingly important in peanut production due to its unique advantages in enhancing both yield per unit area and overall e...With the expansion of peanut planting area year by year,film mulching cultivation has become increasingly important in peanut production due to its unique advantages in enhancing both yield per unit area and overall economic benefits.Based on the varietal characteristics of‘Zhouhua 5’and addressing practical issues in peanut production,this paper summarized key techniques for high-yield and high-efficiency film mulching cultivation of this variety.These techniques cover all critical stages,including land preparation and fertilization,seed preparation,sowing methods,field management,and timely harvesting,providing technical guidance for varietal promotion and peanut production.展开更多
Currently,the number of patients with myopia is increasing rapidly across the globe.Traditional Chinese medicine(TCM),with its long history and rich experience,has shown promise in effectively managing and treating th...Currently,the number of patients with myopia is increasing rapidly across the globe.Traditional Chinese medicine(TCM),with its long history and rich experience,has shown promise in effectively managing and treating this condition.Nevertheless,considering the vast amount of research that is currently being conducted,focusing on the utilization of TCM in the management of myopia,there is an urgent requirement for a thorough and comprehensive review.The review would serve to clarify the practical applications of TCM within this specific field,and it would also aim to elucidate the underlying mechanisms that are at play,providing a deeper understanding of how TCM principles can be effectively integrated into modern medical practices.Here,some modern medical pathogenesis of myopia and appropriate TCM techniques studies are summarized in the prevention and treatment of myopia.Further,we discussed the potential mechanisms and the future research directions of TCM against myopia.Identifying these mechanisms is crucial for understanding how TCM can be effectively utilized in this context.The combination of various TCM methods or the combination of traditional Chinese and Western medicine is of great significance for the prevention and control of myopia in the future.展开更多
Network-on-Chip(NoC)systems are progressively deployed in connecting massively parallel megacore systems in the new computing architecture.As a result,application mapping has become an important aspect of performance ...Network-on-Chip(NoC)systems are progressively deployed in connecting massively parallel megacore systems in the new computing architecture.As a result,application mapping has become an important aspect of performance and scalability,as current trends require the distribution of computation across network nodes/points.In this paper,we survey a large number of mapping and scheduling techniques designed for NoC architectures.This time,we concentrated on 3D systems.We take a systematic literature review approach to analyze existing methods across static,dynamic,hybrid,and machine-learning-based approaches,alongside preliminary AI-based dynamic models in recent works.We classify them into several main aspects covering power-aware mapping,fault tolerance,load-balancing,and adaptive for dynamic workloads.Also,we assess the efficacy of each method against performance parameters,such as latency,throughput,response time,and error rate.Key challenges,including energy efficiency,real-time adaptability,and reinforcement learning integration,are highlighted as well.To the best of our knowledge,this is one of the recent reviews that identifies both traditional and AI-based algorithms for mapping over a modern NoC,and opens research challenges.Finally,we provide directions for future work toward improved adaptability and scalability via lightweight learned models and hierarchical mapping frameworks.展开更多
Soil greenhouse gas(GHG)emissions contribute profoundly to global warming;however,how plant detritus input alters GHG emissions is poorly understood.Here,we used detritus input and removal treatments(i.e.,DIRT:control...Soil greenhouse gas(GHG)emissions contribute profoundly to global warming;however,how plant detritus input alters GHG emissions is poorly understood.Here,we used detritus input and removal treatments(i.e.,DIRT:control,CK;double litter,DL;no roots with double litter,NRDL;no litter,NL;no roots,NR;no roots and no litter,NRNL)to assess the effects of litter and root inputs on soil CO_(2),CH_(4),and N_(2)O fluxes in soils in a coniferous(Pinus yunnanensis)and a broad-leaf forest(Quercus pannosa)in a subalpine region in southwestern China.Litter addition increased CO_(2) emissions on average 22.22%,but did not significantly alter CH_(4) uptake and N_(2)O emission compared to the CK.Litter removal(NL and NRNL)significantly reduced CO_(2) emissions on average 30.22%and N_(2)O emissions on average 31.16%from both forest soils,but did not significantly affect soil CH_(4) uptake.Root removal(NR and NRNL)generally decreased these three soil GHG fluxes.Changes inβ-1,4-glucosidase(BG)involved in C and phospholipid fatty acid(PLFAs)biomass were projected to influence CO_(2) emissions,while soil microclimates(temperature and moisture)combined with BG activity mainly regulated CH_(4) uptake.Alterations in dissolved organic nitrogen,microbial biomass nitrogen and BG were mainly responsible for changes in N_(2)O emissions.Interestingly,coniferous forest soil seemed to promote CH_(4) uptake more than the broad-leaf forest soil,but CO_(2) and N_(2)O fluxes were not significantly affected by the forest types.As expected,litter addition significantly increased the warming potential,while litter removal relatively lowered it.These findings revealed the divergent roles of plant detritus input and forest type in shaping soil GHG fluxes,thereby providing insights into forest management and predicting contributions of subalpine forests to global warming.展开更多
With the increasing emphasis on personal information protection,encryption through security protocols has emerged as a critical requirement in data transmission and reception processes.Nevertheless,IoT ecosystems comp...With the increasing emphasis on personal information protection,encryption through security protocols has emerged as a critical requirement in data transmission and reception processes.Nevertheless,IoT ecosystems comprise heterogeneous networks where outdated systems coexist with the latest devices,spanning a range of devices from non-encrypted ones to fully encrypted ones.Given the limited visibility into payloads in this context,this study investigates AI-based attack detection methods that leverage encrypted traffic metadata,eliminating the need for decryption and minimizing system performance degradation—especially in light of these heterogeneous devices.Using the UNSW-NB15 and CICIoT-2023 dataset,encrypted and unencrypted traffic were categorized according to security protocol,and AI-based intrusion detection experiments were conducted for each traffic type based on metadata.To mitigate the problem of class imbalance,eight different data sampling techniques were applied.The effectiveness of these sampling techniques was then comparatively analyzed using two ensemble models and three Deep Learning(DL)models from various perspectives.The experimental results confirmed that metadata-based attack detection is feasible using only encrypted traffic.In the UNSW-NB15 dataset,the f1-score of encrypted traffic was approximately 0.98,which is 4.3%higher than that of unencrypted traffic(approximately 0.94).In addition,analysis of the encrypted traffic in the CICIoT-2023 dataset using the same method showed a significantly lower f1-score of roughly 0.43,indicating that the quality of the dataset and the preprocessing approach have a substantial impact on detection performance.Furthermore,when data sampling techniques were applied to encrypted traffic,the recall in the UNSWNB15(Encrypted)dataset improved by up to 23.0%,and in the CICIoT-2023(Encrypted)dataset by 20.26%,showing a similar level of improvement.Notably,in CICIoT-2023,f1-score and Receiver Operation Characteristic-Area Under the Curve(ROC-AUC)increased by 59.0%and 55.94%,respectively.These results suggest that data sampling can have a positive effect even in encrypted environments.However,the extent of the improvement may vary depending on data quality,model architecture,and sampling strategy.展开更多
This paper elaborates on the concept of Traditional Chinese Medicine(TCM)nursing appropriate techniques,selects techniques including moxibustion,auricular seed pressing,acupoint application,massage and Tuina,Chinese h...This paper elaborates on the concept of Traditional Chinese Medicine(TCM)nursing appropriate techniques,selects techniques including moxibustion,auricular seed pressing,acupoint application,massage and Tuina,Chinese herbal foot bath,five-tone therapy,and aromatherapy,and summarizes the application mechanisms,methods,and clinical effects of these techniques in patients with insomnia.It also analyzes the existing problems in their application and discusses future development and practice directions,aiming to provide references for establishing more standardized and scientific nursing plans for patients with insomnia.展开更多
1.Introduction.Pancreaticoduodenectomy is an essential surgical procedure for the treatment of malignant tumors in the pancreatic head,distal common bile duct,and duodenal papilla,and is widely used in clinical practi...1.Introduction.Pancreaticoduodenectomy is an essential surgical procedure for the treatment of malignant tumors in the pancreatic head,distal common bile duct,and duodenal papilla,and is widely used in clinical practice.One of the primary determinants of surgical success is the durability of the pancreaticojejunal anastomosis.展开更多
Objective: To evaluate the preventive effect of shoulder dystocia midwifery techniques combined with predictive nursing on shoulder dystocia. Methods: A total of 82 high-risk pregnant women with shoulder dystocia admi...Objective: To evaluate the preventive effect of shoulder dystocia midwifery techniques combined with predictive nursing on shoulder dystocia. Methods: A total of 82 high-risk pregnant women with shoulder dystocia admitted for childbirth from January 2022 to January 2025 were selected and equally divided using a random number table. The experimental group received shoulder dystocia midwifery techniques combined with predictive nursing, while the reference group received routine midwifery care. Indicators such as the preventive effect on shoulder dystocia were compared between the two groups. Results: The incidence of shoulder dystocia in the experimental group was lower than that in the reference group, the duration of labor was shorter, the amount of intra-partum bleeding was less, the incidence of adverse delivery outcomes was lower, and the score for fear of childbirth after intervention was lower than that in the reference group (p < 0.05). Conclusion: Implementing shoulder dystocia midwifery techniques combined with predictive nursing for high-risk pregnant women with shoulder dystocia can prevent shoulder dystocia and other adverse delivery outcomes, shorten the duration of labor, reduce intra-partum bleeding, and alleviate pregnant women’s fear of childbirth, demonstrating high nursing value.展开更多
Ganmai Dazao Decoction,originating from“Jin Gui Yao Lue”(Synopsis of the Golden Chamber),is a classical prescription for treating visceral agitation.Composed of three medicinal and edible substances-licorice(Gancao)...Ganmai Dazao Decoction,originating from“Jin Gui Yao Lue”(Synopsis of the Golden Chamber),is a classical prescription for treating visceral agitation.Composed of three medicinal and edible substances-licorice(Gancao),wheat(Xiaomai),and jujube(Dazao),it functions to nourish the heart and calm the mind,harmonize the middle burner and regulate Qi,and alleviate urgency and restlessness.As its clinical application has expanded from traditional emotional disorders to neurological,endocrine,and various psychosomatic diseases,establishing a scientifically precise quality control system and deeply elucidating its pharmacodynamic material basis and mechanism of action have become critical tasks.Modern analytical methods,typified by chromatography,spectroscopy,and their hyphenated techniques,with their high sensitivity,high resolution,and powerful substance characterization capabilities,have become the core driving force for standardizing the quality control and modernizing the clinical application research of this formula.This paper systematically reviews the progress of the aforementioned analytical techniques and chemometrics in interpreting the chemical composition,establishing fingerprint profiles,controlling process quality,and researching the pharmacodynamic material basis of Ganmai Dazao Decoction.Furthermore,it discusses integrated approaches combining analytical techniques with pharmacology and clinical medicine to reveal mechanisms of action and explore therapeutic biomarkers.Finally,it provides an outlook on future directions and challenges,including technological integration and innovation,standardization of whole-process quality control systems,and evidence-based research aimed at internationalization.展开更多
Synaptic pruning is a crucial process in synaptic refinement,eliminating unstable synaptic connections in neural circuits.This process is triggered and regulated primarily by spontaneous neural activity and experience...Synaptic pruning is a crucial process in synaptic refinement,eliminating unstable synaptic connections in neural circuits.This process is triggered and regulated primarily by spontaneous neural activity and experience-dependent mechanisms.The pruning process involves multiple molecular signals and a series of regulatory activities governing the“eat me”and“don't eat me”states.Under physiological conditions,the interaction between glial cells and neurons results in the clearance of unnecessary synapses,maintaining normal neural circuit functionality via synaptic pruning.Alterations in genetic and environmental factors can lead to imbalanced synaptic pruning,thus promoting the occurrence and development of autism spectrum disorder,schizophrenia,Alzheimer's disease,and other neurological disorders.In this review,we investigated the molecular mechanisms responsible for synaptic pruning during neural development.We focus on how synaptic pruning can regulate neural circuits and its association with neurological disorders.Furthermore,we discuss the application of emerging optical and imaging technologies to observe synaptic structure and function,as well as their potential for clinical translation.Our aim was to enhance our understanding of synaptic pruning during neural development,including the molecular basis underlying the regulation of synaptic function and the dynamic changes in synaptic density,and to investigate the potential role of these mechanisms in the pathophysiology of neurological diseases,thus providing a theoretical foundation for the treatment of neurological disorders.展开更多
THE Nanjing Yunjin brocade,known for its stunning luster,exquisite patterns,and a wealth of shades,represents the highest level of Chinese brocade craftsmanship.It was the designated textile for the imperial courts of...THE Nanjing Yunjin brocade,known for its stunning luster,exquisite patterns,and a wealth of shades,represents the highest level of Chinese brocade craftsmanship.It was the designated textile for the imperial courts of the Yuan(1206-1368),Ming(1368-1644),and Qing(1616-1911)dynasties,and is still highly regarded to this day.展开更多
Water electrolysis is pivotal for converting renewable energy into clean hydrogen fuel,addressing global energy demand sustainably.However,the development of highly efficient and cost-effective catalysts for the oxyge...Water electrolysis is pivotal for converting renewable energy into clean hydrogen fuel,addressing global energy demand sustainably.However,the development of highly efficient and cost-effective catalysts for the oxygen evolution reaction(OER)remains a significant challenge,particularly at the industrial scale.This report explores a newly discovered pathway,the oxide path mechanism(OPM) for OER-mechanism involving the oxide formation and evolution during the reaction,emphasizing its potential to overcome existing limitations.OPM enables direct O-O coupling without oxygen vacancies,offering superior stability.We detail both classical and innovative in-situ characterization techniques that are central to unraveling the OER mechanism.The advanced in-situ electrochemical techniques,such as inductively coupled plasma mass spectroscopy,X-ray photoelectron spectroscopy,and Mössbauer spectroscopy,coupled with in-situ structural analyses,provide crucial insights into the catalyst surface,the electrode-electrolyte interface and the kinetics of OER.This review provides a systematic analysis integrating classical electrochemical methods with advanced in-situ/operando techniques,specifically focusing on understanding OPM.While numerous studies have examined individual characterization methods,this study systematically integrates traditional electrochemical approaches with in-situ and operando techniques,offering critical insights into their complementary roles in elucidating reaction pathways.The integration of these methodologies provides unprecedented understanding of catalyst behavior under operational conditions,guiding the rational design of next-generation OER catalysts.Furthermore,we discuss essential standardized test toolkits and protocols,such as those for rotating disk electrode and membrane electrode assembly,which are vital for ensuring reproducibility and scalability in OER catalyst research.展开更多
In-situ stress is a key parameter for underground mine design and rock stability analysis.The borehole overcoring technique is widely used for in-situ stress measurement,but the rheological recovery deformation of roc...In-situ stress is a key parameter for underground mine design and rock stability analysis.The borehole overcoring technique is widely used for in-situ stress measurement,but the rheological recovery deformation of rocks after stress relief introduces errors.To improve accuracy,this study proposes an in-situ stress solution theory that incorporates time-dependent stress relief effects.Triaxial stepwise loadingunloading rheological tests on granite and siltstone established quantitative relationships between instantaneous elastic recovery and viscoelastic recovery under different stress levels,confirming their impact on measurement accuracy.By integrating a dual-class elastic deformation recovery model,an improved in-situ stress solution theory was derived.Additionally,accounting for the nonlinear characteristics of rock masses,a determination method for time-dependent nonlinear mechanical parameters was proposed.Based on the CSIRO hollow inclusion strain cell,time-dependent strain correction equations and long-term confining pressure calibration equations were formulated.Finally,the proposed theory was successfully applied at one iron mine(736 m depth)in Xinjiang,China,and one coal mine(510 m depth)in Ningxia,China.Compared to classical theory,the calculated mean stress values showed accuracy improvements of 6.0%and 9.4%,respectively,validating the applicability and reliability of the proposed theory.展开更多
Water quality analysis is essential to understand the ecological status of aquatic life.Conventional water quality index(WQI)assessment methods are limited to features such as water acidic or basicity(pH),dissolved ox...Water quality analysis is essential to understand the ecological status of aquatic life.Conventional water quality index(WQI)assessment methods are limited to features such as water acidic or basicity(pH),dissolved oxygen(DO),biological oxygen demand(BOD),chemical oxygen demand(COD),ammoniacal nitrogen(NH3-N),and suspended solids(SS).These features are often insufficient to represent the water quality of a heavy metal–polluted river.Therefore,this paper aims to explore and analyze novel input features in order to formulate an improved WQI.In this work,prospective insights on the feasibility of alternative water quality input variables as new discriminant features are discussed.The new discriminant features are a step toward formulating adaptive water quality parameters according to the land use activities surrounding the river.The results and analysis obtained from this study have proven the possibility of predicting WQI using new input features.This work analyzes 17 new input features,namely conductivity(COND),salinity(SAL),turbidity(TUR),dissolved solids(DS),nitrate(NO3),chloride(Cl),phosphate(PO4),arsenic(As),chromium(Cr),zinc(Zn),calcium(Ca),iron(Fe),potassium(K),magnesium(Mg),sodium(Na),E.coli,and total coliform,in predicting WQI using machine learning techniques.Five regression algorithms-random forest(RF),AdaBoost,support vector regression(SVR),decision tree regression(DTR),and multilayer perception(MLP)-are applied for preliminary model selection.The results show that the RF algorithm exhibits better prediction performance,with R2 of 0.974.Then,this work proposes a modified RF by incorporating the synthetic minority oversampling technique(SMOTE)into the conventional RF method.The proposed modified RF method is shown to achieve 77.68%,74%,69%,and 71%accuracy,precision,recall,and F1-score,respectively.In addition,the sensitivity analysis is included to highlight the importance of the turbidity variable in WQI prediction.The results of sensitivity analysis highlight the importance of certain water quality variables that are not present in the conventional WQI formulation.展开更多
The Simultaneous Noise and Input Voltage Standing Wave Ratio (VSWR) Matching (SNIM) condition for Low Noise Amplifier (LNA), in principle, can only be satisfied at a single fre-quency. In this paper, by analyzing the ...The Simultaneous Noise and Input Voltage Standing Wave Ratio (VSWR) Matching (SNIM) condition for Low Noise Amplifier (LNA), in principle, can only be satisfied at a single fre-quency. In this paper, by analyzing the fundamental limitations of the narrowband SNIM technique for the broadband application, the authors present a broadband SNIM LNA systematic design technique. The designed LNA guided by the proposed methodology achieves 10 dB power gain with a low Noise Figure of 0.53 dB. Meanwhile, it provides wonderful input matching of 27 dB across the fre-quency range of 3～5 GHz. Therefore, broadband SNIM is realized.展开更多
Lung cancer continues to be a leading cause of cancer-related deaths worldwide,emphasizing the critical need for improved diagnostic techniques.Early detection of lung tumors significantly increases the chances of suc...Lung cancer continues to be a leading cause of cancer-related deaths worldwide,emphasizing the critical need for improved diagnostic techniques.Early detection of lung tumors significantly increases the chances of successful treatment and survival.However,current diagnostic methods often fail to detect tumors at an early stage or to accurately pinpoint their location within the lung tissue.Single-model deep learning technologies for lung cancer detection,while beneficial,cannot capture the full range of features present in medical imaging data,leading to incomplete or inaccurate detection.Furthermore,it may not be robust enough to handle the wide variability in medical images due to different imaging conditions,patient anatomy,and tumor characteristics.To overcome these disadvantages,dual-model or multi-model approaches can be employed.This research focuses on enhancing the detection of lung cancer by utilizing a combination of two learning models:a Convolutional Neural Network(CNN)for categorization and the You Only Look Once(YOLOv8)architecture for real-time identification and pinpointing of tumors.CNNs automatically learn to extract hierarchical features from raw image data,capturing patterns such as edges,textures,and complex structures that are crucial for identifying lung cancer.YOLOv8 incorporates multiscale feature extraction,enabling the detection of tumors of varying sizes and scales within a single image.This is particularly beneficial for identifying small or irregularly shaped tumors that may be challenging to detect.Furthermore,through the utilization of cutting-edge data augmentation methods,such as Deep Convolutional Generative Adversarial Networks(DCGAN),the suggested approach can handle the issue of limited data and boost the models’ability to learn from diverse and comprehensive datasets.The combined method not only improved accuracy and localization but also ensured efficient real-time processing,which is crucial for practical clinical applications.The CNN achieved an accuracy of 97.67%in classifying lung tissues into healthy and cancerous categories.The YOLOv8 model achieved an Intersection over Union(IoU)score of 0.85 for tumor localization,reflecting high precision in detecting and marking tumor boundaries within the images.Finally,the incorporation of synthetic images generated by DCGAN led to a 10%improvement in both the CNN classification accuracy and YOLOv8 detection performance.展开更多
文摘WE observe that the response speed of a linear timeinvariant system to a step reference input depends not only on the system parameters but also on the magnitude of the step input.Based on this observation,we demonstrate a method to schedule the magnitude of the reference input to achieve a faster response.
基金supported by the National Natural Science Foundation of China(No.51804232)Beijing Municipal Natural Science Foundation(No.2212041)+1 种基金supported by the Interdisciplinary Research Project for Young Teachers of USTB(Fundamental Research Funds for the Central Universities)(FRF-IDRY-20-020)GIMRT Program of the Institute for Materials Research,Tohoku University(202303-RDKGE-0518).
文摘Low heat input welding is widely used in the industry.The microstructure and toughness of the welded joints under low heat input conditions have received less attention than those under high heat input.The impact toughness,microstructure and failure mechanisms of the coarse-grain heat-affected zone(CGHAZ)in a micro-alloyed steel were investigated by welding thermal simulation with the heat input ranging from 15 to 65 kJ/cm.The impact toughness of CGHAZ is highly sensitive to variations in low heat input.The failure mechanisms were discussed from the viewpoints of micro-voids formation and micro-cracks propagation.The micro-voids are preferred to be formed and grow at soft phase of grain boundary ferrite(GBF).At the heat inputs no more than 22 kJ/cm,martensite was dominantly formed,and the micro-cracks initiated from the GBF were propagated into the grain interiors,leading to the brittle fracture and low toughness.When the heat input was increased to 31.2 kJ/cm,granular bainite became the dominant constitute,causing cracks to deflect away from GBF and propagate into prior austenite grains.The high density high-angle and low-angle grain boundaries and the presence of retained austenite,effectively restricted the crack propagation,resulting in ductile fracture behavior and enhanced toughness.High heat input(62.3 kJ/cm)promoted coarse GBF formation,providing continuous paths for microcrack propagation.This direct intergranular crack progression caused brittle fracture and low toughness.Industrial cold cracking in the CGHAZ can thus be controlled by heat input optimization to maximize toughness.
文摘This study integrates explicit input enhancement into comparative continuation writing,defined as a task in which learners produce a continuation by comparing their own expression with an input text,aligning with its discourse structure and linguistic features,while developing their own ideas.It aims to examine whether English as a Foreign Language(EFL)learners in China exhibit differences in discourse competence and writing performance when completing comparative continuation writing combined with different input enhancement techniques,and whether the alignment effect occurs at the discourse level.Sixty first-year Chinese senior middle school students were divided into four groups:three groups engaged in comparative continuation writing with varying input enhancement,achieved by combining different techniques,while a control group performed a designated-topic writing task.The results revealed that three comparative continuation writing groups outperformed the designated-topic writing group in discourse competence,particularly in the use of temporal connectives.However,differences and some inconsistencies were observed among the comparative continuation writing groups across individual indices.The study highlights effective ways to incorporate comparative continuation writing into English instruction and demonstrates how explicit input enhancement can complement the task,simultaneously activating the alignment effect proposed by the xu-argument and enhancing discourse competence in writing.
基金supported in part by the National Natural Science Fundation of China under Grant Nos.62403263 and 62373207in part by the Natural Science Fundation of Qingdao,China under Grant No.24-4-4-zrjj-88-jch+1 种基金in part by the Team Plan for Youth Innovation of Universities in Shandong Province under Grant No.2024KJH148in part by the Foundation of Key Laboratory of Autonomous Systems and Networked Control(South China University of Technology),Ministry of Education under Grant No.2024A01.
文摘In this paper,we study the issue of controlling a rotating flexible body-beam system(RFBBS)which consists of a tip mass attached to the free-end and a rigid disk attached to the clamped-end of an Euler-Bernoulli beam.The boundary control input is affected by both unknown disturbance and nonlinear input backlash.First,the input backlash is considered as desired control input combined with a nonlinear input error,converting it to an external disturbance,and then,the control signal is designed through the energy-based control method.Next,the closed-loop system’s stability is analysed through Lyapunov direct method.Finally,the efficacy of the proposed control scheme is tested through numerical simulations utilizing the finite difference method.
基金Supported by Zhoukou Key Science and Technology Research Project(20200816).
文摘With the expansion of peanut planting area year by year,film mulching cultivation has become increasingly important in peanut production due to its unique advantages in enhancing both yield per unit area and overall economic benefits.Based on the varietal characteristics of‘Zhouhua 5’and addressing practical issues in peanut production,this paper summarized key techniques for high-yield and high-efficiency film mulching cultivation of this variety.These techniques cover all critical stages,including land preparation and fertilization,seed preparation,sowing methods,field management,and timely harvesting,providing technical guidance for varietal promotion and peanut production.
基金supported by Healthy China initiative of Traditional Chinese Medicine(No.889042).
文摘Currently,the number of patients with myopia is increasing rapidly across the globe.Traditional Chinese medicine(TCM),with its long history and rich experience,has shown promise in effectively managing and treating this condition.Nevertheless,considering the vast amount of research that is currently being conducted,focusing on the utilization of TCM in the management of myopia,there is an urgent requirement for a thorough and comprehensive review.The review would serve to clarify the practical applications of TCM within this specific field,and it would also aim to elucidate the underlying mechanisms that are at play,providing a deeper understanding of how TCM principles can be effectively integrated into modern medical practices.Here,some modern medical pathogenesis of myopia and appropriate TCM techniques studies are summarized in the prevention and treatment of myopia.Further,we discussed the potential mechanisms and the future research directions of TCM against myopia.Identifying these mechanisms is crucial for understanding how TCM can be effectively utilized in this context.The combination of various TCM methods or the combination of traditional Chinese and Western medicine is of great significance for the prevention and control of myopia in the future.
基金the Deanship of Graduate Studies and Scientific Research at University of Bisha for supporting this work through the Fast-Track Research Support Programthe Deanship of Scientific Research at Northern Border University,Arar,KSA for funding this research work through the project number“NBU-FFR-2025-2903-09”.
文摘Network-on-Chip(NoC)systems are progressively deployed in connecting massively parallel megacore systems in the new computing architecture.As a result,application mapping has become an important aspect of performance and scalability,as current trends require the distribution of computation across network nodes/points.In this paper,we survey a large number of mapping and scheduling techniques designed for NoC architectures.This time,we concentrated on 3D systems.We take a systematic literature review approach to analyze existing methods across static,dynamic,hybrid,and machine-learning-based approaches,alongside preliminary AI-based dynamic models in recent works.We classify them into several main aspects covering power-aware mapping,fault tolerance,load-balancing,and adaptive for dynamic workloads.Also,we assess the efficacy of each method against performance parameters,such as latency,throughput,response time,and error rate.Key challenges,including energy efficiency,real-time adaptability,and reinforcement learning integration,are highlighted as well.To the best of our knowledge,this is one of the recent reviews that identifies both traditional and AI-based algorithms for mapping over a modern NoC,and opens research challenges.Finally,we provide directions for future work toward improved adaptability and scalability via lightweight learned models and hierarchical mapping frameworks.
基金supported by the National Natural Science Foundation of China(32130069)the National Key Research and Development Program of China(2024YFF1306700)the Scientific Research Foundation of Education Department of Yunnan Province(2024Y004).
文摘Soil greenhouse gas(GHG)emissions contribute profoundly to global warming;however,how plant detritus input alters GHG emissions is poorly understood.Here,we used detritus input and removal treatments(i.e.,DIRT:control,CK;double litter,DL;no roots with double litter,NRDL;no litter,NL;no roots,NR;no roots and no litter,NRNL)to assess the effects of litter and root inputs on soil CO_(2),CH_(4),and N_(2)O fluxes in soils in a coniferous(Pinus yunnanensis)and a broad-leaf forest(Quercus pannosa)in a subalpine region in southwestern China.Litter addition increased CO_(2) emissions on average 22.22%,but did not significantly alter CH_(4) uptake and N_(2)O emission compared to the CK.Litter removal(NL and NRNL)significantly reduced CO_(2) emissions on average 30.22%and N_(2)O emissions on average 31.16%from both forest soils,but did not significantly affect soil CH_(4) uptake.Root removal(NR and NRNL)generally decreased these three soil GHG fluxes.Changes inβ-1,4-glucosidase(BG)involved in C and phospholipid fatty acid(PLFAs)biomass were projected to influence CO_(2) emissions,while soil microclimates(temperature and moisture)combined with BG activity mainly regulated CH_(4) uptake.Alterations in dissolved organic nitrogen,microbial biomass nitrogen and BG were mainly responsible for changes in N_(2)O emissions.Interestingly,coniferous forest soil seemed to promote CH_(4) uptake more than the broad-leaf forest soil,but CO_(2) and N_(2)O fluxes were not significantly affected by the forest types.As expected,litter addition significantly increased the warming potential,while litter removal relatively lowered it.These findings revealed the divergent roles of plant detritus input and forest type in shaping soil GHG fluxes,thereby providing insights into forest management and predicting contributions of subalpine forests to global warming.
基金supported by the Institute of Information&Communications Technology Planning&Evaluation(IITP)grant funded by the Korea government(MSIT)(No.RS-2023-00235509Development of security monitoring technology based network behavior against encrypted cyber threats in ICT convergence environment).
文摘With the increasing emphasis on personal information protection,encryption through security protocols has emerged as a critical requirement in data transmission and reception processes.Nevertheless,IoT ecosystems comprise heterogeneous networks where outdated systems coexist with the latest devices,spanning a range of devices from non-encrypted ones to fully encrypted ones.Given the limited visibility into payloads in this context,this study investigates AI-based attack detection methods that leverage encrypted traffic metadata,eliminating the need for decryption and minimizing system performance degradation—especially in light of these heterogeneous devices.Using the UNSW-NB15 and CICIoT-2023 dataset,encrypted and unencrypted traffic were categorized according to security protocol,and AI-based intrusion detection experiments were conducted for each traffic type based on metadata.To mitigate the problem of class imbalance,eight different data sampling techniques were applied.The effectiveness of these sampling techniques was then comparatively analyzed using two ensemble models and three Deep Learning(DL)models from various perspectives.The experimental results confirmed that metadata-based attack detection is feasible using only encrypted traffic.In the UNSW-NB15 dataset,the f1-score of encrypted traffic was approximately 0.98,which is 4.3%higher than that of unencrypted traffic(approximately 0.94).In addition,analysis of the encrypted traffic in the CICIoT-2023 dataset using the same method showed a significantly lower f1-score of roughly 0.43,indicating that the quality of the dataset and the preprocessing approach have a substantial impact on detection performance.Furthermore,when data sampling techniques were applied to encrypted traffic,the recall in the UNSWNB15(Encrypted)dataset improved by up to 23.0%,and in the CICIoT-2023(Encrypted)dataset by 20.26%,showing a similar level of improvement.Notably,in CICIoT-2023,f1-score and Receiver Operation Characteristic-Area Under the Curve(ROC-AUC)increased by 59.0%and 55.94%,respectively.These results suggest that data sampling can have a positive effect even in encrypted environments.However,the extent of the improvement may vary depending on data quality,model architecture,and sampling strategy.
文摘This paper elaborates on the concept of Traditional Chinese Medicine(TCM)nursing appropriate techniques,selects techniques including moxibustion,auricular seed pressing,acupoint application,massage and Tuina,Chinese herbal foot bath,five-tone therapy,and aromatherapy,and summarizes the application mechanisms,methods,and clinical effects of these techniques in patients with insomnia.It also analyzes the existing problems in their application and discusses future development and practice directions,aiming to provide references for establishing more standardized and scientific nursing plans for patients with insomnia.
文摘1.Introduction.Pancreaticoduodenectomy is an essential surgical procedure for the treatment of malignant tumors in the pancreatic head,distal common bile duct,and duodenal papilla,and is widely used in clinical practice.One of the primary determinants of surgical success is the durability of the pancreaticojejunal anastomosis.
文摘Objective: To evaluate the preventive effect of shoulder dystocia midwifery techniques combined with predictive nursing on shoulder dystocia. Methods: A total of 82 high-risk pregnant women with shoulder dystocia admitted for childbirth from January 2022 to January 2025 were selected and equally divided using a random number table. The experimental group received shoulder dystocia midwifery techniques combined with predictive nursing, while the reference group received routine midwifery care. Indicators such as the preventive effect on shoulder dystocia were compared between the two groups. Results: The incidence of shoulder dystocia in the experimental group was lower than that in the reference group, the duration of labor was shorter, the amount of intra-partum bleeding was less, the incidence of adverse delivery outcomes was lower, and the score for fear of childbirth after intervention was lower than that in the reference group (p < 0.05). Conclusion: Implementing shoulder dystocia midwifery techniques combined with predictive nursing for high-risk pregnant women with shoulder dystocia can prevent shoulder dystocia and other adverse delivery outcomes, shorten the duration of labor, reduce intra-partum bleeding, and alleviate pregnant women’s fear of childbirth, demonstrating high nursing value.
文摘Ganmai Dazao Decoction,originating from“Jin Gui Yao Lue”(Synopsis of the Golden Chamber),is a classical prescription for treating visceral agitation.Composed of three medicinal and edible substances-licorice(Gancao),wheat(Xiaomai),and jujube(Dazao),it functions to nourish the heart and calm the mind,harmonize the middle burner and regulate Qi,and alleviate urgency and restlessness.As its clinical application has expanded from traditional emotional disorders to neurological,endocrine,and various psychosomatic diseases,establishing a scientifically precise quality control system and deeply elucidating its pharmacodynamic material basis and mechanism of action have become critical tasks.Modern analytical methods,typified by chromatography,spectroscopy,and their hyphenated techniques,with their high sensitivity,high resolution,and powerful substance characterization capabilities,have become the core driving force for standardizing the quality control and modernizing the clinical application research of this formula.This paper systematically reviews the progress of the aforementioned analytical techniques and chemometrics in interpreting the chemical composition,establishing fingerprint profiles,controlling process quality,and researching the pharmacodynamic material basis of Ganmai Dazao Decoction.Furthermore,it discusses integrated approaches combining analytical techniques with pharmacology and clinical medicine to reveal mechanisms of action and explore therapeutic biomarkers.Finally,it provides an outlook on future directions and challenges,including technological integration and innovation,standardization of whole-process quality control systems,and evidence-based research aimed at internationalization.
基金supported by the National Natural Science Foundation of China,No.31760290,82160688the Key Development Areas Project of Ganzhou Science and Technology,No.2022B-SF9554(all to XL)。
文摘Synaptic pruning is a crucial process in synaptic refinement,eliminating unstable synaptic connections in neural circuits.This process is triggered and regulated primarily by spontaneous neural activity and experience-dependent mechanisms.The pruning process involves multiple molecular signals and a series of regulatory activities governing the“eat me”and“don't eat me”states.Under physiological conditions,the interaction between glial cells and neurons results in the clearance of unnecessary synapses,maintaining normal neural circuit functionality via synaptic pruning.Alterations in genetic and environmental factors can lead to imbalanced synaptic pruning,thus promoting the occurrence and development of autism spectrum disorder,schizophrenia,Alzheimer's disease,and other neurological disorders.In this review,we investigated the molecular mechanisms responsible for synaptic pruning during neural development.We focus on how synaptic pruning can regulate neural circuits and its association with neurological disorders.Furthermore,we discuss the application of emerging optical and imaging technologies to observe synaptic structure and function,as well as their potential for clinical translation.Our aim was to enhance our understanding of synaptic pruning during neural development,including the molecular basis underlying the regulation of synaptic function and the dynamic changes in synaptic density,and to investigate the potential role of these mechanisms in the pathophysiology of neurological diseases,thus providing a theoretical foundation for the treatment of neurological disorders.
文摘THE Nanjing Yunjin brocade,known for its stunning luster,exquisite patterns,and a wealth of shades,represents the highest level of Chinese brocade craftsmanship.It was the designated textile for the imperial courts of the Yuan(1206-1368),Ming(1368-1644),and Qing(1616-1911)dynasties,and is still highly regarded to this day.
基金funded by the EU H2020 Marie Skłodowska-Curie Fellowship (1439425)the National Natural Science Foundation of China (No. 52171199 and 22479011)
文摘Water electrolysis is pivotal for converting renewable energy into clean hydrogen fuel,addressing global energy demand sustainably.However,the development of highly efficient and cost-effective catalysts for the oxygen evolution reaction(OER)remains a significant challenge,particularly at the industrial scale.This report explores a newly discovered pathway,the oxide path mechanism(OPM) for OER-mechanism involving the oxide formation and evolution during the reaction,emphasizing its potential to overcome existing limitations.OPM enables direct O-O coupling without oxygen vacancies,offering superior stability.We detail both classical and innovative in-situ characterization techniques that are central to unraveling the OER mechanism.The advanced in-situ electrochemical techniques,such as inductively coupled plasma mass spectroscopy,X-ray photoelectron spectroscopy,and Mössbauer spectroscopy,coupled with in-situ structural analyses,provide crucial insights into the catalyst surface,the electrode-electrolyte interface and the kinetics of OER.This review provides a systematic analysis integrating classical electrochemical methods with advanced in-situ/operando techniques,specifically focusing on understanding OPM.While numerous studies have examined individual characterization methods,this study systematically integrates traditional electrochemical approaches with in-situ and operando techniques,offering critical insights into their complementary roles in elucidating reaction pathways.The integration of these methodologies provides unprecedented understanding of catalyst behavior under operational conditions,guiding the rational design of next-generation OER catalysts.Furthermore,we discuss essential standardized test toolkits and protocols,such as those for rotating disk electrode and membrane electrode assembly,which are vital for ensuring reproducibility and scalability in OER catalyst research.
基金supported by the National Science and Technology Major Project of the Ministry of Science and Technology of China(No.2024ZD1700201)the National Natural Science Foundation of China(Nos.U2034206,51974014 and 51574014)+1 种基金the Guangdong Basic and Applied Basic Research Foundation(No.2024A1515011631)the National Key Research and Development Project of China(No.2022YFC3004601)。
文摘In-situ stress is a key parameter for underground mine design and rock stability analysis.The borehole overcoring technique is widely used for in-situ stress measurement,but the rheological recovery deformation of rocks after stress relief introduces errors.To improve accuracy,this study proposes an in-situ stress solution theory that incorporates time-dependent stress relief effects.Triaxial stepwise loadingunloading rheological tests on granite and siltstone established quantitative relationships between instantaneous elastic recovery and viscoelastic recovery under different stress levels,confirming their impact on measurement accuracy.By integrating a dual-class elastic deformation recovery model,an improved in-situ stress solution theory was derived.Additionally,accounting for the nonlinear characteristics of rock masses,a determination method for time-dependent nonlinear mechanical parameters was proposed.Based on the CSIRO hollow inclusion strain cell,time-dependent strain correction equations and long-term confining pressure calibration equations were formulated.Finally,the proposed theory was successfully applied at one iron mine(736 m depth)in Xinjiang,China,and one coal mine(510 m depth)in Ningxia,China.Compared to classical theory,the calculated mean stress values showed accuracy improvements of 6.0%and 9.4%,respectively,validating the applicability and reliability of the proposed theory.
基金supported by the Ministry of Higher Education through MRUN Young Researchers Grant Scheme(MY-RGS),MR001-2019,entitled“Climate Change Mitigation:Artificial Intelligence-Based Integrated Environmental System for Mangrove Forest Conservation”and UM-RU Grant,ST065-2021,entitled“Climate-Smart Mitigation and Adaptation:Integrated Climate Resilience Strategy for Tropical Marine Ecosystem.”。
文摘Water quality analysis is essential to understand the ecological status of aquatic life.Conventional water quality index(WQI)assessment methods are limited to features such as water acidic or basicity(pH),dissolved oxygen(DO),biological oxygen demand(BOD),chemical oxygen demand(COD),ammoniacal nitrogen(NH3-N),and suspended solids(SS).These features are often insufficient to represent the water quality of a heavy metal–polluted river.Therefore,this paper aims to explore and analyze novel input features in order to formulate an improved WQI.In this work,prospective insights on the feasibility of alternative water quality input variables as new discriminant features are discussed.The new discriminant features are a step toward formulating adaptive water quality parameters according to the land use activities surrounding the river.The results and analysis obtained from this study have proven the possibility of predicting WQI using new input features.This work analyzes 17 new input features,namely conductivity(COND),salinity(SAL),turbidity(TUR),dissolved solids(DS),nitrate(NO3),chloride(Cl),phosphate(PO4),arsenic(As),chromium(Cr),zinc(Zn),calcium(Ca),iron(Fe),potassium(K),magnesium(Mg),sodium(Na),E.coli,and total coliform,in predicting WQI using machine learning techniques.Five regression algorithms-random forest(RF),AdaBoost,support vector regression(SVR),decision tree regression(DTR),and multilayer perception(MLP)-are applied for preliminary model selection.The results show that the RF algorithm exhibits better prediction performance,with R2 of 0.974.Then,this work proposes a modified RF by incorporating the synthetic minority oversampling technique(SMOTE)into the conventional RF method.The proposed modified RF method is shown to achieve 77.68%,74%,69%,and 71%accuracy,precision,recall,and F1-score,respectively.In addition,the sensitivity analysis is included to highlight the importance of the turbidity variable in WQI prediction.The results of sensitivity analysis highlight the importance of certain water quality variables that are not present in the conventional WQI formulation.
文摘The Simultaneous Noise and Input Voltage Standing Wave Ratio (VSWR) Matching (SNIM) condition for Low Noise Amplifier (LNA), in principle, can only be satisfied at a single fre-quency. In this paper, by analyzing the fundamental limitations of the narrowband SNIM technique for the broadband application, the authors present a broadband SNIM LNA systematic design technique. The designed LNA guided by the proposed methodology achieves 10 dB power gain with a low Noise Figure of 0.53 dB. Meanwhile, it provides wonderful input matching of 27 dB across the fre-quency range of 3～5 GHz. Therefore, broadband SNIM is realized.
文摘Lung cancer continues to be a leading cause of cancer-related deaths worldwide,emphasizing the critical need for improved diagnostic techniques.Early detection of lung tumors significantly increases the chances of successful treatment and survival.However,current diagnostic methods often fail to detect tumors at an early stage or to accurately pinpoint their location within the lung tissue.Single-model deep learning technologies for lung cancer detection,while beneficial,cannot capture the full range of features present in medical imaging data,leading to incomplete or inaccurate detection.Furthermore,it may not be robust enough to handle the wide variability in medical images due to different imaging conditions,patient anatomy,and tumor characteristics.To overcome these disadvantages,dual-model or multi-model approaches can be employed.This research focuses on enhancing the detection of lung cancer by utilizing a combination of two learning models:a Convolutional Neural Network(CNN)for categorization and the You Only Look Once(YOLOv8)architecture for real-time identification and pinpointing of tumors.CNNs automatically learn to extract hierarchical features from raw image data,capturing patterns such as edges,textures,and complex structures that are crucial for identifying lung cancer.YOLOv8 incorporates multiscale feature extraction,enabling the detection of tumors of varying sizes and scales within a single image.This is particularly beneficial for identifying small or irregularly shaped tumors that may be challenging to detect.Furthermore,through the utilization of cutting-edge data augmentation methods,such as Deep Convolutional Generative Adversarial Networks(DCGAN),the suggested approach can handle the issue of limited data and boost the models’ability to learn from diverse and comprehensive datasets.The combined method not only improved accuracy and localization but also ensured efficient real-time processing,which is crucial for practical clinical applications.The CNN achieved an accuracy of 97.67%in classifying lung tissues into healthy and cancerous categories.The YOLOv8 model achieved an Intersection over Union(IoU)score of 0.85 for tumor localization,reflecting high precision in detecting and marking tumor boundaries within the images.Finally,the incorporation of synthetic images generated by DCGAN led to a 10%improvement in both the CNN classification accuracy and YOLOv8 detection performance.
