Lead chalcohalides(PbYX,X=Cl,Br,I;Y=S,Se)is an extension of the classic Pb chalcogenides(PbY).Constructing the heterogeneous integration with PbYX and PbY material systems makes it possible to achieve significantly im...Lead chalcohalides(PbYX,X=Cl,Br,I;Y=S,Se)is an extension of the classic Pb chalcogenides(PbY).Constructing the heterogeneous integration with PbYX and PbY material systems makes it possible to achieve significantly improved optoelectronic performance.In this work,we studied the effect of introducing halogen precursors on the structure of classical PbS nanocrystals(NCs)during the synthesis process and realized the preparation of PbS/Pb_(3)S_(2)X_(2) core/shell structure for the first time.The core/shell structure can effectively improve their optical properties.Furthermore,our approach enables the synthesis of Pb_(3)S_(2)Br_(2) that had not yet been reported.Our results not only provide valuable insights into the heterogeneous integration of PbYX and PbY materials to elevate material properties but also provide an effective method for further expanding the preparation of PbYX material systems.展开更多
Anomaly detection in wind turbines involves emphasizing its ability to improve operational efficiency,reduce maintenance costs,extend their lifespan,and enhance reliability in the wind energy sector.This is particular...Anomaly detection in wind turbines involves emphasizing its ability to improve operational efficiency,reduce maintenance costs,extend their lifespan,and enhance reliability in the wind energy sector.This is particularly necessary in offshore wind,currently one of the most critical assets for achieving sustainable energy generation goals,due to the harsh marine environment and the difficulty of maintenance tasks.To address this problem,this work proposes a data-driven methodology for detecting power generation anomalies in offshore wind turbines,using normalized and linearized operational data.The proposed framework transforms heterogeneous wind speed and power measurements into a unified scale,enabling the development of a new wind power index(WPi)that quantifies deviations from expected performance.Additionally,spatial and temporal coherence analyses of turbines within a wind farm ensure the validity of these normalized measurements across different wind turbine models and operating conditions.Furthermore,a Support Vector Machine(SVM)refines the classification process,effectively distinguishing measurement errors from actual power generation failures.Validation of this strategy using real-world data from the Alpha Ventus wind farm demonstrates that the proposed approach not only improves predictive maintenance but also optimizes energy production,highlighting its potential for broad application in offshore wind installations.展开更多
Recent advances in all-inorganic perovskite semiconductors have garnered significant research interest due to their potential for high-performance optoelectronic devices and enhanced stability under harsh environmenta...Recent advances in all-inorganic perovskite semiconductors have garnered significant research interest due to their potential for high-performance optoelectronic devices and enhanced stability under harsh environmental conditions.A deeper understanding of their structural,chemical,and physical properties has driven notable progress in addressing challenges related to electrical characteristics,reproducibility,and long-term operational stability in perovskite-based memristors.These advancements have been realized through composition engineering,dimensionality modulation,thin-film processing,and device optimization.This review concisely summarizes recent developments in all-inorganic perovskite memristors,highlighting their diverse material properties,device performance,and applications in artificial synapses and logic operations.We discuss key resistance-switching mechanisms,optimization strategies,and operational capabilities while outlining remaining challenges and future directions for perovskitebased memory technologies.展开更多
Quantum information processing and communication(QIPC) is an area of science that has two main goals: On one side,it tries to explore(still not well known) potential of quantum phenomena for(efficient and reliable) in...Quantum information processing and communication(QIPC) is an area of science that has two main goals: On one side,it tries to explore(still not well known) potential of quantum phenomena for(efficient and reliable) information processing and(efficient,reliable and secure) communication.On the other side,it tries to use quantum information storing,processing and transmitting paradigms,principles,laws,limitations,concepts,models and tools to get deeper insights into the phenomena of quantum world and to find efficient ways to describe and handle/simulate various complex physical phenomena.In order to do that QIPC has to use concepts,models,theories,methods and tools of both physics and informatics.The main role of physics at that is to discover primitive physical phenomena that can be used to design and maintain complex and reliable information storing,processing and transmitting systems.The main role of informatics is,one one side,to explore,from the information processing and communication point of view,limitations and potentials of the potential quantum information processing and communication technology,and to prepare information processing methods that could utilise potential of quantum information processing and communication technologies.On the other side,the main role of informatics is to guide and support,by theoretical tools and outcomes,physics oriented research in QIPC.The paper is to describe and analyse a variety of ways and potential informatics contributes and should/could contribute to the development of QIPC--see also Gruska(1999,2006,2008).展开更多
THE Lebanese wireless device explosion incident has drawn widespread attention,involving devices such as pagers,walkie-talkies,and other common devices[1].This event has revealed and highlighted the security vulnerabi...THE Lebanese wireless device explosion incident has drawn widespread attention,involving devices such as pagers,walkie-talkies,and other common devices[1].This event has revealed and highlighted the security vulnerabilities in global supply chains from raw material manufacturing and distribution to the usage of devices and equipment,signaling the onset of a new wave of"supply chain warfare"[2].展开更多
Despite all efforts,long-term changes in the adult sex ratios of breeding duck populations are still unclear;this uncertainty is especially true for male-bias populations,which are often under the scrutiny of research...Despite all efforts,long-term changes in the adult sex ratios of breeding duck populations are still unclear;this uncertainty is especially true for male-bias populations,which are often under the scrutiny of researchers lacking convenient results for the active protection of endangered species.Species with male-bias populations are usually strongly affected by a decline in population size that leads to a higher extinction risk.In this study,we examined our long-term data of the abundance of breeding populations in six duck species(Mallard Anas platyrhynchos,Gadwall Mareca strepera,Red-crested Pochard Netta rufina,Common Pochard Aythya ferina,Tufted Duck Aythya fuligula,and Common Goldeneye Bucephala clangula)from fishponds in South Bohemia,Czechia,between 2004 and 2022.This evidence was used to assess long-term changes in the adult sex ratio in these breeding populations and investigate the possible effects of the NAO index(North Atlantic Oscillation index)on them,indicating climate conditions in winter.We determined a long-term decrease of the proportion of females in the breeding season in two of the six examined species:Common Pochard and Red-crested Pochard,which is driven by the long-term increase in the number of males in contrast to the decreasing or stable number of females likely caused by different migration behaviours between females and males.In the case of Common Pochard,in breeding populations,we estimated 60-65%of males in the early 2000s rising to 75-80%in the early 2020s.However,we establish no significant effects linked to climate conditions of the previous winter in these species as a crucial cause of the changes of the proportion of females in the breeding population.展开更多
When it comes to smart healthcare business systems,network-based intrusion detection systems are crucial for protecting the system and its networks from malicious network assaults.To protect IoMT devices and networks ...When it comes to smart healthcare business systems,network-based intrusion detection systems are crucial for protecting the system and its networks from malicious network assaults.To protect IoMT devices and networks in healthcare and medical settings,our proposed model serves as a powerful tool for monitoring IoMT networks.This study presents a robust methodology for intrusion detection in Internet of Medical Things(IoMT)environments,integrating data augmentation,feature selection,and ensemble learning to effectively handle IoMT data complexity.Following rigorous preprocessing,including feature extraction,correlation removal,and Recursive Feature Elimi-nation(RFE),selected features are standardized and reshaped for deep learning models.Augmentation using the BAT algorithm enhances dataset variability.Three deep learning models,Transformer-based neural networks,self-attention Deep Convolutional Neural Networks(DCNNs),and Long Short-Term Memory(LSTM)networks,are trained to capture diverse data aspects.Their predictions form a meta-feature set for a subsequent meta-learner,which combines model strengths.Conventional classifiers validate meta-learner features for broad algorithm suitability.This comprehensive method demonstrates high accuracy and robustness in IoMT intrusion detection.Evaluations were conducted using two datasets:the publicly available WUSTL-EHMS-2020 dataset,which contains two distinct categories,and the CICIoMT2024 dataset,encompassing sixteen categories.Experimental results showcase the method’s exceptional performance,achieving optimal scores of 100%on the WUSTL-EHMS-2020 dataset and 99%on the CICIoMT2024.展开更多
Effective user authentication is key to ensuring equipment security,data privacy,and personalized services in Internet of Things(IoT)systems.However,conventional mode-based authentication methods(e.g.,passwords and sm...Effective user authentication is key to ensuring equipment security,data privacy,and personalized services in Internet of Things(IoT)systems.However,conventional mode-based authentication methods(e.g.,passwords and smart cards)may be vulnerable to a broad range of attacks(e.g.,eavesdropping and side-channel attacks).Hence,there have been attempts to design biometric-based authentication solutions,which rely on physiological and behavioral characteristics.Behavioral characteristics need continuous monitoring and specific environmental settings,which can be challenging to implement in practice.However,we can also leverage Artificial Intelligence(AI)in the extraction and classification of physiological characteristics from IoT devices processing to facilitate authentication.Thus,we review the literature on the use of AI in physiological characteristics recognition pub-lished after 2015.We use the three-layer architecture of the IoT(i.e.,sensing layer,feature layer,and algorithm layer)to guide the discussion of existing approaches and their limitations.We also identify a number of future research opportunities,which will hopefully guide the design of next generation solutions.展开更多
This study evaluates the performance and reliability of a vision transformer (ViT) compared to convolutional neural networks (CNNs) using the ResNet50 model in classifying lung cancer from CT images into four categori...This study evaluates the performance and reliability of a vision transformer (ViT) compared to convolutional neural networks (CNNs) using the ResNet50 model in classifying lung cancer from CT images into four categories: lung adenocarcinoma (LUAD), lung squamous cell carcinoma (LUSC), large cell carcinoma (LULC), and normal. Although CNNs have made significant advancements in medical imaging, their limited capacity to capture long-range dependencies has led to the exploration of ViTs, which leverage self-attention mechanisms for a more comprehensive global understanding of images. The study utilized a dataset of 748 lung CT images to train both models with standardized input sizes, assessing their performance through conventional metrics—accuracy, precision, recall, F1 score, specificity, and AUC—as well as cross entropy, a novel metric for evaluating prediction uncertainty. Both models achieved similar accuracy rates (95%), with ViT demonstrating a slight edge over ResNet50 in precision and F1 scores for specific classes. However, ResNet50 exhibited higher recall for LULC, indicating fewer missed cases. Cross entropy analysis showed that the ViT model had lower average uncertainty, particularly in the LUAD, Normal, and LUSC classes, compared to ResNet50. This finding suggests that ViT predictions are generally more reliable, though ResNet50 performed better for LULC. The study underscores that accuracy alone is insufficient for model comparison, as cross entropy offers deeper insights into the reliability and confidence of model predictions. The results highlight the importance of incorporating cross entropy alongside traditional metrics for a more comprehensive evaluation of deep learning models in medical image classification, providing a nuanced understanding of their performance and reliability. While the ViT outperformed the CNN-based ResNet50 in lung cancer classification based on cross-entropy values, the performance differences were minor and may not hold clinical significance. Therefore, it may be premature to consider replacing CNNs with ViTs in this specific application.展开更多
Cross entropy is a measure in machine learning and deep learning that assesses the difference between predicted and actual probability distributions. In this study, we propose cross entropy as a performance evaluation...Cross entropy is a measure in machine learning and deep learning that assesses the difference between predicted and actual probability distributions. In this study, we propose cross entropy as a performance evaluation metric for image classifier models and apply it to the CT image classification of lung cancer. A convolutional neural network is employed as the deep neural network (DNN) image classifier, with the residual network (ResNet) 50 chosen as the DNN archi-tecture. The image data used comprise a lung CT image set. Two classification models are built from datasets with varying amounts of data, and lung cancer is categorized into four classes using 10-fold cross-validation. Furthermore, we employ t-distributed stochastic neighbor embedding to visually explain the data distribution after classification. Experimental results demonstrate that cross en-tropy is a highly useful metric for evaluating the reliability of image classifier models. It is noted that for a more comprehensive evaluation of model perfor-mance, combining with other evaluation metrics is considered essential. .展开更多
This study evaluates the impact of the"4GEON;Four continents connected through geoeducation"project on engaging local and Indigenous communities within UNE-SCO Global Geoparks(UGGps)through immersive and pla...This study evaluates the impact of the"4GEON;Four continents connected through geoeducation"project on engaging local and Indigenous communities within UNE-SCO Global Geoparks(UGGps)through immersive and playful geoeducation initiatives.It aims to assess the effects on environmental commitment,participation,perception of geological heritage,and fostering sustainable development and social responsibility among youths in selected geoparks.Qualitative research techniques,including semi-structured interviews and dynamic discussions,were employed.The systematic analysis of project documentation and align-ment with the United Nations Sustainable Development Goals(SDGs)was conducted to understand the project's broader implications.The findings underscore the crucial role of systematic knowledge transfer in enhancing geo-education within geoparks and emphasize the importance of inclusive communication,with a specific focus on the intercultural dimension of knowledge exchange.By fostering a deeper understanding and appreciation of diverse cultural perspectives,the project contributes to bridging gaps and building mutual respect among different communities.Practi-cal implications include insights for designing effective educational strategies that acknowledge and respect cultural diversity,aligning initiatives with SDGs,and leveraging Information and Communication Technology(ICT)tools to enhance engagement and learning outcomes,particu-larly for youth audiences.展开更多
Many real⁃world machine learning applications face the challenge of dealing with changing data over time,known as concept drift,and the issue of data indeterminacy,where all the true labels available are unrealistic.T...Many real⁃world machine learning applications face the challenge of dealing with changing data over time,known as concept drift,and the issue of data indeterminacy,where all the true labels available are unrealistic.This can lead to a decrease in the accuracy of the prediction models.The aim of this study is to introduce a new approach for detecting drift,which is based on neutrosophic set theory.This approach takes into account uncertainty in the prediction model and is able to handle indeterminate information,considering its impact on the models performance.The proposed method reads data into windows and calculates a set of values based on the concept of neutrosophic membership.These values are then used in the Neutrosophic Support Vector Machine(N⁃SVM).To address the issue of indeterminate true label data,the values issued by N⁃SVM are expressed as entropy and used as input for the ADWIN(Adaptive Windowing)change detector.When a drift is detected,the prediction model is retrained by including only the most recent instances with the original training data set.The proposed method gives promising results in terms of drift detection accuracy compared to the state of existing drift detection methods such as KSWIN,ADWIN,and DWM.展开更多
Underwater Wireless Sensor Networks(UWSNs)are gaining popularity because of their potential uses in oceanography,seismic activity monitoring,environmental preservation,and underwater mapping.Yet,these networks are fac...Underwater Wireless Sensor Networks(UWSNs)are gaining popularity because of their potential uses in oceanography,seismic activity monitoring,environmental preservation,and underwater mapping.Yet,these networks are faced with challenges such as self-interference,long propagation delays,limited bandwidth,and changing network topologies.These challenges are coped with by designing advanced routing protocols.In this work,we present Under Water Fuzzy-Routing Protocol for Low power and Lossy networks(UWF-RPL),an enhanced fuzzy-based protocol that improves decision-making during path selection and traffic distribution over different network nodes.Our method extends RPL with the aid of fuzzy logic to optimize depth,energy,Received Signal Strength Indicator(RSSI)to Expected Transmission Count(ETX)ratio,and latency.Theproposed protocol outperforms other techniques in that it offersmore energy efficiency,better packet delivery,lowdelay,and no queue overflow.It also exhibits better scalability and reliability in dynamic underwater networks,which is of very high importance in maintaining the network operations efficiency and the lifetime of UWSNs optimized.Compared to other recent methods,it offers improved network convergence time(10%–23%),energy efficiency(15%),packet delivery(17%),and delay(24%).展开更多
The measurement of the surface quality and the profile preciseness is major issues in many industrial branches such that the surface quality of semi products directly affects the subsequent production steps.Although,t...The measurement of the surface quality and the profile preciseness is major issues in many industrial branches such that the surface quality of semi products directly affects the subsequent production steps.Although,there are many ways to obtain required data,the hardware necessary for the measurements such as 2D or 3D scanners,depending on the problem’s complexity,is too expensive.Therefore,in this paper,what we put forward as a novelty is an algorithm which is verified on the model of simple 3D scanner on the image processing basis with the resolution of 0.1 mm.There are many ways to scan surface profile;however,the image processing currently is the most trending topic in industry automation.Most importantly,in order to obtain surface images,standard high resolution reflex camera is used and thus the post processing could be realized with MatLab as the software environment.Therefore,this solution is an alternative to the expensive scanners,and single-purpose devices could be extended by many additional functions.展开更多
The general principles and realizations of FBG wavelength tuning with elastic beams are proposed and demonstrated.Theories and experiments show that when displacement at the center point of simple beams,deflection of ...The general principles and realizations of FBG wavelength tuning with elastic beams are proposed and demonstrated.Theories and experiments show that when displacement at the center point of simple beams,deflection of cantilever beams and torsion strain of torsion beams are relatively small,Bragg wavelength shifts of sensing FBGs have linear relationship with applied external stress,lateral displacement,torque and torsional angles,respectively.The experimental results indicate that the curvature sensitivity of the simple beam is 1.65 nm/m-1,the displacement sensitivity of the equivalent-strain cantilever beam is 4.4 cm/kg and the torque and torsional angle sensitivities of the torsion beam are 6.27 nm/Nm and 0.086 7 nm/degree,respectively.展开更多
In this paper,the effects of thermal radiation and viscous dissipation on the stagnation–point flow of a micropolar fluid over a permeable stretching sheet with suction and injection are analyzed and discussed.A suit...In this paper,the effects of thermal radiation and viscous dissipation on the stagnation–point flow of a micropolar fluid over a permeable stretching sheet with suction and injection are analyzed and discussed.A suitable similarity transformation is used to convert the governing nonlinear partial differential equations into a system of nonlinear ordinary differential equations,which are then solved numerically by a fourth–order Runge–Kutta method.It is found that the linear fluid velocity decreases with the enhancement of the porosity,boundary,and suction parameters.Conversely,it increases with the micropolar and injection parameters.The angular velocity grows with the boundary,porosity,and suction parameters,whereas it is reduced if the micropolar and injection parameters become larger.It is concluded that the thermal boundary layer extension increases with the injection parameter and decreases with the suction parameter.展开更多
In order to measure the thermophysical properties of ammoniated salt (CaCl2.mNH3: m = 4, 8) as an energy storage system utilizing natural resources, the measurement unit was developed, and the thermophysical propertie...In order to measure the thermophysical properties of ammoniated salt (CaCl2.mNH3: m = 4, 8) as an energy storage system utilizing natural resources, the measurement unit was developed, and the thermophysical properties (effective thermal conductivity and thermal diffusivity) of CaCl2.mNH3 and CaCl2.mNH3 with heat transfer media (Ti: titanium) were measured by the any heating method. The effective thermal conductivities of CaCl2.4NH3 + Ti and CaCl2.8NH3 + Ti were 0.14 - 0.17 and 0.18 - 0.20 W/(m.K) in the measuring temperature range of 290 - 350 K, respectively, and these values were approximately 1.5 - 2.2 times larger than those of CaCl2.4NH3 and CaCl2.8NH3. The effective thermal diffusivities were 0.22 - 0.24 × 10-6 and 0.18 - 0.19 × 10-6 m2/sin the measuring temperature range of 290 - 350 K, respectively, and these values were approximately 1.3 - 1.5 times larger than those of CaCl2.4NH3 and CaCl2.8NH3. The obtained results show that the thermophysical properties have a dependence on the bulk densities and specific heats of CaCl2.mNH3 and CaCl2.mNH3 + Ti. It reveals that the thermophysical properties in this measurement would be the valuable design factors to develop energy and H2 storage systems utilizing natural resources such as solar energy.展开更多
The exothermic chemical reaction of CaCl2 (calcium chloride) with NH3 (ammonia) can be utilized as an energy storage system. Since this reaction is a typical gas-solid reaction, the reaction rate is controlled by the ...The exothermic chemical reaction of CaCl2 (calcium chloride) with NH3 (ammonia) can be utilized as an energy storage system. Since this reaction is a typical gas-solid reaction, the reaction rate is controlled by the heat transfer rate. In order to improve the low heat transfer rate of the ammoniation and the deammoniation of CaCl2, the influence of a heat transfer media (Ti: titanium) on the heat transfer rate of the solid ammoniated salt (CaCl2.mNH3) was studied and tested experimentally. The performance tests were carried out under the conditions of various weight ratios of Ti. No decrease of the activation of chemical reaction and no corrosion of experimental apparatus were observed on the repeated runs (≥30 times each). The heat transfer rate of ammoniated salt was greatly improved by adding Ti under the constant pressure (0.5 MPa). The reaction time required for the ammoniation of CaCl2 mixed with Ti was approximately 16% - 54% shorter than that of CaCl2 alone, and the reaction time required for the deammoniation was also approximately 19% - 59% shorter than that of CaCl2 alone.展开更多
This review briefly describes the origin,chemistry,molecular mechanism of action,pharmacology,toxicology,and ecotoxicology of palytoxin and its analogues. Palytoxin and its analogues are produced by marine dinoflagell...This review briefly describes the origin,chemistry,molecular mechanism of action,pharmacology,toxicology,and ecotoxicology of palytoxin and its analogues. Palytoxin and its analogues are produced by marine dinoflagellates. Palytoxin is also produced by Zoanthids（i.e. Palythoa）,and Cyanobacteria（Trichodesmium）. Palytoxin is a very large,non-proteinaceous molecule with a complex chemical structure having both lipophilic and hydrophilic moieties. Palytoxin is one of the most potent marine toxins with an LD50 of 150 ng/kg body weight in mice exposed intravenously. Pharmacological and electrophysiological studies have demonstrated that palytoxin acts as a hemolysin and alters the function of excitable cells through multiple mechanisms of action. Palytoxin selectively binds to Na＋/K＋-ATPase with a Kd of 20 p M and transforms the pump into a channel permeable to monovalent cations with a single-channel conductance of 10 p S. This mechanism of action could have multiple effects on cells. Evaluation of palytoxin toxicity using various animal models revealed that palytoxin is an extremely potent neurotoxin following an intravenous,intraperitoneal,intramuscular,subcutaneous or intratracheal route of exposure. Palytoxin also causes non-lethal,yet serious toxic effects following dermal or ocular exposure. Most incidents of palytoxin poisoning have manifested after oral intake of contaminated seafood. Poisonings in humans have also been noted after inhalation,cutaneous/systemic exposures with direct contact of aerosolized seawater during Ostreopsis blooms and/or through maintaining aquaria containing Cnidarian zoanthids. Palytoxin has a strong potential for toxicity in humans and animals,and currently this toxin is of great concern worldwide.展开更多
Cybersecurity is a global goal that is central to national security planning in many countries.One of the most active research fields is design of practices for the development of so-called highly secure software as a...Cybersecurity is a global goal that is central to national security planning in many countries.One of the most active research fields is design of practices for the development of so-called highly secure software as a kind of protection and reduction of the risks from cyber threats.The use of a secure software product in a real environment enables the reduction of the vulnerability of the system as a whole.It would be logical to find the most optimal solution for the integration of secure coding in the classic SDLC(software development life cycle).This paper aims to suggest practices and tips that should be followed for secure coding,in order to avoid cost and time overruns because of untimely identification of security issues.It presents the implementation of secure coding practices in software development,and showcases several real-world scenarios from different phases of the SDLC,as well as mitigation strategies.The paper covers techniques for SQL injection mitigation,authentication management for staging environments,and access control verification using JSON Web Tokens.展开更多
基金supported by the National Key Research and Development Program of China(Grant No.2022YFE0110300)the National Natural Science Foundation of China(Grant Nos.52372215,92163114,and 52202274)+5 种基金the Natural Science Foundation of Jiangsu Province of China(Grant No.BK20230504)the Special Fund for the"Dual Carbon"Science and Technology Innovation of Jiangsu province(Industrial Prospect and Key Technology Research program)(Grant Nos.BE2022023 and BE2022021)the Natural Science Foundation of the Jiangsu Higher Education Institutions of China(Grant No.21KJA430004)Gusu Innovation and Entre preneurship Leading Talent Program(Grant No.ZXL2022451)the China Postdoctoral Science Foundation(Grant No.2023M732523)supported by Suzhou Key Laboratory of Functional Nano&Soft Materials,Collaborative Innovation Center of Suzhou Nano Science&Technology,the 111 Project.
文摘Lead chalcohalides(PbYX,X=Cl,Br,I;Y=S,Se)is an extension of the classic Pb chalcogenides(PbY).Constructing the heterogeneous integration with PbYX and PbY material systems makes it possible to achieve significantly improved optoelectronic performance.In this work,we studied the effect of introducing halogen precursors on the structure of classical PbS nanocrystals(NCs)during the synthesis process and realized the preparation of PbS/Pb_(3)S_(2)X_(2) core/shell structure for the first time.The core/shell structure can effectively improve their optical properties.Furthermore,our approach enables the synthesis of Pb_(3)S_(2)Br_(2) that had not yet been reported.Our results not only provide valuable insights into the heterogeneous integration of PbYX and PbY materials to elevate material properties but also provide an effective method for further expanding the preparation of PbYX material systems.
基金supported by the Spanish Ministry of Science and Innovation under the MCI/AEI/FEDER project number PID2021-123543OBC21.
文摘Anomaly detection in wind turbines involves emphasizing its ability to improve operational efficiency,reduce maintenance costs,extend their lifespan,and enhance reliability in the wind energy sector.This is particularly necessary in offshore wind,currently one of the most critical assets for achieving sustainable energy generation goals,due to the harsh marine environment and the difficulty of maintenance tasks.To address this problem,this work proposes a data-driven methodology for detecting power generation anomalies in offshore wind turbines,using normalized and linearized operational data.The proposed framework transforms heterogeneous wind speed and power measurements into a unified scale,enabling the development of a new wind power index(WPi)that quantifies deviations from expected performance.Additionally,spatial and temporal coherence analyses of turbines within a wind farm ensure the validity of these normalized measurements across different wind turbine models and operating conditions.Furthermore,a Support Vector Machine(SVM)refines the classification process,effectively distinguishing measurement errors from actual power generation failures.Validation of this strategy using real-world data from the Alpha Ventus wind farm demonstrates that the proposed approach not only improves predictive maintenance but also optimizes energy production,highlighting its potential for broad application in offshore wind installations.
基金supported by the JST SPRING Grant number JPMJSP2131funded by the Research Fellow Scheme from The Chinese University of Hong KongUniversiti Teknologi Malaysia AJ090000.6700.09453-Tabung Pembayaran Lantikan Skim Prominent Visiting Researcher Scheme JTNCPI。
文摘Recent advances in all-inorganic perovskite semiconductors have garnered significant research interest due to their potential for high-performance optoelectronic devices and enhanced stability under harsh environmental conditions.A deeper understanding of their structural,chemical,and physical properties has driven notable progress in addressing challenges related to electrical characteristics,reproducibility,and long-term operational stability in perovskite-based memristors.These advancements have been realized through composition engineering,dimensionality modulation,thin-film processing,and device optimization.This review concisely summarizes recent developments in all-inorganic perovskite memristors,highlighting their diverse material properties,device performance,and applications in artificial synapses and logic operations.We discuss key resistance-switching mechanisms,optimization strategies,and operational capabilities while outlining remaining challenges and future directions for perovskitebased memory technologies.
基金Support of the grant MSM00211622419 is to be acknowledge
文摘Quantum information processing and communication(QIPC) is an area of science that has two main goals: On one side,it tries to explore(still not well known) potential of quantum phenomena for(efficient and reliable) information processing and(efficient,reliable and secure) communication.On the other side,it tries to use quantum information storing,processing and transmitting paradigms,principles,laws,limitations,concepts,models and tools to get deeper insights into the phenomena of quantum world and to find efficient ways to describe and handle/simulate various complex physical phenomena.In order to do that QIPC has to use concepts,models,theories,methods and tools of both physics and informatics.The main role of physics at that is to discover primitive physical phenomena that can be used to design and maintain complex and reliable information storing,processing and transmitting systems.The main role of informatics is,one one side,to explore,from the information processing and communication point of view,limitations and potentials of the potential quantum information processing and communication technology,and to prepare information processing methods that could utilise potential of quantum information processing and communication technologies.On the other side,the main role of informatics is to guide and support,by theoretical tools and outcomes,physics oriented research in QIPC.The paper is to describe and analyse a variety of ways and potential informatics contributes and should/could contribute to the development of QIPC--see also Gruska(1999,2006,2008).
基金partly supported by the Science and Technology Development Fund,Macao Special Administrative Region(SAR)(0093/2023/RIA2,0145/2023/RIA3)The National Natural Science Foundation of China(62103411)。
文摘THE Lebanese wireless device explosion incident has drawn widespread attention,involving devices such as pagers,walkie-talkies,and other common devices[1].This event has revealed and highlighted the security vulnerabilities in global supply chains from raw material manufacturing and distribution to the usage of devices and equipment,signaling the onset of a new wave of"supply chain warfare"[2].
基金supported by the project 2021B0038 of the Internal Grant Agency of Faculty of Environmental Sciences,CZU Prague entitled“Effect of incubation behaviour on predation risk in ducks(Common Pochard Aythya ferina and Tufted Duck Aythya fuligula)in two different habitats”the project SS01010280 of the Technology Agency of the Czech Republic entitled“Fishpond management optimization as a tool to biodiversity conservation under climate change”.
文摘Despite all efforts,long-term changes in the adult sex ratios of breeding duck populations are still unclear;this uncertainty is especially true for male-bias populations,which are often under the scrutiny of researchers lacking convenient results for the active protection of endangered species.Species with male-bias populations are usually strongly affected by a decline in population size that leads to a higher extinction risk.In this study,we examined our long-term data of the abundance of breeding populations in six duck species(Mallard Anas platyrhynchos,Gadwall Mareca strepera,Red-crested Pochard Netta rufina,Common Pochard Aythya ferina,Tufted Duck Aythya fuligula,and Common Goldeneye Bucephala clangula)from fishponds in South Bohemia,Czechia,between 2004 and 2022.This evidence was used to assess long-term changes in the adult sex ratio in these breeding populations and investigate the possible effects of the NAO index(North Atlantic Oscillation index)on them,indicating climate conditions in winter.We determined a long-term decrease of the proportion of females in the breeding season in two of the six examined species:Common Pochard and Red-crested Pochard,which is driven by the long-term increase in the number of males in contrast to the decreasing or stable number of females likely caused by different migration behaviours between females and males.In the case of Common Pochard,in breeding populations,we estimated 60-65%of males in the early 2000s rising to 75-80%in the early 2020s.However,we establish no significant effects linked to climate conditions of the previous winter in these species as a crucial cause of the changes of the proportion of females in the breeding population.
基金supported by the Deanship of Graduate Studies and Scientific Research at Jouf University under grant No.DGSSR-2023-02-02116.
文摘When it comes to smart healthcare business systems,network-based intrusion detection systems are crucial for protecting the system and its networks from malicious network assaults.To protect IoMT devices and networks in healthcare and medical settings,our proposed model serves as a powerful tool for monitoring IoMT networks.This study presents a robust methodology for intrusion detection in Internet of Medical Things(IoMT)environments,integrating data augmentation,feature selection,and ensemble learning to effectively handle IoMT data complexity.Following rigorous preprocessing,including feature extraction,correlation removal,and Recursive Feature Elimi-nation(RFE),selected features are standardized and reshaped for deep learning models.Augmentation using the BAT algorithm enhances dataset variability.Three deep learning models,Transformer-based neural networks,self-attention Deep Convolutional Neural Networks(DCNNs),and Long Short-Term Memory(LSTM)networks,are trained to capture diverse data aspects.Their predictions form a meta-feature set for a subsequent meta-learner,which combines model strengths.Conventional classifiers validate meta-learner features for broad algorithm suitability.This comprehensive method demonstrates high accuracy and robustness in IoMT intrusion detection.Evaluations were conducted using two datasets:the publicly available WUSTL-EHMS-2020 dataset,which contains two distinct categories,and the CICIoMT2024 dataset,encompassing sixteen categories.Experimental results showcase the method’s exceptional performance,achieving optimal scores of 100%on the WUSTL-EHMS-2020 dataset and 99%on the CICIoMT2024.
基金funded in part by the National Natural Science Foundation of China under Grant No.61872038in part by the Fundamental Research Funds for the Central Universities under Grant No.FRF-GF-20-15B.
文摘Effective user authentication is key to ensuring equipment security,data privacy,and personalized services in Internet of Things(IoT)systems.However,conventional mode-based authentication methods(e.g.,passwords and smart cards)may be vulnerable to a broad range of attacks(e.g.,eavesdropping and side-channel attacks).Hence,there have been attempts to design biometric-based authentication solutions,which rely on physiological and behavioral characteristics.Behavioral characteristics need continuous monitoring and specific environmental settings,which can be challenging to implement in practice.However,we can also leverage Artificial Intelligence(AI)in the extraction and classification of physiological characteristics from IoT devices processing to facilitate authentication.Thus,we review the literature on the use of AI in physiological characteristics recognition pub-lished after 2015.We use the three-layer architecture of the IoT(i.e.,sensing layer,feature layer,and algorithm layer)to guide the discussion of existing approaches and their limitations.We also identify a number of future research opportunities,which will hopefully guide the design of next generation solutions.
文摘This study evaluates the performance and reliability of a vision transformer (ViT) compared to convolutional neural networks (CNNs) using the ResNet50 model in classifying lung cancer from CT images into four categories: lung adenocarcinoma (LUAD), lung squamous cell carcinoma (LUSC), large cell carcinoma (LULC), and normal. Although CNNs have made significant advancements in medical imaging, their limited capacity to capture long-range dependencies has led to the exploration of ViTs, which leverage self-attention mechanisms for a more comprehensive global understanding of images. The study utilized a dataset of 748 lung CT images to train both models with standardized input sizes, assessing their performance through conventional metrics—accuracy, precision, recall, F1 score, specificity, and AUC—as well as cross entropy, a novel metric for evaluating prediction uncertainty. Both models achieved similar accuracy rates (95%), with ViT demonstrating a slight edge over ResNet50 in precision and F1 scores for specific classes. However, ResNet50 exhibited higher recall for LULC, indicating fewer missed cases. Cross entropy analysis showed that the ViT model had lower average uncertainty, particularly in the LUAD, Normal, and LUSC classes, compared to ResNet50. This finding suggests that ViT predictions are generally more reliable, though ResNet50 performed better for LULC. The study underscores that accuracy alone is insufficient for model comparison, as cross entropy offers deeper insights into the reliability and confidence of model predictions. The results highlight the importance of incorporating cross entropy alongside traditional metrics for a more comprehensive evaluation of deep learning models in medical image classification, providing a nuanced understanding of their performance and reliability. While the ViT outperformed the CNN-based ResNet50 in lung cancer classification based on cross-entropy values, the performance differences were minor and may not hold clinical significance. Therefore, it may be premature to consider replacing CNNs with ViTs in this specific application.
文摘Cross entropy is a measure in machine learning and deep learning that assesses the difference between predicted and actual probability distributions. In this study, we propose cross entropy as a performance evaluation metric for image classifier models and apply it to the CT image classification of lung cancer. A convolutional neural network is employed as the deep neural network (DNN) image classifier, with the residual network (ResNet) 50 chosen as the DNN archi-tecture. The image data used comprise a lung CT image set. Two classification models are built from datasets with varying amounts of data, and lung cancer is categorized into four classes using 10-fold cross-validation. Furthermore, we employ t-distributed stochastic neighbor embedding to visually explain the data distribution after classification. Experimental results demonstrate that cross en-tropy is a highly useful metric for evaluating the reliability of image classifier models. It is noted that for a more comprehensive evaluation of model perfor-mance, combining with other evaluation metrics is considered essential. .
基金support of the Project“751-4GEON:Four Con-tinents Connected through Playful Geoeducation”and financial sup-port of the Specific Research Project“Information and Knowledge Management and Cognitive Science in Tourism”of FIM UHK is gratefully acknowledged.The authors wish to express their thanks to StanislavŠafránek,FIM UHK student,and David Zejda and Zuzana Kroulíková,former FIM UHK students,who assisted with the graphical elements.
文摘This study evaluates the impact of the"4GEON;Four continents connected through geoeducation"project on engaging local and Indigenous communities within UNE-SCO Global Geoparks(UGGps)through immersive and playful geoeducation initiatives.It aims to assess the effects on environmental commitment,participation,perception of geological heritage,and fostering sustainable development and social responsibility among youths in selected geoparks.Qualitative research techniques,including semi-structured interviews and dynamic discussions,were employed.The systematic analysis of project documentation and align-ment with the United Nations Sustainable Development Goals(SDGs)was conducted to understand the project's broader implications.The findings underscore the crucial role of systematic knowledge transfer in enhancing geo-education within geoparks and emphasize the importance of inclusive communication,with a specific focus on the intercultural dimension of knowledge exchange.By fostering a deeper understanding and appreciation of diverse cultural perspectives,the project contributes to bridging gaps and building mutual respect among different communities.Practi-cal implications include insights for designing effective educational strategies that acknowledge and respect cultural diversity,aligning initiatives with SDGs,and leveraging Information and Communication Technology(ICT)tools to enhance engagement and learning outcomes,particu-larly for youth audiences.
文摘Many real⁃world machine learning applications face the challenge of dealing with changing data over time,known as concept drift,and the issue of data indeterminacy,where all the true labels available are unrealistic.This can lead to a decrease in the accuracy of the prediction models.The aim of this study is to introduce a new approach for detecting drift,which is based on neutrosophic set theory.This approach takes into account uncertainty in the prediction model and is able to handle indeterminate information,considering its impact on the models performance.The proposed method reads data into windows and calculates a set of values based on the concept of neutrosophic membership.These values are then used in the Neutrosophic Support Vector Machine(N⁃SVM).To address the issue of indeterminate true label data,the values issued by N⁃SVM are expressed as entropy and used as input for the ADWIN(Adaptive Windowing)change detector.When a drift is detected,the prediction model is retrained by including only the most recent instances with the original training data set.The proposed method gives promising results in terms of drift detection accuracy compared to the state of existing drift detection methods such as KSWIN,ADWIN,and DWM.
文摘Underwater Wireless Sensor Networks(UWSNs)are gaining popularity because of their potential uses in oceanography,seismic activity monitoring,environmental preservation,and underwater mapping.Yet,these networks are faced with challenges such as self-interference,long propagation delays,limited bandwidth,and changing network topologies.These challenges are coped with by designing advanced routing protocols.In this work,we present Under Water Fuzzy-Routing Protocol for Low power and Lossy networks(UWF-RPL),an enhanced fuzzy-based protocol that improves decision-making during path selection and traffic distribution over different network nodes.Our method extends RPL with the aid of fuzzy logic to optimize depth,energy,Received Signal Strength Indicator(RSSI)to Expected Transmission Count(ETX)ratio,and latency.Theproposed protocol outperforms other techniques in that it offersmore energy efficiency,better packet delivery,lowdelay,and no queue overflow.It also exhibits better scalability and reliability in dynamic underwater networks,which is of very high importance in maintaining the network operations efficiency and the lifetime of UWSNs optimized.Compared to other recent methods,it offers improved network convergence time(10%–23%),energy efficiency(15%),packet delivery(17%),and delay(24%).
基金Project(2102–2020)supported by the SPEV Project,University of Hradec Kralove,FIM,Czech RepublicProject(Vot-20H04)supported by Universiti Teknologi Malaysia(UTM)+1 种基金Project(Vot 4L876)supported by Malaysia Research University Network(MRUN)Project(Vot 5F073)supported by the Fundamental Research Grant Scheme(FRGS),Ministry of Education Malaysia。
文摘The measurement of the surface quality and the profile preciseness is major issues in many industrial branches such that the surface quality of semi products directly affects the subsequent production steps.Although,there are many ways to obtain required data,the hardware necessary for the measurements such as 2D or 3D scanners,depending on the problem’s complexity,is too expensive.Therefore,in this paper,what we put forward as a novelty is an algorithm which is verified on the model of simple 3D scanner on the image processing basis with the resolution of 0.1 mm.There are many ways to scan surface profile;however,the image processing currently is the most trending topic in industry automation.Most importantly,in order to obtain surface images,standard high resolution reflex camera is used and thus the post processing could be realized with MatLab as the software environment.Therefore,this solution is an alternative to the expensive scanners,and single-purpose devices could be extended by many additional functions.
文摘The general principles and realizations of FBG wavelength tuning with elastic beams are proposed and demonstrated.Theories and experiments show that when displacement at the center point of simple beams,deflection of cantilever beams and torsion strain of torsion beams are relatively small,Bragg wavelength shifts of sensing FBGs have linear relationship with applied external stress,lateral displacement,torque and torsional angles,respectively.The experimental results indicate that the curvature sensitivity of the simple beam is 1.65 nm/m-1,the displacement sensitivity of the equivalent-strain cantilever beam is 4.4 cm/kg and the torque and torsional angle sensitivities of the torsion beam are 6.27 nm/Nm and 0.086 7 nm/degree,respectively.
文摘In this paper,the effects of thermal radiation and viscous dissipation on the stagnation–point flow of a micropolar fluid over a permeable stretching sheet with suction and injection are analyzed and discussed.A suitable similarity transformation is used to convert the governing nonlinear partial differential equations into a system of nonlinear ordinary differential equations,which are then solved numerically by a fourth–order Runge–Kutta method.It is found that the linear fluid velocity decreases with the enhancement of the porosity,boundary,and suction parameters.Conversely,it increases with the micropolar and injection parameters.The angular velocity grows with the boundary,porosity,and suction parameters,whereas it is reduced if the micropolar and injection parameters become larger.It is concluded that the thermal boundary layer extension increases with the injection parameter and decreases with the suction parameter.
文摘In order to measure the thermophysical properties of ammoniated salt (CaCl2.mNH3: m = 4, 8) as an energy storage system utilizing natural resources, the measurement unit was developed, and the thermophysical properties (effective thermal conductivity and thermal diffusivity) of CaCl2.mNH3 and CaCl2.mNH3 with heat transfer media (Ti: titanium) were measured by the any heating method. The effective thermal conductivities of CaCl2.4NH3 + Ti and CaCl2.8NH3 + Ti were 0.14 - 0.17 and 0.18 - 0.20 W/(m.K) in the measuring temperature range of 290 - 350 K, respectively, and these values were approximately 1.5 - 2.2 times larger than those of CaCl2.4NH3 and CaCl2.8NH3. The effective thermal diffusivities were 0.22 - 0.24 × 10-6 and 0.18 - 0.19 × 10-6 m2/sin the measuring temperature range of 290 - 350 K, respectively, and these values were approximately 1.3 - 1.5 times larger than those of CaCl2.4NH3 and CaCl2.8NH3. The obtained results show that the thermophysical properties have a dependence on the bulk densities and specific heats of CaCl2.mNH3 and CaCl2.mNH3 + Ti. It reveals that the thermophysical properties in this measurement would be the valuable design factors to develop energy and H2 storage systems utilizing natural resources such as solar energy.
文摘The exothermic chemical reaction of CaCl2 (calcium chloride) with NH3 (ammonia) can be utilized as an energy storage system. Since this reaction is a typical gas-solid reaction, the reaction rate is controlled by the heat transfer rate. In order to improve the low heat transfer rate of the ammoniation and the deammoniation of CaCl2, the influence of a heat transfer media (Ti: titanium) on the heat transfer rate of the solid ammoniated salt (CaCl2.mNH3) was studied and tested experimentally. The performance tests were carried out under the conditions of various weight ratios of Ti. No decrease of the activation of chemical reaction and no corrosion of experimental apparatus were observed on the repeated runs (≥30 times each). The heat transfer rate of ammoniated salt was greatly improved by adding Ti under the constant pressure (0.5 MPa). The reaction time required for the ammoniation of CaCl2 mixed with Ti was approximately 16% - 54% shorter than that of CaCl2 alone, and the reaction time required for the deammoniation was also approximately 19% - 59% shorter than that of CaCl2 alone.
基金supported by Long Term Development Plan of University Hospital Hradec Kralove and University of Hradec Kralove,the Project of Excellence FIM UHK,as well as,Yangtze Youth Talents Fund(Yangtze University)
文摘This review briefly describes the origin,chemistry,molecular mechanism of action,pharmacology,toxicology,and ecotoxicology of palytoxin and its analogues. Palytoxin and its analogues are produced by marine dinoflagellates. Palytoxin is also produced by Zoanthids（i.e. Palythoa）,and Cyanobacteria（Trichodesmium）. Palytoxin is a very large,non-proteinaceous molecule with a complex chemical structure having both lipophilic and hydrophilic moieties. Palytoxin is one of the most potent marine toxins with an LD50 of 150 ng/kg body weight in mice exposed intravenously. Pharmacological and electrophysiological studies have demonstrated that palytoxin acts as a hemolysin and alters the function of excitable cells through multiple mechanisms of action. Palytoxin selectively binds to Na＋/K＋-ATPase with a Kd of 20 p M and transforms the pump into a channel permeable to monovalent cations with a single-channel conductance of 10 p S. This mechanism of action could have multiple effects on cells. Evaluation of palytoxin toxicity using various animal models revealed that palytoxin is an extremely potent neurotoxin following an intravenous,intraperitoneal,intramuscular,subcutaneous or intratracheal route of exposure. Palytoxin also causes non-lethal,yet serious toxic effects following dermal or ocular exposure. Most incidents of palytoxin poisoning have manifested after oral intake of contaminated seafood. Poisonings in humans have also been noted after inhalation,cutaneous/systemic exposures with direct contact of aerosolized seawater during Ostreopsis blooms and/or through maintaining aquaria containing Cnidarian zoanthids. Palytoxin has a strong potential for toxicity in humans and animals,and currently this toxin is of great concern worldwide.
文摘Cybersecurity is a global goal that is central to national security planning in many countries.One of the most active research fields is design of practices for the development of so-called highly secure software as a kind of protection and reduction of the risks from cyber threats.The use of a secure software product in a real environment enables the reduction of the vulnerability of the system as a whole.It would be logical to find the most optimal solution for the integration of secure coding in the classic SDLC(software development life cycle).This paper aims to suggest practices and tips that should be followed for secure coding,in order to avoid cost and time overruns because of untimely identification of security issues.It presents the implementation of secure coding practices in software development,and showcases several real-world scenarios from different phases of the SDLC,as well as mitigation strategies.The paper covers techniques for SQL injection mitigation,authentication management for staging environments,and access control verification using JSON Web Tokens.
