Despite significant advancements in the power conversion efficiency(PCE)of perovskite/silicon tandem solar cells,improving carrier management in top cells remains challenging due to the defective dual interfaces of wi...Despite significant advancements in the power conversion efficiency(PCE)of perovskite/silicon tandem solar cells,improving carrier management in top cells remains challenging due to the defective dual interfaces of wide-bandgap perovskite,particularly on textured silicon surfaces.Herein,a series of halide ions(Cl^(-),Br^(-),I^(-))substituted piperazinium salts are designed and synthesized as post-treatment modifiers for perovskite surfaces.Notably,piperazinium chloride induces an asymmetric bidirectional ions distribution from the top to the bottom surface,with large piperazinium cations concentrating at the perovskite surface and small chloride anions migrating downward to accumulate at the buried interface.This results in effective dual-interface defect passivation and energy band modulation,enabling wide-bandgap(1.68 eV)perovskite solar cells to achieve a PCE of 22.3%and a record product of open-circuit voltage×fill factor(84.4%relative to the Shockley-Queisser limit).Furthermore,the device retains 91.3%of its initial efficiency after 1200 h of maximum power point tracking without encapsulation.When integrated with double-textured silicon heterojunction solar cells,a remarkable PCE of 31.5%is achieved for a 1.04 cm^(2) monolithic perovskite/silicon tandem solar cell,exhibiting excellent long-term operational stability(T_(80)=755 h)without encapsulation in ambient air.This work provides a convenient strategy on dual-interface engineering for making high-efficiency and stable perovskite platforms.展开更多
The present investigation aims at unveiling the main causes of the recorded disparate phylogeographic patterning among the two highly dispersive coastal crab species Carcinus aestuarii and Pachygrapsus marmoratus in t...The present investigation aims at unveiling the main causes of the recorded disparate phylogeographic patterning among the two highly dispersive coastal crab species Carcinus aestuarii and Pachygrapsus marmoratus in the Mediterranean Sea.For this purpose,available mitochondrial and nuclear data for both species were re-analyzed and investigated for genetic polymorphism and differentiation patterns across three defined geographic scales in their distribution ranges,but also across the same locations in the Mediterranean Sea.The temporal frame of genetic diversification was also determined for both species in order to check whether observed differences in phylogeographic patterns among these coastal decapods could be attributed to different evolutionary histories.The obtained results revealed a more variable and diversified gene pool in the green crab C.aestuarii than the one recorded in the marbled crab P.marmoratus.Lack of significant correlation between pairwise genetic dissimilarities observed among C.aestuarii populations and those detected for P.marmoratus was notably discerned across the same defined Mediterranean locations.This finding indicates that the pattern of pairwise genetic differentiation does not vary in the same way in both examined crab species.Significant outputs of population genetic differentiation,retrieved within both species,were shown to be differently associated with the potential effects of various kinds of isolation processes(related to geography,environment and biogeographic boundary).Evolutionary history reconstruction showed older genetic diversification event in C.aestuarii than the one recorded in P.marmoratus.These recorded temporal frames suggest different modes of genetic diversification in both crab species(glacial vicariance for C.aestuarii and interglacial dispersal for P.marmoratus).They may also provide an explanation for the recorded differences in variation of patterns of population genetic diversity and structure,when integrated with species ecological requirements and life-history traits.展开更多
Determining the adsorption of shale gas on complex surfaces remains a challenge in molecular simulation studies.Difficulties essentially stem from the need to create a realistic shale structure model in terms of miner...Determining the adsorption of shale gas on complex surfaces remains a challenge in molecular simulation studies.Difficulties essentially stem from the need to create a realistic shale structure model in terms of mineral heterogeneityand multiplicity.Moreover,precise characterization of the competitive adsorption of hydrogen andmethane in shale generally requires the experimental determination of the related adsorptive capacity.In thisstudy,the adsorption of adsorbates,methane(CH_(4)),and hydrogen(H_(2))on heterogeneous shale surface modelsof Kaolinite,Orthoclase,Muscovite,Mica,C_(60),and Butane has been simulated in the frame of a moleculardynamic’s numerical technique.The results show that these behaviors are influenced by pressure and potentialenergy.On increasing the pressure from 500 to 2000 psi,the sorption effect for CH_(4)significantly increasesbut shows a decline at a certain stage(if compared to H_(2)).The research findings also indicate that raw shalehas a higher capacity to adsorb CH_(4)compared to hydrogen.However,in shale,this difference is negligible.展开更多
作为全球应对气候变化的技术途径之一，碳捕集与封存（Carbon Capture and Storage，CCS）技术受到了世界各国的广泛重视。尽管国人对其尚有陌生，但CCS技术已是当前气候变化领域最前沿、最重大的课题之一，全球积极倡导碳减排的主要能...作为全球应对气候变化的技术途径之一，碳捕集与封存（Carbon Capture and Storage，CCS）技术受到了世界各国的广泛重视。尽管国人对其尚有陌生，但CCS技术已是当前气候变化领域最前沿、最重大的课题之一，全球积极倡导碳减排的主要能源研究机构、组织和国家，已经一致将CCS技术列为未来的碳减排关键技术，并斥巨资开展CCS技术的相关研究和工业化实践。展开更多
Facial Expression Recognition(FER)has been an interesting area of research in places where there is human-computer interaction.Human psychol-ogy,emotions and behaviors can be analyzed in FER.Classifiers used in FER hav...Facial Expression Recognition(FER)has been an interesting area of research in places where there is human-computer interaction.Human psychol-ogy,emotions and behaviors can be analyzed in FER.Classifiers used in FER have been perfect on normal faces but have been found to be constrained in occluded faces.Recently,Deep Learning Techniques(DLT)have gained popular-ity in applications of real-world problems including recognition of human emo-tions.The human face reflects emotional states and human intentions.An expression is the most natural and powerful way of communicating non-verbally.Systems which form communications between the two are termed Human Machine Interaction(HMI)systems.FER can improve HMI systems as human expressions convey useful information to an observer.This paper proposes a FER scheme called EECNN(Enhanced Convolution Neural Network with Atten-tion mechanism)to recognize seven types of human emotions with satisfying results in its experiments.Proposed EECNN achieved 89.8%accuracy in classi-fying the images.展开更多
Generation-based linguistic steganography is a popular research area of information hiding.The text generative steganographic method based on conditional probability coding is the direction that researchers have recen...Generation-based linguistic steganography is a popular research area of information hiding.The text generative steganographic method based on conditional probability coding is the direction that researchers have recently paid attention to.However,in the course of our experiment,we found that the secret information hiding in the text tends to destroy the statistical distribution characteristics of the original text,which indicates that this method has the problem of the obvious reduction of text quality when the embedding rate increases,and that the topic of generated texts is uncontrollable,so there is still room for improvement in concealment.In this paper,we propose a topic-controlled steganography method which is guided by graph-to-text generation.The proposed model can automatically generate steganographic texts carrying secret messages from knowledge graphs,and the topic of the generated texts is controllable.We also provide a graph path coding method with corresponding detailed algorithms for graph-to-text generation.Different from traditional linguistic steganography methods,we encode the secret information during graph path coding rather than using conditional probability.We test our method in different aspects and compare it with other text generative steganographic methods.The experimental results show that the model proposed in this paper can effectively improve the quality of the generated text and significantly improve the concealment of steganographic text.展开更多
At an early point,the diagnosis of pancreatic cancer is mediocre,since the radiologist is skill deficient.Serious threats have been posed due to the above reasons,hence became mandatory for the need of skilled technici...At an early point,the diagnosis of pancreatic cancer is mediocre,since the radiologist is skill deficient.Serious threats have been posed due to the above reasons,hence became mandatory for the need of skilled technicians.However,it also became a time-consuming process.Hence the need for automated diagnosis became mandatory.In order to identify the tumor accurately,this research pro-poses a novel Convolution Neural Network(CNN)based superior image classi-fication technique.The proposed deep learning classification strategy has a precision of 97.7%,allowing for more effective usage of the automatically exe-cuted feature extraction technique to diagnose cancer cells.Comparative analysis with CNN-Grey Wolf Optimization(GWO)is carried based on varied testing and training outcomes.The suggested study is carried out at a rate of 90%–10%,80%–20%,and 70%–30%,indicating the robustness of the proposed research work.Outcomes show that the suggested method is effective.GWO-CNN is reli-able and accurate relative to other detection methods available in the literatures.展开更多
The aim of the study was to taste mask ciprofloxacin(CP)by using ion-exchange resins(IERs)followed by sustain release of CP by forming interpenetrating polymer network(IPN).IERs based on the copolymerization of acryli...The aim of the study was to taste mask ciprofloxacin(CP)by using ion-exchange resins(IERs)followed by sustain release of CP by forming interpenetrating polymer network(IPN).IERs based on the copolymerization of acrylic acid with different cross linking agents were synthesised.Drug-resin complexes(DRCs)with three different ratios of drug to IERs(1:1,1:2,1:4)were prepared&evaluated for taste masking by following in vivo and in vitro methods.Human volunteers graded ADC 1:4,acrylic acid-divinyl benzene(ADC-3)resin as tasteless.Characterization studies such as FTIR,SEM,DSC,P-XRD differentiated ADC 1:4,from physical mixture(PM 1:4)and confirmed the formation of complex.In vitro drug release of ADC 1:4 showed complete release of CP within 60 min at simulated gastric fluid(SGF)i.e.pH 1.2.IPN beads were prepared with ADC 1:4 by using sodium alginate(AL)and sodium alginate-chitosan(AL-CS)for sustain release of CP at SGF pH and followed by simulated intestinal fluid(SIF i.e.pH 7.4).FTIR spectra confirmed the formation of IPN beads.The release of CP was sustain at SGF pH(<20%)whereas in SIF media it was more(>75%).The kinetic model of IPN beads showed the release of CP was non-Fickian diffusion type.展开更多
In this research paper,we propose a corpus for the task of detecting religious extremism in social networks and open sources and compare various machine learning algorithms for the binary classification problem using ...In this research paper,we propose a corpus for the task of detecting religious extremism in social networks and open sources and compare various machine learning algorithms for the binary classification problem using a previously created corpus,thereby checking whether it is possible to detect extremist messages in the Kazakh language.To do this,the authors trained models using six classic machine-learning algorithms such as Support Vector Machine,Decision Tree,Random Forest,K Nearest Neighbors,Naive Bayes,and Logistic Regression.To increase the accuracy of detecting extremist texts,we used various characteristics such as Statistical Features,TF-IDF,POS,LIWC,and applied oversampling and undersampling techniques to handle imbalanced data.As a result,we achieved 98%accuracy in detecting religious extremism in Kazakh texts for the collected dataset.Testing the developed machine learningmodels in various databases that are often found in everyday life“Jokes”,“News”,“Toxic content”,“Spam”,“Advertising”has also shown high rates of extremism detection.展开更多
Cloud computing is the technology that is currently used to provide users with infrastructure,platform,and software services effectively.Under this system,Platform as a Service(PaaS)offers a medium headed for a web de...Cloud computing is the technology that is currently used to provide users with infrastructure,platform,and software services effectively.Under this system,Platform as a Service(PaaS)offers a medium headed for a web development platform that uniformly distributes the requests and resources.Hackers using Denial of service(DoS)and Distributed Denial of Service(DDoS)attacks abruptly interrupt these requests.Even though several existing methods like signature-based,statistical anomaly-based,and stateful protocol analysis are available,they are not sufficient enough to get rid of Denial of service(DoS)and Distributed Denial of Service(DDoS)attacks and hence there is a great need for a definite algorithm.Concerning this issue,we propose an improved hybrid algorithm which is a combination of Multivariate correlation analysis,Spearman coefficient,and mitigation technique.It can easily differentiate common traffic and attack traffic.Not only that,it greatly helps the network to distribute the resources only for authenticated requests.The effects of comparing with the normalized information have shown an extra encouraging detection accuracy of 99%for the numerous DoS attack as well as DDoS attacks.展开更多
基金supported by the National Natural Science Foundation of China(Grant No.62204245,U23A200098)Baima Lake Laboratory Joint Funds of the Zhejiang Provincial Natural Science Foundation of China(Grant No.LBMHD24E020002)+4 种基金Key Research and Development Program of Zhejiang Province(Grant No.2022C01215,2024C01092)China Postdoctoral Science Foundation(Grant No.2023M743620,2024T170960)Key Research and Development Program of Ningbo(Grant No.2023Z151)National Key Research and Development Program of China(Grant No.2024YFB3817304)Zhejiang Provincial Natural Science Foundation of China(Grant No.LY24F040003).
文摘Despite significant advancements in the power conversion efficiency(PCE)of perovskite/silicon tandem solar cells,improving carrier management in top cells remains challenging due to the defective dual interfaces of wide-bandgap perovskite,particularly on textured silicon surfaces.Herein,a series of halide ions(Cl^(-),Br^(-),I^(-))substituted piperazinium salts are designed and synthesized as post-treatment modifiers for perovskite surfaces.Notably,piperazinium chloride induces an asymmetric bidirectional ions distribution from the top to the bottom surface,with large piperazinium cations concentrating at the perovskite surface and small chloride anions migrating downward to accumulate at the buried interface.This results in effective dual-interface defect passivation and energy band modulation,enabling wide-bandgap(1.68 eV)perovskite solar cells to achieve a PCE of 22.3%and a record product of open-circuit voltage×fill factor(84.4%relative to the Shockley-Queisser limit).Furthermore,the device retains 91.3%of its initial efficiency after 1200 h of maximum power point tracking without encapsulation.When integrated with double-textured silicon heterojunction solar cells,a remarkable PCE of 31.5%is achieved for a 1.04 cm^(2) monolithic perovskite/silicon tandem solar cell,exhibiting excellent long-term operational stability(T_(80)=755 h)without encapsulation in ambient air.This work provides a convenient strategy on dual-interface engineering for making high-efficiency and stable perovskite platforms.
文摘The present investigation aims at unveiling the main causes of the recorded disparate phylogeographic patterning among the two highly dispersive coastal crab species Carcinus aestuarii and Pachygrapsus marmoratus in the Mediterranean Sea.For this purpose,available mitochondrial and nuclear data for both species were re-analyzed and investigated for genetic polymorphism and differentiation patterns across three defined geographic scales in their distribution ranges,but also across the same locations in the Mediterranean Sea.The temporal frame of genetic diversification was also determined for both species in order to check whether observed differences in phylogeographic patterns among these coastal decapods could be attributed to different evolutionary histories.The obtained results revealed a more variable and diversified gene pool in the green crab C.aestuarii than the one recorded in the marbled crab P.marmoratus.Lack of significant correlation between pairwise genetic dissimilarities observed among C.aestuarii populations and those detected for P.marmoratus was notably discerned across the same defined Mediterranean locations.This finding indicates that the pattern of pairwise genetic differentiation does not vary in the same way in both examined crab species.Significant outputs of population genetic differentiation,retrieved within both species,were shown to be differently associated with the potential effects of various kinds of isolation processes(related to geography,environment and biogeographic boundary).Evolutionary history reconstruction showed older genetic diversification event in C.aestuarii than the one recorded in P.marmoratus.These recorded temporal frames suggest different modes of genetic diversification in both crab species(glacial vicariance for C.aestuarii and interglacial dispersal for P.marmoratus).They may also provide an explanation for the recorded differences in variation of patterns of population genetic diversity and structure,when integrated with species ecological requirements and life-history traits.
基金PETRONAS Research fund(PRF)under PETRONAS Teknologi Transfer(PTT)Pre-Commercialization—External:YUTP-PRG Cycle 2022(015PBC-020).
文摘Determining the adsorption of shale gas on complex surfaces remains a challenge in molecular simulation studies.Difficulties essentially stem from the need to create a realistic shale structure model in terms of mineral heterogeneityand multiplicity.Moreover,precise characterization of the competitive adsorption of hydrogen andmethane in shale generally requires the experimental determination of the related adsorptive capacity.In thisstudy,the adsorption of adsorbates,methane(CH_(4)),and hydrogen(H_(2))on heterogeneous shale surface modelsof Kaolinite,Orthoclase,Muscovite,Mica,C_(60),and Butane has been simulated in the frame of a moleculardynamic’s numerical technique.The results show that these behaviors are influenced by pressure and potentialenergy.On increasing the pressure from 500 to 2000 psi,the sorption effect for CH_(4)significantly increasesbut shows a decline at a certain stage(if compared to H_(2)).The research findings also indicate that raw shalehas a higher capacity to adsorb CH_(4)compared to hydrogen.However,in shale,this difference is negligible.
文摘作为全球应对气候变化的技术途径之一，碳捕集与封存（Carbon Capture and Storage，CCS）技术受到了世界各国的广泛重视。尽管国人对其尚有陌生，但CCS技术已是当前气候变化领域最前沿、最重大的课题之一，全球积极倡导碳减排的主要能源研究机构、组织和国家，已经一致将CCS技术列为未来的碳减排关键技术，并斥巨资开展CCS技术的相关研究和工业化实践。
文摘Facial Expression Recognition(FER)has been an interesting area of research in places where there is human-computer interaction.Human psychol-ogy,emotions and behaviors can be analyzed in FER.Classifiers used in FER have been perfect on normal faces but have been found to be constrained in occluded faces.Recently,Deep Learning Techniques(DLT)have gained popular-ity in applications of real-world problems including recognition of human emo-tions.The human face reflects emotional states and human intentions.An expression is the most natural and powerful way of communicating non-verbally.Systems which form communications between the two are termed Human Machine Interaction(HMI)systems.FER can improve HMI systems as human expressions convey useful information to an observer.This paper proposes a FER scheme called EECNN(Enhanced Convolution Neural Network with Atten-tion mechanism)to recognize seven types of human emotions with satisfying results in its experiments.Proposed EECNN achieved 89.8%accuracy in classi-fying the images.
基金supported in part by the National Natural Science Foundation of China [62102136]the 2020 Opening Fund for Hubei Key Laboratory of Intelligent Vision Based Monitoring for Hydroelectric Engineering [2020SDSJ06]the Construction Fund for Hubei Key Laboratory of Intelligent Vision Based Monitoring for Hydroelectric Engineering [2019ZYYD007].
文摘Generation-based linguistic steganography is a popular research area of information hiding.The text generative steganographic method based on conditional probability coding is the direction that researchers have recently paid attention to.However,in the course of our experiment,we found that the secret information hiding in the text tends to destroy the statistical distribution characteristics of the original text,which indicates that this method has the problem of the obvious reduction of text quality when the embedding rate increases,and that the topic of generated texts is uncontrollable,so there is still room for improvement in concealment.In this paper,we propose a topic-controlled steganography method which is guided by graph-to-text generation.The proposed model can automatically generate steganographic texts carrying secret messages from knowledge graphs,and the topic of the generated texts is controllable.We also provide a graph path coding method with corresponding detailed algorithms for graph-to-text generation.Different from traditional linguistic steganography methods,we encode the secret information during graph path coding rather than using conditional probability.We test our method in different aspects and compare it with other text generative steganographic methods.The experimental results show that the model proposed in this paper can effectively improve the quality of the generated text and significantly improve the concealment of steganographic text.
文摘At an early point,the diagnosis of pancreatic cancer is mediocre,since the radiologist is skill deficient.Serious threats have been posed due to the above reasons,hence became mandatory for the need of skilled technicians.However,it also became a time-consuming process.Hence the need for automated diagnosis became mandatory.In order to identify the tumor accurately,this research pro-poses a novel Convolution Neural Network(CNN)based superior image classi-fication technique.The proposed deep learning classification strategy has a precision of 97.7%,allowing for more effective usage of the automatically exe-cuted feature extraction technique to diagnose cancer cells.Comparative analysis with CNN-Grey Wolf Optimization(GWO)is carried based on varied testing and training outcomes.The suggested study is carried out at a rate of 90%–10%,80%–20%,and 70%–30%,indicating the robustness of the proposed research work.Outcomes show that the suggested method is effective.GWO-CNN is reli-able and accurate relative to other detection methods available in the literatures.
文摘The aim of the study was to taste mask ciprofloxacin(CP)by using ion-exchange resins(IERs)followed by sustain release of CP by forming interpenetrating polymer network(IPN).IERs based on the copolymerization of acrylic acid with different cross linking agents were synthesised.Drug-resin complexes(DRCs)with three different ratios of drug to IERs(1:1,1:2,1:4)were prepared&evaluated for taste masking by following in vivo and in vitro methods.Human volunteers graded ADC 1:4,acrylic acid-divinyl benzene(ADC-3)resin as tasteless.Characterization studies such as FTIR,SEM,DSC,P-XRD differentiated ADC 1:4,from physical mixture(PM 1:4)and confirmed the formation of complex.In vitro drug release of ADC 1:4 showed complete release of CP within 60 min at simulated gastric fluid(SGF)i.e.pH 1.2.IPN beads were prepared with ADC 1:4 by using sodium alginate(AL)and sodium alginate-chitosan(AL-CS)for sustain release of CP at SGF pH and followed by simulated intestinal fluid(SIF i.e.pH 7.4).FTIR spectra confirmed the formation of IPN beads.The release of CP was sustain at SGF pH(<20%)whereas in SIF media it was more(>75%).The kinetic model of IPN beads showed the release of CP was non-Fickian diffusion type.
基金This work was supported by the grant“Development of models,algorithms for semantic analysis to identify extremist content in web resources and creation the tool for cyber forensics”funded by the Ministry of Digital Development,Innovations and Aerospace industry of the Republic of Kazakhstan.Grant No.IRN AP06851248.Supervisor of the project is Shynar Mussiraliyeva,email:mussiraliyevash@gmail.com.
文摘In this research paper,we propose a corpus for the task of detecting religious extremism in social networks and open sources and compare various machine learning algorithms for the binary classification problem using a previously created corpus,thereby checking whether it is possible to detect extremist messages in the Kazakh language.To do this,the authors trained models using six classic machine-learning algorithms such as Support Vector Machine,Decision Tree,Random Forest,K Nearest Neighbors,Naive Bayes,and Logistic Regression.To increase the accuracy of detecting extremist texts,we used various characteristics such as Statistical Features,TF-IDF,POS,LIWC,and applied oversampling and undersampling techniques to handle imbalanced data.As a result,we achieved 98%accuracy in detecting religious extremism in Kazakh texts for the collected dataset.Testing the developed machine learningmodels in various databases that are often found in everyday life“Jokes”,“News”,“Toxic content”,“Spam”,“Advertising”has also shown high rates of extremism detection.
文摘Cloud computing is the technology that is currently used to provide users with infrastructure,platform,and software services effectively.Under this system,Platform as a Service(PaaS)offers a medium headed for a web development platform that uniformly distributes the requests and resources.Hackers using Denial of service(DoS)and Distributed Denial of Service(DDoS)attacks abruptly interrupt these requests.Even though several existing methods like signature-based,statistical anomaly-based,and stateful protocol analysis are available,they are not sufficient enough to get rid of Denial of service(DoS)and Distributed Denial of Service(DDoS)attacks and hence there is a great need for a definite algorithm.Concerning this issue,we propose an improved hybrid algorithm which is a combination of Multivariate correlation analysis,Spearman coefficient,and mitigation technique.It can easily differentiate common traffic and attack traffic.Not only that,it greatly helps the network to distribute the resources only for authenticated requests.The effects of comparing with the normalized information have shown an extra encouraging detection accuracy of 99%for the numerous DoS attack as well as DDoS attacks.
