In this study the medium-term response of beach profiles was investigated at two sites： a gently sloping sandy beach and a steeper mixed sand and gravel beach. The former is the Duck site in North Carolina, on the ea...In this study the medium-term response of beach profiles was investigated at two sites： a gently sloping sandy beach and a steeper mixed sand and gravel beach. The former is the Duck site in North Carolina, on the east coast of the USA, which is exposed to Atlantic Ocean swells and storm waves, and the latter is the Milford-on-Sea site at Christchurch Bay, on the south coast of England, which is partially sheltered from Atlantic swells but has a directionally bimodal wave exposure. The data sets comprise detailed bathymetric surveys of beach profiles covering a period of more than 25 years for the Duck site and over 18 years for the Milford-on-Sea site. The structure of the data sets and the data-driven methods are described. Canonical correlation analysis （CCA） was used to find linkages between the wave characteristics and beach profiles. The sensitivity of the linkages was investigated by deploying a wave height threshold to filter out the smaller waves incrementally. The results of the analysis indicate that, for the gently sloping sandy beach, waves of all heights are important to the morphological response. For the mixed sand and gravel beach, filtering the smaller waves improves the statistical fit and it suggests that low-height waves do not play a primary role in the medium-term morohological resoonse, which is primarily driven by the intermittent larger storm waves.展开更多
Introducing IoT devices to healthcare fields has made it possible to remotely monitor patients’information and provide a proper diagnosis as needed,resulting in the Internet of Medical Things(IoMT).However,obtaining ...Introducing IoT devices to healthcare fields has made it possible to remotely monitor patients’information and provide a proper diagnosis as needed,resulting in the Internet of Medical Things(IoMT).However,obtaining good security features that ensure the integrity and confidentiality of patient’s information is a significant challenge.However,due to the computational resources being limited,an edge device may struggle to handle heavy detection tasks such as complex machine learning algorithms.Therefore,designing and developing a lightweight detection mechanism is crucial.To address the aforementioned challenges,a new lightweight IDS approach is developed to effectively combat a diverse range of cyberattacks in IoMT networks.The proposed anomaly-based IDS is divided into three steps:pre-processing,feature selection,and decision.In the pre-processing phase,data cleaning and normalization are performed.In the feature selection step,the proposed approach uses two data-driven kernel techniques:kernel principal component analysis and kernel partial least square techniques to reduce the dimension of extracted features and to ameliorate the detection results.Therefore,in decision step,in order to classify whether the traffic flow is normal or malicious the kernel extreme learning machine is used.To check the efficiency of the developed detection scheme,a modern IoMT dataset named WUSTL-EHMS-2020 is considered to evaluate and discuss the achieved results.The proposed method achieved 99.9%accuracy,99.8%specificity,100%Sensitivity,99.9 F-score.展开更多
Due to growing concerns regarding climate change and environmental protection,smart power generation has become essential for the economical and safe operation of both conventional thermal power plants and sustainable...Due to growing concerns regarding climate change and environmental protection,smart power generation has become essential for the economical and safe operation of both conventional thermal power plants and sustainable energy.Traditional first-principle model-based methods are becoming insufficient when faced with the ever-growing system scale and its various uncertainties.The burgeoning era of machine learning(ML)and data-driven control(DDC)techniques promises an improved alternative to these outdated methods.This paper reviews typical applications of ML and DDC at the level of monitoring,control,optimization,and fault detection of power generation systems,with a particular focus on uncovering how these methods can function in evaluating,counteracting,or withstanding the effects of the associated uncertainties.A holistic view is provided on the control techniques of smart power generation,from the regulation level to the planning level.The benefits of ML and DDC techniques are accordingly interpreted in terms of visibility,maneuverability,flexibility,profitability,and safety(abbreviated as the“5-TYs”),respectively.Finally,an outlook on future research and applications is presented.展开更多
As artificial intelligence(AI)technology evolves,data-driven approaches are gaining attention in predicting lithium-ion battery's remaining useful life(RUL).Indeed,accurate RUL prediction is challenging,primarily ...As artificial intelligence(AI)technology evolves,data-driven approaches are gaining attention in predicting lithium-ion battery's remaining useful life(RUL).Indeed,accurate RUL prediction is challenging,primarily because of the complex nature of the work and dynamic shifts in model parameters.To address these challenges,this article comprehensively explores five significant publicly accessible lithium-ion battery datasets,encompassing diverse usage conditions and battery types,offering researchers a rich repository of experimental data.In particular,we not only provide detailed information and access addresses for each dataset,but also present,four innovative methods for battery aging health factor extraction.These methods,based on advanced AI techniques,are able to effectively identify and quantify key indicators of battery performance degradation,thereby enhancing the precision and dependability of RUL prediction.Additionally,the article identifies major challenges faced by current predictive techniques,including data quality,model generalization capabilities,and computational cost,highlighting the need for research focused on dataset diversity,multiple algorithm fusion,and hybrid physicaldata-driven models to enhance prediction accuracy.We believe that this review will help researchers gain a comprehensive understanding of RUL estimation methods and promote the development of AI in battery.展开更多
Construction engineering and management(CEM)has become increasingly complicated with the increasing size of engineering projects under different construction environments,motivating the digital transformation of CEM.T...Construction engineering and management(CEM)has become increasingly complicated with the increasing size of engineering projects under different construction environments,motivating the digital transformation of CEM.To contribute to a better understanding of the state of the art of smart techniques for engineering projects,this paper provides a comprehensive review of multi-criteria decision-making(MCDM)techniques,intelligent techniques,and their applications in CEM.First,a comprehensive framework detailing smart technologies for construction projects is developed.Next,the characteristics of CEM are summarized.A bibliometric review is then conducted to investigate the keywords,journals,and clusters related to the application of smart techniques in CEM during 2000-2022.Recent advancements in intelligent techniques are also discussed under the following six topics:①big data technology;②computer vision;③speech recognition;④natural language processing;⑤machine learning;and⑥knowledge representation,understanding,and reasoning.The applications of smart techniques are then illustrated via underground space exploitation.Finally,future research directions for the sustainable development of smart construction are highlighted.展开更多
Precise transverse emittance assessment in electron beams is crucial for advancing high-brightness beam injectors.As opposed to intricate methodologies that use specialized devices,quadrupole focusing strength scannin...Precise transverse emittance assessment in electron beams is crucial for advancing high-brightness beam injectors.As opposed to intricate methodologies that use specialized devices,quadrupole focusing strength scanning(Q-scanning)techniques offer notable advantages for various injectors owing to their inherent convenience and cost-effectiveness.However,their stringent approximation conditions lead to inevitable errors in practical operation,thereby limiting their widespread application.This study addressed these challenges by revisiting the analytical derivation procedure and investigating the effects of the underlying approximation conditions.Preliminary corrections were explored through a combination of data processing analysis and numerical simulations.Furthermore,based on theoretical derivations,virtual measurements using beam dynamics calculations were employed to evaluate the correction reliability.Subsequent experimental validations were performed at the Huazhong University of Science and Technology injector to verify the effectiveness of the proposed compensation method.Both the virtual and experimental results confirm the feasibility and reliability of the enhanced Q-scanning-based diagnosis for transverse emittance in typical beam injectors operating under common conditions.Through the integration of these corrections and compensations,enhanced Q-scanning-based techniques emerge as promising alternatives to traditional emittance diagnosis methods.展开更多
BACKGROUND The induced-membrane technique was initially described by Masquelet as an effective treatment for large bone defects,especially those caused by infection.Here,we report a case of chronic osteomyelitis of th...BACKGROUND The induced-membrane technique was initially described by Masquelet as an effective treatment for large bone defects,especially those caused by infection.Here,we report a case of chronic osteomyelitis of the radius associated with a 9 cm bone defect,which was filled with a large allogeneic cortical bone graft from a bone bank.Complete bony union was achieved after 14 months of follow-up.Previous studies have used autogenous bone as the primary bone source for the Masquelet technique;in our case,the exclusive use of allografts is as successful as the use of autologous bone grafts.With the advent of bone banks,it is possible to obtain an unlimited amount of allograft,and the Masquelet technique may be further improved based on this new way of bone grafting.CASE SUMMARY In this study,we reported a case of repair of a long bone defect in a 40-year-old male patient,which was characterized by the utilization of allograft cortical bone combined with the Masquelet technique for the treatment of the patient's long bone defect in the forearm.The patient's results of functional recovery of the forearm were surprising,which further deepens the scope of application of Masquelet technique and helps to strengthen the efficacy of Masquelet technique in the treatment of long bones indeed.CONCLUSION Allograft cortical bone combined with the Masquelet technique provides a new method of treatment to large bone defect.展开更多
A polarization-sensitive and flexible photodetector was fabricated through the precise alignment of perovskite nanowires(NWs)using a brush coating technique.The alignment of the NWs was meticulously examined,consideri...A polarization-sensitive and flexible photodetector was fabricated through the precise alignment of perovskite nanowires(NWs)using a brush coating technique.The alignment of the NWs was meticulously examined,considering various chemical properties of the solvent,such as boiling point,viscosity,and surface tension.Notably,when the NWs were brush-coated with toluene dispersion,the NWs were aligned in higher order than those processed from octane dispersion.The degree of alignment was correlated with the photodetector property.Especially,the well-aligned NW photodetector exhibited a two-fold disparity in current response contingent on the polarization direction.Furthermore,even after enduring 500 bending cycles,the device retained 80%of its photodetector performance.This approach underscores the potential of solution-processed flexible photodetectors for advanced optical applications under dynamic operating conditions.展开更多
This paper presents a high-fidelity lumpedparameter(LP)thermal model(HF-LPTM)for permanent magnet synchronous machines(PMSMs)in electric vehicle(EV)applications,where various cooling techniques are considered,includin...This paper presents a high-fidelity lumpedparameter(LP)thermal model(HF-LPTM)for permanent magnet synchronous machines(PMSMs)in electric vehicle(EV)applications,where various cooling techniques are considered,including frame forced air/liquid cooling,oil jet cooling for endwinding,and rotor shaft cooling.To address the temperature misestimation in the LP thermal modelling due to assumptions of concentrated loss input and uniform heat flows,the developed HF-LPTM introduces two compensation thermal resistances for the winding and PM components,which are analytically derived from the multi-dimensional heat transfer equations and are robust against different load/thermal conditions.As validated by the finite element analysis method and experiments,the conventional LPTMs exhibit significant winding temperature deviations,while the proposed HF-LPTM can accurately predict both the midpoint and average temperatures.The developed HFLPTM is further used to assess the effectiveness of various cooling techniques under different scenarios,i.e.,steady-state thermal states under the rated load condition,and transient temperature profiles under city,freeway,and hybrid(city+freeway)driving cycles.Results indicate that no single cooling technique can maintain both winding and PM temperatures within safety limits.The combination of frame liquid cooling and oil jet cooling for end winding can sufficiently mitigate PMSM thermal stress in EV applications.展开更多
With the rapid advancement of visual generative models such as Generative Adversarial Networks(GANs)and stable Diffusion,the creation of highly realistic Deepfake through automated forgery has significantly progressed...With the rapid advancement of visual generative models such as Generative Adversarial Networks(GANs)and stable Diffusion,the creation of highly realistic Deepfake through automated forgery has significantly progressed.This paper examines the advancements inDeepfake detection and defense technologies,emphasizing the shift from passive detection methods to proactive digital watermarking techniques.Passive detection methods,which involve extracting features from images or videos to identify forgeries,encounter challenges such as poor performance against unknown manipulation techniques and susceptibility to counter-forensic tactics.In contrast,proactive digital watermarking techniques embed specificmarkers into images or videos,facilitating real-time detection and traceability,thereby providing a preemptive defense againstDeepfake content.We offer a comprehensive analysis of digitalwatermarking-based forensic techniques,discussing their advantages over passivemethods and highlighting four key benefits:real-time detection,embedded defense,resistance to tampering,and provision of legal evidence.Additionally,the paper identifies gaps in the literature concerning proactive forensic techniques and suggests future research directions,including cross-domain watermarking and adaptive watermarking strategies.By systematically classifying and comparing existing techniques,this review aims to contribute valuable insights for the development of more effective proactive defense strategies in Deepfake forensics.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
One of the detection objectives of the Chinese Asteroid Exploration mission is to investigate the space environment near the Main-belt Comet(MBC,Active Asteroid)311P/PANSTARRS.This paper outlines the scientific object...One of the detection objectives of the Chinese Asteroid Exploration mission is to investigate the space environment near the Main-belt Comet(MBC,Active Asteroid)311P/PANSTARRS.This paper outlines the scientific objectives,measurement targets,and measurement requirements for the proposed Gas and Ion Analyzer(GIA).The GIA is designed for in-situ mass spectrometry of neutral gases and low-energy ions,such as hydrogen,carbon,and oxygen,in the vicinity of 311P.Ion sampling techniques are essential for the GIA's Time-of-Flight(TOF)mass analysis capabilities.In this paper,we present an enhanced ion sampling technique through the development of an ion attraction model and an ion source model.The ion attraction model demonstrates that adjusting attraction grid voltage can enhance the detection efficiency of low-energy ions and mitigate the repulsive force of ions during sampling,which is influenced by the satellite's surface positive charging.The ion source model simulates the processes of gas ionization and ion multiplication.Simulation results indicate that the GIA can achieve a lower pressure limit below 10-13Pa and possess a dynamic range exceeding 10~9.These performances ensure the generation of ions with stable and consistent current,which is crucial for high-resolution and broad dynamic range mass spectrometer analysis.Preliminary testing experiments have verified GIA's capability to detect gas compositions such as H2O and N2.In-situ measurements near 311P using GIA are expected to significantly contribute to our understanding of asteroid activity mechanisms,the evolution of the atmospheric and ionized environments of main-belt comets,the interactions with solar wind,and the origin of Earth's water.展开更多
Despite advancements in neuroimaging,false positive diagnoses of intracranial aneurysms remain a significant concern.This article examines the causes,prevalence,and implications of such false-positive diagnoses.We dis...Despite advancements in neuroimaging,false positive diagnoses of intracranial aneurysms remain a significant concern.This article examines the causes,prevalence,and implications of such false-positive diagnoses.We discuss how conditions like arterial occlusion with vascular stump formation and infundibular widening can mimic aneurysms,particularly in the anterior circulation.The article compares various imaging modalities,including computer tomography angiogram,magnetic resonance imaging/angiography,and digital subtraction angiogram,highlighting their strengths and limitations.We emphasize the im-portance of accurate differentiation to avoid unnecessary surgical interventions.The potential of emerging technologies,such as high-resolution vessel wall ima-ging and deep neural networks for automated detection,is explored as promising avenues for improving diagnostic accuracy.This manuscript underscores the need for continued research and clinical vigilance in the diagnosis of intracranial aneurysms.展开更多
Short process forming techniques for brazing and soldering materials can shorten the process,improve product quality,and increase production efficiency,which has received much attention from welding researchers.This r...Short process forming techniques for brazing and soldering materials can shorten the process,improve product quality,and increase production efficiency,which has received much attention from welding researchers.This review mainly summarized the research reports on short process forming techniques for brazing and soldering materials.Firstly,the traditional process and its shortcomings were presented.Secondly,the latest research of short process forming technologies,such as continuous casting technique,atomization powder technique,solder ball forming technique,and rapid solidification technique,was summarized,and the traditional forming performance of several brazing and soldering materials was introduced.Finally,the current restrictions and research trends of short process forming technique for brazing and solder materials were put forward,providing theoretical guidance and reference for related research and technique development in brazing and soldering field.展开更多
Low-voltage direct current(DC)microgrids have recently emerged as a promising and viable alternative to traditional alternating cur-rent(AC)microgrids,offering numerous advantages.Consequently,researchers are explorin...Low-voltage direct current(DC)microgrids have recently emerged as a promising and viable alternative to traditional alternating cur-rent(AC)microgrids,offering numerous advantages.Consequently,researchers are exploring the potential of DC microgrids across var-ious configurations.However,despite the sustainability and accuracy offered by DC microgrids,they pose various challenges when integrated into modern power distribution systems.Among these challenges,fault diagnosis holds significant importance.Rapid fault detection in DC microgrids is essential to maintain stability and ensure an uninterrupted power supply to critical loads.A primary chal-lenge is the lack of standards and guidelines for the protection and safety of DC microgrids,including fault detection,location,and clear-ing procedures for both grid-connected and islanded modes.In response,this study presents a brief overview of various approaches for protecting DC microgrids.展开更多
BACKGROUND Uniportal full-endoscopy(UFE)technique has been continuously developed and applied for treating lumbar spinal stenosis.However,achieving effective decompression outcome of using the UFE technique remains te...BACKGROUND Uniportal full-endoscopy(UFE)technique has been continuously developed and applied for treating lumbar spinal stenosis.However,achieving effective decompression outcome of using the UFE technique remains technically demanding and uncertain.Previously,we have proposed the biportal full-endoscopy(BFE)technique to integrate the respective advantages of both UFE and unilateral biportal endoscopy technique.There is limited published data on the comparison of clinical outcomes between biportal and UFE techniques in lumbar spinal stenosis with bilateral symptoms.AIM To contrast the clinical outcomes between biportal and UFE techniques for treating lumbar spinal stenosis with bilateral symptoms.METHODS This study retrospectively examined 100 patients diagnosed with lumbar spinal stenosis and bilateral symptoms.Among them,52 cases were part of group A(BFE technique group),and 48 cases belonged to group B(UFE technique group).The visual analogue scale(VAS),Oswestry Disability Index(ODI),and modified Macnab criteria were used to evaluate the clinical outcomes.RESULTS Group A had significantly shorter operation time than group B.Both groups experienced substantial relief in lower back and lower extremity pain on the severe side at postoperative 3 days,3 months,and 12 months.Group A had notably lower VAS scores for mild side lower extremity pain at postoperative 3 months and 12 months compared to group B.Group A's ODI scores were significantly lower at postoperative 3 months and 12 months,whereas group B's scores did not significantly differ from preoperative values.Group A's ODI scores were significantly lower than group B's at postoperative 3 months and 12 months.Group A had a significantly higher excellent and good response rate(94.23%)compared to group B(81.25%)at postoperative 12 months based on the modified Macnab scale outcomes.CONCLUSION The BFE technique offers multiple benefits,including reduced trauma and quicker recovery as a minimally invasive surgery,and enhanced decompression efficiency over the UFE technique when treating lumbar spinal stenosis with bilateral symptoms.展开更多
Every second, a large volume of useful data is created in social media about the various kind of online purchases and in another forms of reviews. Particularly, purchased products review data is enormously growing in ...Every second, a large volume of useful data is created in social media about the various kind of online purchases and in another forms of reviews. Particularly, purchased products review data is enormously growing in different database repositories every day. Most of the review data are useful to new customers for theier further purchases as well as existing companies to view customers feedback about various products. Data Mining and Machine Leaning techniques are familiar to analyse such kind of data to visualise and know the potential use of the purchased items through online. The customers are making quality of products through their sentiments about the purchased items from different online companies. In this research work, it is analysed sentiments of Headphone review data, which is collected from online repositories. For the analysis of Headphone review data, some of the Machine Learning techniques like Support Vector Machines, Naive Bayes, Decision Trees and Random Forest Algorithms and a Hybrid method are applied to find the quality via the customers’ sentiments. The accuracy and performance of the taken algorithms are also analysed based on the three types of sentiments such as positive, negative and neutral.展开更多
LONGQUAN,a historic city in east China’s Zhejiang Province,is renowned for its exquisite celadon ware,featuring fine texture and pure,jade-like glaze.The region has a potterymaking tradition that spans over 1,600 yea...LONGQUAN,a historic city in east China’s Zhejiang Province,is renowned for its exquisite celadon ware,featuring fine texture and pure,jade-like glaze.The region has a potterymaking tradition that spans over 1,600 years.Its celadon firing technique originated during the Three Kingdoms Period(220-280)and reached its peak in the Southern Song Dynasty(1127-1279).Since the Song Dynasty(960-1368),Longquan was among the main suppliers of porcelain for the imperial court.From the 12th to the 15th centuries.展开更多
BACKGROUND Surgically created arterio-venous fistulas(AVFs)are the gold standard for haemodialysis access for patients with end-stage renal disease.Standard practice of AVF creation involves selecting the non-dominant...BACKGROUND Surgically created arterio-venous fistulas(AVFs)are the gold standard for haemodialysis access for patients with end-stage renal disease.Standard practice of AVF creation involves selecting the non-dominant upper limb and starting with most distally with radio-cephalic arterio-venous fistula.The primary patency rate of radio-cephalic arterio-venous fistula varies from 20%-25%.It has been suggested the neointimal hyperplasia at the mobilized venous segment causes stenosis of the anastomosis.Therefore,the radial artery deviation and reimplantation(RADAR)technique,in which the vein is minimally mobilized,should result in a higher success rate.AIM To compare the RADAR technique with classical technique in creation of AVF including:(1)Success rate;(2)Time to maturation;(3)Duration of surgery;and(4)Complication rate.METHODS In our study we recruited 94 patients in two randomized groups and performed the AVF by the classical method or the RADAR method.RESULTS The RADAR group had higher primary success rate(P=0.007),less rate of complications(P=0.04),shorter duration of surgery(P=0.00)and early time to maturation(0.001)when compared with the classical group.The RADAR procedure is a safe and a more efficient alternative to the current classical method of AVF creation.Longer duration of follow-up is required to assess the long-term outcomes in the future.CONCLUSION The RADAR procedure is a safe and more efficient alternative to the current classical method of AVF creation.Longer duration of follow-up is required to assess the long-term outcomes in the future.展开更多
Objectives:The objective of this study was to assess the impact of two relaxation techniques,the Jacobson’s progressive muscle relaxation technique(JPMR),and the Benson’s relaxation technique(BRT),on the levels of s...Objectives:The objective of this study was to assess the impact of two relaxation techniques,the Jacobson’s progressive muscle relaxation technique(JPMR),and the Benson’s relaxation technique(BRT),on the levels of stress and anxiety experienced by patients undergoing coronary angioplasty.Materials and Methods:Quantitative research approach with quasi-experimental pre-test and posttest control group design was conducted with seventy coronary angioplasty patients from the Institute of Medical Science,and SUM Hospital,Bhubaneswar,Odisha.The participants were purposively selected and divided into Experimental Group 1(n=35)and Experimental Group 2(n=35).Each group received either BRT or JPMR for three consecutive days.Pretest and posttest data were collected using a structured demographic questionnaire and the modified depression anxiety stress scale-21.Results:Both BRT and JPMR significantly decreased the levels of stress and anxiety among patients undergoing angioplasty compared to baseline(P<0.05).However,there was no significant difference between the two techniques based on Fisher’s exact P value.This suggests that both interventions are effective in reducing stress and anxiety among angioplasty patients.Conclusion:BRT or JPMR are noninvasive,nonpharmacological interventions that effectively reduce stress and anxiety in patients undergoing angioplasty.These findings underscore the importance of incorporating relaxation techniques into nursing practice and hospital programs to enhance patient care and promote holistic well-being post-angioplasty.展开更多
基金supported by the UK Natural Environment Research Council(Grant No.NE/J005606/1)the UK Engineering and Physical Sciences Research Council(Grant No.EP/C005392/1)the Ensemble Estimation of Flood Risk in a Changing Climate(EFRa CC)project funded by the British Council under its Global Innovation Initiative
文摘In this study the medium-term response of beach profiles was investigated at two sites： a gently sloping sandy beach and a steeper mixed sand and gravel beach. The former is the Duck site in North Carolina, on the east coast of the USA, which is exposed to Atlantic Ocean swells and storm waves, and the latter is the Milford-on-Sea site at Christchurch Bay, on the south coast of England, which is partially sheltered from Atlantic swells but has a directionally bimodal wave exposure. The data sets comprise detailed bathymetric surveys of beach profiles covering a period of more than 25 years for the Duck site and over 18 years for the Milford-on-Sea site. The structure of the data sets and the data-driven methods are described. Canonical correlation analysis （CCA） was used to find linkages between the wave characteristics and beach profiles. The sensitivity of the linkages was investigated by deploying a wave height threshold to filter out the smaller waves incrementally. The results of the analysis indicate that, for the gently sloping sandy beach, waves of all heights are important to the morphological response. For the mixed sand and gravel beach, filtering the smaller waves improves the statistical fit and it suggests that low-height waves do not play a primary role in the medium-term morohological resoonse, which is primarily driven by the intermittent larger storm waves.
基金supported by the Deanship of Scientific Research at the University of Tabuk through Research No.S-1443-0111.
文摘Introducing IoT devices to healthcare fields has made it possible to remotely monitor patients’information and provide a proper diagnosis as needed,resulting in the Internet of Medical Things(IoMT).However,obtaining good security features that ensure the integrity and confidentiality of patient’s information is a significant challenge.However,due to the computational resources being limited,an edge device may struggle to handle heavy detection tasks such as complex machine learning algorithms.Therefore,designing and developing a lightweight detection mechanism is crucial.To address the aforementioned challenges,a new lightweight IDS approach is developed to effectively combat a diverse range of cyberattacks in IoMT networks.The proposed anomaly-based IDS is divided into three steps:pre-processing,feature selection,and decision.In the pre-processing phase,data cleaning and normalization are performed.In the feature selection step,the proposed approach uses two data-driven kernel techniques:kernel principal component analysis and kernel partial least square techniques to reduce the dimension of extracted features and to ameliorate the detection results.Therefore,in decision step,in order to classify whether the traffic flow is normal or malicious the kernel extreme learning machine is used.To check the efficiency of the developed detection scheme,a modern IoMT dataset named WUSTL-EHMS-2020 is considered to evaluate and discuss the achieved results.The proposed method achieved 99.9%accuracy,99.8%specificity,100%Sensitivity,99.9 F-score.
文摘Due to growing concerns regarding climate change and environmental protection,smart power generation has become essential for the economical and safe operation of both conventional thermal power plants and sustainable energy.Traditional first-principle model-based methods are becoming insufficient when faced with the ever-growing system scale and its various uncertainties.The burgeoning era of machine learning(ML)and data-driven control(DDC)techniques promises an improved alternative to these outdated methods.This paper reviews typical applications of ML and DDC at the level of monitoring,control,optimization,and fault detection of power generation systems,with a particular focus on uncovering how these methods can function in evaluating,counteracting,or withstanding the effects of the associated uncertainties.A holistic view is provided on the control techniques of smart power generation,from the regulation level to the planning level.The benefits of ML and DDC techniques are accordingly interpreted in terms of visibility,maneuverability,flexibility,profitability,and safety(abbreviated as the“5-TYs”),respectively.Finally,an outlook on future research and applications is presented.
基金supported by the National Natural Science Foundation of China(No.22278127)the Fundamental Research Funds for the Central Universities(No.2022ZFJH004)the Shanghai Pilot Program for Basic Research(22T01400100-18).
文摘As artificial intelligence(AI)technology evolves,data-driven approaches are gaining attention in predicting lithium-ion battery's remaining useful life(RUL).Indeed,accurate RUL prediction is challenging,primarily because of the complex nature of the work and dynamic shifts in model parameters.To address these challenges,this article comprehensively explores five significant publicly accessible lithium-ion battery datasets,encompassing diverse usage conditions and battery types,offering researchers a rich repository of experimental data.In particular,we not only provide detailed information and access addresses for each dataset,but also present,four innovative methods for battery aging health factor extraction.These methods,based on advanced AI techniques,are able to effectively identify and quantify key indicators of battery performance degradation,thereby enhancing the precision and dependability of RUL prediction.Additionally,the article identifies major challenges faced by current predictive techniques,including data quality,model generalization capabilities,and computational cost,highlighting the need for research focused on dataset diversity,multiple algorithm fusion,and hybrid physicaldata-driven models to enhance prediction accuracy.We believe that this review will help researchers gain a comprehensive understanding of RUL estimation methods and promote the development of AI in battery.
基金funded by the project of Guangdong Provincial Basic and Applied Basic Research Fund Committee(2022A1515240073)the Pearl River Talent Recruitment Program(2019CX01G338),Guangdong Province.
文摘Construction engineering and management(CEM)has become increasingly complicated with the increasing size of engineering projects under different construction environments,motivating the digital transformation of CEM.To contribute to a better understanding of the state of the art of smart techniques for engineering projects,this paper provides a comprehensive review of multi-criteria decision-making(MCDM)techniques,intelligent techniques,and their applications in CEM.First,a comprehensive framework detailing smart technologies for construction projects is developed.Next,the characteristics of CEM are summarized.A bibliometric review is then conducted to investigate the keywords,journals,and clusters related to the application of smart techniques in CEM during 2000-2022.Recent advancements in intelligent techniques are also discussed under the following six topics:①big data technology;②computer vision;③speech recognition;④natural language processing;⑤machine learning;and⑥knowledge representation,understanding,and reasoning.The applications of smart techniques are then illustrated via underground space exploitation.Finally,future research directions for the sustainable development of smart construction are highlighted.
基金supported by the National Natural Science Foundation of China(Nos.12341501 and 11905074)。
文摘Precise transverse emittance assessment in electron beams is crucial for advancing high-brightness beam injectors.As opposed to intricate methodologies that use specialized devices,quadrupole focusing strength scanning(Q-scanning)techniques offer notable advantages for various injectors owing to their inherent convenience and cost-effectiveness.However,their stringent approximation conditions lead to inevitable errors in practical operation,thereby limiting their widespread application.This study addressed these challenges by revisiting the analytical derivation procedure and investigating the effects of the underlying approximation conditions.Preliminary corrections were explored through a combination of data processing analysis and numerical simulations.Furthermore,based on theoretical derivations,virtual measurements using beam dynamics calculations were employed to evaluate the correction reliability.Subsequent experimental validations were performed at the Huazhong University of Science and Technology injector to verify the effectiveness of the proposed compensation method.Both the virtual and experimental results confirm the feasibility and reliability of the enhanced Q-scanning-based diagnosis for transverse emittance in typical beam injectors operating under common conditions.Through the integration of these corrections and compensations,enhanced Q-scanning-based techniques emerge as promising alternatives to traditional emittance diagnosis methods.
文摘BACKGROUND The induced-membrane technique was initially described by Masquelet as an effective treatment for large bone defects,especially those caused by infection.Here,we report a case of chronic osteomyelitis of the radius associated with a 9 cm bone defect,which was filled with a large allogeneic cortical bone graft from a bone bank.Complete bony union was achieved after 14 months of follow-up.Previous studies have used autogenous bone as the primary bone source for the Masquelet technique;in our case,the exclusive use of allografts is as successful as the use of autologous bone grafts.With the advent of bone banks,it is possible to obtain an unlimited amount of allograft,and the Masquelet technique may be further improved based on this new way of bone grafting.CASE SUMMARY In this study,we reported a case of repair of a long bone defect in a 40-year-old male patient,which was characterized by the utilization of allograft cortical bone combined with the Masquelet technique for the treatment of the patient's long bone defect in the forearm.The patient's results of functional recovery of the forearm were surprising,which further deepens the scope of application of Masquelet technique and helps to strengthen the efficacy of Masquelet technique in the treatment of long bones indeed.CONCLUSION Allograft cortical bone combined with the Masquelet technique provides a new method of treatment to large bone defect.
基金supported by a Commercialization Promotion Agency for R&D Outcomes(COMPA)Grant funded by the Korean Government(Ministry of Science and ICT)(No.RS-2023-00304743)the National Research Foundation of Korea(NRF)Grant funded by the Korean Government(MSIT)(No.2022M3J7A1066428)"Regional Innovation Strategy(RIS)"through the National Research Foundation of Korea(NRF)funded by the Ministry of Education(MOE)(No.2023RIS-008).
文摘A polarization-sensitive and flexible photodetector was fabricated through the precise alignment of perovskite nanowires(NWs)using a brush coating technique.The alignment of the NWs was meticulously examined,considering various chemical properties of the solvent,such as boiling point,viscosity,and surface tension.Notably,when the NWs were brush-coated with toluene dispersion,the NWs were aligned in higher order than those processed from octane dispersion.The degree of alignment was correlated with the photodetector property.Especially,the well-aligned NW photodetector exhibited a two-fold disparity in current response contingent on the polarization direction.Furthermore,even after enduring 500 bending cycles,the device retained 80%of its photodetector performance.This approach underscores the potential of solution-processed flexible photodetectors for advanced optical applications under dynamic operating conditions.
文摘This paper presents a high-fidelity lumpedparameter(LP)thermal model(HF-LPTM)for permanent magnet synchronous machines(PMSMs)in electric vehicle(EV)applications,where various cooling techniques are considered,including frame forced air/liquid cooling,oil jet cooling for endwinding,and rotor shaft cooling.To address the temperature misestimation in the LP thermal modelling due to assumptions of concentrated loss input and uniform heat flows,the developed HF-LPTM introduces two compensation thermal resistances for the winding and PM components,which are analytically derived from the multi-dimensional heat transfer equations and are robust against different load/thermal conditions.As validated by the finite element analysis method and experiments,the conventional LPTMs exhibit significant winding temperature deviations,while the proposed HF-LPTM can accurately predict both the midpoint and average temperatures.The developed HFLPTM is further used to assess the effectiveness of various cooling techniques under different scenarios,i.e.,steady-state thermal states under the rated load condition,and transient temperature profiles under city,freeway,and hybrid(city+freeway)driving cycles.Results indicate that no single cooling technique can maintain both winding and PM temperatures within safety limits.The combination of frame liquid cooling and oil jet cooling for end winding can sufficiently mitigate PMSM thermal stress in EV applications.
基金supported by the National Fund Cultivation Project from China People’s Police University(Grant Number:JJPY202402)National Natural Science Foundation of China(Grant Number:62172165).
文摘With the rapid advancement of visual generative models such as Generative Adversarial Networks(GANs)and stable Diffusion,the creation of highly realistic Deepfake through automated forgery has significantly progressed.This paper examines the advancements inDeepfake detection and defense technologies,emphasizing the shift from passive detection methods to proactive digital watermarking techniques.Passive detection methods,which involve extracting features from images or videos to identify forgeries,encounter challenges such as poor performance against unknown manipulation techniques and susceptibility to counter-forensic tactics.In contrast,proactive digital watermarking techniques embed specificmarkers into images or videos,facilitating real-time detection and traceability,thereby providing a preemptive defense againstDeepfake content.We offer a comprehensive analysis of digitalwatermarking-based forensic techniques,discussing their advantages over passivemethods and highlighting four key benefits:real-time detection,embedded defense,resistance to tampering,and provision of legal evidence.Additionally,the paper identifies gaps in the literature concerning proactive forensic techniques and suggests future research directions,including cross-domain watermarking and adaptive watermarking strategies.By systematically classifying and comparing existing techniques,this review aims to contribute valuable insights for the development of more effective proactive defense strategies in Deepfake forensics.
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.
基金Supported by the National Natural Science Foundation of China(42474239,41204128)China National Space Administration(Pre-research project on Civil Aerospace Technologies No.D010301)Strategic Priority Research Program of the Chinese Academy of Sciences(XDA17010303)。
文摘One of the detection objectives of the Chinese Asteroid Exploration mission is to investigate the space environment near the Main-belt Comet(MBC,Active Asteroid)311P/PANSTARRS.This paper outlines the scientific objectives,measurement targets,and measurement requirements for the proposed Gas and Ion Analyzer(GIA).The GIA is designed for in-situ mass spectrometry of neutral gases and low-energy ions,such as hydrogen,carbon,and oxygen,in the vicinity of 311P.Ion sampling techniques are essential for the GIA's Time-of-Flight(TOF)mass analysis capabilities.In this paper,we present an enhanced ion sampling technique through the development of an ion attraction model and an ion source model.The ion attraction model demonstrates that adjusting attraction grid voltage can enhance the detection efficiency of low-energy ions and mitigate the repulsive force of ions during sampling,which is influenced by the satellite's surface positive charging.The ion source model simulates the processes of gas ionization and ion multiplication.Simulation results indicate that the GIA can achieve a lower pressure limit below 10-13Pa and possess a dynamic range exceeding 10~9.These performances ensure the generation of ions with stable and consistent current,which is crucial for high-resolution and broad dynamic range mass spectrometer analysis.Preliminary testing experiments have verified GIA's capability to detect gas compositions such as H2O and N2.In-situ measurements near 311P using GIA are expected to significantly contribute to our understanding of asteroid activity mechanisms,the evolution of the atmospheric and ionized environments of main-belt comets,the interactions with solar wind,and the origin of Earth's water.
文摘Despite advancements in neuroimaging,false positive diagnoses of intracranial aneurysms remain a significant concern.This article examines the causes,prevalence,and implications of such false-positive diagnoses.We discuss how conditions like arterial occlusion with vascular stump formation and infundibular widening can mimic aneurysms,particularly in the anterior circulation.The article compares various imaging modalities,including computer tomography angiogram,magnetic resonance imaging/angiography,and digital subtraction angiogram,highlighting their strengths and limitations.We emphasize the im-portance of accurate differentiation to avoid unnecessary surgical interventions.The potential of emerging technologies,such as high-resolution vessel wall ima-ging and deep neural networks for automated detection,is explored as promising avenues for improving diagnostic accuracy.This manuscript underscores the need for continued research and clinical vigilance in the diagnosis of intracranial aneurysms.
基金National Key Research and Development Program(2021YFB3401101)。
文摘Short process forming techniques for brazing and soldering materials can shorten the process,improve product quality,and increase production efficiency,which has received much attention from welding researchers.This review mainly summarized the research reports on short process forming techniques for brazing and soldering materials.Firstly,the traditional process and its shortcomings were presented.Secondly,the latest research of short process forming technologies,such as continuous casting technique,atomization powder technique,solder ball forming technique,and rapid solidification technique,was summarized,and the traditional forming performance of several brazing and soldering materials was introduced.Finally,the current restrictions and research trends of short process forming technique for brazing and solder materials were put forward,providing theoretical guidance and reference for related research and technique development in brazing and soldering field.
文摘Low-voltage direct current(DC)microgrids have recently emerged as a promising and viable alternative to traditional alternating cur-rent(AC)microgrids,offering numerous advantages.Consequently,researchers are exploring the potential of DC microgrids across var-ious configurations.However,despite the sustainability and accuracy offered by DC microgrids,they pose various challenges when integrated into modern power distribution systems.Among these challenges,fault diagnosis holds significant importance.Rapid fault detection in DC microgrids is essential to maintain stability and ensure an uninterrupted power supply to critical loads.A primary chal-lenge is the lack of standards and guidelines for the protection and safety of DC microgrids,including fault detection,location,and clear-ing procedures for both grid-connected and islanded modes.In response,this study presents a brief overview of various approaches for protecting DC microgrids.
基金Supported by National Natural Science Foundation of China,No.82202694Clinical Research Innovation Plan of Shanghai General Hospital,No.CTCCR-2021C10.
文摘BACKGROUND Uniportal full-endoscopy(UFE)technique has been continuously developed and applied for treating lumbar spinal stenosis.However,achieving effective decompression outcome of using the UFE technique remains technically demanding and uncertain.Previously,we have proposed the biportal full-endoscopy(BFE)technique to integrate the respective advantages of both UFE and unilateral biportal endoscopy technique.There is limited published data on the comparison of clinical outcomes between biportal and UFE techniques in lumbar spinal stenosis with bilateral symptoms.AIM To contrast the clinical outcomes between biportal and UFE techniques for treating lumbar spinal stenosis with bilateral symptoms.METHODS This study retrospectively examined 100 patients diagnosed with lumbar spinal stenosis and bilateral symptoms.Among them,52 cases were part of group A(BFE technique group),and 48 cases belonged to group B(UFE technique group).The visual analogue scale(VAS),Oswestry Disability Index(ODI),and modified Macnab criteria were used to evaluate the clinical outcomes.RESULTS Group A had significantly shorter operation time than group B.Both groups experienced substantial relief in lower back and lower extremity pain on the severe side at postoperative 3 days,3 months,and 12 months.Group A had notably lower VAS scores for mild side lower extremity pain at postoperative 3 months and 12 months compared to group B.Group A's ODI scores were significantly lower at postoperative 3 months and 12 months,whereas group B's scores did not significantly differ from preoperative values.Group A's ODI scores were significantly lower than group B's at postoperative 3 months and 12 months.Group A had a significantly higher excellent and good response rate(94.23%)compared to group B(81.25%)at postoperative 12 months based on the modified Macnab scale outcomes.CONCLUSION The BFE technique offers multiple benefits,including reduced trauma and quicker recovery as a minimally invasive surgery,and enhanced decompression efficiency over the UFE technique when treating lumbar spinal stenosis with bilateral symptoms.
文摘Every second, a large volume of useful data is created in social media about the various kind of online purchases and in another forms of reviews. Particularly, purchased products review data is enormously growing in different database repositories every day. Most of the review data are useful to new customers for theier further purchases as well as existing companies to view customers feedback about various products. Data Mining and Machine Leaning techniques are familiar to analyse such kind of data to visualise and know the potential use of the purchased items through online. The customers are making quality of products through their sentiments about the purchased items from different online companies. In this research work, it is analysed sentiments of Headphone review data, which is collected from online repositories. For the analysis of Headphone review data, some of the Machine Learning techniques like Support Vector Machines, Naive Bayes, Decision Trees and Random Forest Algorithms and a Hybrid method are applied to find the quality via the customers’ sentiments. The accuracy and performance of the taken algorithms are also analysed based on the three types of sentiments such as positive, negative and neutral.
文摘LONGQUAN,a historic city in east China’s Zhejiang Province,is renowned for its exquisite celadon ware,featuring fine texture and pure,jade-like glaze.The region has a potterymaking tradition that spans over 1,600 years.Its celadon firing technique originated during the Three Kingdoms Period(220-280)and reached its peak in the Southern Song Dynasty(1127-1279).Since the Song Dynasty(960-1368),Longquan was among the main suppliers of porcelain for the imperial court.From the 12th to the 15th centuries.
文摘BACKGROUND Surgically created arterio-venous fistulas(AVFs)are the gold standard for haemodialysis access for patients with end-stage renal disease.Standard practice of AVF creation involves selecting the non-dominant upper limb and starting with most distally with radio-cephalic arterio-venous fistula.The primary patency rate of radio-cephalic arterio-venous fistula varies from 20%-25%.It has been suggested the neointimal hyperplasia at the mobilized venous segment causes stenosis of the anastomosis.Therefore,the radial artery deviation and reimplantation(RADAR)technique,in which the vein is minimally mobilized,should result in a higher success rate.AIM To compare the RADAR technique with classical technique in creation of AVF including:(1)Success rate;(2)Time to maturation;(3)Duration of surgery;and(4)Complication rate.METHODS In our study we recruited 94 patients in two randomized groups and performed the AVF by the classical method or the RADAR method.RESULTS The RADAR group had higher primary success rate(P=0.007),less rate of complications(P=0.04),shorter duration of surgery(P=0.00)and early time to maturation(0.001)when compared with the classical group.The RADAR procedure is a safe and a more efficient alternative to the current classical method of AVF creation.Longer duration of follow-up is required to assess the long-term outcomes in the future.CONCLUSION The RADAR procedure is a safe and more efficient alternative to the current classical method of AVF creation.Longer duration of follow-up is required to assess the long-term outcomes in the future.
文摘Objectives:The objective of this study was to assess the impact of two relaxation techniques,the Jacobson’s progressive muscle relaxation technique(JPMR),and the Benson’s relaxation technique(BRT),on the levels of stress and anxiety experienced by patients undergoing coronary angioplasty.Materials and Methods:Quantitative research approach with quasi-experimental pre-test and posttest control group design was conducted with seventy coronary angioplasty patients from the Institute of Medical Science,and SUM Hospital,Bhubaneswar,Odisha.The participants were purposively selected and divided into Experimental Group 1(n=35)and Experimental Group 2(n=35).Each group received either BRT or JPMR for three consecutive days.Pretest and posttest data were collected using a structured demographic questionnaire and the modified depression anxiety stress scale-21.Results:Both BRT and JPMR significantly decreased the levels of stress and anxiety among patients undergoing angioplasty compared to baseline(P<0.05).However,there was no significant difference between the two techniques based on Fisher’s exact P value.This suggests that both interventions are effective in reducing stress and anxiety among angioplasty patients.Conclusion:BRT or JPMR are noninvasive,nonpharmacological interventions that effectively reduce stress and anxiety in patients undergoing angioplasty.These findings underscore the importance of incorporating relaxation techniques into nursing practice and hospital programs to enhance patient care and promote holistic well-being post-angioplasty.
