Epilepsy can be defined as a dysfunction of the brain network,and each type of epilepsy involves different brain-network changes that are implicated diffe rently in the control and propagation of interictal or ictal d...Epilepsy can be defined as a dysfunction of the brain network,and each type of epilepsy involves different brain-network changes that are implicated diffe rently in the control and propagation of interictal or ictal discharges.Gaining more detailed information on brain network alterations can help us to further understand the mechanisms of epilepsy and pave the way for brain network-based precise therapeutic approaches in clinical practice.An increasing number of advanced neuroimaging techniques and electrophysiological techniques such as diffusion tensor imaging-based fiber tra ctography,diffusion kurtosis imaging-based fiber tractography,fiber ball imagingbased tra ctography,electroencephalography,functional magnetic resonance imaging,magnetoencephalography,positron emission tomography,molecular imaging,and functional ultrasound imaging have been extensively used to delineate epileptic networks.In this review,we summarize the relevant neuroimaging and neuroelectrophysiological techniques for assessing structural and functional brain networks in patients with epilepsy,and extensively analyze the imaging mechanisms,advantages,limitations,and clinical application ranges of each technique.A greater focus on emerging advanced technologies,new data analysis software,a combination of multiple techniques,and the construction of personalized virtual epilepsy models can provide a theoretical basis to better understand the brain network mechanisms of epilepsy and make surgical decisions.展开更多
The widespread adoption of the Internet of Things (IoT) has transformed various sectors globally, making themmore intelligent and connected. However, this advancement comes with challenges related to the effectiveness...The widespread adoption of the Internet of Things (IoT) has transformed various sectors globally, making themmore intelligent and connected. However, this advancement comes with challenges related to the effectiveness ofIoT devices. These devices, present in offices, homes, industries, and more, need constant monitoring to ensuretheir proper functionality. The success of smart systems relies on their seamless operation and ability to handlefaults. Sensors, crucial components of these systems, gather data and contribute to their functionality. Therefore,sensor faults can compromise the system’s reliability and undermine the trustworthiness of smart environments.To address these concerns, various techniques and algorithms can be employed to enhance the performance ofIoT devices through effective fault detection. This paper conducted a thorough review of the existing literature andconducted a detailed analysis.This analysis effectively links sensor errors with a prominent fault detection techniquecapable of addressing them. This study is innovative because it paves theway for future researchers to explore errorsthat have not yet been tackled by existing fault detection methods. Significant, the paper, also highlights essentialfactors for selecting and adopting fault detection techniques, as well as the characteristics of datasets and theircorresponding recommended techniques. Additionally, the paper presents amethodical overview of fault detectiontechniques employed in smart devices, including themetrics used for evaluation. Furthermore, the paper examinesthe body of academic work related to sensor faults and fault detection techniques within the domain. This reflectsthe growing inclination and scholarly attention of researchers and academicians toward strategies for fault detectionwithin the realm of the Internet of Things.展开更多
In the increasingly decentralized energy environment,economical power dispatching from distributed generations(DGs)is crucial to minimizing operating costs,optimizing resource utilization,and guaranteeing a consistent...In the increasingly decentralized energy environment,economical power dispatching from distributed generations(DGs)is crucial to minimizing operating costs,optimizing resource utilization,and guaranteeing a consistent and sustainable supply of electricity.A comprehensive review of optimization techniques for economic power dispatching from distributed generations is imperative to identify the most effective strategies for minimizing operational costs while maintaining grid stability and sustainability.The choice of optimization technique for economic power dispatching from DGs depends on a number of factors,such as the size and complexity of the power system,the availability of computational resources,and the specific requirements of the application.Optimization techniques for economic power dispatching from distributed generations(DGs)can be classified into two main categories:(i)Classical optimization techniques,(ii)Heuristic optimization techniques.In classical optimization techniques,the linear programming(LP)model is one of the most popular optimization methods.Utilizing the LP model,power demand and network constraints are met while minimizing the overall cost of generating electricity from DGs.This approach is efficient in determining the best DGs dispatch and is capable of handling challenging optimization issues in the large-scale system including renewables.The quadratic programming(QP)model,a classical optimization technique,is a further popular optimization method,to consider non-linearity.The QP model can take into account the quadratic cost of energy production,with consideration constraints like network capacity,voltage,and frequency.The metaheuristic optimization techniques are also used for economic power dispatching from DGs,which include genetic algorithms(GA),particle swarm optimization(PSO),and ant colony optimization(ACO).Also,Some researchers are developing hybrid optimization techniques that combine elements of classical and heuristic optimization techniques with the incorporation of droop control,predictive control,and fuzzy-based methods.These methods can deal with large-scale systems with many objectives and non-linear,non-convex optimization issues.The most popular approaches are the LP and QP models,while more difficult problems are handled using metaheuristic optimization techniques.In summary,in order to increase efficiency,reduce costs,and ensure a consistent supply of electricity,optimization techniques are essential tools used in economic power dispatching from DGs.展开更多
Chinese chive is a kind of medicinal and edible plant,with many diseases,and chemical fungicides are usually used for control.In order to find out the risk of pesticide residues in Chinese chives,this paper summarized...Chinese chive is a kind of medicinal and edible plant,with many diseases,and chemical fungicides are usually used for control.In order to find out the risk of pesticide residues in Chinese chives,this paper summarized relevant literatures published in recent years,and sorted out and analyzed the types of pesticides used and detection techniques of common diseases in Chinese chives.展开更多
When a customer uses the software, then it is possible to occur defects that can be removed in the updated versions of the software. Hence, in the present work, a robust examination of cross-project software defect pr...When a customer uses the software, then it is possible to occur defects that can be removed in the updated versions of the software. Hence, in the present work, a robust examination of cross-project software defect prediction is elaborated through an innovative hybrid machine learning framework. The proposed technique combines an advanced deep neural network architecture with ensemble models such as Support Vector Machine (SVM), Random Forest (RF), and XGBoost. The study evaluates the performance by considering multiple software projects like CM1, JM1, KC1, and PC1 using datasets from the PROMISE Software Engineering Repository. The three hybrid models that are compared are Hybrid Model-1 (SVM, RandomForest, XGBoost, Neural Network), Hybrid Model-2 (GradientBoosting, DecisionTree, LogisticRegression, Neural Network), and Hybrid Model-3 (KNeighbors, GaussianNB, Support Vector Classification (SVC), Neural Network), and the Hybrid Model 3 surpasses the others in terms of recall, F1-score, accuracy, ROC AUC, and precision. The presented work offers valuable insights into the effectiveness of hybrid techniques for cross-project defect prediction, providing a comparative perspective on early defect identification and mitigation strategies. .展开更多
Introduction: Urethroplasty remains the gold standard for the management of urethral stricture. However, the treatment of stricture disease in the elderly tends to be less invasive due to the presumption that they mig...Introduction: Urethroplasty remains the gold standard for the management of urethral stricture. However, the treatment of stricture disease in the elderly tends to be less invasive due to the presumption that they might not be able to stand long hours of surgery and might have higher rates of recurrence due to poor wound healing from microangiopathy. We present our experience with the outcomes of urethroplasty among elderly men seen at the Komfo Anokye Teaching Hospital from January 2012 to December 2021. Methods: This was a retrospective review of data captured in the urology database on all patients 65 years and above who underwent urethroplasty at the hospital over the study period. Data was obtained on patients’ demographics, stricture characteristics, urethroplasty technique, and outcome. A successful outcome was defined as peak flow rate > 15 mls/s, a patent urethra on retrograde urethrogram, patient satisfaction with urine stream, or restoration of the normal stream of urine with only one attempt at urethral calibration or internal urethrotomy postoperatively. Data was analyzed using PASW Statistics for Windows, Version 18.0. Results: Overall, 43 urethroplasties were done over the study period in elderly men. The age range was 65 to 87 years. The commonest aetiology was catheterization (62.79%) followed by urethritis (32.56%). Stricture length ranged from 0.5 cm to 16 cm with a mean of 3.93 cm. Most patients (60.46%) had bulbar urethral strictures. The repair methods employed were anastomotic urethroplasty (62.80%), fasciocutaneous flap (FCF) ventral onlay (13.95%), buccal mucosa graft (BMG) ventral onlay urethroplasty (4.65%), and staged urethroplasty (4.65%). Three of the patients (6.98%) had a combination of anastomotic and tissue transfer urethroplasty. The overall success rate was 88.37%. Complications included three surgical site infections, two urethral diverticula and one glans dehiscence. Conclusion: Elderly men tolerate urethroplasty well and the procedure should not be denied solely based on age.展开更多
In light of the rapid growth and development of social media, it has become the focus of interest in many different scientific fields. They seek to extract useful information from it, and this is called (knowledge), s...In light of the rapid growth and development of social media, it has become the focus of interest in many different scientific fields. They seek to extract useful information from it, and this is called (knowledge), such as extracting information related to people’s behaviors and interactions to analyze feelings or understand the behavior of users or groups, and many others. This extracted knowledge has a very important role in decision-making, creating and improving marketing objectives and competitive advantage, monitoring events, whether political or economic, and development in all fields. Therefore, to extract this knowledge, we need to analyze the vast amount of data found within social media using the most popular data mining techniques and applications related to social media sites.展开更多
This thorough review explores the complexities of geotechnical engineering, emphasizing soil-structure interaction (SSI). The investigation centers on sheet pile design, examining two primary methodologies: Limit Equi...This thorough review explores the complexities of geotechnical engineering, emphasizing soil-structure interaction (SSI). The investigation centers on sheet pile design, examining two primary methodologies: Limit Equilibrium Methods (LEM) and Soil-Structure Interaction Methods (SSIM). While LEM methods, grounded in classical principles, provide valuable insights for preliminary design considerations, they may encounter limitations in addressing real-world complexities. In contrast, SSIM methods, including the SSI-SR approach, introduce precision and depth to the field. By employing numerical techniques such as Finite Element (FE) and Finite Difference (FD) analyses, these methods enable engineers to navigate the dynamics of soil-structure interaction. The exploration extends to SSI-FE, highlighting its essential role in civil engineering. By integrating Finite Element analysis with considerations for soil-structure interaction, the SSI-FE method offers a holistic understanding of how structures dynamically interact with their geotechnical environment. Throughout this exploration, the study dissects critical components governing SSIM methods, providing engineers with tools to navigate the intricate landscape of geotechnical design. The study acknowledges the significance of the Mohr-Coulomb constitutive model while recognizing its limitations, and guiding practitioners toward informed decision-making in geotechnical analyses. As the article concludes, it underscores the importance of continuous learning and innovation for the future of geotechnical engineering. With advancing technology and an evolving understanding of soil-structure interaction, the study remains committed to ensuring the safety, stability, and efficiency of geotechnical structures through cutting-edge design and analysis techniques.展开更多
Electrocatalytic oxygen reduction reaction(ORR)is one of the most important reactions in electrochemical energy technologies such as fuel cells and metal–O2/air batteries,etc.However,the essential catalysts to overco...Electrocatalytic oxygen reduction reaction(ORR)is one of the most important reactions in electrochemical energy technologies such as fuel cells and metal–O2/air batteries,etc.However,the essential catalysts to overcome its slow reaction kinetic always undergo a complex dynamic evolution in the actual catalytic process,and the concomitant intermediates and catalytic products also occur continuous conversion and reconstruction.This makes them difficult to be accurately captured,making the identification of ORR active sites and the elucidation of ORR mechanisms difficult.Thus,it is necessary to use extensive in-situ characterization techniques to proceed the real-time monitoring of the catalyst structure and the evolution state of intermediates and products during ORR.This work reviews the major advances in the use of various in-situ techniques to characterize the catalytic processes of various catalysts.Specifically,the catalyst structure evolutions revealed directly by in-situ techniques are systematically summarized,such as phase,valence,electronic transfer,coordination,and spin states varies.In-situ revelation of intermediate adsorption/desorption behavior,and the real-time monitoring of the product nucleation,growth,and reconstruction evolution are equally emphasized in the discussion.Other interference factors,as well as in-situ signal assignment with the aid of theoretical calculations,are also covered.Finally,some major challenges and prospects of in-situ techniques for future catalysts research in the ORR process are proposed.展开更多
In the world,nonalcoholic fatty liver disease(NAFLD)accounts for majority of diffuse hepatic diseases.Notably,substantial liver fat accumulation can trigger and accelerate hepatic fibrosis,thus contributing to disease...In the world,nonalcoholic fatty liver disease(NAFLD)accounts for majority of diffuse hepatic diseases.Notably,substantial liver fat accumulation can trigger and accelerate hepatic fibrosis,thus contributing to disease progression.Moreover,the presence of NAFLD not only puts adverse influences for liver but is also associated with an increased risk of type 2 diabetes and cardiovascular diseases.Therefore,early detection and quantified measurement of hepatic fat content are of great importance.Liver biopsy is currently the most accurate method for the evaluation of hepatic steatosis.However,liver biopsy has several limitations,namely,its invasiveness,sampling error,high cost and moderate intraobserver and interobserver reproducibility.Recently,various quantitative imaging techniques have been developed for the diagnosis and quantified measurement of hepatic fat content,including ultrasound-or magnetic resonancebased methods.These quantitative imaging techniques can provide objective continuous metrics associated with liver fat content and be recorded for comparison when patients receive check-ups to evaluate changes in liver fat content,which is useful for longitudinal follow-up.In this review,we introduce several imaging techniques and describe their diagnostic performance for the diagnosis and quantified measurement of hepatic fat content.展开更多
Through vehicle-to-vehicle(V2V)communication,autonomizing a vehicle platoon can significantly reduce the distance between vehicles,thereby reducing air resistance and improving road traffic efficiency.The gradual matu...Through vehicle-to-vehicle(V2V)communication,autonomizing a vehicle platoon can significantly reduce the distance between vehicles,thereby reducing air resistance and improving road traffic efficiency.The gradual maturation of platoon control technology is enabling vehicle platoons to achieve basic driving functions,thereby permitting large-scale vehicle platoon scheduling and planning,which is essential for industrialized platoon applications and generates significant economic benefits.Scheduling and planning are required in many aspects of vehicle platoon operation;here,we outline the advantages and challenges of a number of the most important applications,including platoon formation scheduling,lane-change planning,passing traffic light scheduling,and vehicle resource allocation.This paper’s primary objective is to integrate current independent platoon scheduling and planning techniques into an integrated architecture to meet the demands of large-scale platoon applications.To this end,we first summarize the general techniques of vehicle platoon scheduling and planning,then list the primary scenarios for scheduling and planning technique application,and finally discuss current challenges and future development trends in platoon scheduling and planning.We hope that this paper can encourage related platoon researchers to conduct more systematic research and integrate multiple platoon scheduling and planning technologies and applications.展开更多
Pseudocapacitive materials that store charges via reversible surface or near-surface faradaic reactions are capable of overcoming the capacity limitations of electrical double-layer capacitors.Revealing the structure...Pseudocapacitive materials that store charges via reversible surface or near-surface faradaic reactions are capable of overcoming the capacity limitations of electrical double-layer capacitors.Revealing the structure–activity relationship between the microstructural features of pseudocapacitive materials and their electrochemical performance on the atomic scale is the key to build high-performance capacitor-type devices containing ideal pseudocapacitance effect.Currently,the high brightness(flux),and spectral and coherent nature of synchrotron X-ray analytical techniques make it a powerful tool for probing the structure–property relationship of pseudocapacitive materials.Herein,we report a comprehensive and systematic review of four typical characterization techniques(synchrotron X-ray diffraction,pair distribution function[PDF]analysis,soft X-ray absorption spectroscopy,and hard X-ray absorption spectroscopy)for the study of pseudocapacitance mechanisms.In addition,we offered significant insights for understanding and identifying pseudocapacitance mechanisms(surface redox pseudocapacitance,intercalation pseudocapacitance,and the extrinsic pseudocapacitance phenomenon in battery materials)by combining in situ hard XAS and electrochemical analyses.Finally,a perspective for further depth of understanding into the pseudocapacitance mechanism using synchrotron X-ray analytical techniques is proposed.展开更多
With the development of urbanization,the problem of neurological diseases brought about by population aging has gradually become a social problem of worldwide concern.Aging leads to gradual degeneration of the central...With the development of urbanization,the problem of neurological diseases brought about by population aging has gradually become a social problem of worldwide concern.Aging leads to gradual degeneration of the central nervous system,shrinkage of brain tissue,and decline in physical function in many elderlies,making them susceptible to neurological diseases such as Alzheimer’s disease(AD),stroke,Parkinson’s and major depressive disorder(MDD).Due to the influence of these neurological diseases,the elderly have troubles such as memory loss,inability to move,falling,and getting lost,which seriously affect their quality of life.Tracking and positioning of elderly with neurological diseases and keeping track of their location in real-time are necessary and crucial in order to detect and treat dangerous and unexpected situations in time.Considering that the elderly with neurological diseases forget to wear a positioning device or have mobility problems due to carrying a positioning device,device-free positioning as a passive positioning technology that detects device-free individuals is more suitable than traditional active positioning for the home-based care of the elderly with neurological diseases.This paper provides an extensive and in-depth survey of device-free indoor positioning technology for home-based care and an in-depth analysis of the main features of current positioning systems,as well as the techniques,technologies andmethods they employ,fromthe perspective of the needs of the elderly with neurological conditions.Moreover,evaluation criteria and possible solutions of positioning techniques for the home-based care of the elderly with neurological conditions are proposed.Finally,the opportunities and challenges for the development of indoor positioning technology in 6G mobile networks for home-based care of the elderly with neurological diseases are discussed.This review has provided comprehensive and effective tracking and positioning techniques,technologies and methods for the elderly,by which we can obtain the location information of the elderly in real-time and make home-based care more comfortable and safer for the elderly with neurological diseases.展开更多
Transition metal sulfides have been regarded as promising anode materials for sodium-ion batteries(SIB).However,they face the challenges of poor electronic conductivity and large volume change,which result in capacity...Transition metal sulfides have been regarded as promising anode materials for sodium-ion batteries(SIB).However,they face the challenges of poor electronic conductivity and large volume change,which result in capacity fade and low rate capability.In this work,a composite containing ultrasmall CoS(~7 nm)nanoparticles embedded in heteroatom(N,S,and O)-doped carbon was synthesized by an efficient one-step sulfidation process using a Co(Salen)precursor.The ultrasmall CoS nanoparticles are beneficial for mechanical stability and shortening Na-ions diffusion pathways.Furthermore,the N,S,and O-doped defect-rich carbon provides a robust and highly conductive framework enriched with active sites for sodium storage as well as mitigates volume expansion and polysulfide shuttle.As anode for SIB,CoS@HDC exhibits a high initial capacity of 906 mA h g^(-1)at 100 mA g^(-1)and a stable long-term cycling life with over 1000 cycles at 500 mA g^(-1),showing a reversible capacity of 330 mA h g^(-1).Meanwhile,the CoS@HDC anode is proven to maintain its structural integrity and compositional reversibility during cycling.Furthermore,Na-ion full batteries based on the CoS@HDC anode and Na_(3)V_(2)(PO_(4))_(3)cathode demonstrate a stable cycling behavior with a reversible specific capacity of~200 m A h g^(-1)at least for 100 cycles.Moreover,advanced synchrotron operando X-ray diffraction,ex-situ X-ray absorption spectroscopy,and comprehensive electrochemical tests reveal the structural transformation and the Co coordination chemistry evolution of the CoS@HDC during cycling,providing fundamental insights into the sodium storage mechanism.展开更多
While sufficient review articles exist on inductive short-range wireless power transfer(WPT),long-haul microwave WPT(MWPT)for solar power satellites,and ambient microwave wireless energy harvesting(MWEH)in urban areas...While sufficient review articles exist on inductive short-range wireless power transfer(WPT),long-haul microwave WPT(MWPT)for solar power satellites,and ambient microwave wireless energy harvesting(MWEH)in urban areas,few studies focus on the fundamental modeling and related design automation of receiver systems.This article reviews the development of MWPT and MWEH receivers,with a focus on rectenna design automation.A novel rectifier model capable of accurately modeling the rectification process under both high and low input power is presented.The model reveals the theoretical boundary of radio frequency-to-direct current(dc)power conversion efficiency and,most importantly,enables an automated system design.The automated rectenna design flow is sequential,with the minimal engagement of iterative optimization.It covers the design automation of every module(i.e.,rectifiers,matching circuits,antennae,and dc–dc converters).Scaling-up of the technique to large rectenna arrays is also possible,where the challenges in array partitioning and power combining are briefly discussed.In addition,several cutting-edge rectenna techniques for MWPT and MWEH are reviewed,including the dynamic range extension technique,the harmonics-based retro-directive technique,and the simultaneous wireless information and power transfer technique,which can be good complements to the presented automated design methodology.展开更多
A novel model termed a bipolar complex fuzzy N-soft set(BCFN-SS)is initiated for tackling information that involves positive and negative aspects,the second dimension,and parameterised grading simultaneously.The theor...A novel model termed a bipolar complex fuzzy N-soft set(BCFN-SS)is initiated for tackling information that involves positive and negative aspects,the second dimension,and parameterised grading simultaneously.The theory of BCFN-SS is the generalisation of two various theories,that is,bipolar complex fuzzy(BCF)and N-SS.The invented model of BCFN-SS helps decision-makers to cope with the genuine-life dilemmas containing BCF information along with parameterised grading at the same time.Further,various algebraic operations,including the usual type of union,intersection,complements,and a few others types,are invented.Certain primary operational laws for BCFNSS are also invented.Moreover,a technique for order preference by similarity to the ideal solution(TOPSIS)approach is devised in the setting of BCFN-SS for managing strategic decision-making(DM)dilemmas containing BCFN-SS information.Keeping in mind the usefulness and benefits of the TOPSIS approach,two various types of TOPSIS approaches in the environment of BCFN-SS are devised and then a numerical example for exposing the usefulness of the devised TOPSIS approach is interpreted.To disclose the prominence and benefits of the devised work,the devised approaches with numerous prevailing work are compared.展开更多
Residential sector is one of the energy-consuming districts of countries that causes CO_(2)emission in large extent.In this regard,this sector must be considered in energy policy making related to the reduction of emi...Residential sector is one of the energy-consuming districts of countries that causes CO_(2)emission in large extent.In this regard,this sector must be considered in energy policy making related to the reduction of emission of CO_(2)and other greenhouse gases.In the present work,CO_(2)emission related to the residential sector of three countries,including Indonesia,Thailand,and Vietnam in Southeast Asia,are discussed and modeled by employing Group Method of Data Handling(GMDH)and Multilayer Perceptron(MLP)neural networks as powerful intelligent methods.Prior to modeling,data related to the energy consumption of these countries are represented,discussed,and analyzed.Subsequently,to propose a model,electricity,natural gas,coal,and oil products consumptions are applied as inputs,and CO_(2)emission is considered as the model’s output.The obtained R^(2) values for the generated models based on MLP and GMDH are 0.9987 and 0.9985,respectively.Furthermore,values of the Average Absolute Relative Deviation(AARD)of the regressions using the mentioned techniques are around 4.56%and 5.53%,respectively.These values reveal significant exactness of the models proposed in this article;however,making use of MLP with the optimal architecture would lead to higher accuracy.展开更多
In this era of post-COVID-19,humans are psychologically restricted to interact less with other humans.According to the world health organization(WHO),there are many scenarios where human interactions cause severe mult...In this era of post-COVID-19,humans are psychologically restricted to interact less with other humans.According to the world health organization(WHO),there are many scenarios where human interactions cause severe multiplication of viruses from human to human and spread worldwide.Most healthcare systems shifted to isolation during the pandemic and a very restricted work environment.Investigations were done to overcome the remedy,and the researcher developed different techniques and recommended solutions.Telepresence robot was the solution achieved by all industries to continue their operations but with almost zero physical interaction with other humans.It played a vital role in this perspective to help humans to perform daily routine tasks.Healthcare workers can use telepresence robots to interact with patients who visit the healthcare center for initial diagnosis for better healthcare system performance without direct interaction.The presented paper aims to compare different telepresence robots and their different controlling techniques to perform the needful in the respective scenario of healthcare environments.This paper comprehensively analyzes and reviews the applications of presented techniques to control different telepresence robots.However,our feature-wise analysis also points to specific technical,appropriate,and ethical challenges that remain to be solved.The proposed investigation summarizes the need for further multifaceted research on the design and impact of a telepresence robot for healthcare centers,building on new perceptions during the COVID-19 pandemic.展开更多
BACKGROUND Heterotopic pregnancy(HP)is a rare condition in which both ectopic and intrauterine pregnancies occur.HP is uncommon after natural conception but has recently received more attention due to the widespread u...BACKGROUND Heterotopic pregnancy(HP)is a rare condition in which both ectopic and intrauterine pregnancies occur.HP is uncommon after natural conception but has recently received more attention due to the widespread use of assisted reproductive techniques(ART)such as ovulation promotion therapy.CASE SUMMARY Here,we describe a case of HP that occurred after ART with concurrent tubal and intrauterine singleton pregnancies.This was treated successfully with surgery to preserve the intrauterine pregnancy,resulting in the birth of a low-weight premature infant.This case report aims to increase awareness of the possibility of HP during routine first-trimester ultrasound examinations,especially in pregnancies resulting from ART and even if multiple intrauterine pregnancies are present.CONCLUSION This case alerts us to the importance of comprehensive data collection during regular consultations.It is important for us to remind ourselves of the possibility of HP in all patients presenting after ART,especially in women with an established and stable intrauterine pregnancy that complain of constant abdominal discomfort and also in women with an unusually raised human chorionic gonadotropin level compared with simplex intrauterine pregnancy.This will allow symptomatic and timeous treatment of patients with better results.展开更多
Big Data is reforming many industrial domains by providing decision support through analyzing large data volumes.Big Data testing aims to ensure that Big Data systems run smoothly and error-free while maintaining the ...Big Data is reforming many industrial domains by providing decision support through analyzing large data volumes.Big Data testing aims to ensure that Big Data systems run smoothly and error-free while maintaining the performance and quality of data.However,because of the diversity and complexity of data,testing Big Data is challenging.Though numerous research efforts deal with Big Data testing,a comprehensive review to address testing techniques and challenges of BigData is not available as yet.Therefore,we have systematically reviewed the Big Data testing techniques’evidence occurring in the period 2010–2021.This paper discusses testing data processing by highlighting the techniques used in every processing phase.Furthermore,we discuss the challenges and future directions.Our findings show that diverse functional,non-functional and combined(functional and non-functional)testing techniques have been used to solve specific problems related to Big Data.At the same time,most of the testing challenges have been faced during the MapReduce validation phase.In addition,the combinatorial testing technique is one of the most applied techniques in combination with other techniques(i.e.,random testing,mutation testing,input space partitioning and equivalence testing)to find various functional faults through Big Data testing.展开更多
基金supported by the Natural Science Foundation of Sichuan Province of China,Nos.2022NSFSC1545 (to YG),2022NSFSC1387 (to ZF)the Natural Science Foundation of Chongqing of China,Nos.CSTB2022NSCQ-LZX0038,cstc2021ycjh-bgzxm0035 (both to XT)+3 种基金the National Natural Science Foundation of China,No.82001378 (to XT)the Joint Project of Chongqing Health Commission and Science and Technology Bureau,No.2023QNXM009 (to XT)the Science and Technology Research Program of Chongqing Education Commission of China,No.KJQN202200435 (to XT)the Chongqing Talents:Exceptional Young Talents Project,No.CQYC202005014 (to XT)。
文摘Epilepsy can be defined as a dysfunction of the brain network,and each type of epilepsy involves different brain-network changes that are implicated diffe rently in the control and propagation of interictal or ictal discharges.Gaining more detailed information on brain network alterations can help us to further understand the mechanisms of epilepsy and pave the way for brain network-based precise therapeutic approaches in clinical practice.An increasing number of advanced neuroimaging techniques and electrophysiological techniques such as diffusion tensor imaging-based fiber tra ctography,diffusion kurtosis imaging-based fiber tractography,fiber ball imagingbased tra ctography,electroencephalography,functional magnetic resonance imaging,magnetoencephalography,positron emission tomography,molecular imaging,and functional ultrasound imaging have been extensively used to delineate epileptic networks.In this review,we summarize the relevant neuroimaging and neuroelectrophysiological techniques for assessing structural and functional brain networks in patients with epilepsy,and extensively analyze the imaging mechanisms,advantages,limitations,and clinical application ranges of each technique.A greater focus on emerging advanced technologies,new data analysis software,a combination of multiple techniques,and the construction of personalized virtual epilepsy models can provide a theoretical basis to better understand the brain network mechanisms of epilepsy and make surgical decisions.
文摘The widespread adoption of the Internet of Things (IoT) has transformed various sectors globally, making themmore intelligent and connected. However, this advancement comes with challenges related to the effectiveness ofIoT devices. These devices, present in offices, homes, industries, and more, need constant monitoring to ensuretheir proper functionality. The success of smart systems relies on their seamless operation and ability to handlefaults. Sensors, crucial components of these systems, gather data and contribute to their functionality. Therefore,sensor faults can compromise the system’s reliability and undermine the trustworthiness of smart environments.To address these concerns, various techniques and algorithms can be employed to enhance the performance ofIoT devices through effective fault detection. This paper conducted a thorough review of the existing literature andconducted a detailed analysis.This analysis effectively links sensor errors with a prominent fault detection techniquecapable of addressing them. This study is innovative because it paves theway for future researchers to explore errorsthat have not yet been tackled by existing fault detection methods. Significant, the paper, also highlights essentialfactors for selecting and adopting fault detection techniques, as well as the characteristics of datasets and theircorresponding recommended techniques. Additionally, the paper presents amethodical overview of fault detectiontechniques employed in smart devices, including themetrics used for evaluation. Furthermore, the paper examinesthe body of academic work related to sensor faults and fault detection techniques within the domain. This reflectsthe growing inclination and scholarly attention of researchers and academicians toward strategies for fault detectionwithin the realm of the Internet of Things.
文摘In the increasingly decentralized energy environment,economical power dispatching from distributed generations(DGs)is crucial to minimizing operating costs,optimizing resource utilization,and guaranteeing a consistent and sustainable supply of electricity.A comprehensive review of optimization techniques for economic power dispatching from distributed generations is imperative to identify the most effective strategies for minimizing operational costs while maintaining grid stability and sustainability.The choice of optimization technique for economic power dispatching from DGs depends on a number of factors,such as the size and complexity of the power system,the availability of computational resources,and the specific requirements of the application.Optimization techniques for economic power dispatching from distributed generations(DGs)can be classified into two main categories:(i)Classical optimization techniques,(ii)Heuristic optimization techniques.In classical optimization techniques,the linear programming(LP)model is one of the most popular optimization methods.Utilizing the LP model,power demand and network constraints are met while minimizing the overall cost of generating electricity from DGs.This approach is efficient in determining the best DGs dispatch and is capable of handling challenging optimization issues in the large-scale system including renewables.The quadratic programming(QP)model,a classical optimization technique,is a further popular optimization method,to consider non-linearity.The QP model can take into account the quadratic cost of energy production,with consideration constraints like network capacity,voltage,and frequency.The metaheuristic optimization techniques are also used for economic power dispatching from DGs,which include genetic algorithms(GA),particle swarm optimization(PSO),and ant colony optimization(ACO).Also,Some researchers are developing hybrid optimization techniques that combine elements of classical and heuristic optimization techniques with the incorporation of droop control,predictive control,and fuzzy-based methods.These methods can deal with large-scale systems with many objectives and non-linear,non-convex optimization issues.The most popular approaches are the LP and QP models,while more difficult problems are handled using metaheuristic optimization techniques.In summary,in order to increase efficiency,reduce costs,and ensure a consistent supply of electricity,optimization techniques are essential tools used in economic power dispatching from DGs.
基金Supported by Special Project of the Central Government in Guidance of Local Science and Technology Development (Scientific and Technological Innovation Base Project) (226Z5504G)The Fourth Batch of High-end Talent Project in Hebei Province.
文摘Chinese chive is a kind of medicinal and edible plant,with many diseases,and chemical fungicides are usually used for control.In order to find out the risk of pesticide residues in Chinese chives,this paper summarized relevant literatures published in recent years,and sorted out and analyzed the types of pesticides used and detection techniques of common diseases in Chinese chives.
文摘When a customer uses the software, then it is possible to occur defects that can be removed in the updated versions of the software. Hence, in the present work, a robust examination of cross-project software defect prediction is elaborated through an innovative hybrid machine learning framework. The proposed technique combines an advanced deep neural network architecture with ensemble models such as Support Vector Machine (SVM), Random Forest (RF), and XGBoost. The study evaluates the performance by considering multiple software projects like CM1, JM1, KC1, and PC1 using datasets from the PROMISE Software Engineering Repository. The three hybrid models that are compared are Hybrid Model-1 (SVM, RandomForest, XGBoost, Neural Network), Hybrid Model-2 (GradientBoosting, DecisionTree, LogisticRegression, Neural Network), and Hybrid Model-3 (KNeighbors, GaussianNB, Support Vector Classification (SVC), Neural Network), and the Hybrid Model 3 surpasses the others in terms of recall, F1-score, accuracy, ROC AUC, and precision. The presented work offers valuable insights into the effectiveness of hybrid techniques for cross-project defect prediction, providing a comparative perspective on early defect identification and mitigation strategies. .
文摘Introduction: Urethroplasty remains the gold standard for the management of urethral stricture. However, the treatment of stricture disease in the elderly tends to be less invasive due to the presumption that they might not be able to stand long hours of surgery and might have higher rates of recurrence due to poor wound healing from microangiopathy. We present our experience with the outcomes of urethroplasty among elderly men seen at the Komfo Anokye Teaching Hospital from January 2012 to December 2021. Methods: This was a retrospective review of data captured in the urology database on all patients 65 years and above who underwent urethroplasty at the hospital over the study period. Data was obtained on patients’ demographics, stricture characteristics, urethroplasty technique, and outcome. A successful outcome was defined as peak flow rate > 15 mls/s, a patent urethra on retrograde urethrogram, patient satisfaction with urine stream, or restoration of the normal stream of urine with only one attempt at urethral calibration or internal urethrotomy postoperatively. Data was analyzed using PASW Statistics for Windows, Version 18.0. Results: Overall, 43 urethroplasties were done over the study period in elderly men. The age range was 65 to 87 years. The commonest aetiology was catheterization (62.79%) followed by urethritis (32.56%). Stricture length ranged from 0.5 cm to 16 cm with a mean of 3.93 cm. Most patients (60.46%) had bulbar urethral strictures. The repair methods employed were anastomotic urethroplasty (62.80%), fasciocutaneous flap (FCF) ventral onlay (13.95%), buccal mucosa graft (BMG) ventral onlay urethroplasty (4.65%), and staged urethroplasty (4.65%). Three of the patients (6.98%) had a combination of anastomotic and tissue transfer urethroplasty. The overall success rate was 88.37%. Complications included three surgical site infections, two urethral diverticula and one glans dehiscence. Conclusion: Elderly men tolerate urethroplasty well and the procedure should not be denied solely based on age.
文摘In light of the rapid growth and development of social media, it has become the focus of interest in many different scientific fields. They seek to extract useful information from it, and this is called (knowledge), such as extracting information related to people’s behaviors and interactions to analyze feelings or understand the behavior of users or groups, and many others. This extracted knowledge has a very important role in decision-making, creating and improving marketing objectives and competitive advantage, monitoring events, whether political or economic, and development in all fields. Therefore, to extract this knowledge, we need to analyze the vast amount of data found within social media using the most popular data mining techniques and applications related to social media sites.
文摘This thorough review explores the complexities of geotechnical engineering, emphasizing soil-structure interaction (SSI). The investigation centers on sheet pile design, examining two primary methodologies: Limit Equilibrium Methods (LEM) and Soil-Structure Interaction Methods (SSIM). While LEM methods, grounded in classical principles, provide valuable insights for preliminary design considerations, they may encounter limitations in addressing real-world complexities. In contrast, SSIM methods, including the SSI-SR approach, introduce precision and depth to the field. By employing numerical techniques such as Finite Element (FE) and Finite Difference (FD) analyses, these methods enable engineers to navigate the dynamics of soil-structure interaction. The exploration extends to SSI-FE, highlighting its essential role in civil engineering. By integrating Finite Element analysis with considerations for soil-structure interaction, the SSI-FE method offers a holistic understanding of how structures dynamically interact with their geotechnical environment. Throughout this exploration, the study dissects critical components governing SSIM methods, providing engineers with tools to navigate the intricate landscape of geotechnical design. The study acknowledges the significance of the Mohr-Coulomb constitutive model while recognizing its limitations, and guiding practitioners toward informed decision-making in geotechnical analyses. As the article concludes, it underscores the importance of continuous learning and innovation for the future of geotechnical engineering. With advancing technology and an evolving understanding of soil-structure interaction, the study remains committed to ensuring the safety, stability, and efficiency of geotechnical structures through cutting-edge design and analysis techniques.
基金the National Natural Science Foundation of China(No.52072256)Shanxi Science and Technology Major Project(No.20201101016)+1 种基金Key R&D program of Shanxi Province(No.202102030201006)Research Project Supported by Shanxi Scholarship Council of China(HGKY2019031).
文摘Electrocatalytic oxygen reduction reaction(ORR)is one of the most important reactions in electrochemical energy technologies such as fuel cells and metal–O2/air batteries,etc.However,the essential catalysts to overcome its slow reaction kinetic always undergo a complex dynamic evolution in the actual catalytic process,and the concomitant intermediates and catalytic products also occur continuous conversion and reconstruction.This makes them difficult to be accurately captured,making the identification of ORR active sites and the elucidation of ORR mechanisms difficult.Thus,it is necessary to use extensive in-situ characterization techniques to proceed the real-time monitoring of the catalyst structure and the evolution state of intermediates and products during ORR.This work reviews the major advances in the use of various in-situ techniques to characterize the catalytic processes of various catalysts.Specifically,the catalyst structure evolutions revealed directly by in-situ techniques are systematically summarized,such as phase,valence,electronic transfer,coordination,and spin states varies.In-situ revelation of intermediate adsorption/desorption behavior,and the real-time monitoring of the product nucleation,growth,and reconstruction evolution are equally emphasized in the discussion.Other interference factors,as well as in-situ signal assignment with the aid of theoretical calculations,are also covered.Finally,some major challenges and prospects of in-situ techniques for future catalysts research in the ORR process are proposed.
文摘In the world,nonalcoholic fatty liver disease(NAFLD)accounts for majority of diffuse hepatic diseases.Notably,substantial liver fat accumulation can trigger and accelerate hepatic fibrosis,thus contributing to disease progression.Moreover,the presence of NAFLD not only puts adverse influences for liver but is also associated with an increased risk of type 2 diabetes and cardiovascular diseases.Therefore,early detection and quantified measurement of hepatic fat content are of great importance.Liver biopsy is currently the most accurate method for the evaluation of hepatic steatosis.However,liver biopsy has several limitations,namely,its invasiveness,sampling error,high cost and moderate intraobserver and interobserver reproducibility.Recently,various quantitative imaging techniques have been developed for the diagnosis and quantified measurement of hepatic fat content,including ultrasound-or magnetic resonancebased methods.These quantitative imaging techniques can provide objective continuous metrics associated with liver fat content and be recorded for comparison when patients receive check-ups to evaluate changes in liver fat content,which is useful for longitudinal follow-up.In this review,we introduce several imaging techniques and describe their diagnostic performance for the diagnosis and quantified measurement of hepatic fat content.
基金funded by the Shanghai Municipal Science and Technology Major Project(2018SHZDZX01)of Zhang Jiang Laboratory and Shanghai Center for Brain Science and Brain-Inspired TechnologyShanghai Rising Star Program(21QC1400900)Tongji–Westwell Autonomous Vehicle Joint Lab Project。
文摘Through vehicle-to-vehicle(V2V)communication,autonomizing a vehicle platoon can significantly reduce the distance between vehicles,thereby reducing air resistance and improving road traffic efficiency.The gradual maturation of platoon control technology is enabling vehicle platoons to achieve basic driving functions,thereby permitting large-scale vehicle platoon scheduling and planning,which is essential for industrialized platoon applications and generates significant economic benefits.Scheduling and planning are required in many aspects of vehicle platoon operation;here,we outline the advantages and challenges of a number of the most important applications,including platoon formation scheduling,lane-change planning,passing traffic light scheduling,and vehicle resource allocation.This paper’s primary objective is to integrate current independent platoon scheduling and planning techniques into an integrated architecture to meet the demands of large-scale platoon applications.To this end,we first summarize the general techniques of vehicle platoon scheduling and planning,then list the primary scenarios for scheduling and planning technique application,and finally discuss current challenges and future development trends in platoon scheduling and planning.We hope that this paper can encourage related platoon researchers to conduct more systematic research and integrate multiple platoon scheduling and planning technologies and applications.
基金financialy supported by National Key R&D Program of China(2022YFB2402600)the National Natural Science Foundation of China(22279166)+1 种基金the Research Start-up Funds from Sun Yat-Sen University(200306)the Fundamental Research Funds for the Central Universities,Sun Yat-Sen University(22qntd0101 and 22dfx01)
文摘Pseudocapacitive materials that store charges via reversible surface or near-surface faradaic reactions are capable of overcoming the capacity limitations of electrical double-layer capacitors.Revealing the structure–activity relationship between the microstructural features of pseudocapacitive materials and their electrochemical performance on the atomic scale is the key to build high-performance capacitor-type devices containing ideal pseudocapacitance effect.Currently,the high brightness(flux),and spectral and coherent nature of synchrotron X-ray analytical techniques make it a powerful tool for probing the structure–property relationship of pseudocapacitive materials.Herein,we report a comprehensive and systematic review of four typical characterization techniques(synchrotron X-ray diffraction,pair distribution function[PDF]analysis,soft X-ray absorption spectroscopy,and hard X-ray absorption spectroscopy)for the study of pseudocapacitance mechanisms.In addition,we offered significant insights for understanding and identifying pseudocapacitance mechanisms(surface redox pseudocapacitance,intercalation pseudocapacitance,and the extrinsic pseudocapacitance phenomenon in battery materials)by combining in situ hard XAS and electrochemical analyses.Finally,a perspective for further depth of understanding into the pseudocapacitance mechanism using synchrotron X-ray analytical techniques is proposed.
基金supported by the National Natural Science Foundation of China under Grant No.61701284the Innovative Research Foundation of Qingdao under Grant No.19-6-2-1-CG+5 种基金the Elite Plan Project of Shandong University of Science and Technology under Grant No.skr21-3-B-048the Sci.&Tech.Development Fund of Shandong Province of China under Grant Nos.ZR202102230289,ZR202102250695,and ZR2019LZH001the Humanities and Social Science Research Project of the Ministry of Education under Grant No.18YJAZH017the Taishan Scholar Program of Shandong Province,the Shandong Chongqing Science and Technology Cooperation Project under Grant No.cstc2020jscx-lyjsAX0008the Sci.&Tech.Development Fund of Qingdao under Grant No.21-1-5-zlyj-1-zc,SDUST Research Fund under Grant No.2015TDJH102the Science and Technology Support Plan of Youth Innovation Team of Shandong higher School under Grant No.2019KJN024.
文摘With the development of urbanization,the problem of neurological diseases brought about by population aging has gradually become a social problem of worldwide concern.Aging leads to gradual degeneration of the central nervous system,shrinkage of brain tissue,and decline in physical function in many elderlies,making them susceptible to neurological diseases such as Alzheimer’s disease(AD),stroke,Parkinson’s and major depressive disorder(MDD).Due to the influence of these neurological diseases,the elderly have troubles such as memory loss,inability to move,falling,and getting lost,which seriously affect their quality of life.Tracking and positioning of elderly with neurological diseases and keeping track of their location in real-time are necessary and crucial in order to detect and treat dangerous and unexpected situations in time.Considering that the elderly with neurological diseases forget to wear a positioning device or have mobility problems due to carrying a positioning device,device-free positioning as a passive positioning technology that detects device-free individuals is more suitable than traditional active positioning for the home-based care of the elderly with neurological diseases.This paper provides an extensive and in-depth survey of device-free indoor positioning technology for home-based care and an in-depth analysis of the main features of current positioning systems,as well as the techniques,technologies andmethods they employ,fromthe perspective of the needs of the elderly with neurological conditions.Moreover,evaluation criteria and possible solutions of positioning techniques for the home-based care of the elderly with neurological conditions are proposed.Finally,the opportunities and challenges for the development of indoor positioning technology in 6G mobile networks for home-based care of the elderly with neurological diseases are discussed.This review has provided comprehensive and effective tracking and positioning techniques,technologies and methods for the elderly,by which we can obtain the location information of the elderly in real-time and make home-based care more comfortable and safer for the elderly with neurological diseases.
基金the financial support from China Scholarship Council(202108080263)Financial support by the Federal Ministry of Education and Research(BMBF)under the project“He Na”(03XP0390C)+1 种基金the German Research Foundation(DFG)under the joint German-Russian DFG project“KIBSS”(448719339)are acknowledgedthe financial support from the Federal Ministry of Education and Research(BMBF)under the project“Ka Si Li”(03XP0254D)in the competence cluster“Excell Batt Mat”。
文摘Transition metal sulfides have been regarded as promising anode materials for sodium-ion batteries(SIB).However,they face the challenges of poor electronic conductivity and large volume change,which result in capacity fade and low rate capability.In this work,a composite containing ultrasmall CoS(~7 nm)nanoparticles embedded in heteroatom(N,S,and O)-doped carbon was synthesized by an efficient one-step sulfidation process using a Co(Salen)precursor.The ultrasmall CoS nanoparticles are beneficial for mechanical stability and shortening Na-ions diffusion pathways.Furthermore,the N,S,and O-doped defect-rich carbon provides a robust and highly conductive framework enriched with active sites for sodium storage as well as mitigates volume expansion and polysulfide shuttle.As anode for SIB,CoS@HDC exhibits a high initial capacity of 906 mA h g^(-1)at 100 mA g^(-1)and a stable long-term cycling life with over 1000 cycles at 500 mA g^(-1),showing a reversible capacity of 330 mA h g^(-1).Meanwhile,the CoS@HDC anode is proven to maintain its structural integrity and compositional reversibility during cycling.Furthermore,Na-ion full batteries based on the CoS@HDC anode and Na_(3)V_(2)(PO_(4))_(3)cathode demonstrate a stable cycling behavior with a reversible specific capacity of~200 m A h g^(-1)at least for 100 cycles.Moreover,advanced synchrotron operando X-ray diffraction,ex-situ X-ray absorption spectroscopy,and comprehensive electrochemical tests reveal the structural transformation and the Co coordination chemistry evolution of the CoS@HDC during cycling,providing fundamental insights into the sodium storage mechanism.
基金supported by the Singapore Ministry of Education Academic Research Fund Tier 1。
文摘While sufficient review articles exist on inductive short-range wireless power transfer(WPT),long-haul microwave WPT(MWPT)for solar power satellites,and ambient microwave wireless energy harvesting(MWEH)in urban areas,few studies focus on the fundamental modeling and related design automation of receiver systems.This article reviews the development of MWPT and MWEH receivers,with a focus on rectenna design automation.A novel rectifier model capable of accurately modeling the rectification process under both high and low input power is presented.The model reveals the theoretical boundary of radio frequency-to-direct current(dc)power conversion efficiency and,most importantly,enables an automated system design.The automated rectenna design flow is sequential,with the minimal engagement of iterative optimization.It covers the design automation of every module(i.e.,rectifiers,matching circuits,antennae,and dc–dc converters).Scaling-up of the technique to large rectenna arrays is also possible,where the challenges in array partitioning and power combining are briefly discussed.In addition,several cutting-edge rectenna techniques for MWPT and MWEH are reviewed,including the dynamic range extension technique,the harmonics-based retro-directive technique,and the simultaneous wireless information and power transfer technique,which can be good complements to the presented automated design methodology.
文摘A novel model termed a bipolar complex fuzzy N-soft set(BCFN-SS)is initiated for tackling information that involves positive and negative aspects,the second dimension,and parameterised grading simultaneously.The theory of BCFN-SS is the generalisation of two various theories,that is,bipolar complex fuzzy(BCF)and N-SS.The invented model of BCFN-SS helps decision-makers to cope with the genuine-life dilemmas containing BCF information along with parameterised grading at the same time.Further,various algebraic operations,including the usual type of union,intersection,complements,and a few others types,are invented.Certain primary operational laws for BCFNSS are also invented.Moreover,a technique for order preference by similarity to the ideal solution(TOPSIS)approach is devised in the setting of BCFN-SS for managing strategic decision-making(DM)dilemmas containing BCFN-SS information.Keeping in mind the usefulness and benefits of the TOPSIS approach,two various types of TOPSIS approaches in the environment of BCFN-SS are devised and then a numerical example for exposing the usefulness of the devised TOPSIS approach is interpreted.To disclose the prominence and benefits of the devised work,the devised approaches with numerous prevailing work are compared.
基金This work was funded by the Ministry of Higher Education Malaysia under the Fundamental Research Grant Scheme No.FRGS/1/2020/TK0/UNIMAS/03/4.
文摘Residential sector is one of the energy-consuming districts of countries that causes CO_(2)emission in large extent.In this regard,this sector must be considered in energy policy making related to the reduction of emission of CO_(2)and other greenhouse gases.In the present work,CO_(2)emission related to the residential sector of three countries,including Indonesia,Thailand,and Vietnam in Southeast Asia,are discussed and modeled by employing Group Method of Data Handling(GMDH)and Multilayer Perceptron(MLP)neural networks as powerful intelligent methods.Prior to modeling,data related to the energy consumption of these countries are represented,discussed,and analyzed.Subsequently,to propose a model,electricity,natural gas,coal,and oil products consumptions are applied as inputs,and CO_(2)emission is considered as the model’s output.The obtained R^(2) values for the generated models based on MLP and GMDH are 0.9987 and 0.9985,respectively.Furthermore,values of the Average Absolute Relative Deviation(AARD)of the regressions using the mentioned techniques are around 4.56%and 5.53%,respectively.These values reveal significant exactness of the models proposed in this article;however,making use of MLP with the optimal architecture would lead to higher accuracy.
文摘In this era of post-COVID-19,humans are psychologically restricted to interact less with other humans.According to the world health organization(WHO),there are many scenarios where human interactions cause severe multiplication of viruses from human to human and spread worldwide.Most healthcare systems shifted to isolation during the pandemic and a very restricted work environment.Investigations were done to overcome the remedy,and the researcher developed different techniques and recommended solutions.Telepresence robot was the solution achieved by all industries to continue their operations but with almost zero physical interaction with other humans.It played a vital role in this perspective to help humans to perform daily routine tasks.Healthcare workers can use telepresence robots to interact with patients who visit the healthcare center for initial diagnosis for better healthcare system performance without direct interaction.The presented paper aims to compare different telepresence robots and their different controlling techniques to perform the needful in the respective scenario of healthcare environments.This paper comprehensively analyzes and reviews the applications of presented techniques to control different telepresence robots.However,our feature-wise analysis also points to specific technical,appropriate,and ethical challenges that remain to be solved.The proposed investigation summarizes the need for further multifaceted research on the design and impact of a telepresence robot for healthcare centers,building on new perceptions during the COVID-19 pandemic.
基金Supported by Science and Technology Development Project of Jilin Province,No.YDZJ202201ZYTS060。
文摘BACKGROUND Heterotopic pregnancy(HP)is a rare condition in which both ectopic and intrauterine pregnancies occur.HP is uncommon after natural conception but has recently received more attention due to the widespread use of assisted reproductive techniques(ART)such as ovulation promotion therapy.CASE SUMMARY Here,we describe a case of HP that occurred after ART with concurrent tubal and intrauterine singleton pregnancies.This was treated successfully with surgery to preserve the intrauterine pregnancy,resulting in the birth of a low-weight premature infant.This case report aims to increase awareness of the possibility of HP during routine first-trimester ultrasound examinations,especially in pregnancies resulting from ART and even if multiple intrauterine pregnancies are present.CONCLUSION This case alerts us to the importance of comprehensive data collection during regular consultations.It is important for us to remind ourselves of the possibility of HP in all patients presenting after ART,especially in women with an established and stable intrauterine pregnancy that complain of constant abdominal discomfort and also in women with an unusually raised human chorionic gonadotropin level compared with simplex intrauterine pregnancy.This will allow symptomatic and timeous treatment of patients with better results.
基金Science Foundation Ireland(SFI)under Grant Number SFI/16/RC/3918(Confirm)and Marie Sklodowska Curie Grant agreement No.847577 co-fundedthe European Regional Development Fund.Wasif Afzal has received funding from the European Union’s Horizon 2020 research and innovation program under CMC,2023,vol.74,no.22767 Grant agreement Nos.871319,957212from the ECSEL Joint Undertaking(JU)under Grant agreement No 101007350.
文摘Big Data is reforming many industrial domains by providing decision support through analyzing large data volumes.Big Data testing aims to ensure that Big Data systems run smoothly and error-free while maintaining the performance and quality of data.However,because of the diversity and complexity of data,testing Big Data is challenging.Though numerous research efforts deal with Big Data testing,a comprehensive review to address testing techniques and challenges of BigData is not available as yet.Therefore,we have systematically reviewed the Big Data testing techniques’evidence occurring in the period 2010–2021.This paper discusses testing data processing by highlighting the techniques used in every processing phase.Furthermore,we discuss the challenges and future directions.Our findings show that diverse functional,non-functional and combined(functional and non-functional)testing techniques have been used to solve specific problems related to Big Data.At the same time,most of the testing challenges have been faced during the MapReduce validation phase.In addition,the combinatorial testing technique is one of the most applied techniques in combination with other techniques(i.e.,random testing,mutation testing,input space partitioning and equivalence testing)to find various functional faults through Big Data testing.
