Electric Vehicle Charging Systems(EVCS)are increasingly vulnerable to cybersecurity threats as they integrate deeply into smart grids and Internet ofThings(IoT)environments,raising significant security challenges.Most...Electric Vehicle Charging Systems(EVCS)are increasingly vulnerable to cybersecurity threats as they integrate deeply into smart grids and Internet ofThings(IoT)environments,raising significant security challenges.Most existing research primarily emphasizes network-level anomaly detection,leaving critical vulnerabilities at the host level underexplored.This study introduces a novel forensic analysis framework leveraging host-level data,including system logs,kernel events,and Hardware Performance Counters(HPC),to detect and analyze sophisticated cyberattacks such as cryptojacking,Denial-of-Service(DoS),and reconnaissance activities targeting EVCS.Using comprehensive forensic analysis and machine learning models,the proposed framework significantly outperforms existing methods,achieving an accuracy of 98.81%.The findings offer insights into distinct behavioral signatures associated with specific cyber threats,enabling improved cybersecurity strategies and actionable recommendations for robust EVCS infrastructure protection.展开更多
BACKGROUND The early acquisition of skills required to perform hemostasis during endoscopy may be hindered by the lack of tools that allow assessments of the operator’s viewpoint.Understanding the operator’s viewpoi...BACKGROUND The early acquisition of skills required to perform hemostasis during endoscopy may be hindered by the lack of tools that allow assessments of the operator’s viewpoint.Understanding the operator’s viewpoint may facilitate the skills.AIM To evaluate the effects of a training system using operator gaze patterns during gastric endoscopic submucosal dissection(ESD)on hemostasis.METHODS An eye-tracking system was developed to record the operator’s viewpoints during gastric ESD,displaying the viewpoint as a circle.In phase 1,videos of three trainees’viewpoints were recorded.After reviewing these,trainees were recorded again in phase 2.The videos from both phases were retrospectively reviewed,and short clips were created to evaluate the hemostasis skills.Outcome measures included the time to recognize the bleeding point,the time to complete hemostasis,and the number of coagulation attempts.RESULTS Eight cases treated with ESD were reviewed,and 10 video clips of hemostasis were created.The time required to recognize the bleeding point during phase 2 was significantly shorter than that during phase 1(8.3±4.1 seconds vs 23.1±19.2 seconds;P=0.049).The time required to complete hemostasis during phase 1 and that during phase 2 were not significantly different(15.4±6.8 seconds vs 31.9±21.7 seconds;P=0.056).Significantly fewer coagulation attempts were performed during phase 2(1.8±0.7 vs 3.2±1.0;P=0.004).CONCLUSION Short-term training did not reduce hemostasis completion time but significantly improved bleeding point recognition and reduced coagulation attempts.Learning from the operator’s viewpoint can facilitate acquiring hemostasis skills during ESD.展开更多
This article delves into the analysis of performance and utilization of Support Vector Machines (SVMs) for the critical task of forest fire detection using image datasets. With the increasing threat of forest fires to...This article delves into the analysis of performance and utilization of Support Vector Machines (SVMs) for the critical task of forest fire detection using image datasets. With the increasing threat of forest fires to ecosystems and human settlements, the need for rapid and accurate detection systems is of utmost importance. SVMs, renowned for their strong classification capabilities, exhibit proficiency in recognizing patterns associated with fire within images. By training on labeled data, SVMs acquire the ability to identify distinctive attributes associated with fire, such as flames, smoke, or alterations in the visual characteristics of the forest area. The document thoroughly examines the use of SVMs, covering crucial elements like data preprocessing, feature extraction, and model training. It rigorously evaluates parameters such as accuracy, efficiency, and practical applicability. The knowledge gained from this study aids in the development of efficient forest fire detection systems, enabling prompt responses and improving disaster management. Moreover, the correlation between SVM accuracy and the difficulties presented by high-dimensional datasets is carefully investigated, demonstrated through a revealing case study. The relationship between accuracy scores and the different resolutions used for resizing the training datasets has also been discussed in this article. These comprehensive studies result in a definitive overview of the difficulties faced and the potential sectors requiring further improvement and focus.展开更多
The Internet of Things(IoT)is integral to modern infrastructure,enabling connectivity among a wide range of devices from home automation to industrial control systems.With the exponential increase in data generated by...The Internet of Things(IoT)is integral to modern infrastructure,enabling connectivity among a wide range of devices from home automation to industrial control systems.With the exponential increase in data generated by these interconnected devices,robust anomaly detection mechanisms are essential.Anomaly detection in this dynamic environment necessitates methods that can accurately distinguish between normal and anomalous behavior by learning intricate patterns.This paper presents a novel approach utilizing generative adversarial networks(GANs)for anomaly detection in IoT systems.However,optimizing GANs involves tuning hyper-parameters such as learning rate,batch size,and optimization algorithms,which can be challenging due to the non-convex nature of GAN loss functions.To address this,we propose a five-dimensional Gray wolf optimizer(5DGWO)to optimize GAN hyper-parameters.The 5DGWO introduces two new types of wolves:gamma(γ)for improved exploitation and convergence,and theta(θ)for enhanced exploration and escaping local minima.The proposed system framework comprises four key stages:1)preprocessing,2)generative model training,3)autoencoder(AE)training,and 4)predictive model training.The generative models are utilized to assist the AE training,and the final predictive models(including convolutional neural network(CNN),deep belief network(DBN),recurrent neural network(RNN),random forest(RF),and extreme gradient boosting(XGBoost))are trained using the generated data and AE-encoded features.We evaluated the system on three benchmark datasets:NSL-KDD,UNSW-NB15,and IoT-23.Experiments conducted on diverse IoT datasets show that our method outperforms existing anomaly detection strategies and significantly reduces false positives.The 5DGWO-GAN-CNNAE exhibits superior performance in various metrics,including accuracy,recall,precision,root mean square error(RMSE),and convergence trend.The proposed 5DGWO-GAN-CNNAE achieved the lowest RMSE values across the NSL-KDD,UNSW-NB15,and IoT-23 datasets,with values of 0.24,1.10,and 0.09,respectively.Additionally,it attained the highest accuracy,ranging from 94%to 100%.These results suggest a promising direction for future IoT security frameworks,offering a scalable and efficient solution to safeguard against evolving cyber threats.展开更多
BACKGROUND Hepatocellular carcinoma(HCC)remains a significant public health concern in South Korea even though the incidence rates are declining.While medical travel for cancer treatment is common,its patterns and inf...BACKGROUND Hepatocellular carcinoma(HCC)remains a significant public health concern in South Korea even though the incidence rates are declining.While medical travel for cancer treatment is common,its patterns and influencing factors for patients with HCC are unknown.AIM To assess medical travel patterns and determinants and their policy implications among patients with newly diagnosed HCC in South Korea.METHODS This retrospective cohort study used the National Health Insurance Service database to identify patients with newly diagnosed HCC from 2013 to 2021.Medical travel was defined as receiving initial treatment outside one’s residential region.Patient characteristics and regional trends were analyzed,and factors influencing medical travel were identified using logistic regression analysis.RESULTS Among 64808 patients 52.4%received treatment in the capital.This proportion increased to 67.4%when including the surrounding metropolitan area.Medical travel was significantly more common among younger and wealthier patients.Patients with greater comorbidity burden or liver cirrhosis were less likely to travel.While geographic distance influenced travel patterns,high-volume academic centers in the capital attracted patients nationwide regardless of proximity.CONCLUSION This nationwide study highlighted the centralization of HCC care in the capital.This observation indicates that regional cancer hubs should be strengthened and promoted for equitable healthcare access.展开更多
The authors regret that the affiliation b and c are wrong.Affiliation b should be changed to“School of Civil and Environmental Engineering,Harbin Institute of Technology,Shenzhen,China;Department of Data Analysis and...The authors regret that the affiliation b and c are wrong.Affiliation b should be changed to“School of Civil and Environmental Engineering,Harbin Institute of Technology,Shenzhen,China;Department of Data Analysis and Mathematical Modelling,Ghent University,Belgium”.And affiliation c should be changed to“State Key Laboratory of Urban Water Resource and Environment(SKLUWRE),School of Environment,Harbin Institute of Technology,China”.展开更多
Thin-walled parts have been widely employed as critical components in high-performance equipment due to the high specific strength and light weight.However,owing to their relatively weak rigidity and poor damping prop...Thin-walled parts have been widely employed as critical components in high-performance equipment due to the high specific strength and light weight.However,owing to their relatively weak rigidity and poor damping properties,chatter vibration is likely to occur during the milling process,which severely deteriorates surface quality and decreases machining productivity.Therefore,chatter suppression is essential for improving the dynamic machinability of thin-walled structures and has attracted extensive attention over the past few decades.This paper reviews the current state of the art in research concerning chatter suppression during the milling of thin-walled workpieces.In consideration of the dynamic characteristics of this process,the challenges in design and application of chatter attenuation methods are highlighted.Moreover,various chatter suppression techniques,involving passive,active,and semi-active methods,are comprehensively discussed in terms of basic concepts,working mechanism,optimal design,and application.Finally,future research opportunities in chatter mitigation technology for thin-wall milling are recommended.展开更多
Spherical bubble oscillations are widely used to model cavitation phenomena in biomedical and naval hydrodynamic systems.During collapse,a sudden increase in surrounding pressure initiates the collapse of a cavitation...Spherical bubble oscillations are widely used to model cavitation phenomena in biomedical and naval hydrodynamic systems.During collapse,a sudden increase in surrounding pressure initiates the collapse of a cavitation bubble,followed by a rebound driven by the high internal gas pressure.While the ideal gas equation of state(EOS)is commonly used to describe the internal pressure and temperature of the bubble,it is limited in its capacity to capture molecular-level effects under highly compressed conditions.In the present study,we employ non-ideal EOS for the gas(the van der Waals EOS and its volume-limited case)to investigate bubble oscillations with a focus on energy redistribution.Bubble oscillation is modeled in two phases:collapse,described by the Keller−Miksis formulation,and rebound,where peak shock pressure is estimated using similitude-based relations.To assess the role of EOS in energy redistribution,we introduce a framework that quantifies energy components in the bubble−liquid system while conserving total energy,tailored to each EOS.Using this framework,we evaluate energy concentration,acoustic radiation,and shock propagation and statistically analyze their dependence on both the driving pressure and the EOS of gas.We statistically derive scaling relations of key bubble dynamics quantities,energy concentration and radiation,and shock pressure using the driving pressure ratio.This work provides a generalizable framework and set of scaling relations for predicting bubble dynamics and energy transfer,with potential applications in evaluating the impacts of cavitation phenomena in complex practical systems.展开更多
The increased accessibility of social networking services(SNSs)has facilitated communication and information sharing among users.However,it has also heightened concerns about digital safety,particularly for children a...The increased accessibility of social networking services(SNSs)has facilitated communication and information sharing among users.However,it has also heightened concerns about digital safety,particularly for children and adolescents who are increasingly exposed to online grooming crimes.Early and accurate identification of grooming conversations is crucial in preventing long-term harm to victims.However,research on grooming detection in South Korea remains limited,as existing models trained primarily on English text and fail to reflect the unique linguistic features of SNS conversations,leading to inaccurate classifications.To address these issues,this study proposes a novel framework that integrates optical character recognition(OCR)technology with KcELECTRA,a deep learning-based natural language processing(NLP)model that shows excellent performance in processing the colloquial Korean language.In the proposed framework,the KcELECTRA model is fine-tuned by an extensive dataset,including Korean social media conversations,Korean ethical verification data from AI-Hub,and Korean hate speech data from Hug-gingFace,to enable more accurate classification of text extracted from social media conversation images.Experimental results show that the proposed framework achieves an accuracy of 0.953,outperforming existing transformer-based models.Furthermore,OCR technology shows high accuracy in extracting text from images,demonstrating that the proposed framework is effective for online grooming detection.The proposed framework is expected to contribute to the more accurate detection of grooming text and the prevention of grooming-related crimes.展开更多
The advent of sixth-generation(6G)networks introduces unprecedented challenges in achieving seamless connectivity,ultra-low latency,and efficient resource management in highly dynamic environments.Although fifth-gener...The advent of sixth-generation(6G)networks introduces unprecedented challenges in achieving seamless connectivity,ultra-low latency,and efficient resource management in highly dynamic environments.Although fifth-generation(5G)networks transformed mobile broadband and machine-type communications at massive scales,their properties of scaling,interference management,and latency remain a limitation in dense high mobility settings.To overcome these limitations,artificial intelligence(AI)and unmanned aerial vehicles(UAVs)have emerged as potential solutions to develop versatile,dynamic,and energy-efficient communication systems.The study proposes an AI-based UAV architecture that utilizes cooperative reinforcement learning(CoRL)to manage an autonomous network.The UAVs collaborate by sharing local observations and real-time state exchanges to optimize user connectivity,movement directions,allocate power,and resource distribution.Unlike conventional centralized or autonomous methods,CoRL involves joint state sharing and conflict-sensitive reward shaping,which ensures fair coverage,less interference,and enhanced adaptability in a dynamic urban environment.Simulations conducted in smart city scenarios with 10 UAVs and 50 ground users demonstrate that the proposed CoRL-based UAV system increases user coverage by up to 10%,achieves convergence 40%faster,and reduces latency and energy consumption by 30%compared with centralized and decentralized baselines.Furthermore,the distributed nature of the algorithm ensures scalability and flexibility,making it well-suited for future large-scale 6G deployments.The results highlighted that AI-enabled UAV systems enhance connectivity,support ultra-reliable low-latency communications(URLLC),and improve 6G network efficiency.Future work will extend the framework with adaptive modulation,beamforming-aware positioning,and real-world testbed deployment.展开更多
OBJECTIVE:To systematically investigate the clinical effectiveness and safety of traditional Chinese herbs(TCHs)as an alternative to conventional medicine(CM)in children with cough variant asthma(CVA).METHODS:Randomiz...OBJECTIVE:To systematically investigate the clinical effectiveness and safety of traditional Chinese herbs(TCHs)as an alternative to conventional medicine(CM)in children with cough variant asthma(CVA).METHODS:Randomized controlled trial(RCT)studies that were published from their inceptions to March 31,2020,were identified from the electronic databases of China National Knowledge Infrastructure,Wangfang,Pub Med,and Cochrane Central Library.The primary outcome of the review was the total effective rate(TER),and the secondary outcomes were immunoglobulin E(Ig E),peak expiratory flow(PEF),adverse drug reactions,and relapse rates of interventions.RESULTS:For the Meta-analysis,13 studies involving 992 children with CVA were included.In terms of TER and Ig E,the experimental interventions of TCH,when compared with the control interventions of CM,on pediatric CVA were found to be significantly effective(P<0.0001),whereas for spirometry,PEF was not significantly improved in the TCH group(P=0.48).The incident rates of adverse drug reaction and relapse were found to be significantly lower in the TCH group than those in the CM group(P=0.02 and P<0.0001,respectively).CONCLUSION:Compared with CM therapy,the effects of TCH therapy on pediatric CVA were significantly beneficial in terms of TER and Ig E,but not for PEF,and the methodological quality of included studies was poor.Therefore,the results should be interpreted with caution.More randomized controlled trials with rigorous experimental methodologies are required for objectivity in the future.展开更多
BACKGROUND Sodium glucose cotransporter-2 inhibitors(SGLT-2i)are a class of drugs with modest antidiabetic efficacy,weight loss effect,and cardiovascular benefits as proven by multiple randomised controlled trials(RCT...BACKGROUND Sodium glucose cotransporter-2 inhibitors(SGLT-2i)are a class of drugs with modest antidiabetic efficacy,weight loss effect,and cardiovascular benefits as proven by multiple randomised controlled trials(RCTs).However,real-world data on the comparative efficacy and safety of individual SGLT-2i medications is sparse.AIM To study the comparative efficacy and safety of SGLT-2i using real-world clinical data.METHODS We evaluated the comparative efficacy data of 3 SGLT-2i drugs(dapagliflozin,canagliflozin,and empagliflozin)used for treating patients with type 2 diabetes mellitus.Data on the reduction of glycated hemoglobin(HbA1c),body weight,blood pressure(BP),urine albumin creatinine ratio(ACR),and adverse effects were recorded retrospectively.RESULTS Data from 467 patients with a median age of 64(14.8)years,294(62.96%)males and 375(80.5%)Caucasians were analysed.Median diabetes duration was 16.0(9.0)years,and the duration of SGLT-2i use was 3.6(2.1)years.SGLT-2i molecules used were dapagliflozin 10 mg(n=227;48.6%),canagliflozin 300 mg(n=160;34.3%),and empagliflozin 25 mg(n=80;17.1).Baseline median(interquartile range)HbA1c in mmol/mol were:dapagliflozin-78.0(25.3),canagliflozin-80.0(25.5),and empagliflozin-75.0(23.5)respectively.The respective median HbA1c reduction at 12 months and the latest review(just prior to the study)were:66.5(22.8)&69.0(24.0),67.0(16.3)&66.0(28.0),and 67.0(22.5)&66.5(25.8)respectively(P<0.001 for all comparisons from baseline).Significant improvements in body weight(in kilograms)from baseline to study end were noticed with dapagliflozin-101(29.5)to 92.2(25.6),and canagliflozin 100(28.3)to 95.3(27.5)only.Significant reductions in median systolic and diastolic BP,from 144(21)mmHg to 139(23)mmHg;(P=0.015),and from 82(16)mmHg to 78(19)mmHg;(P<0.001)respectively were also observed.A significant reduction of microalbuminuria was observed with canagliflozin only[ACR 14.6(42.6)at baseline to 8.9(23.7)at the study end;P=0.043].Adverse effects of SGLT-2i were as follows:genital thrush and urinary infection-20(8.8%)&17(7.5%)with dapagliflozin;9(5.6%)&5(3.13%)with canagliflozin;and 4(5%)&4(5%)with empagliflozin.Diabetic ketoacidosis was observed in 4(1.8%)with dapagliflozin and 1(0.63%)with canagliflozin.CONCLUSION Treatment of patients with SGLT-2i is associated with statistically significant reductions in HbA1c,body weight,and better than those reported in RCTs,with low side effect profiles.A review of large-scale real-world data is needed to inform better clinical practice decision making.展开更多
Free-space optical(FSO)communication is of supreme importance for designing next-generation networks.Over the past decades,the radio frequency(RF)spectrum has been the main topic of interest for wireless technology.Th...Free-space optical(FSO)communication is of supreme importance for designing next-generation networks.Over the past decades,the radio frequency(RF)spectrum has been the main topic of interest for wireless technology.The RF spectrum is becoming denser and more employed,making its availability tough for additional channels.Optical communication,exploited for messages or indications in historical times,is now becoming famous and useful in combination with error-correcting codes(ECC)to mitigate the effects of fading caused by atmospheric turbulence.A free-space communication system(FSCS)in which the hybrid technology is based on FSO and RF.FSCS is a capable solution to overcome the downsides of current schemes and enhance the overall link reliability and availability.The proposed FSCS with regular low-density parity-check(LDPC)for coding techniques is deliberated and evaluated in terms of signal-to-noise ratio(SNR)in this paper.The extrinsic information transfer(EXIT)methodology is an incredible technique employed to investigate the sum-product decoding algorithm of LDPC codes and optimize the EXIT chart by applying curve fitting.In this research work,we also analyze the behavior of the EXIT chart of regular/irregular LDPC for the FSCS.We also investigate the error performance of LDPC code for the proposed FSCS.展开更多
Background:Sleep disturbance is commonly seen in fibromyalgia syndrome (FMS);however,high quality studies involving manual therapies that target FMS-linked poor sleep quality are lacking for the Indian population.Obje...Background:Sleep disturbance is commonly seen in fibromyalgia syndrome (FMS);however,high quality studies involving manual therapies that target FMS-linked poor sleep quality are lacking for the Indian population.Objective:Craniosacral therapy (CST),Bowen therapy and exercises have been found to influence the autonomic nervous system,which plays a crucial role in sleep physiology.Given the paucity of evidence concerning these effects in individuals with FMS,our study tests the effectiveness of CST,Bowen therapy and a standard exercise program against static touch (the manual placebo group) on sleep quality in FMS.Design,setting,participants and intervention:A placebo-controlled randomized trial was conducted on132 FMS participants with poor sleep at a hospital in Bangalore.The participants were randomly allocated to one of the four study groups,including CST,Bowen therapy,standard exercise program,and a manual placebo control group that received static touch.CST,Bowen therapy and static touch treatments were administered in once-weekly 45-minute sessions for 12 weeks;the standard exercise group received weekly supervised exercises for 6 weeks with home exercises until 12 weeks.After 12 weeks,all study participants performed the standard exercises at home for another 12 weeks.Main outcome measures:Sleep quality,pressure pain threshold (PPT),quality of life and fibromyalgia impact,physical function,fatigue,pain catastrophizing,kinesiophobia,and positive–negative affect were recorded at baseline,and at weeks 12 and 24 of the intervention.Results:At the end of 12 weeks,the sleep quality improved significantly in the CST group (P=0.037) and Bowen therapy group (P=0.023),and the PPT improved significantly in the Bowen therapy group(P=0.002) and the standard exercise group (P<0.001),compared to the static touch group.These improvements were maintained at 24 weeks.No between-group differences were observed for other secondary outcomes.Conclusion:CST and Bowen therapy improved sleep quality,and Bowen therapy and standard exercises improved pain threshold in the short term.These improvements were retained within the groups in the long term by adding exercises.CST and Bowen therapy are treatment options to improve sleep and reduce pain in FMS.展开更多
Further treatment of secondary effluents before their discharge into the receiving water bodies could alleviate water eutrophication.In this study,the Chlorella proteinosa was cultured in a membrane photobioreactor to...Further treatment of secondary effluents before their discharge into the receiving water bodies could alleviate water eutrophication.In this study,the Chlorella proteinosa was cultured in a membrane photobioreactor to further remove nitrogen from the secondary effluents.The effect of hydraulic retention time(HRT)on microalgae biomass yields and nutrient removal was studied.The results showed that soluble algal products concentration reduced in the suspension at low HRT,thereby alleviating microalgal growth inhibition.In addition,the lower HRT reduced the nitrogen limitation for Chlorella proteinosa’s growth through the phase-out of nitrogen-related functional bacteria.As a result,the productivity for Chlorella proteinosa increased from 6.12 mg/L/day at an HRT of 24 hr to 20.18 mg/L/day at an HRT of 8 hr.The highest removal rates of 19.7 mg/L/day,23.8 mg/L/day,and 105.4 mg/L/day were achieved at an HRT of 8 hr for total nitrogen(TN),ammonia,and chemical oxygen demand(COD),respectively.However,in terms of removal rate,TN and COD were the largest when HRT is 24 hr,which were 74.5%and 82.6%respectively.The maximum removal rate of ammonia nitrogen was 99.2%when HRT was 8 hr.展开更多
Amid the landscape of Cloud Computing(CC),the Cloud Datacenter(DC)stands as a conglomerate of physical servers,whose performance can be hindered by bottlenecks within the realm of proliferating CC services.A linchpin ...Amid the landscape of Cloud Computing(CC),the Cloud Datacenter(DC)stands as a conglomerate of physical servers,whose performance can be hindered by bottlenecks within the realm of proliferating CC services.A linchpin in CC’s performance,the Cloud Service Broker(CSB),orchestrates DC selection.Failure to adroitly route user requests with suitable DCs transforms the CSB into a bottleneck,endangering service quality.To tackle this,deploying an efficient CSB policy becomes imperative,optimizing DC selection to meet stringent Qualityof-Service(QoS)demands.Amidst numerous CSB policies,their implementation grapples with challenges like costs and availability.This article undertakes a holistic review of diverse CSB policies,concurrently surveying the predicaments confronted by current policies.The foremost objective is to pinpoint research gaps and remedies to invigorate future policy development.Additionally,it extensively clarifies various DC selection methodologies employed in CC,enriching practitioners and researchers alike.Employing synthetic analysis,the article systematically assesses and compares myriad DC selection techniques.These analytical insights equip decision-makers with a pragmatic framework to discern the apt technique for their needs.In summation,this discourse resoundingly underscores the paramount importance of adept CSB policies in DC selection,highlighting the imperative role of efficient CSB policies in optimizing CC performance.By emphasizing the significance of these policies and their modeling implications,the article contributes to both the general modeling discourse and its practical applications in the CC domain.展开更多
Regular physical activity(PA)is known to enhance multifaceted health benefits,including both physical and mental health.However,traditional in-person physical activity programs have drawbacks,including time constraints...Regular physical activity(PA)is known to enhance multifaceted health benefits,including both physical and mental health.However,traditional in-person physical activity programs have drawbacks,including time constraints for busy people.Although evidence suggests positive impacts on mental health through mobile-based physical activity,effects of accumulated short bouts of physical activity using mobile devices are unexplored.Thus,this study aims to investigate these effects,focusing on depression,perceived stress,and negative affectivity among South Korean college students.Forty-six healthy college students were divided into the accumulated group(n=23,female=47.8%)and control group(n=23,female=47.6%).The accumulated group engaged in mobile-based physical activity,following guidelines to accumulate a minimum of two times per day and three times a week.Sessions were divided into short bouts,ensuing each bout lasted at least 10 min.The control group did not engage in any specific physical activity.The data analysis involved comparing the scores of the intervention and control groups using several statistical techniques,such as independent sample t-test,paired sample t-tests,and 2(time)×2(group)repeated measures analysis of variance.The demographic characteristics at the pre-test showed no statistically significant differences between the groups.The accumulated group had significant decreases in depression(t_(40)=2.59,p=0.013,Cohen’s D=0.84)and perceived stress(t_(40)=2.06,p=0.046,Cohen’s D=0.56)from the pre-to post-test.The control group exhibited no statistically significant differences in any variables.Furthermore,there were significant effects of time on depression scores(F1,36=4.77,p=0.036,η_(p)^(2)=0.12)while significant interaction effects were also observed for depression(F_(1,36)=6.59,p=0.015,η_(p)^(2)=0.16).This study offers informative insights into the potential advantages of mobile-based physical activity programs with accumulated periods for enhancing mental health,specifically in relation to depression.This study illuminates the current ongoing discussions on efficient approaches to encourage mobile-based physical activity and improve mental well-being,addressing various lifestyles and busy schedules.展开更多
Connected automated vehicles(CAVs)rely heavily on intelligent algorithms and remote sensors.If the control center or on-board sensors are under cyber-attack due to the security vulnerability of wireless communication,...Connected automated vehicles(CAVs)rely heavily on intelligent algorithms and remote sensors.If the control center or on-board sensors are under cyber-attack due to the security vulnerability of wireless communication,it can cause significant damage to CAVs or passengers.The primary objective of this study is to model cyberattacked traffic flow and evaluate the impacts of cyber-attack on the traffic system filled with CAVs in a connected environment.Based on the analysis on environmental perception system and possible cyber-attacks on sensors,a novel lane-changing model for CAVs is proposed and multiple traffic scenarios for cyber-attacks are designed.The impact of the proportion of cyber-attacked vehicles and the severity of the cyber-attack on the lanechanging process is then quantitatively analyzed.The evaluation indexes include spatio-temporal evolution of average speed,spatial distribution of selected lane-changing gaps,lane-changing rate distribution,lane-changing preparation search time,efficiency and safety.Finally,the numerical simulation results show that the freeway traffic near an off-ramp is more sensitive to the proportion of cyber-attacked vehicles than to the severity of the cyber-attack.Also,when the traffic system is under cyber-attack,more unsafe back gaps are chosen for lane-changing,especially in the center lane.Therefore,more lane-changing maneuvers are concentrated on approaching the off-ramp,causing severe congestions and potential rear-end collisions.In addition,as the number of cyber-attacked vehicles and the severity of cyber-attacks increase,the road capacity and safety level will rapidly decrease.The results of this study can provide a theoretical basis for accident avoidance and efficiency improvement for the design of CAVs and management of automated highway systems.展开更多
BACKGROUND Ulcerative colitis(UC)with concomitant primary sclerosing cholangitis(PSC)represents a distinct disease entity(PSC-UC).Mayo endoscopic subscore(MES)is a standard tool for assessing disease activity in UC bu...BACKGROUND Ulcerative colitis(UC)with concomitant primary sclerosing cholangitis(PSC)represents a distinct disease entity(PSC-UC).Mayo endoscopic subscore(MES)is a standard tool for assessing disease activity in UC but its relevance in PSC-UC remains unclear.AIM To assess the accuracy of MES in UC and PSC-UC patients,we performed histological scoring using Nancy histological index(NHI).METHODS MES was assessed in 30 PSC-UC and 29 UC adult patients during endoscopy.NHI and inflammation were evaluated in biopsies from the cecum,rectum,and terminal ileum.In addition,perinuclear anti-neutrophil cytoplasmic antibodies,fecal calprotectin,body mass index,and other relevant clinical characteristics were collected.RESULTS The median MES and NHI were similar for UC patients(MES grade 2 and NHI grade 2 in the rectum)but were different for PSC-UC patients(MES grade 0 and NHI grade 2 in the cecum).There was a correlation between MES and NHI for UC patients(Spearman's r=0.40,P=0.029)but not for PSC-UC patients.Histopathological examination revealed persistent microscopic inflammation in 88%of PSC-UC patients with MES grade 0(46%of all PSC-UC patients).Moreover,MES overestimated the severity of active inflammation in an additional 11%of PSCUC patients.CONCLUSION MES insufficiently identifies microscopic inflammation in PSC-UC.This indicates that histological evaluation should become a routine procedure of the diagnostic and grading system in both PSC-UC and PSC.展开更多
This paper proposes a blockchain-based system as a secure, efficient, and cost-effective alternative to SWIFT for cross-border remittances. The current SWIFT system faces challenges, including slow settlement times, h...This paper proposes a blockchain-based system as a secure, efficient, and cost-effective alternative to SWIFT for cross-border remittances. The current SWIFT system faces challenges, including slow settlement times, high transaction costs, and vulnerability to fraud. Leveraging blockchain technology’s decentralized, transparent, and immutable nature, the proposed system aims to address these limitations. Key features include modular architecture, implementation of microservices, and advanced cryptographic protocols. The system incorporates Proof of Stake consensus with BLS signatures, smart contract execution with dynamic pricing, and a decentralized oracle network for currency conversion. A sophisticated risk-based authentication system utilizes Bayesian networks and machine learning for enhanced security. Mathematical models are presented for critical components, including transaction validation, currency conversion, and regulatory compliance. Simulations demonstrate potential improvements in transaction speed and costs. However, challenges such as regulatory hurdles, user adoption, scalability, and integration with legacy systems must be addressed. The paper provides a comparative analysis between the proposed blockchain system and SWIFT, highlighting advantages in transaction speed, costs, and security. Mitigation strategies are proposed for key challenges. Recommendations are made for further research into scaling solutions, regulatory frameworks, and user-centric designs. The adoption of blockchain-based remittances could significantly impact the financial sector, potentially disrupting traditional models and promoting financial inclusion in underserved markets. However, successful implementation will require collaboration between blockchain innovators, financial institutions, and regulators to create an enabling environment for this transformative system.展开更多
文摘Electric Vehicle Charging Systems(EVCS)are increasingly vulnerable to cybersecurity threats as they integrate deeply into smart grids and Internet ofThings(IoT)environments,raising significant security challenges.Most existing research primarily emphasizes network-level anomaly detection,leaving critical vulnerabilities at the host level underexplored.This study introduces a novel forensic analysis framework leveraging host-level data,including system logs,kernel events,and Hardware Performance Counters(HPC),to detect and analyze sophisticated cyberattacks such as cryptojacking,Denial-of-Service(DoS),and reconnaissance activities targeting EVCS.Using comprehensive forensic analysis and machine learning models,the proposed framework significantly outperforms existing methods,achieving an accuracy of 98.81%.The findings offer insights into distinct behavioral signatures associated with specific cyber threats,enabling improved cybersecurity strategies and actionable recommendations for robust EVCS infrastructure protection.
基金Supported by the Japan Society for the Promotion of Science Grant-in-Aid for Scientific Research,No.23K11902.
文摘BACKGROUND The early acquisition of skills required to perform hemostasis during endoscopy may be hindered by the lack of tools that allow assessments of the operator’s viewpoint.Understanding the operator’s viewpoint may facilitate the skills.AIM To evaluate the effects of a training system using operator gaze patterns during gastric endoscopic submucosal dissection(ESD)on hemostasis.METHODS An eye-tracking system was developed to record the operator’s viewpoints during gastric ESD,displaying the viewpoint as a circle.In phase 1,videos of three trainees’viewpoints were recorded.After reviewing these,trainees were recorded again in phase 2.The videos from both phases were retrospectively reviewed,and short clips were created to evaluate the hemostasis skills.Outcome measures included the time to recognize the bleeding point,the time to complete hemostasis,and the number of coagulation attempts.RESULTS Eight cases treated with ESD were reviewed,and 10 video clips of hemostasis were created.The time required to recognize the bleeding point during phase 2 was significantly shorter than that during phase 1(8.3±4.1 seconds vs 23.1±19.2 seconds;P=0.049).The time required to complete hemostasis during phase 1 and that during phase 2 were not significantly different(15.4±6.8 seconds vs 31.9±21.7 seconds;P=0.056).Significantly fewer coagulation attempts were performed during phase 2(1.8±0.7 vs 3.2±1.0;P=0.004).CONCLUSION Short-term training did not reduce hemostasis completion time but significantly improved bleeding point recognition and reduced coagulation attempts.Learning from the operator’s viewpoint can facilitate acquiring hemostasis skills during ESD.
文摘This article delves into the analysis of performance and utilization of Support Vector Machines (SVMs) for the critical task of forest fire detection using image datasets. With the increasing threat of forest fires to ecosystems and human settlements, the need for rapid and accurate detection systems is of utmost importance. SVMs, renowned for their strong classification capabilities, exhibit proficiency in recognizing patterns associated with fire within images. By training on labeled data, SVMs acquire the ability to identify distinctive attributes associated with fire, such as flames, smoke, or alterations in the visual characteristics of the forest area. The document thoroughly examines the use of SVMs, covering crucial elements like data preprocessing, feature extraction, and model training. It rigorously evaluates parameters such as accuracy, efficiency, and practical applicability. The knowledge gained from this study aids in the development of efficient forest fire detection systems, enabling prompt responses and improving disaster management. Moreover, the correlation between SVM accuracy and the difficulties presented by high-dimensional datasets is carefully investigated, demonstrated through a revealing case study. The relationship between accuracy scores and the different resolutions used for resizing the training datasets has also been discussed in this article. These comprehensive studies result in a definitive overview of the difficulties faced and the potential sectors requiring further improvement and focus.
基金described in this paper has been developed with in the project PRESECREL(PID2021-124502OB-C43)。
文摘The Internet of Things(IoT)is integral to modern infrastructure,enabling connectivity among a wide range of devices from home automation to industrial control systems.With the exponential increase in data generated by these interconnected devices,robust anomaly detection mechanisms are essential.Anomaly detection in this dynamic environment necessitates methods that can accurately distinguish between normal and anomalous behavior by learning intricate patterns.This paper presents a novel approach utilizing generative adversarial networks(GANs)for anomaly detection in IoT systems.However,optimizing GANs involves tuning hyper-parameters such as learning rate,batch size,and optimization algorithms,which can be challenging due to the non-convex nature of GAN loss functions.To address this,we propose a five-dimensional Gray wolf optimizer(5DGWO)to optimize GAN hyper-parameters.The 5DGWO introduces two new types of wolves:gamma(γ)for improved exploitation and convergence,and theta(θ)for enhanced exploration and escaping local minima.The proposed system framework comprises four key stages:1)preprocessing,2)generative model training,3)autoencoder(AE)training,and 4)predictive model training.The generative models are utilized to assist the AE training,and the final predictive models(including convolutional neural network(CNN),deep belief network(DBN),recurrent neural network(RNN),random forest(RF),and extreme gradient boosting(XGBoost))are trained using the generated data and AE-encoded features.We evaluated the system on three benchmark datasets:NSL-KDD,UNSW-NB15,and IoT-23.Experiments conducted on diverse IoT datasets show that our method outperforms existing anomaly detection strategies and significantly reduces false positives.The 5DGWO-GAN-CNNAE exhibits superior performance in various metrics,including accuracy,recall,precision,root mean square error(RMSE),and convergence trend.The proposed 5DGWO-GAN-CNNAE achieved the lowest RMSE values across the NSL-KDD,UNSW-NB15,and IoT-23 datasets,with values of 0.24,1.10,and 0.09,respectively.Additionally,it attained the highest accuracy,ranging from 94%to 100%.These results suggest a promising direction for future IoT security frameworks,offering a scalable and efficient solution to safeguard against evolving cyber threats.
基金Supported by Dong-A University Research Fund,No.20230598.
文摘BACKGROUND Hepatocellular carcinoma(HCC)remains a significant public health concern in South Korea even though the incidence rates are declining.While medical travel for cancer treatment is common,its patterns and influencing factors for patients with HCC are unknown.AIM To assess medical travel patterns and determinants and their policy implications among patients with newly diagnosed HCC in South Korea.METHODS This retrospective cohort study used the National Health Insurance Service database to identify patients with newly diagnosed HCC from 2013 to 2021.Medical travel was defined as receiving initial treatment outside one’s residential region.Patient characteristics and regional trends were analyzed,and factors influencing medical travel were identified using logistic regression analysis.RESULTS Among 64808 patients 52.4%received treatment in the capital.This proportion increased to 67.4%when including the surrounding metropolitan area.Medical travel was significantly more common among younger and wealthier patients.Patients with greater comorbidity burden or liver cirrhosis were less likely to travel.While geographic distance influenced travel patterns,high-volume academic centers in the capital attracted patients nationwide regardless of proximity.CONCLUSION This nationwide study highlighted the centralization of HCC care in the capital.This observation indicates that regional cancer hubs should be strengthened and promoted for equitable healthcare access.
文摘The authors regret that the affiliation b and c are wrong.Affiliation b should be changed to“School of Civil and Environmental Engineering,Harbin Institute of Technology,Shenzhen,China;Department of Data Analysis and Mathematical Modelling,Ghent University,Belgium”.And affiliation c should be changed to“State Key Laboratory of Urban Water Resource and Environment(SKLUWRE),School of Environment,Harbin Institute of Technology,China”.
基金supported by the National Natural Science Foundation of China(Grant No.U22A20202)。
文摘Thin-walled parts have been widely employed as critical components in high-performance equipment due to the high specific strength and light weight.However,owing to their relatively weak rigidity and poor damping properties,chatter vibration is likely to occur during the milling process,which severely deteriorates surface quality and decreases machining productivity.Therefore,chatter suppression is essential for improving the dynamic machinability of thin-walled structures and has attracted extensive attention over the past few decades.This paper reviews the current state of the art in research concerning chatter suppression during the milling of thin-walled workpieces.In consideration of the dynamic characteristics of this process,the challenges in design and application of chatter attenuation methods are highlighted.Moreover,various chatter suppression techniques,involving passive,active,and semi-active methods,are comprehensively discussed in terms of basic concepts,working mechanism,optimal design,and application.Finally,future research opportunities in chatter mitigation technology for thin-wall milling are recommended.
基金supported by Institute of Information&Communications Technology Planning&Evaluation(IITP)grant funded by the Korea government(MSIT)(No.RS-2022-00155966Artificial Intelligence Convergence Innovation Human Resources Development(EwhaWomans University)).
文摘Spherical bubble oscillations are widely used to model cavitation phenomena in biomedical and naval hydrodynamic systems.During collapse,a sudden increase in surrounding pressure initiates the collapse of a cavitation bubble,followed by a rebound driven by the high internal gas pressure.While the ideal gas equation of state(EOS)is commonly used to describe the internal pressure and temperature of the bubble,it is limited in its capacity to capture molecular-level effects under highly compressed conditions.In the present study,we employ non-ideal EOS for the gas(the van der Waals EOS and its volume-limited case)to investigate bubble oscillations with a focus on energy redistribution.Bubble oscillation is modeled in two phases:collapse,described by the Keller−Miksis formulation,and rebound,where peak shock pressure is estimated using similitude-based relations.To assess the role of EOS in energy redistribution,we introduce a framework that quantifies energy components in the bubble−liquid system while conserving total energy,tailored to each EOS.Using this framework,we evaluate energy concentration,acoustic radiation,and shock propagation and statistically analyze their dependence on both the driving pressure and the EOS of gas.We statistically derive scaling relations of key bubble dynamics quantities,energy concentration and radiation,and shock pressure using the driving pressure ratio.This work provides a generalizable framework and set of scaling relations for predicting bubble dynamics and energy transfer,with potential applications in evaluating the impacts of cavitation phenomena in complex practical systems.
基金supported by the IITP(Institute of Information&Communications Technology Planning&Evaluation)-ITRC(Information Technology Research Center)grant funded by the Korean government(Ministry of Science and ICT)(IITP-2025-RS-2024-00438056).
文摘The increased accessibility of social networking services(SNSs)has facilitated communication and information sharing among users.However,it has also heightened concerns about digital safety,particularly for children and adolescents who are increasingly exposed to online grooming crimes.Early and accurate identification of grooming conversations is crucial in preventing long-term harm to victims.However,research on grooming detection in South Korea remains limited,as existing models trained primarily on English text and fail to reflect the unique linguistic features of SNS conversations,leading to inaccurate classifications.To address these issues,this study proposes a novel framework that integrates optical character recognition(OCR)technology with KcELECTRA,a deep learning-based natural language processing(NLP)model that shows excellent performance in processing the colloquial Korean language.In the proposed framework,the KcELECTRA model is fine-tuned by an extensive dataset,including Korean social media conversations,Korean ethical verification data from AI-Hub,and Korean hate speech data from Hug-gingFace,to enable more accurate classification of text extracted from social media conversation images.Experimental results show that the proposed framework achieves an accuracy of 0.953,outperforming existing transformer-based models.Furthermore,OCR technology shows high accuracy in extracting text from images,demonstrating that the proposed framework is effective for online grooming detection.The proposed framework is expected to contribute to the more accurate detection of grooming text and the prevention of grooming-related crimes.
基金supported by the National Research Foundation of Korea(NRF)grant funded by the Korea government(MSIT)(RS-2025-00559546)supported by the IITP(Institute of Information&Coummunications Technology Planning&Evaluation)-ITRC(Information Technology Research Center)grant funded by the Korea government(Ministry of Science and ICT)(IITP-2025-RS-2023-00259004).
文摘The advent of sixth-generation(6G)networks introduces unprecedented challenges in achieving seamless connectivity,ultra-low latency,and efficient resource management in highly dynamic environments.Although fifth-generation(5G)networks transformed mobile broadband and machine-type communications at massive scales,their properties of scaling,interference management,and latency remain a limitation in dense high mobility settings.To overcome these limitations,artificial intelligence(AI)and unmanned aerial vehicles(UAVs)have emerged as potential solutions to develop versatile,dynamic,and energy-efficient communication systems.The study proposes an AI-based UAV architecture that utilizes cooperative reinforcement learning(CoRL)to manage an autonomous network.The UAVs collaborate by sharing local observations and real-time state exchanges to optimize user connectivity,movement directions,allocate power,and resource distribution.Unlike conventional centralized or autonomous methods,CoRL involves joint state sharing and conflict-sensitive reward shaping,which ensures fair coverage,less interference,and enhanced adaptability in a dynamic urban environment.Simulations conducted in smart city scenarios with 10 UAVs and 50 ground users demonstrate that the proposed CoRL-based UAV system increases user coverage by up to 10%,achieves convergence 40%faster,and reduces latency and energy consumption by 30%compared with centralized and decentralized baselines.Furthermore,the distributed nature of the algorithm ensures scalability and flexibility,making it well-suited for future large-scale 6G deployments.The results highlighted that AI-enabled UAV systems enhance connectivity,support ultra-reliable low-latency communications(URLLC),and improve 6G network efficiency.Future work will extend the framework with adaptive modulation,beamforming-aware positioning,and real-world testbed deployment.
文摘OBJECTIVE:To systematically investigate the clinical effectiveness and safety of traditional Chinese herbs(TCHs)as an alternative to conventional medicine(CM)in children with cough variant asthma(CVA).METHODS:Randomized controlled trial(RCT)studies that were published from their inceptions to March 31,2020,were identified from the electronic databases of China National Knowledge Infrastructure,Wangfang,Pub Med,and Cochrane Central Library.The primary outcome of the review was the total effective rate(TER),and the secondary outcomes were immunoglobulin E(Ig E),peak expiratory flow(PEF),adverse drug reactions,and relapse rates of interventions.RESULTS:For the Meta-analysis,13 studies involving 992 children with CVA were included.In terms of TER and Ig E,the experimental interventions of TCH,when compared with the control interventions of CM,on pediatric CVA were found to be significantly effective(P<0.0001),whereas for spirometry,PEF was not significantly improved in the TCH group(P=0.48).The incident rates of adverse drug reaction and relapse were found to be significantly lower in the TCH group than those in the CM group(P=0.02 and P<0.0001,respectively).CONCLUSION:Compared with CM therapy,the effects of TCH therapy on pediatric CVA were significantly beneficial in terms of TER and Ig E,but not for PEF,and the methodological quality of included studies was poor.Therefore,the results should be interpreted with caution.More randomized controlled trials with rigorous experimental methodologies are required for objectivity in the future.
文摘BACKGROUND Sodium glucose cotransporter-2 inhibitors(SGLT-2i)are a class of drugs with modest antidiabetic efficacy,weight loss effect,and cardiovascular benefits as proven by multiple randomised controlled trials(RCTs).However,real-world data on the comparative efficacy and safety of individual SGLT-2i medications is sparse.AIM To study the comparative efficacy and safety of SGLT-2i using real-world clinical data.METHODS We evaluated the comparative efficacy data of 3 SGLT-2i drugs(dapagliflozin,canagliflozin,and empagliflozin)used for treating patients with type 2 diabetes mellitus.Data on the reduction of glycated hemoglobin(HbA1c),body weight,blood pressure(BP),urine albumin creatinine ratio(ACR),and adverse effects were recorded retrospectively.RESULTS Data from 467 patients with a median age of 64(14.8)years,294(62.96%)males and 375(80.5%)Caucasians were analysed.Median diabetes duration was 16.0(9.0)years,and the duration of SGLT-2i use was 3.6(2.1)years.SGLT-2i molecules used were dapagliflozin 10 mg(n=227;48.6%),canagliflozin 300 mg(n=160;34.3%),and empagliflozin 25 mg(n=80;17.1).Baseline median(interquartile range)HbA1c in mmol/mol were:dapagliflozin-78.0(25.3),canagliflozin-80.0(25.5),and empagliflozin-75.0(23.5)respectively.The respective median HbA1c reduction at 12 months and the latest review(just prior to the study)were:66.5(22.8)&69.0(24.0),67.0(16.3)&66.0(28.0),and 67.0(22.5)&66.5(25.8)respectively(P<0.001 for all comparisons from baseline).Significant improvements in body weight(in kilograms)from baseline to study end were noticed with dapagliflozin-101(29.5)to 92.2(25.6),and canagliflozin 100(28.3)to 95.3(27.5)only.Significant reductions in median systolic and diastolic BP,from 144(21)mmHg to 139(23)mmHg;(P=0.015),and from 82(16)mmHg to 78(19)mmHg;(P<0.001)respectively were also observed.A significant reduction of microalbuminuria was observed with canagliflozin only[ACR 14.6(42.6)at baseline to 8.9(23.7)at the study end;P=0.043].Adverse effects of SGLT-2i were as follows:genital thrush and urinary infection-20(8.8%)&17(7.5%)with dapagliflozin;9(5.6%)&5(3.13%)with canagliflozin;and 4(5%)&4(5%)with empagliflozin.Diabetic ketoacidosis was observed in 4(1.8%)with dapagliflozin and 1(0.63%)with canagliflozin.CONCLUSION Treatment of patients with SGLT-2i is associated with statistically significant reductions in HbA1c,body weight,and better than those reported in RCTs,with low side effect profiles.A review of large-scale real-world data is needed to inform better clinical practice decision making.
文摘Free-space optical(FSO)communication is of supreme importance for designing next-generation networks.Over the past decades,the radio frequency(RF)spectrum has been the main topic of interest for wireless technology.The RF spectrum is becoming denser and more employed,making its availability tough for additional channels.Optical communication,exploited for messages or indications in historical times,is now becoming famous and useful in combination with error-correcting codes(ECC)to mitigate the effects of fading caused by atmospheric turbulence.A free-space communication system(FSCS)in which the hybrid technology is based on FSO and RF.FSCS is a capable solution to overcome the downsides of current schemes and enhance the overall link reliability and availability.The proposed FSCS with regular low-density parity-check(LDPC)for coding techniques is deliberated and evaluated in terms of signal-to-noise ratio(SNR)in this paper.The extrinsic information transfer(EXIT)methodology is an incredible technique employed to investigate the sum-product decoding algorithm of LDPC codes and optimize the EXIT chart by applying curve fitting.In this research work,we also analyze the behavior of the EXIT chart of regular/irregular LDPC for the FSCS.We also investigate the error performance of LDPC code for the proposed FSCS.
文摘Background:Sleep disturbance is commonly seen in fibromyalgia syndrome (FMS);however,high quality studies involving manual therapies that target FMS-linked poor sleep quality are lacking for the Indian population.Objective:Craniosacral therapy (CST),Bowen therapy and exercises have been found to influence the autonomic nervous system,which plays a crucial role in sleep physiology.Given the paucity of evidence concerning these effects in individuals with FMS,our study tests the effectiveness of CST,Bowen therapy and a standard exercise program against static touch (the manual placebo group) on sleep quality in FMS.Design,setting,participants and intervention:A placebo-controlled randomized trial was conducted on132 FMS participants with poor sleep at a hospital in Bangalore.The participants were randomly allocated to one of the four study groups,including CST,Bowen therapy,standard exercise program,and a manual placebo control group that received static touch.CST,Bowen therapy and static touch treatments were administered in once-weekly 45-minute sessions for 12 weeks;the standard exercise group received weekly supervised exercises for 6 weeks with home exercises until 12 weeks.After 12 weeks,all study participants performed the standard exercises at home for another 12 weeks.Main outcome measures:Sleep quality,pressure pain threshold (PPT),quality of life and fibromyalgia impact,physical function,fatigue,pain catastrophizing,kinesiophobia,and positive–negative affect were recorded at baseline,and at weeks 12 and 24 of the intervention.Results:At the end of 12 weeks,the sleep quality improved significantly in the CST group (P=0.037) and Bowen therapy group (P=0.023),and the PPT improved significantly in the Bowen therapy group(P=0.002) and the standard exercise group (P<0.001),compared to the static touch group.These improvements were maintained at 24 weeks.No between-group differences were observed for other secondary outcomes.Conclusion:CST and Bowen therapy improved sleep quality,and Bowen therapy and standard exercises improved pain threshold in the short term.These improvements were retained within the groups in the long term by adding exercises.CST and Bowen therapy are treatment options to improve sleep and reduce pain in FMS.
基金supported by the China Hunan Provincial Science&Technology Department(Nos.2022SK2091 and 2019JJ50646)the Hunan Provincial Department of Education(Nos.18C0206 and 19B040).
文摘Further treatment of secondary effluents before their discharge into the receiving water bodies could alleviate water eutrophication.In this study,the Chlorella proteinosa was cultured in a membrane photobioreactor to further remove nitrogen from the secondary effluents.The effect of hydraulic retention time(HRT)on microalgae biomass yields and nutrient removal was studied.The results showed that soluble algal products concentration reduced in the suspension at low HRT,thereby alleviating microalgal growth inhibition.In addition,the lower HRT reduced the nitrogen limitation for Chlorella proteinosa’s growth through the phase-out of nitrogen-related functional bacteria.As a result,the productivity for Chlorella proteinosa increased from 6.12 mg/L/day at an HRT of 24 hr to 20.18 mg/L/day at an HRT of 8 hr.The highest removal rates of 19.7 mg/L/day,23.8 mg/L/day,and 105.4 mg/L/day were achieved at an HRT of 8 hr for total nitrogen(TN),ammonia,and chemical oxygen demand(COD),respectively.However,in terms of removal rate,TN and COD were the largest when HRT is 24 hr,which were 74.5%and 82.6%respectively.The maximum removal rate of ammonia nitrogen was 99.2%when HRT was 8 hr.
文摘Amid the landscape of Cloud Computing(CC),the Cloud Datacenter(DC)stands as a conglomerate of physical servers,whose performance can be hindered by bottlenecks within the realm of proliferating CC services.A linchpin in CC’s performance,the Cloud Service Broker(CSB),orchestrates DC selection.Failure to adroitly route user requests with suitable DCs transforms the CSB into a bottleneck,endangering service quality.To tackle this,deploying an efficient CSB policy becomes imperative,optimizing DC selection to meet stringent Qualityof-Service(QoS)demands.Amidst numerous CSB policies,their implementation grapples with challenges like costs and availability.This article undertakes a holistic review of diverse CSB policies,concurrently surveying the predicaments confronted by current policies.The foremost objective is to pinpoint research gaps and remedies to invigorate future policy development.Additionally,it extensively clarifies various DC selection methodologies employed in CC,enriching practitioners and researchers alike.Employing synthetic analysis,the article systematically assesses and compares myriad DC selection techniques.These analytical insights equip decision-makers with a pragmatic framework to discern the apt technique for their needs.In summation,this discourse resoundingly underscores the paramount importance of adept CSB policies in DC selection,highlighting the imperative role of efficient CSB policies in optimizing CC performance.By emphasizing the significance of these policies and their modeling implications,the article contributes to both the general modeling discourse and its practical applications in the CC domain.
基金supported by the Bio&Medical Technology Development Program of the National Research Foundation(NRF)funded by the Korean government(MSIT)(NRF-2021M3A9E4080780)Hankuk University of Foreign Studies(2023).
文摘Regular physical activity(PA)is known to enhance multifaceted health benefits,including both physical and mental health.However,traditional in-person physical activity programs have drawbacks,including time constraints for busy people.Although evidence suggests positive impacts on mental health through mobile-based physical activity,effects of accumulated short bouts of physical activity using mobile devices are unexplored.Thus,this study aims to investigate these effects,focusing on depression,perceived stress,and negative affectivity among South Korean college students.Forty-six healthy college students were divided into the accumulated group(n=23,female=47.8%)and control group(n=23,female=47.6%).The accumulated group engaged in mobile-based physical activity,following guidelines to accumulate a minimum of two times per day and three times a week.Sessions were divided into short bouts,ensuing each bout lasted at least 10 min.The control group did not engage in any specific physical activity.The data analysis involved comparing the scores of the intervention and control groups using several statistical techniques,such as independent sample t-test,paired sample t-tests,and 2(time)×2(group)repeated measures analysis of variance.The demographic characteristics at the pre-test showed no statistically significant differences between the groups.The accumulated group had significant decreases in depression(t_(40)=2.59,p=0.013,Cohen’s D=0.84)and perceived stress(t_(40)=2.06,p=0.046,Cohen’s D=0.56)from the pre-to post-test.The control group exhibited no statistically significant differences in any variables.Furthermore,there were significant effects of time on depression scores(F1,36=4.77,p=0.036,η_(p)^(2)=0.12)while significant interaction effects were also observed for depression(F_(1,36)=6.59,p=0.015,η_(p)^(2)=0.16).This study offers informative insights into the potential advantages of mobile-based physical activity programs with accumulated periods for enhancing mental health,specifically in relation to depression.This study illuminates the current ongoing discussions on efficient approaches to encourage mobile-based physical activity and improve mental well-being,addressing various lifestyles and busy schedules.
基金jointly supported by the National Key Research and Development Program of China(No.2022ZD0115600)National Natural Science Foundation of China(No.52072067)+3 种基金Natural Science Foundation of Jiangsu Province(No.BK20210249)China Postdoctoral Science Foundation(No.2020M681466)Jiangsu Planned Projects for Postdoctoral Research Funds(No.SBK2021041144)Jiangsu Planned Projects for Postdoctoral Research Funds(No.2021K094A)。
文摘Connected automated vehicles(CAVs)rely heavily on intelligent algorithms and remote sensors.If the control center or on-board sensors are under cyber-attack due to the security vulnerability of wireless communication,it can cause significant damage to CAVs or passengers.The primary objective of this study is to model cyberattacked traffic flow and evaluate the impacts of cyber-attack on the traffic system filled with CAVs in a connected environment.Based on the analysis on environmental perception system and possible cyber-attacks on sensors,a novel lane-changing model for CAVs is proposed and multiple traffic scenarios for cyber-attacks are designed.The impact of the proportion of cyber-attacked vehicles and the severity of the cyber-attack on the lanechanging process is then quantitatively analyzed.The evaluation indexes include spatio-temporal evolution of average speed,spatial distribution of selected lane-changing gaps,lane-changing rate distribution,lane-changing preparation search time,efficiency and safety.Finally,the numerical simulation results show that the freeway traffic near an off-ramp is more sensitive to the proportion of cyber-attacked vehicles than to the severity of the cyber-attack.Also,when the traffic system is under cyber-attack,more unsafe back gaps are chosen for lane-changing,especially in the center lane.Therefore,more lane-changing maneuvers are concentrated on approaching the off-ramp,causing severe congestions and potential rear-end collisions.In addition,as the number of cyber-attacked vehicles and the severity of cyber-attacks increase,the road capacity and safety level will rapidly decrease.The results of this study can provide a theoretical basis for accident avoidance and efficiency improvement for the design of CAVs and management of automated highway systems.
基金Supported by Grant Agency of the Ministry of Health of the Czech Republic,No.NV17-31538AGrant Agency of the Czech Republic No.20-16520Y and No.21-21736SMinistry of Education,Youth and Sports of the Czech Republic Project,No.LX22NPO05102.
文摘BACKGROUND Ulcerative colitis(UC)with concomitant primary sclerosing cholangitis(PSC)represents a distinct disease entity(PSC-UC).Mayo endoscopic subscore(MES)is a standard tool for assessing disease activity in UC but its relevance in PSC-UC remains unclear.AIM To assess the accuracy of MES in UC and PSC-UC patients,we performed histological scoring using Nancy histological index(NHI).METHODS MES was assessed in 30 PSC-UC and 29 UC adult patients during endoscopy.NHI and inflammation were evaluated in biopsies from the cecum,rectum,and terminal ileum.In addition,perinuclear anti-neutrophil cytoplasmic antibodies,fecal calprotectin,body mass index,and other relevant clinical characteristics were collected.RESULTS The median MES and NHI were similar for UC patients(MES grade 2 and NHI grade 2 in the rectum)but were different for PSC-UC patients(MES grade 0 and NHI grade 2 in the cecum).There was a correlation between MES and NHI for UC patients(Spearman's r=0.40,P=0.029)but not for PSC-UC patients.Histopathological examination revealed persistent microscopic inflammation in 88%of PSC-UC patients with MES grade 0(46%of all PSC-UC patients).Moreover,MES overestimated the severity of active inflammation in an additional 11%of PSCUC patients.CONCLUSION MES insufficiently identifies microscopic inflammation in PSC-UC.This indicates that histological evaluation should become a routine procedure of the diagnostic and grading system in both PSC-UC and PSC.
文摘This paper proposes a blockchain-based system as a secure, efficient, and cost-effective alternative to SWIFT for cross-border remittances. The current SWIFT system faces challenges, including slow settlement times, high transaction costs, and vulnerability to fraud. Leveraging blockchain technology’s decentralized, transparent, and immutable nature, the proposed system aims to address these limitations. Key features include modular architecture, implementation of microservices, and advanced cryptographic protocols. The system incorporates Proof of Stake consensus with BLS signatures, smart contract execution with dynamic pricing, and a decentralized oracle network for currency conversion. A sophisticated risk-based authentication system utilizes Bayesian networks and machine learning for enhanced security. Mathematical models are presented for critical components, including transaction validation, currency conversion, and regulatory compliance. Simulations demonstrate potential improvements in transaction speed and costs. However, challenges such as regulatory hurdles, user adoption, scalability, and integration with legacy systems must be addressed. The paper provides a comparative analysis between the proposed blockchain system and SWIFT, highlighting advantages in transaction speed, costs, and security. Mitigation strategies are proposed for key challenges. Recommendations are made for further research into scaling solutions, regulatory frameworks, and user-centric designs. The adoption of blockchain-based remittances could significantly impact the financial sector, potentially disrupting traditional models and promoting financial inclusion in underserved markets. However, successful implementation will require collaboration between blockchain innovators, financial institutions, and regulators to create an enabling environment for this transformative system.
