Obesity has become a significant global public health issue.Previous studies have found that the Chenpi has the anti-obesity activity.However,the anti-obesity phytochemicals and their mechanisms are still unclear.This...Obesity has become a significant global public health issue.Previous studies have found that the Chenpi has the anti-obesity activity.However,the anti-obesity phytochemicals and their mechanisms are still unclear.This study investigated the anti-obesity phytochemicals and molecular mechanisms involved in treating obesity by Chenpi through network pharmacology and molecular docking.A total of 17 bioactive phytochemicals from Chenpi and its 475 related anti-obesity targets have been identified.The KEGG pathway analysis showed that the PI3K/Akt signaling pathway,MAPK signaling pathway,AMPK signaling pathway,and nuclear factor kappa B signaling pathway are the main signaling pathways involved in the anti-obesity effect of Chenpi.According to molecular docking analysis,the phytochemicals of Chenpi can bind to central anti-obesity targets.Based on the ADMET analysis and network pharmacology results,tangeretin exhibited the lowest predicted toxicity and potential for anti-obesity effects.In the in vitro lipid accumulation model,tangeretin effectively suppressed the free fatty acid-induced lipid in Hep G2 cells by upregulating the PI3K/Akt/GSK3βsignaling pathway based on the result of q-PCR and Western blotting.The outcomes of this research give insights for future research on the anti-obesity phytochemicals and molecular mechanisms derived from Chenpi,also providing the theoretical basis for developing anti-obesity functional foods based on Chenpi.展开更多
This study aims to investigate the short-term effects of ambient air pollutants on outpatient visits for childhood allergic diseases.Daily data on ambient air pollutants(NO2,SO2,CO and PM2.5)and outpatient visits for ...This study aims to investigate the short-term effects of ambient air pollutants on outpatient visits for childhood allergic diseases.Daily data on ambient air pollutants(NO2,SO2,CO and PM2.5)and outpatient visits for childhood allergic diseases(asthma,atopic dermatitis and allergic rhinitis)were obtained in Shanghai,China from 2013 to 2014.The effects of ambient air pollutants were estimated for total outpatient visits for childhood allergic diseases,gender and age stratification and disease classification by using distributed lag non-linear model(DLNM).We found positive associations between short-term exposure to air pollutants and childhood allergic diseases.Girls and children aged 7 years old were more likely to be sensitive to ambient air pollutants.NO2 and SO2 showed stronger effects on asthma and atopic dermatitis,respectively.This study provides evidence that short-term exposure to ambient air pollutants can increase the risk of childhood allergic diseases.展开更多
The development of artificial intelligence(AI)and the mining of biomedical data complement each other.From the direct use of computer vision results to analyze medical images for disease screening,to now integrating b...The development of artificial intelligence(AI)and the mining of biomedical data complement each other.From the direct use of computer vision results to analyze medical images for disease screening,to now integrating biological knowledge into models and even accelerating the development of new AI based on biological discoveries,the boundaries of both are constantly expanding,and their connections are becoming closer.Therefore,the theme of the 2024 Annual Quantitative Biology Conference is set as“Biomedical Data and AI”,and was held in Chengdu,China from July 15 to 17,2024.展开更多
The problem of automated seizure detection is treated using clinical electroencephalograms(EEG) and machine learning algorithms on the Temple University Hospital EEG Seizure Corpus(TUSZ).Performances on this complex d...The problem of automated seizure detection is treated using clinical electroencephalograms(EEG) and machine learning algorithms on the Temple University Hospital EEG Seizure Corpus(TUSZ).Performances on this complex data set are still not encountering expectations.The purpose of this work is to determine to what extent the use of larger amount of data can help to improve the performances.Two methods are explored:a standard partitioning on a recent and larger version of the TUSZ,and a leave-one-out approach used to increase the amount of data for the training set.XGBoost,a fast implementation of the gradient boosting classifier,is the ideal algorithm for these tasks.The performances obtained are in the range of what is reported until now in the literature with deep learning models.We give interpretation to our results by identifying the most relevant features and analyzing performances by seizure types.We show that generalized seizures tend to be far better predicted than focal ones.We also notice that some EEG channels and features are more important than others to distinguish seizure from background.展开更多
BACKGROUND The prevalence of left atrial appendage(LAA) thrombus detection by transesophageal echocardiogram(TEE) in patients with non-valvular atrial fibrillation(AF) anticoagulated with apixaban is not well defined ...BACKGROUND The prevalence of left atrial appendage(LAA) thrombus detection by transesophageal echocardiogram(TEE) in patients with non-valvular atrial fibrillation(AF) anticoagulated with apixaban is not well defined and identification of additional risk factors may help guide the selection process for pre-procedural TEE. The purpose of our study was to retrospectively analyze the prevalence of LAA thrombus detection by TEE in patients continuously anticoagulated with apixaban for ≥ 4 wk and evaluate for any cardiac risk factors or echocardiographic characteristics which may serve as predictors of thrombus formation.AIM To retrospectively analyze the prevalence of LAA thrombus detection by TEE in patients continuously anticoagulated with apixaban.METHODS Clinical and echocardiographic data for 820 consecutive patients with AF undergoing TEE at Augusta University Medical Center over a four-year period were retrospectively analyzed. All patients(apixaban: 226) with non-valvular AF and documented compliance with apixaban for ≥ 4 wk prior to index TEE were included.RESULTS Following ≥ 4 wk of continuous anticoagulation with apixaban, the prevalence ofLAA thrombus and LAA thrombus/dense spontaneous echocardiographic contrast was 3.1% and 6.6%, respectively. Persistent AF, left ventricular ejection fraction < 30%, severe LA dilation, and reduced LAA velocity were associated with thrombus formation. Following multivariate logistic regression, persistent AF(OR: 7.427; 95%CI: 1.02 to 53.92; P = 0.0474), and reduced LAA velocity(OR:1.086; 95%CI: 1.010 to 1.187; P = 0.0489) were identified as independent predictors of LAA thrombus. No Thrombi were detected in patients with a CHA2 DS2-VASc score ≤ 1.CONCLUSION Among patients with non-valvular AF and ≥ 4 wk of anticoagulation with apixaban, the prevalence of LAA thrombus detected by TEE was 3.1%. This suggests that continuous therapy with apixaban does not completely eliminate the risk of LAA thrombus and that TEE prior to cardioversion or catheter ablation may be of benefit in patients with multiple risk factors.展开更多
Sparse code multiple access (SCMA) is the most concerning scheme among non-orthogonal multiple access (NOMA) technologies for 5G wireless communication new interface. Another efficient technique in 5G aimed to improve...Sparse code multiple access (SCMA) is the most concerning scheme among non-orthogonal multiple access (NOMA) technologies for 5G wireless communication new interface. Another efficient technique in 5G aimed to improve spectral efficiency for local communications is device-to-device (D2D) communications. Therefore, we utilize the SCMA cellular network coexisting with D2D communications for the connection demand of the Internet of things (IOT), and improve the system sum rate performance of the hybrid network. We first derive the information-theoretic expression of the capacity for all users and find the capacity bound of cellular users based on the mutual interference between cellular users and D2D users. Then we consider the power optimization problem for the cellular users and D2D users jointly to maximize the system sum rate. To tackle the non-convex optimization problem, we propose a geometric programming (GP) based iterative power allocation algorithm. Simulation results demonstrate that the proposed algorithm converges fast and well improves the sum rate performance.展开更多
Anomaly detection(AD)is an important aspect of various domains and title insurance(TI)is no exception.Robotic process automation(RPA)is taking over manual tasks in TI business processes,but it has its limitations with...Anomaly detection(AD)is an important aspect of various domains and title insurance(TI)is no exception.Robotic process automation(RPA)is taking over manual tasks in TI business processes,but it has its limitations without the support of artificial intelligence(AI)and machine learning(ML).With increasing data dimensionality and in composite population scenarios,the complexity of detecting anomalies increases and AD in automated document management systems(ADMS)is the least explored domain.Deep learning,being the fastest maturing technology can be combined along with traditional anomaly detectors to facilitate and improve the RPAs in TI.We present a hybrid model for AD,using autoencoders(AE)and a one-class support vector machine(OSVM).In the present study,OSVM receives input features representing real-time documents from the TI business,orchestrated and with dimensions reduced by AE.The results obtained from multiple experiments are comparable with traditional methods and within a business acceptable range,regarding accuracy and performance.展开更多
Fuzzy inference system(FIS)is a process of fuzzy logic reasoning to produce the output based on fuzzified inputs.The system starts with identifying input from data,applying the fuzziness to input using membership func...Fuzzy inference system(FIS)is a process of fuzzy logic reasoning to produce the output based on fuzzified inputs.The system starts with identifying input from data,applying the fuzziness to input using membership functions(MF),generating fuzzy rules for the fuzzy sets and obtaining the output.There are several types of input MFs which can be introduced in FIS,commonly chosen based on the type of real data,sensitivity of certain rule implied and computational limits.This paper focuses on the construction of interval type 2(IT2)trapezoidal shape MF from fuzzy C Means(FCM)that is used for fuzzification process of mamdani FIS.In the process,upper MF(UMF)and lower MF(LMF)of the MF need to be identified to get the range of the footprint of uncertainty(FOU).This paper proposes Genetic tuning process,which is a part of genetic algorithm(GA),to adjust parameters in order to improve the behavior of existing system,especially to enhance the accuracy of the system model.This novel process is a hybrid approach which produces Genetic Fuzzy System(GFS)that helps to enhance fuzzy classification problems and performance.The approach provides a new method for the construction and tuning process of the IT2 MF,based on the FCM outcomes.The result is compared to Gaussian shape IT2 MF and trapezoid IT2 MF generated by the classic GA method.It is shown that the proposed approach is able to outperform the mentioned benchmarked approaches.The work implies a wider range of IT2 MF types,constructed based on FCM outcomes,and an optimum generation of the FOU so that it can be implemented in practical applications such as prediction,analytics and rule-based solutions.展开更多
During the ongoing 2020 CoVid-19 crisis,the use of remote meeting technologies such as Zoom™,Microsoft Teams™and Google Meetings™has been paramount to theoretical teaching in a safe socially distanced environment.Howe...During the ongoing 2020 CoVid-19 crisis,the use of remote meeting technologies such as Zoom™,Microsoft Teams™and Google Meetings™has been paramount to theoretical teaching in a safe socially distanced environment.However,several problems arise when there is a need for an experimental approach.This paper looks at one of the possible solutions,including how to best separate the students,how to minimize close interactions and how a mixed environment of remote/presential teaching is required,minimizing the amount of extra materials,resources and protection equipment required,such that developing countries can quickly adopt this method,without the purchase of any external equipment.展开更多
A web browser is the most basic tool for accessing the internet from any of the machines/equipment.Recently,data breaches have been reported frequently from users who are concerned about their personal information,as ...A web browser is the most basic tool for accessing the internet from any of the machines/equipment.Recently,data breaches have been reported frequently from users who are concerned about their personal information,as well as threats from criminal actors.Giving loss of data and information to an innocent user comes under the jurisdiction of cyber-attack.These kinds of cyber-attacks are far more dangerous when it comes to the many types of devices employed in an internet of things(IoT)environment.Continuous surveillance of IoT devices and forensic tools are required to overcome the issues pertaining to secure data and assets.Peer to peer(P2P)applications have been utilized for criminal operations on the web.Therefore,it is a challenge for a forensic investigator to perform forensic analysis of the evolving hardware and software platforms for IoT.For identity concealment and privacy protection,the Onion Router(Tor)and Chrome with the Invisible Internet Project(I2P)as the foundation browser are often used.Confirmation is required to determine whether Tor is truly anonymous and private as they claim.Some people,on the other hand,utilize the Tor browser for evil reasons.Tools and techniques are available for the collection of artifacts,identifying problem areas,further processing and analysis of data on the computer and IoT.Present research tried to explore a few tools for the tracing of I2P activities over computer on windows 10 that reflects IoT devices.According to the results of this research,it leaves an excessive amount of important digital evidence on the operating system that can be exploited to attack the information of users.This research is based on windows operating system and does not support other operating systems.展开更多
Dear Editor,Monkeypox is an infectious disease that is endemic in a dozen of African countries.Some imported cases have been also reported outside of Africa in the past[1].Since early May 2022,monkeypox infections inc...Dear Editor,Monkeypox is an infectious disease that is endemic in a dozen of African countries.Some imported cases have been also reported outside of Africa in the past[1].Since early May 2022,monkeypox infections including human-to-human transmission,were reported in a multi-country outbreak in non-endemic countries and declared Public Health Emergency of International Concern(PHEIC)by the World Health Organization(WHO)in July 2022[2].As of 20 September 2022,a total of at least 62,798 human cases of monkeypox with 20 deaths have been confirmed in 115 countries in five WHO regions[3].展开更多
Communication is a basic need of every human being;by this,they can learn,express their feelings and exchange their ideas,but deaf people cannot listen and speak.For communication,they use various hands gestures,also ...Communication is a basic need of every human being;by this,they can learn,express their feelings and exchange their ideas,but deaf people cannot listen and speak.For communication,they use various hands gestures,also known as Sign Language(SL),which they learn from special schools.As normal people have not taken SL classes;therefore,they are unable to perform signs of daily routine sentences(e.g.,what are the specifications of this mobile phone?).A technological solution can facilitate in overcoming this communication gap by which normal people can communicate with deaf people.This paper presents an architecture for an application named Sign4PSL that translates the sentences to Pakistan Sign Language(PSL)for deaf people with visual representation using virtual signing character.This research aims to develop a generic independent application that is lightweight and reusable on any platform,including web and mobile,with an ability to perform offline text translation.The Sign4PSL relies on a knowledge base that stores both corpus of PSL Words and their coded form in the notation system.Sign4PSL takes English language text as an input,performs the translation to PSL through sign language notation and displays gestures to the user using virtual character.The system is tested on deaf students at a special school.The results have shown that the students were able to understand the story presented to them appropriately.展开更多
Communication is a basic need of every human being to exchange thoughts and interact with the society.Acute peoples usually confab through different spoken languages,whereas deaf people cannot do so.Therefore,the Sign...Communication is a basic need of every human being to exchange thoughts and interact with the society.Acute peoples usually confab through different spoken languages,whereas deaf people cannot do so.Therefore,the Sign Language(SL)is the communication medium of such people for their conversation and interaction with the society.The SL is expressed in terms of specific gesture for every word and a gesture is consisted in a sequence of performed signs.The acute people normally observe these signs to understand the difference between single and multiple gestures for singular and plural words respectively.The signs for singular words such as I,eat,drink,home are unalike the plural words as school,cars,players.A special training is required to gain the sufficient knowledge and practice so that people can differentiate and understand every gesture/sign appropriately.Innumerable researches have been performed to articulate the computer-based solution to understand the single gesture with the help of a single hand enumeration.The complete understanding of such communications are possible only with the help of this differentiation of gestures in computer-based solution of SL to cope with the real world environment.Hence,there is still a demand for specific environment to automate such a communication solution to interact with such type of special people.This research focuses on facilitating the deaf community by capturing the gestures in video format and then mapping and differentiating as single or multiple gestures used in words.Finally,these are converted into the respective words/sentences within a reasonable time.This provide a real time solution for the deaf people to communicate and interact with the society.展开更多
In this study,we examine the problem of predicting customer defection in a noncontractual setting.Motivated by recent work on machine learning using multiple time slices,we develop a novel training and testing framewo...In this study,we examine the problem of predicting customer defection in a noncontractual setting.Motivated by recent work on machine learning using multiple time slices,we develop a novel training and testing framework,the sliding multi-time slicing(SMTS)method.We apply this method to data from the largest marketplace in Greece,namely,Skroutz,considering the standard features that account for the important characteristics of customer activity and custom performance metrics aimed at capturing business-related goals established by the company.The dataset comprises customers over a relatively short period,since April 2018,the number of which has also exhibited a significant increase in recent months.Despite these difficulties and the inherent seasonality of customer defection,our results demonstrate that,with SMTS,developing models that outperform previous approaches and optimize decision-making is possible.We validate the approach to a benchmark dataset from the commerce sector and discuss the practical considerations and requirements of the proposed method.展开更多
Active learning can be used for optimizing and speeding up the screening phase of systematic reviews.Running simulation studies mimicking the screening process can be used to test the performance of different machine-...Active learning can be used for optimizing and speeding up the screening phase of systematic reviews.Running simulation studies mimicking the screening process can be used to test the performance of different machine-learning models or to study the impact of different training data.This paper presents an architecture design withamultiprocessing computational strategyforrunningmanysuch simulation studiesinparallel,using the ASReview Makita workflow generator and Kubernetes software for deployment with cloud technologies.We provide a technical explanation of the proposed cloud architecture and its usage.In addition to that,we conducted 1140 simulations investigating the computational time using various numbers of CPUs and RAM settings.Our analysis demonstrates the degree to which simulations can be accelerated with multiprocessing computing usage.The parallel computation strategy and the architecture design that was developed in the present paper can contribute to future research with more optimal simulation time and,at the same time,ensure the safe completion of the needed processes.展开更多
While global efforts to operationalize soil spectroscopy are progressing,cooperation is needed to fully leverage its potential for generating digital soil information to support sustainable soil management worldwide.T...While global efforts to operationalize soil spectroscopy are progressing,cooperation is needed to fully leverage its potential for generating digital soil information to support sustainable soil management worldwide.The Global Soil Laboratory Network’s soil spectroscopy initiative(GLOSOLANSpec),led by the Food and Agriculture Organization of the United Nations(FAO)through its Global Soil Partnership(GSP),is dedicated to the further development and adoption of soil spectroscopy by fostering international collaboration via a scientific community of practice to produce accurate and reliable soil information for sustainable soil management and decision-making.To support this effort,we,a global consortium of soil scientists under the auspices of the International Union of Soil Sciences(IUSS)and GLOSOLAN-Spec,aim to address seven key challenges hindering the adoption of soil spectroscopy worldwide.Here,we offer perspectives on what is needed to advance soil spectroscopy as a routine soil analysis method,emphasizing its potential to generate new and reliable spatial and temporal soil data.展开更多
This paper focuses on fine-grained,secure access to FAIR data,for which we propose ontology-based data access policies.These policies take into account both the FAIR aspects of the data relevant to access(such as prov...This paper focuses on fine-grained,secure access to FAIR data,for which we propose ontology-based data access policies.These policies take into account both the FAIR aspects of the data relevant to access(such as provenance and licence),expressed as metadata,and additional metadata describing users.With this tripartite approach(data,associated metadata expressing FAIR information,and additional metadata about users),secure and controlled access to object data can be obtained.This yields a security dimension to the“A”(accessible)in FAIR,which is clearly needed in domains like security and intelligence.These domains need data to be shared under tight controls,with widely varying individual access rights.In this paper,we propose an approach called Ontology-Based Access Control(OBAC),which utilizes concepts and relations from a data set's domain ontology.We argue that ontology-based access policies contribute to data reusability and can be reconciled with privacy-aware data access policies.We illustrate our OBAC approach through a proof-of-concept and propose that OBAC to be adopted as a best practice for access management of FAIR data.展开更多
Comprehensive characterization of spatial and temporal gene expression patterns in humans is critical for uncovering the regulatory codes of the human genome and understanding the molecular mechanisms of human disease...Comprehensive characterization of spatial and temporal gene expression patterns in humans is critical for uncovering the regulatory codes of the human genome and understanding the molecular mechanisms of human diseases.Ubiquitously expressed genes(UEGs)refer to the genes expressed across a majority of,if not all,phenotypic and physiological conditions of an organism.It is known that many human genes are broadly expressed across tissues.However,most previous UEG studies have only focused on providing a list of UEGs without capturing their global expression patterns,thus limiting the potential use of UEG information.In this study,we proposed a novel data-driven framework to leverage the extensive collection of40,000 human transcriptomes to derive a list of UEGs and their corresponding global expression patterns,which offers a valuable resource to further characterize human transcriptome.Our results suggest that about half(12,234;49.01%)of the human genes are expressed in at least 80%of human transcriptomes,and the median size of the human transcriptome is 16,342 genes(65.44%).Through gene clustering,we identified a set of UEGs,named LoVarUEGs,which have stable expression across human transcriptomes and can be used as internal reference genes for expression measurement.To further demonstrate the usefulness of this resource,we evaluated the global expression patterns for 16 previously predicted disallowed genes in islet beta cells and found that seven of these genes showed relatively more varied expression patterns,suggesting that the repression of these genes may not be unique to islet beta cells.展开更多
Based on the wavelength transparency of the Butler matrix(BM)beamforming network,we demonstrate a multibeam optical phased array(MOPA)with an emitting aperture composed of grating couplers at a 1.55μm pitch for wavel...Based on the wavelength transparency of the Butler matrix(BM)beamforming network,we demonstrate a multibeam optical phased array(MOPA)with an emitting aperture composed of grating couplers at a 1.55μm pitch for wavelength-assisted two-dimensional beam-steering.The device is capable of simultaneous multi-beam operation in a field of view(FOV)of 60°×8°in the phased-array scanning axis and the wavelength-tuning scanning axis,respectively.The typical beam divergence is about 4°on both axes.Using multiple linearly chirped lasers,multibeam frequency-modulated continuous wave(FMCW)ranging is realized with an average ranging error of 4 cm.A C-shaped target is imaged for proof-of-concept 2D scanning and ranging.展开更多
Low-power reconfigurable optical circuits are highly demanded to satisfy a variety of different applications. Conventional electro-optic and thermo-optic refractive index tuning methods in silicon photonics are not su...Low-power reconfigurable optical circuits are highly demanded to satisfy a variety of different applications. Conventional electro-optic and thermo-optic refractive index tuning methods in silicon photonics are not suitable for reconfiguration of optical circuits due to their high static power consumption and volatility. We propose and demonstrate a nonvolatile tuning method by utilizing the reversible phase change property of GST integrated on top of the silicon waveguide. The phase change is enabled by applying electrical pulses to the lm-sized GST active region in a sandwich structure. The experimental results show that the optical transmission of the silicon waveguide can be tuned by controlling the phase state of GST.展开更多
基金supported by the Guangdong Provincial Key Laboratory IRADS(2022B1212010006,R0400001-22)。
文摘Obesity has become a significant global public health issue.Previous studies have found that the Chenpi has the anti-obesity activity.However,the anti-obesity phytochemicals and their mechanisms are still unclear.This study investigated the anti-obesity phytochemicals and molecular mechanisms involved in treating obesity by Chenpi through network pharmacology and molecular docking.A total of 17 bioactive phytochemicals from Chenpi and its 475 related anti-obesity targets have been identified.The KEGG pathway analysis showed that the PI3K/Akt signaling pathway,MAPK signaling pathway,AMPK signaling pathway,and nuclear factor kappa B signaling pathway are the main signaling pathways involved in the anti-obesity effect of Chenpi.According to molecular docking analysis,the phytochemicals of Chenpi can bind to central anti-obesity targets.Based on the ADMET analysis and network pharmacology results,tangeretin exhibited the lowest predicted toxicity and potential for anti-obesity effects.In the in vitro lipid accumulation model,tangeretin effectively suppressed the free fatty acid-induced lipid in Hep G2 cells by upregulating the PI3K/Akt/GSK3βsignaling pathway based on the result of q-PCR and Western blotting.The outcomes of this research give insights for future research on the anti-obesity phytochemicals and molecular mechanisms derived from Chenpi,also providing the theoretical basis for developing anti-obesity functional foods based on Chenpi.
基金the Interdisciplinary Program of Shanghai Jiao Tong University(No.ZH2018QNA30)the Three Year Action Plan of Shanghai Public Health System Construction(No.GWV-10.1-XK05)。
文摘This study aims to investigate the short-term effects of ambient air pollutants on outpatient visits for childhood allergic diseases.Daily data on ambient air pollutants(NO2,SO2,CO and PM2.5)and outpatient visits for childhood allergic diseases(asthma,atopic dermatitis and allergic rhinitis)were obtained in Shanghai,China from 2013 to 2014.The effects of ambient air pollutants were estimated for total outpatient visits for childhood allergic diseases,gender and age stratification and disease classification by using distributed lag non-linear model(DLNM).We found positive associations between short-term exposure to air pollutants and childhood allergic diseases.Girls and children aged 7 years old were more likely to be sensitive to ambient air pollutants.NO2 and SO2 showed stronger effects on asthma and atopic dermatitis,respectively.This study provides evidence that short-term exposure to ambient air pollutants can increase the risk of childhood allergic diseases.
文摘The development of artificial intelligence(AI)and the mining of biomedical data complement each other.From the direct use of computer vision results to analyze medical images for disease screening,to now integrating biological knowledge into models and even accelerating the development of new AI based on biological discoveries,the boundaries of both are constantly expanding,and their connections are becoming closer.Therefore,the theme of the 2024 Annual Quantitative Biology Conference is set as“Biomedical Data and AI”,and was held in Chengdu,China from July 15 to 17,2024.
文摘The problem of automated seizure detection is treated using clinical electroencephalograms(EEG) and machine learning algorithms on the Temple University Hospital EEG Seizure Corpus(TUSZ).Performances on this complex data set are still not encountering expectations.The purpose of this work is to determine to what extent the use of larger amount of data can help to improve the performances.Two methods are explored:a standard partitioning on a recent and larger version of the TUSZ,and a leave-one-out approach used to increase the amount of data for the training set.XGBoost,a fast implementation of the gradient boosting classifier,is the ideal algorithm for these tasks.The performances obtained are in the range of what is reported until now in the literature with deep learning models.We give interpretation to our results by identifying the most relevant features and analyzing performances by seizure types.We show that generalized seizures tend to be far better predicted than focal ones.We also notice that some EEG channels and features are more important than others to distinguish seizure from background.
文摘BACKGROUND The prevalence of left atrial appendage(LAA) thrombus detection by transesophageal echocardiogram(TEE) in patients with non-valvular atrial fibrillation(AF) anticoagulated with apixaban is not well defined and identification of additional risk factors may help guide the selection process for pre-procedural TEE. The purpose of our study was to retrospectively analyze the prevalence of LAA thrombus detection by TEE in patients continuously anticoagulated with apixaban for ≥ 4 wk and evaluate for any cardiac risk factors or echocardiographic characteristics which may serve as predictors of thrombus formation.AIM To retrospectively analyze the prevalence of LAA thrombus detection by TEE in patients continuously anticoagulated with apixaban.METHODS Clinical and echocardiographic data for 820 consecutive patients with AF undergoing TEE at Augusta University Medical Center over a four-year period were retrospectively analyzed. All patients(apixaban: 226) with non-valvular AF and documented compliance with apixaban for ≥ 4 wk prior to index TEE were included.RESULTS Following ≥ 4 wk of continuous anticoagulation with apixaban, the prevalence ofLAA thrombus and LAA thrombus/dense spontaneous echocardiographic contrast was 3.1% and 6.6%, respectively. Persistent AF, left ventricular ejection fraction < 30%, severe LA dilation, and reduced LAA velocity were associated with thrombus formation. Following multivariate logistic regression, persistent AF(OR: 7.427; 95%CI: 1.02 to 53.92; P = 0.0474), and reduced LAA velocity(OR:1.086; 95%CI: 1.010 to 1.187; P = 0.0489) were identified as independent predictors of LAA thrombus. No Thrombi were detected in patients with a CHA2 DS2-VASc score ≤ 1.CONCLUSION Among patients with non-valvular AF and ≥ 4 wk of anticoagulation with apixaban, the prevalence of LAA thrombus detected by TEE was 3.1%. This suggests that continuous therapy with apixaban does not completely eliminate the risk of LAA thrombus and that TEE prior to cardioversion or catheter ablation may be of benefit in patients with multiple risk factors.
基金supported by National key project 2018YFB1801102 and 2020YFB1807700by NSFC 62071296STCSM 20JC1416502, 22JC1404000
文摘Sparse code multiple access (SCMA) is the most concerning scheme among non-orthogonal multiple access (NOMA) technologies for 5G wireless communication new interface. Another efficient technique in 5G aimed to improve spectral efficiency for local communications is device-to-device (D2D) communications. Therefore, we utilize the SCMA cellular network coexisting with D2D communications for the connection demand of the Internet of things (IOT), and improve the system sum rate performance of the hybrid network. We first derive the information-theoretic expression of the capacity for all users and find the capacity bound of cellular users based on the mutual interference between cellular users and D2D users. Then we consider the power optimization problem for the cellular users and D2D users jointly to maximize the system sum rate. To tackle the non-convex optimization problem, we propose a geometric programming (GP) based iterative power allocation algorithm. Simulation results demonstrate that the proposed algorithm converges fast and well improves the sum rate performance.
文摘Anomaly detection(AD)is an important aspect of various domains and title insurance(TI)is no exception.Robotic process automation(RPA)is taking over manual tasks in TI business processes,but it has its limitations without the support of artificial intelligence(AI)and machine learning(ML).With increasing data dimensionality and in composite population scenarios,the complexity of detecting anomalies increases and AD in automated document management systems(ADMS)is the least explored domain.Deep learning,being the fastest maturing technology can be combined along with traditional anomaly detectors to facilitate and improve the RPAs in TI.We present a hybrid model for AD,using autoencoders(AE)and a one-class support vector machine(OSVM).In the present study,OSVM receives input features representing real-time documents from the TI business,orchestrated and with dimensions reduced by AE.The results obtained from multiple experiments are comparable with traditional methods and within a business acceptable range,regarding accuracy and performance.
基金The works presented in this paper are part of an ongoing research funded by the Fundamental Research Grant Scheme(FRGS/1/2018/ICT02/UTP/02/1)a grant funded by the Ministry of Higher Education,Malaysia and the Yayasan Universiti Teknologi PETRONAS grant(015LC0-274 and 015LC0-311).
文摘Fuzzy inference system(FIS)is a process of fuzzy logic reasoning to produce the output based on fuzzified inputs.The system starts with identifying input from data,applying the fuzziness to input using membership functions(MF),generating fuzzy rules for the fuzzy sets and obtaining the output.There are several types of input MFs which can be introduced in FIS,commonly chosen based on the type of real data,sensitivity of certain rule implied and computational limits.This paper focuses on the construction of interval type 2(IT2)trapezoidal shape MF from fuzzy C Means(FCM)that is used for fuzzification process of mamdani FIS.In the process,upper MF(UMF)and lower MF(LMF)of the MF need to be identified to get the range of the footprint of uncertainty(FOU).This paper proposes Genetic tuning process,which is a part of genetic algorithm(GA),to adjust parameters in order to improve the behavior of existing system,especially to enhance the accuracy of the system model.This novel process is a hybrid approach which produces Genetic Fuzzy System(GFS)that helps to enhance fuzzy classification problems and performance.The approach provides a new method for the construction and tuning process of the IT2 MF,based on the FCM outcomes.The result is compared to Gaussian shape IT2 MF and trapezoid IT2 MF generated by the classic GA method.It is shown that the proposed approach is able to outperform the mentioned benchmarked approaches.The work implies a wider range of IT2 MF types,constructed based on FCM outcomes,and an optimum generation of the FOU so that it can be implemented in practical applications such as prediction,analytics and rule-based solutions.
文摘During the ongoing 2020 CoVid-19 crisis,the use of remote meeting technologies such as Zoom™,Microsoft Teams™and Google Meetings™has been paramount to theoretical teaching in a safe socially distanced environment.However,several problems arise when there is a need for an experimental approach.This paper looks at one of the possible solutions,including how to best separate the students,how to minimize close interactions and how a mixed environment of remote/presential teaching is required,minimizing the amount of extra materials,resources and protection equipment required,such that developing countries can quickly adopt this method,without the purchase of any external equipment.
基金supported by Yayasan Universiti Teknologi PETRONAS Grant Scheme015LC0029 and 015LC0277.
文摘A web browser is the most basic tool for accessing the internet from any of the machines/equipment.Recently,data breaches have been reported frequently from users who are concerned about their personal information,as well as threats from criminal actors.Giving loss of data and information to an innocent user comes under the jurisdiction of cyber-attack.These kinds of cyber-attacks are far more dangerous when it comes to the many types of devices employed in an internet of things(IoT)environment.Continuous surveillance of IoT devices and forensic tools are required to overcome the issues pertaining to secure data and assets.Peer to peer(P2P)applications have been utilized for criminal operations on the web.Therefore,it is a challenge for a forensic investigator to perform forensic analysis of the evolving hardware and software platforms for IoT.For identity concealment and privacy protection,the Onion Router(Tor)and Chrome with the Invisible Internet Project(I2P)as the foundation browser are often used.Confirmation is required to determine whether Tor is truly anonymous and private as they claim.Some people,on the other hand,utilize the Tor browser for evil reasons.Tools and techniques are available for the collection of artifacts,identifying problem areas,further processing and analysis of data on the computer and IoT.Present research tried to explore a few tools for the tracing of I2P activities over computer on windows 10 that reflects IoT devices.According to the results of this research,it leaves an excessive amount of important digital evidence on the operating system that can be exploited to attack the information of users.This research is based on windows operating system and does not support other operating systems.
基金supported by the Benin Ministry of Health and the Institut Pasteur de Dakar Internal Funds for Research.·。
文摘Dear Editor,Monkeypox is an infectious disease that is endemic in a dozen of African countries.Some imported cases have been also reported outside of Africa in the past[1].Since early May 2022,monkeypox infections including human-to-human transmission,were reported in a multi-country outbreak in non-endemic countries and declared Public Health Emergency of International Concern(PHEIC)by the World Health Organization(WHO)in July 2022[2].As of 20 September 2022,a total of at least 62,798 human cases of monkeypox with 20 deaths have been confirmed in 115 countries in five WHO regions[3].
基金This research is ongoing research supported by Yayasan Universiti Teknologi PETRONAS Grant Scheme,015LC0029 and 015LC0277.
文摘Communication is a basic need of every human being;by this,they can learn,express their feelings and exchange their ideas,but deaf people cannot listen and speak.For communication,they use various hands gestures,also known as Sign Language(SL),which they learn from special schools.As normal people have not taken SL classes;therefore,they are unable to perform signs of daily routine sentences(e.g.,what are the specifications of this mobile phone?).A technological solution can facilitate in overcoming this communication gap by which normal people can communicate with deaf people.This paper presents an architecture for an application named Sign4PSL that translates the sentences to Pakistan Sign Language(PSL)for deaf people with visual representation using virtual signing character.This research aims to develop a generic independent application that is lightweight and reusable on any platform,including web and mobile,with an ability to perform offline text translation.The Sign4PSL relies on a knowledge base that stores both corpus of PSL Words and their coded form in the notation system.Sign4PSL takes English language text as an input,performs the translation to PSL through sign language notation and displays gestures to the user using virtual character.The system is tested on deaf students at a special school.The results have shown that the students were able to understand the story presented to them appropriately.
基金The work presented in this paper is part of an ongoing research funded by Yayasan Universiti Teknologi PETRONAS Grant(015LC0-311 and 015LC0-029).
文摘Communication is a basic need of every human being to exchange thoughts and interact with the society.Acute peoples usually confab through different spoken languages,whereas deaf people cannot do so.Therefore,the Sign Language(SL)is the communication medium of such people for their conversation and interaction with the society.The SL is expressed in terms of specific gesture for every word and a gesture is consisted in a sequence of performed signs.The acute people normally observe these signs to understand the difference between single and multiple gestures for singular and plural words respectively.The signs for singular words such as I,eat,drink,home are unalike the plural words as school,cars,players.A special training is required to gain the sufficient knowledge and practice so that people can differentiate and understand every gesture/sign appropriately.Innumerable researches have been performed to articulate the computer-based solution to understand the single gesture with the help of a single hand enumeration.The complete understanding of such communications are possible only with the help of this differentiation of gestures in computer-based solution of SL to cope with the real world environment.Hence,there is still a demand for specific environment to automate such a communication solution to interact with such type of special people.This research focuses on facilitating the deaf community by capturing the gestures in video format and then mapping and differentiating as single or multiple gestures used in words.Finally,these are converted into the respective words/sentences within a reasonable time.This provide a real time solution for the deaf people to communicate and interact with the society.
文摘In this study,we examine the problem of predicting customer defection in a noncontractual setting.Motivated by recent work on machine learning using multiple time slices,we develop a novel training and testing framework,the sliding multi-time slicing(SMTS)method.We apply this method to data from the largest marketplace in Greece,namely,Skroutz,considering the standard features that account for the important characteristics of customer activity and custom performance metrics aimed at capturing business-related goals established by the company.The dataset comprises customers over a relatively short period,since April 2018,the number of which has also exhibited a significant increase in recent months.Despite these difficulties and the inherent seasonality of customer defection,our results demonstrate that,with SMTS,developing models that outperform previous approaches and optimize decision-making is possible.We validate the approach to a benchmark dataset from the commerce sector and discuss the practical considerations and requirements of the proposed method.
基金supported by the Netherlands eScience Center under grant number ODISSEI.2022.023。
文摘Active learning can be used for optimizing and speeding up the screening phase of systematic reviews.Running simulation studies mimicking the screening process can be used to test the performance of different machine-learning models or to study the impact of different training data.This paper presents an architecture design withamultiprocessing computational strategyforrunningmanysuch simulation studiesinparallel,using the ASReview Makita workflow generator and Kubernetes software for deployment with cloud technologies.We provide a technical explanation of the proposed cloud architecture and its usage.In addition to that,we conducted 1140 simulations investigating the computational time using various numbers of CPUs and RAM settings.Our analysis demonstrates the degree to which simulations can be accelerated with multiprocessing computing usage.The parallel computation strategy and the architecture design that was developed in the present paper can contribute to future research with more optimal simulation time and,at the same time,ensure the safe completion of the needed processes.
基金supported by the Food and Agriculture Organization’s“SoilFER-VACS Framework-Enhancing Integrated Soil-Crop Management for Sustainable Food Systems in Africa”project,funded by the Ministry of Foreign Affairs of Japan.
文摘While global efforts to operationalize soil spectroscopy are progressing,cooperation is needed to fully leverage its potential for generating digital soil information to support sustainable soil management worldwide.The Global Soil Laboratory Network’s soil spectroscopy initiative(GLOSOLANSpec),led by the Food and Agriculture Organization of the United Nations(FAO)through its Global Soil Partnership(GSP),is dedicated to the further development and adoption of soil spectroscopy by fostering international collaboration via a scientific community of practice to produce accurate and reliable soil information for sustainable soil management and decision-making.To support this effort,we,a global consortium of soil scientists under the auspices of the International Union of Soil Sciences(IUSS)and GLOSOLAN-Spec,aim to address seven key challenges hindering the adoption of soil spectroscopy worldwide.Here,we offer perspectives on what is needed to advance soil spectroscopy as a routine soil analysis method,emphasizing its potential to generate new and reliable spatial and temporal soil data.
基金Part of this work was supported by the Titanium Project(funded by the European Comission under grant agreement 740558)The work was also supported by TNO’s internal research project“ERP AI”.
文摘This paper focuses on fine-grained,secure access to FAIR data,for which we propose ontology-based data access policies.These policies take into account both the FAIR aspects of the data relevant to access(such as provenance and licence),expressed as metadata,and additional metadata describing users.With this tripartite approach(data,associated metadata expressing FAIR information,and additional metadata about users),secure and controlled access to object data can be obtained.This yields a security dimension to the“A”(accessible)in FAIR,which is clearly needed in domains like security and intelligence.These domains need data to be shared under tight controls,with widely varying individual access rights.In this paper,we propose an approach called Ontology-Based Access Control(OBAC),which utilizes concepts and relations from a data set's domain ontology.We argue that ontology-based access policies contribute to data reusability and can be reconciled with privacy-aware data access policies.We illustrate our OBAC approach through a proof-of-concept and propose that OBAC to be adopted as a best practice for access management of FAIR data.
基金We thank Dr.Yongkun Wang from the Network and Information Center at Shanghai Jiao Tong University(SJTU)for his support in high-performance computing.We thank Ph.D.Candidate Wei Liu from Yale University for her support in the acquisition of physiological trait-related genes.HL is supported by the National Key R&D Program of China(Grant No.2018YFC0910500)JG and JD are supported by the SJTU-Yale Collaborative Research Seed Fund and Neil Shen’s SJTU Medical Research Fund,China.JG and HL are partially supported by the Shanghai Municipal Commission of Health and Family Planning,China(Grant No.2018ZHYL0223)the Science and Technology Commission of Shanghai Municipality(STCSM),China(Grant No.17DZ2251200).
文摘Comprehensive characterization of spatial and temporal gene expression patterns in humans is critical for uncovering the regulatory codes of the human genome and understanding the molecular mechanisms of human diseases.Ubiquitously expressed genes(UEGs)refer to the genes expressed across a majority of,if not all,phenotypic and physiological conditions of an organism.It is known that many human genes are broadly expressed across tissues.However,most previous UEG studies have only focused on providing a list of UEGs without capturing their global expression patterns,thus limiting the potential use of UEG information.In this study,we proposed a novel data-driven framework to leverage the extensive collection of40,000 human transcriptomes to derive a list of UEGs and their corresponding global expression patterns,which offers a valuable resource to further characterize human transcriptome.Our results suggest that about half(12,234;49.01%)of the human genes are expressed in at least 80%of human transcriptomes,and the median size of the human transcriptome is 16,342 genes(65.44%).Through gene clustering,we identified a set of UEGs,named LoVarUEGs,which have stable expression across human transcriptomes and can be used as internal reference genes for expression measurement.To further demonstrate the usefulness of this resource,we evaluated the global expression patterns for 16 previously predicted disallowed genes in islet beta cells and found that seven of these genes showed relatively more varied expression patterns,suggesting that the repression of these genes may not be unique to islet beta cells.
基金National Key Research and Development Program of China(2022YFB2804502)National Natural Science Foundation of China(6207030193,62090052,62135010)Special-Key Project of Innovation Program of Shanghai Municipal Education Commission(2019-07-00-02-E00075)。
文摘Based on the wavelength transparency of the Butler matrix(BM)beamforming network,we demonstrate a multibeam optical phased array(MOPA)with an emitting aperture composed of grating couplers at a 1.55μm pitch for wavelength-assisted two-dimensional beam-steering.The device is capable of simultaneous multi-beam operation in a field of view(FOV)of 60°×8°in the phased-array scanning axis and the wavelength-tuning scanning axis,respectively.The typical beam divergence is about 4°on both axes.Using multiple linearly chirped lasers,multibeam frequency-modulated continuous wave(FMCW)ranging is realized with an average ranging error of 4 cm.A C-shaped target is imaged for proof-of-concept 2D scanning and ranging.
基金supported by the National Natural Science Foundation of China(61535006,61705129 and 61661130155)Shanghai Municipal Science and Technology Major Project(2017SHZDZX03)
文摘Low-power reconfigurable optical circuits are highly demanded to satisfy a variety of different applications. Conventional electro-optic and thermo-optic refractive index tuning methods in silicon photonics are not suitable for reconfiguration of optical circuits due to their high static power consumption and volatility. We propose and demonstrate a nonvolatile tuning method by utilizing the reversible phase change property of GST integrated on top of the silicon waveguide. The phase change is enabled by applying electrical pulses to the lm-sized GST active region in a sandwich structure. The experimental results show that the optical transmission of the silicon waveguide can be tuned by controlling the phase state of GST.
