BACKGROUND Despite societal guidelines recommending targeted screening for Barrett’s esophagus(BE)and esophageal adenocarcinoma(EAC)in individuals with gastroesophageal reflux symptoms(GERS),screening adherence is su...BACKGROUND Despite societal guidelines recommending targeted screening for Barrett’s esophagus(BE)and esophageal adenocarcinoma(EAC)in individuals with gastroesophageal reflux symptoms(GERS),screening adherence is suboptimal.Current screening approaches fail to identify individuals not seeking medical consultation for GERS or whose GERS are managed with‘over-the-counter’(OTC)acid suppressant therapies.AIM To assess patients’self-management and help-seeking behavior for GERS.METHODS This cross-sectional study collected data from the Dutch general population aged 18-75 years between January and April 2023 using a web-based survey.The survey included questions regarding self-management(e.g.,use of acid suppressant therapy with or without prescription)and help-seeking behavior(e.g.,consulting a primary care provider)for GERS.Simple random sampling was performed to select individuals within the target age group.In total,18156 randomly selected individuals were invited to participate.The study protocol was registered in ClinicalTrials.gov(identifier:NCT05689918).RESULTS Of the 18156 invited individuals,3214 participants(17.7%)completed the survey,of which 1572 participants(48.9%)reported GERS.Of these,904 participants(57.5%)had never consulted a primary care provider for these symptoms,of which 331 participants(36.6%)reported taking OTC acid suppressant therapy in the past six months and 100 participants(11.1%)fulfilled the screening criteria for BE and EAC according to the European Society of Gastrointestinal Endoscopy Guideline.CONCLUSION The population fulfilling the screening criteria for BE and EAC is incompletely identified,suggesting potential underutilization of medical consultation.Raising public awareness of GERS as a risk factor for EAC is needed.展开更多
Improving the quality assurance (QA) processes and acquiring accreditation are top priorities for academic programs. The learning outcomes (LOs)assessment and continuous quality improvement represent core components o...Improving the quality assurance (QA) processes and acquiring accreditation are top priorities for academic programs. The learning outcomes (LOs)assessment and continuous quality improvement represent core components ofthe quality assurance system (QAS). Current assessment methods suffer deficiencies related to accuracy and reliability, and they lack well-organized processes forcontinuous improvement planning. Moreover, the absence of automation, andintegration in QA processes forms a major obstacle towards developing efficientquality system. There is a pressing need to adopt security protocols that providerequired security services to safeguard the valuable information processed byQAS as well. This research proposes an effective methodology for LOs assessment and continuous improvement processes. The proposed approach ensuresmore accurate and reliable LOs assessment results and provides systematic wayfor utilizing those results in the continuous quality improvement. This systematicand well-specified QA processes were then utilized to model and implement automated and secure QAS that efficiently performs quality-related processes. Theproposed system adopts two security protocols that provide confidentiality, integrity, and authentication for quality data and reports. The security protocols avoidthe source repudiation, which is important in the quality reporting system. This isachieved through implementing powerful cryptographic algorithms. The QASenables efficient data collection and processing required for analysis and interpretation. It also prepares for the development of datasets that can be used in futureartificial intelligence (AI) researches to support decision making and improve thequality of academic programs. The proposed approach is implemented in a successful real case study for a computer science program. The current study servesscientific programs struggling to achieve academic accreditation, and gives rise tofully automating and integrating the QA processes and adopting modern AI andsecurity technologies to develop effective QAS.展开更多
Dialects are a specific form of geographic variation of birdsong with relatively sharp boundaries between distinct song characteristics,which provide opportunities for focused studies of processes underlying the emerg...Dialects are a specific form of geographic variation of birdsong with relatively sharp boundaries between distinct song characteristics,which provide opportunities for focused studies of processes underlying the emergence of spatial patterns in vocalization.Several songbird species that exhibit dialects became models for such research,and for some of them large-scale datasets were assembled that included recordings provided by the public.Among them,the Yellowhammer(Emberiza citrinella,Emberizidae) is particularly prominent,as it has been recently a subject of dedicated citizen science projects focusing on its dialect distribution.The most successful,in terms of public participation as well as the number and density of obtained recordings,was the Dialects of Czech Yellowhammers(DCY) project,which assembled detailed data at the whole-country level.A mosaic of almost all common song variants known across Europe was observed in Czechia,but the results indicated that some of the traditionally recognized Yellowhammer dialects may not represent geographically clustered song variants,at least not in Central Europe.We quantitatively analysed variation(frequency and temporal characteristics and modulation) of the terminal song element in three dialects defined by arbitrary frequency thresholds in DCY.Multivariate analyses indicated that pooling these to two distinct groups reflects the variation in the songs,as well as their spatial distribution,better than retaining the current classification to three dialects or their finer splitting to even more categories.We provide simple measures that may be used for classification of these Yellowhammer song variants in Central Europe.However,we warn from indiscriminate transposing of results from one region to another,as that may lead to substantial biases.Future studies of birdsong variation will benefit from big data assembled by citizen scientists,but to maximise their usefulness for further dialect research,careful delineation of dialect boundaries is essential.展开更多
There is a great need to provide educational environments for blind and handicapped people. There are many Islamic websites and applications dedicated to the educational services for the Holy Quran and Its Sciences (Q...There is a great need to provide educational environments for blind and handicapped people. There are many Islamic websites and applications dedicated to the educational services for the Holy Quran and Its Sciences (Quran Recitations, the interpretations, etc.) on the Internet. Unfortunately, blind and handicapped people could not use these services. These people cannot use the keyboard and the mouse. In addition, the ability to read and write is essential to benefit from these services. In this paper, we present an educational environment that allows these people to take full advantage of the scientific materials. This is done through the interaction with the system using voice commands by speaking directly without the need to write or to use the mouse. Google Speech API is used for the universal speech recognition after a preprocessing and post processing phases to improve the accuracy. For blind people, responses of these commands will be played back through the audio device instead of displaying the text to the screen. The text will be displayed on the screen to help other people make use of the system.展开更多
Our study consists of a careful literature review carried out with the aim of better understanding the models developed in the field of biocontrol of postharvest fungal rot in apples(PHFRA)over the past two decades.It...Our study consists of a careful literature review carried out with the aim of better understanding the models developed in the field of biocontrol of postharvest fungal rot in apples(PHFRA)over the past two decades.It aims,more specifically,to shed light on the progress made by examining the products developed,their nature,their target pathogens,their effectiveness,theirs modes of action and the stage of their development.The post-harvest biocontrol of apples has made remarkable progress during the last twenty years of research.Several products(yeasts,bacteria,filamentous fungi and actinomycetes)have been selected.Some,are already marketed,others are at different stages of development.However,several points limit the optimal use of microbial antagonists in the bio-management of post-harvest apple rots as an alternative to chemicals.It is,in fact,still necessary to develop appropriate formulations of these microbial biocontrol agents,to better study their mechanisms of action,to test them under commercial conditions and against a broad spectrum of pathogens and hosts.However,although sometimes considered less effective than chemical treatments,biocontrol products based on microorganisms have major advantages for an application in an integrated post-harvest apple protection strategy.展开更多
Researchers and clinicians have long been interested in the mechanisms of pain,anesthesia,and addiction.The International Association for the Study of Pain(IASP)defines pain as an unpleasant sensory and emotional expe...Researchers and clinicians have long been interested in the mechanisms of pain,anesthesia,and addiction.The International Association for the Study of Pain(IASP)defines pain as an unpleasant sensory and emotional experience associated with,or resembling that associated with,actual or potential tissue damage(Raja et al.,2020).Drug addiction refers to a condition of reliance that develops from regular drug consumption,which may lead to withdrawal symptoms when use is halted.Anesthesia involves the complete loss of consciousness induced by an inhaled or intravenous anesthetic(Tosello et al.,2022).In this special collection,Zoological Research presents research findings focused on pain,addiction,and anesthesia.展开更多
BACKGROUND:This prospective,randomized trial was undertaken to evaluate the utility of adding end-tidal capnometry(ETC)to pulse oximetry(PO)in patients undergoing procedural sedation and analgesia(PSA)in the emergency...BACKGROUND:This prospective,randomized trial was undertaken to evaluate the utility of adding end-tidal capnometry(ETC)to pulse oximetry(PO)in patients undergoing procedural sedation and analgesia(PSA)in the emergency department(ED).METHODS:The patients were randomized to monitoring with or without ETC in addition to the current standard of care.Primary endpoints included respiratory adverse events,with secondary endpoints of level of sedation,hypotension,other PSA-related adverse events and patient satisfaction.RESULTS:Of 986 patients,501 were randomized to usual care and 485 to additional ETC monitoring.In this series,48%of the patients were female,with a mean age of 46 years.Orthopedic manipulations(71%),cardioversion(12%)and abscess incision and drainage(12%)were the most common procedures,and propofol and fentanyl were the sedative/analgesic combination used for most patients.There was no difference in patients experiencing de-saturation(Sa O2<90%)between the two groups;however,patients in the ETC group were more likely to require airway repositioning(12.9%vs.9.3%,P=0.003).Hypotension(SBP<100 mm Hg or<85 mm Hg if baseline<100 mm Hg)was observed in 16(3.3%)patients in the ETC group and 7(1.4%)in the control group(P=0.048).CONCLUSIONS:The addition of ETC does not appear to change any clinically significant outcomes.We found an increased incidence of the use of airway repositioning maneuvers and hypotension in cases where ETC was used.We do not believe that ETC should be recommended as a standard of care for the monitoring of patients undergoing PSA.展开更多
Since its arrival in late November 2022,ChatGPT-3.5 has rapidly gained popularity and significantly impacted how research is planned,conducted,and published using a generative artificial intelligence approach.ChatGPT-...Since its arrival in late November 2022,ChatGPT-3.5 has rapidly gained popularity and significantly impacted how research is planned,conducted,and published using a generative artificial intelligence approach.ChatGPT-4 was released four months later and became more popular in November 2023.However,there is little study about the perception of scientists of these chatbots,especially in soil science.This article presents the new findings of a brief research investigating soil scientists’responses and perceptions towards chatbots in Indonesia.This artificial intelligence application facilitates conversation-based interactions in text format.The study evaluated ten ChatGPT answers to fundamental questions in soil science,which has developed into a normal science with a mutually agreed-upon paradigm.The evaluation was carried out by seven soil scientists recognized for their expertise in Indonesia,using a scale of 1-100.In addition,a questionnaire was distributed to soil scientists at the National Research and Innovation Agency of the Republic of Indonesia(BRIN),universities,and Indonesian Soil Science Society(HITI)members to gauge their perception of ChatGPT’s presence in the research field.The study results indicate that the scores of ChatGPT answers range from 82.99 to 92.24.ChatGPT-4 is better than both the paid and free versions of ChatGPT-3.5.There is no significant difference between the English and Indonesian versions of ChatGPT-4.0.However,the perception of general soil scientists about the level of trust is only 55%.Furthermore,80%of soil scientists believe that chatbots can only be used as digital tools to assist in soil science research and cannot be used without the involvement of soil scientists.展开更多
Security and safety remain paramount concerns for both governments and individuals worldwide.In today’s context,the frequency of crimes and terrorist attacks is alarmingly increasing,becoming increasingly intolerable...Security and safety remain paramount concerns for both governments and individuals worldwide.In today’s context,the frequency of crimes and terrorist attacks is alarmingly increasing,becoming increasingly intolerable to society.Consequently,there is a pressing need for swift identification of potential threats to preemptively alert law enforcement and security forces,thereby preventing potential attacks or violent incidents.Recent advancements in big data analytics and deep learning have significantly enhanced the capabilities of computer vision in object detection,particularly in identifying firearms.This paper introduces a novel automatic firearm detection surveillance system,utilizing a one-stage detection approach named MARIE(Mechanism for Realtime Identification of Firearms).MARIE incorporates the Single Shot Multibox Detector(SSD)model,which has been specifically optimized to balance the speed-accuracy trade-off critical in firearm detection applications.The SSD model was further refined by integrating MobileNetV2 and InceptionV2 architectures for superior feature extraction capabilities.The experimental results demonstrate that this modified SSD configuration provides highly satisfactory performance,surpassing existing methods trained on the same dataset in terms of the critical speedaccuracy trade-off.Through these innovations,MARIE sets a new standard in surveillance technology,offering a robust solution to enhance public safety effectively.展开更多
The joint European Space Agency and Chinese Academy of Sciences Solar wind Magnetosphere Ionosphere Link Explorer(SMILE)mission will explore global dynamics of the magnetosphere under varying solar wind and interplane...The joint European Space Agency and Chinese Academy of Sciences Solar wind Magnetosphere Ionosphere Link Explorer(SMILE)mission will explore global dynamics of the magnetosphere under varying solar wind and interplanetary magnetic field conditions,and simultaneously monitor the auroral response of the Northern Hemisphere ionosphere.Combining these large-scale responses with medium and fine-scale measurements at a variety of cadences by additional ground-based and space-based instruments will enable a much greater scientific impact beyond the original goals of the SMILE mission.Here,we describe current community efforts to prepare for SMILE,and the benefits and context various experiments that have explicitly expressed support for SMILE can offer.A dedicated group of international scientists representing many different experiment types and geographical locations,the Ground-based and Additional Science Working Group,is facilitating these efforts.Preparations include constructing an online SMILE Data Fusion Facility,the discussion of particular or special modes for experiments such as coherent and incoherent scatter radar,and the consideration of particular observing strategies and spacecraft conjunctions.We anticipate growing interest and community engagement with the SMILE mission,and we welcome novel ideas and insights from the solar-terrestrial community.展开更多
Particle Swarm Optimization(PSO)has been utilized as a useful tool for solving intricate optimization problems for various applications in different fields.This paper attempts to carry out an update on PSO and gives a...Particle Swarm Optimization(PSO)has been utilized as a useful tool for solving intricate optimization problems for various applications in different fields.This paper attempts to carry out an update on PSO and gives a review of its recent developments and applications,but also provides arguments for its efficacy in resolving optimization problems in comparison with other algorithms.Covering six strategic areas,which include Data Mining,Machine Learning,Engineering Design,Energy Systems,Healthcare,and Robotics,the study demonstrates the versatility and effectiveness of the PSO.Experimental results are,however,used to show the strong and weak parts of PSO,and performance results are included in tables for ease of comparison.The results stress PSO’s efficiency in providing optimal solutions but also show that there are aspects that need to be improved through combination with algorithms or tuning to the parameters of the method.The review of the advantages and limitations of PSO is intended to provide academics and practitioners with a well-rounded view of the methods of employing such a tool most effectively and to encourage optimized designs of PSO in solving theoretical and practical problems in the future.展开更多
This article presents a detailed theoretical hybrid analysis of the magnetism and the thermal radiative heat transfer in the presence of heat generation affecting the behavior of the dispersed gold nanoparticles(AuNPs...This article presents a detailed theoretical hybrid analysis of the magnetism and the thermal radiative heat transfer in the presence of heat generation affecting the behavior of the dispersed gold nanoparticles(AuNPs)through the blood vessels of the human body.The rheology of gold-blood nanofluid is treated as magnetohydrodynamic(MHD)flow with ferromagnetic properties.The AuNPs take different shapes as bricks,cylinders,and platelets which are considered in changing the nanofluid flow behavior.Physiologically,the blood is circulated under the kinetics of the peristaltic action.The mixed properties of the slip flow,the gravity,the space porosity,the transverse ferromagnetic field,the thermal radiation,the nanoparticles shape factors,the peristaltic amplitude ratio,and the concentration of the AuNPs are interacted and analyzed for the gold-blood circulation in the inclined tube.The appropriate model for the thermal conductivity of the nanofluid is chosen to be the effective Hamilton-Crosser model.The undertaken nanofluid can be treated as incompressible non-Newtonian ferromagnetic fluid.The solutions of the partial differential governing equations of the MHD nanofluid flow are executed by the strategy of perturbation approach under the assumption of long wavelength and low Reynolds number.Graphs for the streamwise velocity distributions,temperature distributions,pressure gradients,pressure drops,and streamlines are presented under the influences of the pertinent properties.The practical implementation of this research finds application in treating cancer through a technique known as photothermal therapy(PTT).The results indicate the control role of the magnetism,the heat generation,the shape factors of the AuNPs,and its concentration on the enhancement of the thermal properties and the streamwise velocity of the nanofluid.The results reveal a marked enhancement in the temperature profiles of the nanofluid,prominently influenced by both the intensified heat source and the heightened volume fractions of the nanoparticles.Furthermore,the platelet shape is regarded as most advantageous for heat conduction owing to its highest effective thermal conductivity.AuNPs proved strong efficiency in delivering and targeting the drug to reach the affected area with tumors.These results offer valuable insights into evaluating the effectiveness of PTT in addressing diverse cancer conditions and regulating their progression.展开更多
Multimodal deep learning has emerged as a key paradigm in contemporary medical diagnostics,advancing precision medicine by enabling integration and learning from diverse data sources.The exponential growth of high-dim...Multimodal deep learning has emerged as a key paradigm in contemporary medical diagnostics,advancing precision medicine by enabling integration and learning from diverse data sources.The exponential growth of high-dimensional healthcare data,encompassing genomic,transcriptomic,and other omics profiles,as well as radiological imaging and histopathological slides,makes this approach increasingly important because,when examined separately,these data sources only offer a fragmented picture of intricate disease processes.Multimodal deep learning leverages the complementary properties of multiple data modalities to enable more accurate prognostic modeling,more robust disease characterization,and improved treatment decision-making.This review provides a comprehensive overview of the current state of multimodal deep learning approaches in medical diagnosis.We classify and examine important application domains,such as(1)radiology,where automated report generation and lesion detection are facilitated by image-text integration;(2)histopathology,where fusion models improve tumor classification and grading;and(3)multi-omics,where molecular subtypes and latent biomarkers are revealed through cross-modal learning.We provide an overview of representative research,methodological advancements,and clinical consequences for each domain.Additionally,we critically analyzed the fundamental issues preventing wider adoption,including computational complexity(particularly in training scalable,multi-branch networks),data heterogeneity(resulting from modality-specific noise,resolution variations,and inconsistent annotations),and the challenge of maintaining significant cross-modal correlations during fusion.These problems impede interpretability,which is crucial for clinical trust and use,in addition to performance and generalizability.Lastly,we outline important areas for future research,including the development of standardized protocols for harmonizing data,the creation of lightweight and interpretable fusion architectures,the integration of real-time clinical decision support systems,and the promotion of cooperation for federated multimodal learning.Our goal is to provide researchers and clinicians with a concise overview of the field’s present state,enduring constraints,and exciting directions for further research through this review.展开更多
The Internet of Things(IoT)has gained substantial attention in both academic research and real-world applications.The proliferation of interconnected devices across various domains promises to deliver intelligent and ...The Internet of Things(IoT)has gained substantial attention in both academic research and real-world applications.The proliferation of interconnected devices across various domains promises to deliver intelligent and advanced services.However,this rapid expansion also heightens the vulnerability of the IoT ecosystem to security threats.Consequently,innovative solutions capable of effectively mitigating risks while accommodating the unique constraints of IoT environments are urgently needed.Recently,the convergence of Blockchain technology and IoT has introduced a decentralized and robust framework for securing data and interactions,commonly referred to as the Internet of Blockchained Things(IoBT).Extensive research efforts have been devoted to adapting Blockchain technology to meet the specific requirements of IoT deployments.Within this context,consensus algorithms play a critical role in assessing the feasibility of integrating Blockchain into IoT ecosystems.The adoption of efficient and lightweight consensus mechanisms for block validation has become increasingly essential.This paper presents a comprehensive examination of lightweight,constraint-aware consensus algorithms tailored for IoBT.The study categorizes these consensus mechanisms based on their core operations,the security of the block validation process,the incorporation of AI techniques,and the specific applications they are designed to support.展开更多
This paper introduces the Integrated Security Embedded Resilience Architecture (ISERA) as an advanced resilience mechanism for Industrial Control Systems (ICS) and Operational Technology (OT) environments. The ISERA f...This paper introduces the Integrated Security Embedded Resilience Architecture (ISERA) as an advanced resilience mechanism for Industrial Control Systems (ICS) and Operational Technology (OT) environments. The ISERA framework integrates security by design principles, micro-segmentation, and Island Mode Operation (IMO) to enhance cyber resilience and ensure continuous, secure operations. The methodology deploys a Forward-Thinking Architecture Strategy (FTAS) algorithm, which utilises an industrial Intrusion Detection System (IDS) implemented with Python’s Network Intrusion Detection System (NIDS) library. The FTAS algorithm successfully identified and responded to cyber-attacks, ensuring minimal system disruption. ISERA has been validated through comprehensive testing scenarios simulating Denial of Service (DoS) attacks and malware intrusions, at both the IT and OT layers where it successfully mitigates the impact of malicious activity. Results demonstrate ISERA’s efficacy in real-time threat detection, containment, and incident response, thus ensuring the integrity and reliability of critical infrastructure systems. ISERA’s decentralised approach contributes to global net zero goals by optimising resource use and minimising environmental impact. By adopting a decentralised control architecture and leveraging virtualisation, ISERA significantly enhances the cyber resilience and sustainability of critical infrastructure systems. This approach not only strengthens defences against evolving cyber threats but also optimises resource allocation, reducing the system’s carbon footprint. As a result, ISERA ensures the uninterrupted operation of essential services while contributing to broader net zero goals.展开更多
The development of efficient,cost-effective catalysts for the oxygen reduction reaction(ORR)is crucial for advancing zinc-air batteries(ZABs).This study presents Fe_(4)N nanoparticles embedded in N-doped carbon nanofi...The development of efficient,cost-effective catalysts for the oxygen reduction reaction(ORR)is crucial for advancing zinc-air batteries(ZABs).This study presents Fe_(4)N nanoparticles embedded in N-doped carbon nanofibers(Fe_(4)N@CNF-NH_(3))as a highly efficient ORR catalyst.The Fe_(4)N@CNF-NH_(3)catalyst was synthesized via electrospinning,followed by high-temperature annealing in an NH_(3)atmosphere.This electrospinning technique ensured the uniform dispersion of Fe_(4)N nanoparticles within the carbon nanofibers(CNFs),preventing agglomeration and enhancing the availability of active sites.Structural and morphological analyses confirmed the formation of Fe_(4)N nanoparticles with a lattice spacing of 0.213 nm,surrounded by graphitic carbon structures that significantly improved the material’s conductivity and stability.Electrochemical tests demonstrated that Fe_(4)N@CNF-NH_(3)exhibited superior ORR activity,with a half-wave potential of 0.904 V,surpassing that of commercial Pt/C catalysts.This enhanced performance is attributed to the synergistic effects of Fe_(4)N nanoparticles and the conductive carbon framework,which facilitated efficient charge and mass transfer during the ORR process.Density functional theory calculations further revealed that the introduction of CNFs positively shifted the d-band center of Fe atoms,optimizing oxygen intermediate adsorption and lowering energy barriers for ORR.The practical applicability of Fe_(4)N@CNF-NH_(3)was validated through the assembly of both liquid-state and solid-state ZABs,which exhibited excellent cycling stability,high power density,and superior discharge voltage.This study offers a promising strategy for developing highly active,low-cost ORR catalysts and advances the potential for the commercialization of ZABs.展开更多
文摘BACKGROUND Despite societal guidelines recommending targeted screening for Barrett’s esophagus(BE)and esophageal adenocarcinoma(EAC)in individuals with gastroesophageal reflux symptoms(GERS),screening adherence is suboptimal.Current screening approaches fail to identify individuals not seeking medical consultation for GERS or whose GERS are managed with‘over-the-counter’(OTC)acid suppressant therapies.AIM To assess patients’self-management and help-seeking behavior for GERS.METHODS This cross-sectional study collected data from the Dutch general population aged 18-75 years between January and April 2023 using a web-based survey.The survey included questions regarding self-management(e.g.,use of acid suppressant therapy with or without prescription)and help-seeking behavior(e.g.,consulting a primary care provider)for GERS.Simple random sampling was performed to select individuals within the target age group.In total,18156 randomly selected individuals were invited to participate.The study protocol was registered in ClinicalTrials.gov(identifier:NCT05689918).RESULTS Of the 18156 invited individuals,3214 participants(17.7%)completed the survey,of which 1572 participants(48.9%)reported GERS.Of these,904 participants(57.5%)had never consulted a primary care provider for these symptoms,of which 331 participants(36.6%)reported taking OTC acid suppressant therapy in the past six months and 100 participants(11.1%)fulfilled the screening criteria for BE and EAC according to the European Society of Gastrointestinal Endoscopy Guideline.CONCLUSION The population fulfilling the screening criteria for BE and EAC is incompletely identified,suggesting potential underutilization of medical consultation.Raising public awareness of GERS as a risk factor for EAC is needed.
基金Author extends his appreciation to the Deanship of Scientific Research at Imam Mohammad Ibn Saud Islamic University for funding and supporting this work through Graduate Student Research Support Program.
文摘Improving the quality assurance (QA) processes and acquiring accreditation are top priorities for academic programs. The learning outcomes (LOs)assessment and continuous quality improvement represent core components ofthe quality assurance system (QAS). Current assessment methods suffer deficiencies related to accuracy and reliability, and they lack well-organized processes forcontinuous improvement planning. Moreover, the absence of automation, andintegration in QA processes forms a major obstacle towards developing efficientquality system. There is a pressing need to adopt security protocols that providerequired security services to safeguard the valuable information processed byQAS as well. This research proposes an effective methodology for LOs assessment and continuous improvement processes. The proposed approach ensuresmore accurate and reliable LOs assessment results and provides systematic wayfor utilizing those results in the continuous quality improvement. This systematicand well-specified QA processes were then utilized to model and implement automated and secure QAS that efficiently performs quality-related processes. Theproposed system adopts two security protocols that provide confidentiality, integrity, and authentication for quality data and reports. The security protocols avoidthe source repudiation, which is important in the quality reporting system. This isachieved through implementing powerful cryptographic algorithms. The QASenables efficient data collection and processing required for analysis and interpretation. It also prepares for the development of datasets that can be used in futureartificial intelligence (AI) researches to support decision making and improve thequality of academic programs. The proposed approach is implemented in a successful real case study for a computer science program. The current study servesscientific programs struggling to achieve academic accreditation, and gives rise tofully automating and integrating the QA processes and adopting modern AI andsecurity technologies to develop effective QAS.
基金funded by the Charles University Grant Agency (project number 312213)
文摘Dialects are a specific form of geographic variation of birdsong with relatively sharp boundaries between distinct song characteristics,which provide opportunities for focused studies of processes underlying the emergence of spatial patterns in vocalization.Several songbird species that exhibit dialects became models for such research,and for some of them large-scale datasets were assembled that included recordings provided by the public.Among them,the Yellowhammer(Emberiza citrinella,Emberizidae) is particularly prominent,as it has been recently a subject of dedicated citizen science projects focusing on its dialect distribution.The most successful,in terms of public participation as well as the number and density of obtained recordings,was the Dialects of Czech Yellowhammers(DCY) project,which assembled detailed data at the whole-country level.A mosaic of almost all common song variants known across Europe was observed in Czechia,but the results indicated that some of the traditionally recognized Yellowhammer dialects may not represent geographically clustered song variants,at least not in Central Europe.We quantitatively analysed variation(frequency and temporal characteristics and modulation) of the terminal song element in three dialects defined by arbitrary frequency thresholds in DCY.Multivariate analyses indicated that pooling these to two distinct groups reflects the variation in the songs,as well as their spatial distribution,better than retaining the current classification to three dialects or their finer splitting to even more categories.We provide simple measures that may be used for classification of these Yellowhammer song variants in Central Europe.However,we warn from indiscriminate transposing of results from one region to another,as that may lead to substantial biases.Future studies of birdsong variation will benefit from big data assembled by citizen scientists,but to maximise their usefulness for further dialect research,careful delineation of dialect boundaries is essential.
文摘There is a great need to provide educational environments for blind and handicapped people. There are many Islamic websites and applications dedicated to the educational services for the Holy Quran and Its Sciences (Quran Recitations, the interpretations, etc.) on the Internet. Unfortunately, blind and handicapped people could not use these services. These people cannot use the keyboard and the mouse. In addition, the ability to read and write is essential to benefit from these services. In this paper, we present an educational environment that allows these people to take full advantage of the scientific materials. This is done through the interaction with the system using voice commands by speaking directly without the need to write or to use the mouse. Google Speech API is used for the universal speech recognition after a preprocessing and post processing phases to improve the accuracy. For blind people, responses of these commands will be played back through the audio device instead of displaying the text to the screen. The text will be displayed on the screen to help other people make use of the system.
文摘Our study consists of a careful literature review carried out with the aim of better understanding the models developed in the field of biocontrol of postharvest fungal rot in apples(PHFRA)over the past two decades.It aims,more specifically,to shed light on the progress made by examining the products developed,their nature,their target pathogens,their effectiveness,theirs modes of action and the stage of their development.The post-harvest biocontrol of apples has made remarkable progress during the last twenty years of research.Several products(yeasts,bacteria,filamentous fungi and actinomycetes)have been selected.Some,are already marketed,others are at different stages of development.However,several points limit the optimal use of microbial antagonists in the bio-management of post-harvest apple rots as an alternative to chemicals.It is,in fact,still necessary to develop appropriate formulations of these microbial biocontrol agents,to better study their mechanisms of action,to test them under commercial conditions and against a broad spectrum of pathogens and hosts.However,although sometimes considered less effective than chemical treatments,biocontrol products based on microorganisms have major advantages for an application in an integrated post-harvest apple protection strategy.
文摘Researchers and clinicians have long been interested in the mechanisms of pain,anesthesia,and addiction.The International Association for the Study of Pain(IASP)defines pain as an unpleasant sensory and emotional experience associated with,or resembling that associated with,actual or potential tissue damage(Raja et al.,2020).Drug addiction refers to a condition of reliance that develops from regular drug consumption,which may lead to withdrawal symptoms when use is halted.Anesthesia involves the complete loss of consciousness induced by an inhaled or intravenous anesthetic(Tosello et al.,2022).In this special collection,Zoological Research presents research findings focused on pain,addiction,and anesthesia.
基金supported by a grant from the Capital Health Research FundHalifax+1 种基金Nova ScotiaCanada
文摘BACKGROUND:This prospective,randomized trial was undertaken to evaluate the utility of adding end-tidal capnometry(ETC)to pulse oximetry(PO)in patients undergoing procedural sedation and analgesia(PSA)in the emergency department(ED).METHODS:The patients were randomized to monitoring with or without ETC in addition to the current standard of care.Primary endpoints included respiratory adverse events,with secondary endpoints of level of sedation,hypotension,other PSA-related adverse events and patient satisfaction.RESULTS:Of 986 patients,501 were randomized to usual care and 485 to additional ETC monitoring.In this series,48%of the patients were female,with a mean age of 46 years.Orthopedic manipulations(71%),cardioversion(12%)and abscess incision and drainage(12%)were the most common procedures,and propofol and fentanyl were the sedative/analgesic combination used for most patients.There was no difference in patients experiencing de-saturation(Sa O2<90%)between the two groups;however,patients in the ETC group were more likely to require airway repositioning(12.9%vs.9.3%,P=0.003).Hypotension(SBP<100 mm Hg or<85 mm Hg if baseline<100 mm Hg)was observed in 16(3.3%)patients in the ETC group and 7(1.4%)in the control group(P=0.048).CONCLUSIONS:The addition of ETC does not appear to change any clinically significant outcomes.We found an increased incidence of the use of airway repositioning maneuvers and hypotension in cases where ETC was used.We do not believe that ETC should be recommended as a standard of care for the monitoring of patients undergoing PSA.
文摘Since its arrival in late November 2022,ChatGPT-3.5 has rapidly gained popularity and significantly impacted how research is planned,conducted,and published using a generative artificial intelligence approach.ChatGPT-4 was released four months later and became more popular in November 2023.However,there is little study about the perception of scientists of these chatbots,especially in soil science.This article presents the new findings of a brief research investigating soil scientists’responses and perceptions towards chatbots in Indonesia.This artificial intelligence application facilitates conversation-based interactions in text format.The study evaluated ten ChatGPT answers to fundamental questions in soil science,which has developed into a normal science with a mutually agreed-upon paradigm.The evaluation was carried out by seven soil scientists recognized for their expertise in Indonesia,using a scale of 1-100.In addition,a questionnaire was distributed to soil scientists at the National Research and Innovation Agency of the Republic of Indonesia(BRIN),universities,and Indonesian Soil Science Society(HITI)members to gauge their perception of ChatGPT’s presence in the research field.The study results indicate that the scores of ChatGPT answers range from 82.99 to 92.24.ChatGPT-4 is better than both the paid and free versions of ChatGPT-3.5.There is no significant difference between the English and Indonesian versions of ChatGPT-4.0.However,the perception of general soil scientists about the level of trust is only 55%.Furthermore,80%of soil scientists believe that chatbots can only be used as digital tools to assist in soil science research and cannot be used without the involvement of soil scientists.
文摘Security and safety remain paramount concerns for both governments and individuals worldwide.In today’s context,the frequency of crimes and terrorist attacks is alarmingly increasing,becoming increasingly intolerable to society.Consequently,there is a pressing need for swift identification of potential threats to preemptively alert law enforcement and security forces,thereby preventing potential attacks or violent incidents.Recent advancements in big data analytics and deep learning have significantly enhanced the capabilities of computer vision in object detection,particularly in identifying firearms.This paper introduces a novel automatic firearm detection surveillance system,utilizing a one-stage detection approach named MARIE(Mechanism for Realtime Identification of Firearms).MARIE incorporates the Single Shot Multibox Detector(SSD)model,which has been specifically optimized to balance the speed-accuracy trade-off critical in firearm detection applications.The SSD model was further refined by integrating MobileNetV2 and InceptionV2 architectures for superior feature extraction capabilities.The experimental results demonstrate that this modified SSD configuration provides highly satisfactory performance,surpassing existing methods trained on the same dataset in terms of the critical speedaccuracy trade-off.Through these innovations,MARIE sets a new standard in surveillance technology,offering a robust solution to enhance public safety effectively.
基金supported by Royal Society grant DHFR1211068funded by UKSA+14 种基金STFCSTFC grant ST/M001083/1funded by STFC grant ST/W00089X/1supported by NERC grant NE/W003309/1(E3d)funded by NERC grant NE/V000748/1support from NERC grants NE/V015133/1,NE/R016038/1(BAS magnetometers),and grants NE/R01700X/1 and NE/R015848/1(EISCAT)supported by NERC grant NE/T000937/1NSFC grants 42174208 and 41821003supported by the Research Council of Norway grant 223252PRODEX arrangement 4000123238 from the European Space Agencysupport of the AUTUMN East-West magnetometer network by the Canadian Space Agencysupported by NASA’s Heliophysics U.S.Participating Investigator Programsupport from grant NSF AGS 2027210supported by grant Dnr:2020-00106 from the Swedish National Space Agencysupported by the German Research Foundation(DFG)under number KR 4375/2-1 within SPP"Dynamic Earth"。
文摘The joint European Space Agency and Chinese Academy of Sciences Solar wind Magnetosphere Ionosphere Link Explorer(SMILE)mission will explore global dynamics of the magnetosphere under varying solar wind and interplanetary magnetic field conditions,and simultaneously monitor the auroral response of the Northern Hemisphere ionosphere.Combining these large-scale responses with medium and fine-scale measurements at a variety of cadences by additional ground-based and space-based instruments will enable a much greater scientific impact beyond the original goals of the SMILE mission.Here,we describe current community efforts to prepare for SMILE,and the benefits and context various experiments that have explicitly expressed support for SMILE can offer.A dedicated group of international scientists representing many different experiment types and geographical locations,the Ground-based and Additional Science Working Group,is facilitating these efforts.Preparations include constructing an online SMILE Data Fusion Facility,the discussion of particular or special modes for experiments such as coherent and incoherent scatter radar,and the consideration of particular observing strategies and spacecraft conjunctions.We anticipate growing interest and community engagement with the SMILE mission,and we welcome novel ideas and insights from the solar-terrestrial community.
文摘Particle Swarm Optimization(PSO)has been utilized as a useful tool for solving intricate optimization problems for various applications in different fields.This paper attempts to carry out an update on PSO and gives a review of its recent developments and applications,but also provides arguments for its efficacy in resolving optimization problems in comparison with other algorithms.Covering six strategic areas,which include Data Mining,Machine Learning,Engineering Design,Energy Systems,Healthcare,and Robotics,the study demonstrates the versatility and effectiveness of the PSO.Experimental results are,however,used to show the strong and weak parts of PSO,and performance results are included in tables for ease of comparison.The results stress PSO’s efficiency in providing optimal solutions but also show that there are aspects that need to be improved through combination with algorithms or tuning to the parameters of the method.The review of the advantages and limitations of PSO is intended to provide academics and practitioners with a well-rounded view of the methods of employing such a tool most effectively and to encourage optimized designs of PSO in solving theoretical and practical problems in the future.
文摘This article presents a detailed theoretical hybrid analysis of the magnetism and the thermal radiative heat transfer in the presence of heat generation affecting the behavior of the dispersed gold nanoparticles(AuNPs)through the blood vessels of the human body.The rheology of gold-blood nanofluid is treated as magnetohydrodynamic(MHD)flow with ferromagnetic properties.The AuNPs take different shapes as bricks,cylinders,and platelets which are considered in changing the nanofluid flow behavior.Physiologically,the blood is circulated under the kinetics of the peristaltic action.The mixed properties of the slip flow,the gravity,the space porosity,the transverse ferromagnetic field,the thermal radiation,the nanoparticles shape factors,the peristaltic amplitude ratio,and the concentration of the AuNPs are interacted and analyzed for the gold-blood circulation in the inclined tube.The appropriate model for the thermal conductivity of the nanofluid is chosen to be the effective Hamilton-Crosser model.The undertaken nanofluid can be treated as incompressible non-Newtonian ferromagnetic fluid.The solutions of the partial differential governing equations of the MHD nanofluid flow are executed by the strategy of perturbation approach under the assumption of long wavelength and low Reynolds number.Graphs for the streamwise velocity distributions,temperature distributions,pressure gradients,pressure drops,and streamlines are presented under the influences of the pertinent properties.The practical implementation of this research finds application in treating cancer through a technique known as photothermal therapy(PTT).The results indicate the control role of the magnetism,the heat generation,the shape factors of the AuNPs,and its concentration on the enhancement of the thermal properties and the streamwise velocity of the nanofluid.The results reveal a marked enhancement in the temperature profiles of the nanofluid,prominently influenced by both the intensified heat source and the heightened volume fractions of the nanoparticles.Furthermore,the platelet shape is regarded as most advantageous for heat conduction owing to its highest effective thermal conductivity.AuNPs proved strong efficiency in delivering and targeting the drug to reach the affected area with tumors.These results offer valuable insights into evaluating the effectiveness of PTT in addressing diverse cancer conditions and regulating their progression.
文摘Multimodal deep learning has emerged as a key paradigm in contemporary medical diagnostics,advancing precision medicine by enabling integration and learning from diverse data sources.The exponential growth of high-dimensional healthcare data,encompassing genomic,transcriptomic,and other omics profiles,as well as radiological imaging and histopathological slides,makes this approach increasingly important because,when examined separately,these data sources only offer a fragmented picture of intricate disease processes.Multimodal deep learning leverages the complementary properties of multiple data modalities to enable more accurate prognostic modeling,more robust disease characterization,and improved treatment decision-making.This review provides a comprehensive overview of the current state of multimodal deep learning approaches in medical diagnosis.We classify and examine important application domains,such as(1)radiology,where automated report generation and lesion detection are facilitated by image-text integration;(2)histopathology,where fusion models improve tumor classification and grading;and(3)multi-omics,where molecular subtypes and latent biomarkers are revealed through cross-modal learning.We provide an overview of representative research,methodological advancements,and clinical consequences for each domain.Additionally,we critically analyzed the fundamental issues preventing wider adoption,including computational complexity(particularly in training scalable,multi-branch networks),data heterogeneity(resulting from modality-specific noise,resolution variations,and inconsistent annotations),and the challenge of maintaining significant cross-modal correlations during fusion.These problems impede interpretability,which is crucial for clinical trust and use,in addition to performance and generalizability.Lastly,we outline important areas for future research,including the development of standardized protocols for harmonizing data,the creation of lightweight and interpretable fusion architectures,the integration of real-time clinical decision support systems,and the promotion of cooperation for federated multimodal learning.Our goal is to provide researchers and clinicians with a concise overview of the field’s present state,enduring constraints,and exciting directions for further research through this review.
文摘The Internet of Things(IoT)has gained substantial attention in both academic research and real-world applications.The proliferation of interconnected devices across various domains promises to deliver intelligent and advanced services.However,this rapid expansion also heightens the vulnerability of the IoT ecosystem to security threats.Consequently,innovative solutions capable of effectively mitigating risks while accommodating the unique constraints of IoT environments are urgently needed.Recently,the convergence of Blockchain technology and IoT has introduced a decentralized and robust framework for securing data and interactions,commonly referred to as the Internet of Blockchained Things(IoBT).Extensive research efforts have been devoted to adapting Blockchain technology to meet the specific requirements of IoT deployments.Within this context,consensus algorithms play a critical role in assessing the feasibility of integrating Blockchain into IoT ecosystems.The adoption of efficient and lightweight consensus mechanisms for block validation has become increasingly essential.This paper presents a comprehensive examination of lightweight,constraint-aware consensus algorithms tailored for IoBT.The study categorizes these consensus mechanisms based on their core operations,the security of the block validation process,the incorporation of AI techniques,and the specific applications they are designed to support.
基金funded by the Office of Gas and Electricity Markets(Ofgem)and supported by De Montfort University(DMU)and Nottingham Trent University(NTU),UK.
文摘This paper introduces the Integrated Security Embedded Resilience Architecture (ISERA) as an advanced resilience mechanism for Industrial Control Systems (ICS) and Operational Technology (OT) environments. The ISERA framework integrates security by design principles, micro-segmentation, and Island Mode Operation (IMO) to enhance cyber resilience and ensure continuous, secure operations. The methodology deploys a Forward-Thinking Architecture Strategy (FTAS) algorithm, which utilises an industrial Intrusion Detection System (IDS) implemented with Python’s Network Intrusion Detection System (NIDS) library. The FTAS algorithm successfully identified and responded to cyber-attacks, ensuring minimal system disruption. ISERA has been validated through comprehensive testing scenarios simulating Denial of Service (DoS) attacks and malware intrusions, at both the IT and OT layers where it successfully mitigates the impact of malicious activity. Results demonstrate ISERA’s efficacy in real-time threat detection, containment, and incident response, thus ensuring the integrity and reliability of critical infrastructure systems. ISERA’s decentralised approach contributes to global net zero goals by optimising resource use and minimising environmental impact. By adopting a decentralised control architecture and leveraging virtualisation, ISERA significantly enhances the cyber resilience and sustainability of critical infrastructure systems. This approach not only strengthens defences against evolving cyber threats but also optimises resource allocation, reducing the system’s carbon footprint. As a result, ISERA ensures the uninterrupted operation of essential services while contributing to broader net zero goals.
基金supported by the National Natural Science Foundation of China(No.11904208the Project of Shandong Province Higher Educational Science and Technology Program(No.J18KB098).
文摘The development of efficient,cost-effective catalysts for the oxygen reduction reaction(ORR)is crucial for advancing zinc-air batteries(ZABs).This study presents Fe_(4)N nanoparticles embedded in N-doped carbon nanofibers(Fe_(4)N@CNF-NH_(3))as a highly efficient ORR catalyst.The Fe_(4)N@CNF-NH_(3)catalyst was synthesized via electrospinning,followed by high-temperature annealing in an NH_(3)atmosphere.This electrospinning technique ensured the uniform dispersion of Fe_(4)N nanoparticles within the carbon nanofibers(CNFs),preventing agglomeration and enhancing the availability of active sites.Structural and morphological analyses confirmed the formation of Fe_(4)N nanoparticles with a lattice spacing of 0.213 nm,surrounded by graphitic carbon structures that significantly improved the material’s conductivity and stability.Electrochemical tests demonstrated that Fe_(4)N@CNF-NH_(3)exhibited superior ORR activity,with a half-wave potential of 0.904 V,surpassing that of commercial Pt/C catalysts.This enhanced performance is attributed to the synergistic effects of Fe_(4)N nanoparticles and the conductive carbon framework,which facilitated efficient charge and mass transfer during the ORR process.Density functional theory calculations further revealed that the introduction of CNFs positively shifted the d-band center of Fe atoms,optimizing oxygen intermediate adsorption and lowering energy barriers for ORR.The practical applicability of Fe_(4)N@CNF-NH_(3)was validated through the assembly of both liquid-state and solid-state ZABs,which exhibited excellent cycling stability,high power density,and superior discharge voltage.This study offers a promising strategy for developing highly active,low-cost ORR catalysts and advances the potential for the commercialization of ZABs.
