With the development of hardware devices and the upgrading of smartphones,a large number of users save privacy-related information in mobile devices,mainly smartphones,which puts forward higher demands on the protecti...With the development of hardware devices and the upgrading of smartphones,a large number of users save privacy-related information in mobile devices,mainly smartphones,which puts forward higher demands on the protection of mobile users’privacy information.At present,mobile user authenticationmethods based on humancomputer interaction have been extensively studied due to their advantages of high precision and non-perception,but there are still shortcomings such as low data collection efficiency,untrustworthy participating nodes,and lack of practicability.To this end,this paper proposes a privacy-enhanced mobile user authentication method with motion sensors,which mainly includes:(1)Construct a smart contract-based private chain and federated learning to improve the data collection efficiency of mobile user authentication,reduce the probability of the model being bypassed by attackers,and reduce the overhead of data centralized processing and the risk of privacy leakage;(2)Use certificateless encryption to realize the authentication of the device to ensure the credibility of the client nodes participating in the calculation;(3)Combine Variational Mode Decomposition(VMD)and Long Short-TermMemory(LSTM)to analyze and model the motion sensor data of mobile devices to improve the accuracy of model certification.The experimental results on the real environment dataset of 1513 people show that themethod proposed in this paper can effectively resist poisoning attacks while ensuring the accuracy and efficiency of mobile user authentication.展开更多
Using an unmanned aerial vehicle (UAV) paired with image semantic segmentation to classify land cover within natural vegetation can promote the development of forest and grassland field. Semantic segmentation normally...Using an unmanned aerial vehicle (UAV) paired with image semantic segmentation to classify land cover within natural vegetation can promote the development of forest and grassland field. Semantic segmentation normally excels in medical and building classification, but its usefulness in mixed forest-grassland ecosystems in semi-arid to semi-humid climates is unknown. This study proposes a new semantic segmentation network of LResU-net in which residual convolution unit (RCU) and loop convolution unit (LCU) are added to the U-net framework to classify images of different land covers generated by UAV high resolution. The selected model enhanced classification accuracy by increasing gradient mapping via RCU and modifying the size of convolution layers via LCU as well as reducing convolution kernels. To achieve this objective, a group of orthophotos were taken at an altitude of 260 m for testing in a natural forest-grassland ecosystem of Keyouqianqi, Inner Mongolia, China, and compared the results with those of three other network models (U-net, ResU-net and LU-net). The results show that both the highest kappa coefficient (0.86) and the highest overall accuracy (93.7%) resulted from LResU-net, and the value of most land covers provided by the producer’s and user’s accuracy generated in LResU-net exceeded 0.85. The pixel-area ratio approach was used to calculate the real areas of 10 different land covers where grasslands were 67.3%. The analysis of the effect of RCU and LCU on the model training performance indicates that the time of each epoch was shortened from U-net (358 s) to LResU-net (282 s). In addition, in order to classify areas that are not distinguishable, unclassified areas were defined and their impact on classification. LResU-net generated significantly more accurate results than the other three models and was regarded as the most appropriate approach to classify land cover in mixed forest-grassland ecosystems.展开更多
Objective:To establish the prevalence and associated risk factors of Schistosoma mansoni(S.mansoni) infection among schoolchildren at a village in Wolaita Zone.Sothern Ethiopia,Methods:A cross-sectional study was carr...Objective:To establish the prevalence and associated risk factors of Schistosoma mansoni(S.mansoni) infection among schoolchildren at a village in Wolaita Zone.Sothern Ethiopia,Methods:A cross-sectional study was carried out among primary schoolchildren.A total of 384 randomly selected study subjects provided stool samples for parasitological examination by Kato-Katz and Formalin-Ether concentration techniques.Secondary parasitological data were obtained from Health Center Laboratory to see the previous history of.S.mansoni infection in the area.Statistical analysis was performed using SPSS software version 16.Results:From the total children examined.85.4% were found positive for at least one helminth infection.S.mansoni infection(81.3% ) was the most prevalent and the prevalence of STH was 32% ..Moderate and heavy infection intensities were only observed in S,mansoni infections.The overall heavy intensity of infection was 56.4% .Contact to Bisarc stream was the most important factor for S.mansoni infection(OR 3.9) followed by herding cattle near the stream(OR2.527).Males were twice more likely to get the infection than females(OR 1.923).Analysis of secondary parasitological data showed that S.mansoni infection was a leading helminthic infection over the past years.Conclusions:The present study found a higher intensity and prevalence of S.mansoni infection in a rural village of Wolaita Zone.Therefore,appropriate integrated control and prevention measures need to be implemented in the study area.展开更多
A polynomial algorithm for the regularity problem of weak and branching bisimilarity on totally normed process algebra(PA) processes is given. Its time complexity is O(n3+ mn), where n is the number of transition rule...A polynomial algorithm for the regularity problem of weak and branching bisimilarity on totally normed process algebra(PA) processes is given. Its time complexity is O(n3+ mn), where n is the number of transition rules and m is the maximal length of the rules. The algorithm works for totally normed basic process algebra(BPA) as well as basic parallel process(BPP).展开更多
Because of their high efficiency, antibiotics have long been the primary treatment for infections, but the rise of drug-resistant pathogens has become a therapeutic concern. Nanoparticles, as novel biomaterials, are c...Because of their high efficiency, antibiotics have long been the primary treatment for infections, but the rise of drug-resistant pathogens has become a therapeutic concern. Nanoparticles, as novel biomaterials, are currently gaining global attention to combat them. Drug-resistant diseases may need the use of nanoparticles as a viable therapeutic option. By altering target locations and enzymes, decreasing cell permeability, inactivating enzymes, and increasing efflux by overexpressing efflux pumps, they can bypass conventional resistance mechanisms. Therefore, understanding how metal and metal oxide nanoparticles affect microorganisms that are resistant to antimicrobial drugs is the main objective of this review. Accordingly, the uses of metal and metal oxide nanoparticles in the fight against drug-resistant diseases appear promising. However, their mechanism of action, dose, and possible long-term effects require special attention and future research. Furthermore, repeated use of silver nanoparticles may cause gram-negative microorganisms to acquire resistance, necessitating additional study.展开更多
We present results of numerical simulations of the tensor-valued elliptic-parabolic PDE model for biological network formation.The numerical method is based on a nonlinear finite difference scheme on a uniform Cartesi...We present results of numerical simulations of the tensor-valued elliptic-parabolic PDE model for biological network formation.The numerical method is based on a nonlinear finite difference scheme on a uniform Cartesian grid in a two-dimensional(2D)domain.The focus is on the impact of different discretization methods and choices of regularization parameters on the symmetry of the numerical solution.In particular,we show that using the symmetric alternating direction implicit(ADI)method for time discretization helps preserve the symmetry of the solution,compared to the(non-symmetric)ADI method.Moreover,we study the effect of the regularization by the isotropic background permeability(r>0),showing that the increased condition number of the elliptic problem due to decreasing value of r leads to loss of symmetry.We show that in this case,neither the use of the symmetric ADI method preserves the symmetry of the solution.Finally,we perform the numerical error analysis of our method making use of the Wasserstein distance.展开更多
The advancement and growth of nanotechnology lead to realizing new and novel multi-metallic nanostructures with well-defined sizes and morphology,resulting in an improvement in their performance in various catalytic a...The advancement and growth of nanotechnology lead to realizing new and novel multi-metallic nanostructures with well-defined sizes and morphology,resulting in an improvement in their performance in various catalytic applications.The trimetallic nanostructured materials are synthesized and designed in different architectures for energy conversion electrocatalysis.The as-synthesized trimetallic nanostructures have found unique physiochemical properties due to the synergistic combination of the three different metals in their structures.A vast array of approaches such as hydrothermal,solvothermal,seedgrowth,galvanic replacement reaction,biological,and other methods are employed to synthesize the trimetallic nanostructures.Noteworthy,the trimetallic nanostructures showed better performance and durability in the electrocatalytic fuel cells.In the present review,we provide a comprehensive overview of the recent strategies employed for synthesizing trimetallic nanostructures and their energy-related applications.With a particular focus on hydrogen evolution,alcohol oxidations,oxygen evolution,and others,we highlight the latest achievements in the field.展开更多
The availability of pulmonary nodules in CT scan image of lung does not completely specify cancer.The noise in an image and morphology of nodules,like shape and size has an implicit and complex association with cancer...The availability of pulmonary nodules in CT scan image of lung does not completely specify cancer.The noise in an image and morphology of nodules,like shape and size has an implicit and complex association with cancer,and thus,a careful analysis should be mandatory on every suspected nodules and the combination of information of every nodule.In this paper,we introduce a“denoising first”two-path convolutional neural network(DFD-Net)to address this complexity.The introduced model is composed of denoising and detection part in an end to end manner.First,a residual learning denoising model(DR-Net)is employed to remove noise during the preprocessing stage.Then,a two-path convolutional neural network which takes the denoised image by DR-Net as an input to detect lung cancer is employed.The two paths focus on the joint integration of local and global features.To this end,each path employs different receptive field size which aids to model local and global dependencies.To further polish our model performance,in different way from the conventional feature concatenation approaches which directly concatenate two sets of features from different CNN layers,we introduce discriminant correlation analysis to concatenate more representative features.Finally,we also propose a retraining technique that allows us to overcome difficulties associated to the image labels imbalance.We found that this type of model easily first reduce noise in an image,balances the receptive field size effect,affords more representative features,and easily adaptable to the inconsistency among nodule shape and size.Our intensive experimental results achieved competitive results.展开更多
This paper is concerned with a delay difference system. Some interesting results are obtained for the asymptotic behaviors of the system. Our theorems improve the corresponding theorems in the relevant literature by r...This paper is concerned with a delay difference system. Some interesting results are obtained for the asymptotic behaviors of the system. Our theorems improve the corresponding theorems in the relevant literature by removing the restriction of the initial conditions.展开更多
Rare earth elements doped with zinc oxide nanoparticles(ZnO-NPs)have gathered a remarkable interest for their potential credence due to their high luminescent intensities.In this research,europium ion(Eu^(3+))doped an...Rare earth elements doped with zinc oxide nanoparticles(ZnO-NPs)have gathered a remarkable interest for their potential credence due to their high luminescent intensities.In this research,europium ion(Eu^(3+))doped and undoped zinc oxide nanoparticles(Eu_(1-x)Zn_(x)O)(x=0.03,0.06,0.09)were synthesized via co-precipitation method.The effects of varying the concentration of the europium ion(Eu^(3+))on the structure and optical properties were investigated.The structural and optical properties of europium ion(Eu^(3+))doped and un-doped zinc oxide nanoparticles(ZnO NPs)were characterized by XRD,UV-Vis,Photoluminescence,and FT-IR Spectroscopy.The XRD results reveal the Europium ion(Eu^(3+))was successfully incorporated into the zinc oxide host matrix and made highly crystalline.All the synthesized samples have a hexagonal wurtzite structure.UV-Vis absorption spectra measurements revealed increasing the dopant concentration increases the energy band compared to the undoped zinc oxide nanoparticles.Photoluminescence spectra confirmed doping europium ion(Eu^(3+))predominantly enhances the visible emission with various series characteristics of blue and green emission compared to undoped zinc oxide nanoparticles(ZnO NPs)which exhibits the near band emission.Fourier Transform Infra Red(FTIR)spectral analysis indicated the presence of functional groups attached to Europium ion(Eu^(3+))doped and undoped zinc oxide nanoparticles(ZnO NPs).In addition,the presence of an additional spectrum band with increasing the concentration of dopant amount demonstrates that europium ions(Eu^(3+))were successfully substituted into the zinc oxide host matrix.The photocatalytic activity response is investigated using organic methylene blue(MB)as a pollutant model and dopant played the role in enhancing the photocatalytic kinetics because Eu^(3+)ions act as an electron acceptor to promote charge separation and photocatalytic activity.The photocatalytic activity of europium ion(Eu^(3+))doped zinc oxide nanoparticles has higher performance than undoped zinc oxide nanoparticles(ZnO-NPs)since the dopant has the potential candidate in minimizing the recombination probability which in turn improves the performance of photocatalytic activities which makes it suitable for the local environment.展开更多
基金Wenzhou Key Scientific and Technological Projects(No.ZG2020031)Wenzhou Polytechnic Research Projects(No.WZY2021002)+3 种基金Key R&D Projects in Zhejiang Province(No.2021C01117)Major Program of Natural Science Foundation of Zhejiang Province(LD22F020002)the Cloud Security Key Technology Research Laboratorythe Researchers Supporting Project Number(RSP2023R509),King Saud University,Riyadh,Saudi Arabia.
文摘With the development of hardware devices and the upgrading of smartphones,a large number of users save privacy-related information in mobile devices,mainly smartphones,which puts forward higher demands on the protection of mobile users’privacy information.At present,mobile user authenticationmethods based on humancomputer interaction have been extensively studied due to their advantages of high precision and non-perception,but there are still shortcomings such as low data collection efficiency,untrustworthy participating nodes,and lack of practicability.To this end,this paper proposes a privacy-enhanced mobile user authentication method with motion sensors,which mainly includes:(1)Construct a smart contract-based private chain and federated learning to improve the data collection efficiency of mobile user authentication,reduce the probability of the model being bypassed by attackers,and reduce the overhead of data centralized processing and the risk of privacy leakage;(2)Use certificateless encryption to realize the authentication of the device to ensure the credibility of the client nodes participating in the calculation;(3)Combine Variational Mode Decomposition(VMD)and Long Short-TermMemory(LSTM)to analyze and model the motion sensor data of mobile devices to improve the accuracy of model certification.The experimental results on the real environment dataset of 1513 people show that themethod proposed in this paper can effectively resist poisoning attacks while ensuring the accuracy and efficiency of mobile user authentication.
基金The work was supported by the Fundamental Research Funds for the Central Universities(NO.2021ZY92)major program of State Administration of Forestry and Grassland“Study on the assessment technologies for ecologically restoring the degraded grasslands”(20,200,507).
文摘Using an unmanned aerial vehicle (UAV) paired with image semantic segmentation to classify land cover within natural vegetation can promote the development of forest and grassland field. Semantic segmentation normally excels in medical and building classification, but its usefulness in mixed forest-grassland ecosystems in semi-arid to semi-humid climates is unknown. This study proposes a new semantic segmentation network of LResU-net in which residual convolution unit (RCU) and loop convolution unit (LCU) are added to the U-net framework to classify images of different land covers generated by UAV high resolution. The selected model enhanced classification accuracy by increasing gradient mapping via RCU and modifying the size of convolution layers via LCU as well as reducing convolution kernels. To achieve this objective, a group of orthophotos were taken at an altitude of 260 m for testing in a natural forest-grassland ecosystem of Keyouqianqi, Inner Mongolia, China, and compared the results with those of three other network models (U-net, ResU-net and LU-net). The results show that both the highest kappa coefficient (0.86) and the highest overall accuracy (93.7%) resulted from LResU-net, and the value of most land covers provided by the producer’s and user’s accuracy generated in LResU-net exceeded 0.85. The pixel-area ratio approach was used to calculate the real areas of 10 different land covers where grasslands were 67.3%. The analysis of the effect of RCU and LCU on the model training performance indicates that the time of each epoch was shortened from U-net (358 s) to LResU-net (282 s). In addition, in order to classify areas that are not distinguishable, unclassified areas were defined and their impact on classification. LResU-net generated significantly more accurate results than the other three models and was regarded as the most appropriate approach to classify land cover in mixed forest-grassland ecosystems.
文摘Objective:To establish the prevalence and associated risk factors of Schistosoma mansoni(S.mansoni) infection among schoolchildren at a village in Wolaita Zone.Sothern Ethiopia,Methods:A cross-sectional study was carried out among primary schoolchildren.A total of 384 randomly selected study subjects provided stool samples for parasitological examination by Kato-Katz and Formalin-Ether concentration techniques.Secondary parasitological data were obtained from Health Center Laboratory to see the previous history of.S.mansoni infection in the area.Statistical analysis was performed using SPSS software version 16.Results:From the total children examined.85.4% were found positive for at least one helminth infection.S.mansoni infection(81.3% ) was the most prevalent and the prevalence of STH was 32% ..Moderate and heavy infection intensities were only observed in S,mansoni infections.The overall heavy intensity of infection was 56.4% .Contact to Bisarc stream was the most important factor for S.mansoni infection(OR 3.9) followed by herding cattle near the stream(OR2.527).Males were twice more likely to get the infection than females(OR 1.923).Analysis of secondary parasitological data showed that S.mansoni infection was a leading helminthic infection over the past years.Conclusions:The present study found a higher intensity and prevalence of S.mansoni infection in a rural village of Wolaita Zone.Therefore,appropriate integrated control and prevention measures need to be implemented in the study area.
基金the National Natural Science Foundation of China(Nos.61261130589 and 61033002)the Fund of the Science and Technology Commission of Shanghai Municipality(No.11XD1402800)
文摘A polynomial algorithm for the regularity problem of weak and branching bisimilarity on totally normed process algebra(PA) processes is given. Its time complexity is O(n3+ mn), where n is the number of transition rules and m is the maximal length of the rules. The algorithm works for totally normed basic process algebra(BPA) as well as basic parallel process(BPP).
文摘Because of their high efficiency, antibiotics have long been the primary treatment for infections, but the rise of drug-resistant pathogens has become a therapeutic concern. Nanoparticles, as novel biomaterials, are currently gaining global attention to combat them. Drug-resistant diseases may need the use of nanoparticles as a viable therapeutic option. By altering target locations and enzymes, decreasing cell permeability, inactivating enzymes, and increasing efflux by overexpressing efflux pumps, they can bypass conventional resistance mechanisms. Therefore, understanding how metal and metal oxide nanoparticles affect microorganisms that are resistant to antimicrobial drugs is the main objective of this review. Accordingly, the uses of metal and metal oxide nanoparticles in the fight against drug-resistant diseases appear promising. However, their mechanism of action, dose, and possible long-term effects require special attention and future research. Furthermore, repeated use of silver nanoparticles may cause gram-negative microorganisms to acquire resistance, necessitating additional study.
文摘We present results of numerical simulations of the tensor-valued elliptic-parabolic PDE model for biological network formation.The numerical method is based on a nonlinear finite difference scheme on a uniform Cartesian grid in a two-dimensional(2D)domain.The focus is on the impact of different discretization methods and choices of regularization parameters on the symmetry of the numerical solution.In particular,we show that using the symmetric alternating direction implicit(ADI)method for time discretization helps preserve the symmetry of the solution,compared to the(non-symmetric)ADI method.Moreover,we study the effect of the regularization by the isotropic background permeability(r>0),showing that the increased condition number of the elliptic problem due to decreasing value of r leads to loss of symmetry.We show that in this case,neither the use of the symmetric ADI method preserves the symmetry of the solution.Finally,we perform the numerical error analysis of our method making use of the Wasserstein distance.
文摘The advancement and growth of nanotechnology lead to realizing new and novel multi-metallic nanostructures with well-defined sizes and morphology,resulting in an improvement in their performance in various catalytic applications.The trimetallic nanostructured materials are synthesized and designed in different architectures for energy conversion electrocatalysis.The as-synthesized trimetallic nanostructures have found unique physiochemical properties due to the synergistic combination of the three different metals in their structures.A vast array of approaches such as hydrothermal,solvothermal,seedgrowth,galvanic replacement reaction,biological,and other methods are employed to synthesize the trimetallic nanostructures.Noteworthy,the trimetallic nanostructures showed better performance and durability in the electrocatalytic fuel cells.In the present review,we provide a comprehensive overview of the recent strategies employed for synthesizing trimetallic nanostructures and their energy-related applications.With a particular focus on hydrogen evolution,alcohol oxidations,oxygen evolution,and others,we highlight the latest achievements in the field.
基金This work was partially funded by the national Key research and development program of China(2018YFC0806802 and 2018YFC0832105)and Bule Hora University of Ethiopia.
文摘The availability of pulmonary nodules in CT scan image of lung does not completely specify cancer.The noise in an image and morphology of nodules,like shape and size has an implicit and complex association with cancer,and thus,a careful analysis should be mandatory on every suspected nodules and the combination of information of every nodule.In this paper,we introduce a“denoising first”two-path convolutional neural network(DFD-Net)to address this complexity.The introduced model is composed of denoising and detection part in an end to end manner.First,a residual learning denoising model(DR-Net)is employed to remove noise during the preprocessing stage.Then,a two-path convolutional neural network which takes the denoised image by DR-Net as an input to detect lung cancer is employed.The two paths focus on the joint integration of local and global features.To this end,each path employs different receptive field size which aids to model local and global dependencies.To further polish our model performance,in different way from the conventional feature concatenation approaches which directly concatenate two sets of features from different CNN layers,we introduce discriminant correlation analysis to concatenate more representative features.Finally,we also propose a retraining technique that allows us to overcome difficulties associated to the image labels imbalance.We found that this type of model easily first reduce noise in an image,balances the receptive field size effect,affords more representative features,and easily adaptable to the inconsistency among nodule shape and size.Our intensive experimental results achieved competitive results.
基金Project supported by NNSF of China (No. 10271044).
文摘This paper is concerned with a delay difference system. Some interesting results are obtained for the asymptotic behaviors of the system. Our theorems improve the corresponding theorems in the relevant literature by removing the restriction of the initial conditions.
基金financially supported by Adama Science and Technology University and the Ministry of Innovation and Technology of Ethiopia.
文摘Rare earth elements doped with zinc oxide nanoparticles(ZnO-NPs)have gathered a remarkable interest for their potential credence due to their high luminescent intensities.In this research,europium ion(Eu^(3+))doped and undoped zinc oxide nanoparticles(Eu_(1-x)Zn_(x)O)(x=0.03,0.06,0.09)were synthesized via co-precipitation method.The effects of varying the concentration of the europium ion(Eu^(3+))on the structure and optical properties were investigated.The structural and optical properties of europium ion(Eu^(3+))doped and un-doped zinc oxide nanoparticles(ZnO NPs)were characterized by XRD,UV-Vis,Photoluminescence,and FT-IR Spectroscopy.The XRD results reveal the Europium ion(Eu^(3+))was successfully incorporated into the zinc oxide host matrix and made highly crystalline.All the synthesized samples have a hexagonal wurtzite structure.UV-Vis absorption spectra measurements revealed increasing the dopant concentration increases the energy band compared to the undoped zinc oxide nanoparticles.Photoluminescence spectra confirmed doping europium ion(Eu^(3+))predominantly enhances the visible emission with various series characteristics of blue and green emission compared to undoped zinc oxide nanoparticles(ZnO NPs)which exhibits the near band emission.Fourier Transform Infra Red(FTIR)spectral analysis indicated the presence of functional groups attached to Europium ion(Eu^(3+))doped and undoped zinc oxide nanoparticles(ZnO NPs).In addition,the presence of an additional spectrum band with increasing the concentration of dopant amount demonstrates that europium ions(Eu^(3+))were successfully substituted into the zinc oxide host matrix.The photocatalytic activity response is investigated using organic methylene blue(MB)as a pollutant model and dopant played the role in enhancing the photocatalytic kinetics because Eu^(3+)ions act as an electron acceptor to promote charge separation and photocatalytic activity.The photocatalytic activity of europium ion(Eu^(3+))doped zinc oxide nanoparticles has higher performance than undoped zinc oxide nanoparticles(ZnO-NPs)since the dopant has the potential candidate in minimizing the recombination probability which in turn improves the performance of photocatalytic activities which makes it suitable for the local environment.
