To achieve online automatic classification of product is a great need of e-commerce de-velopment. By analyzing the characteristics of product images, we proposed a fast supervised image classifier which is based on cl...To achieve online automatic classification of product is a great need of e-commerce de-velopment. By analyzing the characteristics of product images, we proposed a fast supervised image classifier which is based on class-specific Pyramid Histogram Of Words (PHOW) descriptor and Im-age-to-Class distance (PHOW/I2C). In the training phase, the local features are densely sampled and represented as soft-voting PHOW descriptors, and then the class-specific descriptors are built with the means and variances of distribution of each visual word in each labelled class. For online testing, the normalized chi-square distance is calculated between the descriptor of query image and each class-specific descriptor. The class label corresponding to the least I2C distance is taken as the final winner. Experiments demonstrate the effectiveness and quickness of our method in the tasks of product clas-sification.展开更多
The functional properties of glasses are governed by their formation history and the complex relaxation processes they undergo.However,under extreme conditions,glass behaviors are still elusive.In this study,we employ...The functional properties of glasses are governed by their formation history and the complex relaxation processes they undergo.However,under extreme conditions,glass behaviors are still elusive.In this study,we employ simulations with varied protocols to evaluate the effectiveness of different descriptors in predicting mechanical properties across both low-and high-pressure regimes.Our findings demonstrate that conventional structural and configurational descriptors fail to correlate with the mechanical response following pressure release,whereas the activation energy descriptor exhibits robust linearity with shear modulus after correcting for pressure effects.Notably,the soft mode parameter emerges as an ideal and computationally efficient alternative for capturing this mechanical behavior.These findings provide critical insights into the influence of pressure on glassy properties,integrating the distinct features of compressed glasses into a unified theoretical framework.展开更多
Modified 1-ethyl-3-(3-dimethylaminopropyl)carbodiimide(EDC)method was employed to synthesize the artificial antigen of norfloxacin(NOR),and New Zealand rabbits were used to produce anti-NOR polyclonal antibody(pAb).Ba...Modified 1-ethyl-3-(3-dimethylaminopropyl)carbodiimide(EDC)method was employed to synthesize the artificial antigen of norfloxacin(NOR),and New Zealand rabbits were used to produce anti-NOR polyclonal antibody(pAb).Based on the checkerboard titration,an indirect competitive enzyme-linked immunosorbent assay(icELISA) standard curve was established.This assay was sensitive and had a working range from 0.12 to 68.40 ng/ml,with the half maximal inhibitory concentration(IC50)and limit of detection(LOD)values of 2.7 ng/ml and 0.06 ng/ml,respectively.The produced pAb exhibited high cross-reactivity to fluoroquinolones(FQs)tested,and the IC50 values to enoxacin,ciprofloxacin,and pefloxacin were 3.1,3.4,and 4.1 ng/ml,respectively.It also indicated that the concentrations of NaOH and methanol in assay buffer should not be higher than 10%and 30%.When spiked in milk at 5,20,and 50 ng/ml,the recoveries for NOR,enoxacin,ciprofloxacin,and pefloxacin ranged 90.5%-98.0%,84.0%-95.2%,94.0%-106.0%,and 89.5%-100.0%,respectively.The results suggest that this class-specific pAb-based icELISA could be utilized for the primary screening of FQ residues in animal-original products.展开更多
The control of solute segregation at grain boundaries is of significance in engineering alloy properties.However,there is currently a lack of a physics-informed predictive model for estimating solute segre-gation ener...The control of solute segregation at grain boundaries is of significance in engineering alloy properties.However,there is currently a lack of a physics-informed predictive model for estimating solute segre-gation energies.Here we propose novel electronic descriptors for grain-boundary segregation based on the valence,electronegativity and size of solutes.By integrating the non-local coordination number of surfaces,we build a predictive analytic framework for evaluating the segregation energies across various solutes,grain-boundary structures,and segregation sites.This framework uncovers not only the coupling rule of solutes and matrices,but also the origin of solute-segregation determinants,which stems from the d-and sp-states hybridization in alloying.Our scheme establishes a novel picture for grain-boundary segregation and provides a useful tool for the design of advanced alloys.展开更多
Computational approaches,encompassing both physics-based and machine learning(ML)methodologies,have gained substantial traction in drug repurposing efforts targeting specific therapeutic entities.The human dopamine(DA...Computational approaches,encompassing both physics-based and machine learning(ML)methodologies,have gained substantial traction in drug repurposing efforts targeting specific therapeutic entities.The human dopamine(DA)transporter(hDAT)is the primary therapeutic target of numerous psychiatric medications.However,traditional hDAT-targeting drugs,which interact with the primary binding site,encounter significant limitations,including addictive potential and stimulant effects.In this study,we propose an integrated workflow combining virtual screening based on weighted holistic atom localization and entity shape(WHALES)descriptors with in vitro experimental validation to repurpose novel hDAT-targeting drugs.Initially,WHALES descriptors facilitated a similarity search,employing four benztropine-like atypical inhibitors known to bind hDAT's allosteric site as templates.Consequently,from a compound library of 4,921 marketed and clinically tested drugs,we identified 27 candidate atypical inhibitors.Subsequently,ADMETlab was employed to predict the pharmacokinetic and toxicological properties of these candidates,while induced-fit docking(IFD)was performed to estimate their binding affinities.Six compounds were selected for in vitro assessments of neurotransmitter reuptake inhibitory activities.Among these,three exhibited significant inhibitory potency,with half maximal inhibitory concentration(IC_(50))values of 0.753μM,0.542μM,and 1.210μM,respectively.Finally,molecular dynamics(MD)simulations and end-point binding free energy analyses were conducted to elucidate and confirm the inhibitory mechanisms of the repurposed drugs against hDAT in its inward-open conformation.In conclusion,our study not only identifies promising active compounds as potential atypical inhibitors for novel therapeutic drug development targeting hDAT but also validates the effectiveness of our integrated computational and experimental workflow for drug repurposing.展开更多
Retinal Optical Coherence Tomography (OCT) images, a non-invasive imaging technique, have become a standard retinal disease detection tool. Due to disease, there are morphological and textural changes in the layers of...Retinal Optical Coherence Tomography (OCT) images, a non-invasive imaging technique, have become a standard retinal disease detection tool. Due to disease, there are morphological and textural changes in the layers of the retina. Classifying OCT images is challenging, as the morphological manifestations of different diseases may be similar. The OCT images capture the reflectivity characteristics of the retinal tissues. Retinal diseases change the reflectivity property of retinal tissues, resulting in texture variations in OCT images. We propose a hybrid approach to OCT image classification in which the Convolution Neural Network (CNN) model is trained using Multiple Neighborhood Local Ternary Pattern (MNLTP) texture descriptors of the OCT images dataset for a robust disease prediction system. Parallel deep CNN (PDCNN) is proposed to improve feature representation and generalizability. The MNLTP-PDCNN model is tested on two publicly available datasets. The parameter values Accuracy, Precision, Recall, and F1-Score are calculated. The best accuracy obtained specifying the model’s overall performance is 93.98% and 99% for the NEH and OCT2017 datasets, respectively. With the proposed architecture, comparable performance is obtained with a subset of the original OCT2017 data set and a comparatively smaller number of trainable parameters (1.6 million, 1.8 million, and 2.3 million for a single CNN branch, two parallel CNN branches, and three parallel network branches, respectively), compared to off-the-shelf CNN models. Hence, the proposed approach is suitable for real-time OCT image classification systems with fast training of the CNN model and reduced memory requirement for computations.展开更多
An optimal fuzzy tracking synthesis for nonlinear discrete-time descriptor systems is discussed through the Parallel Distributed Compensation(PDC)approach and the Proportional-Difference(P-D)feedback framework.Based o...An optimal fuzzy tracking synthesis for nonlinear discrete-time descriptor systems is discussed through the Parallel Distributed Compensation(PDC)approach and the Proportional-Difference(P-D)feedback framework.Based on the Takagi-Sugeno Fuzzy Descriptor Model(T-SFDM),a nonlinear discrete-time descriptor system is represented as several linear fuzzy subsystems,which facilitates the linear P-D feedback technique and streamlines the fuzzy controller design process.Leveraging the P-D feedback fuzzy controller,the closed-loop T-SFDM can be transformed into a standard system that guarantees non-impulsiveness and causality for the nonlinear discrete-time descriptor system.In view of the disturbance problems,a passive performance constraint is incorporated into the fuzzy tracking synthesis to achieve dissipativity of disturbance energy.To achieve a better balance between state and control responses,the H2 performance requirement is considered and a minimization constraint is applied to optimize the H2 index.It is observed that there is a lack of research focusing on both disturbance and control input issues in nonlinear descriptor systems.Extending the Lyapunov theory,a stability analysis method is proposed for the tracking purpose with the combination of the free-weighting matrix to relax the analysis process while complying multiple performance constraints.Finally,two simulation examples are presented to demonstrate the feasibility and applicability of the proposed approach in practical control scenarios for nonlinear descriptor systems.展开更多
Unmanned aerial vehicle laser scanning(ULS)and terrestrial laser scanning(TLS)systems are effective ways to capture forest structures from top and side views,respectively.The registration of TLS and ULS data is a prer...Unmanned aerial vehicle laser scanning(ULS)and terrestrial laser scanning(TLS)systems are effective ways to capture forest structures from top and side views,respectively.The registration of TLS and ULS data is a prerequisite for a comprehensive forest structure representation.Conventional registration methods based on geometric features(e.g.,points,lines,and planes)are likely to fail due to the irregular natural point distributions of forest point clouds.Currently,automatic registration methods for forest point clouds typically rely on tree attributes(such as tree position and stem diameter).However,these methods are often unsuitable for forests with diverse compositions,complex terrains,irregular tree layouts,and insufficient common trees.In this study,an automated method is proposed to register ULS and TLS forest point clouds using ground points as registration primitives,which operates independently of tree attribute extraction and is estimated to reduce processing time by over 50%.A new evaluation method for registration accuracy evaluation is proposed,where transformation parameters from each TLS scan to the ULS obtained by the proposed registration algorithm are used to derive transformation parameters between TLS scans,which are then compared to reference parameters obtained using artificial spherical targets.Conventional ULS-TLS registration evaluation methods mostly rely on the manual corresponding points selection that is subject to inherent subjective errors,or control points in both TLS and ULS data that are difficult to collect.The proposed method presents an objective and accurate solution for ULS-TLS registration accuracy evaluation that effectively eliminates these limitations.The proposed method was tested on 12 plots with diverse stem densities,tree species,and altitudes located in a mountain forest.A total of 124 TLS scans were successfully registered to ULS data.The registration accuracy was assessed using both the conventional evaluation method and the proposed new evaluation method,with average rotation errors of 2.03 and 2.06 mrad,and average translation errors of 7.63 and 6.51 cm,respectively.The registration accuracies demonstrate that the proposed algorithm effectively and accurately registers TLS to ULS point clouds.展开更多
In order to obtain a large number of correct matches with high accuracy,this article proposes a robust wide baseline point matching method,which is based on Scott s proximity matrix and uses the scale invariant featur...In order to obtain a large number of correct matches with high accuracy,this article proposes a robust wide baseline point matching method,which is based on Scott s proximity matrix and uses the scale invariant feature transform (SIFT). First,the distance between SIFT features is included in the equations of the proximity matrix to measure the similarity between two feature points; then the normalized cross correlation (NCC) used in Scott s method,which has been modified with adaptive scale and orientation,...展开更多
This paper considers the design problem of static output feedback H ∞ controllers for descriptor linear systems with linear matrix inequality (LMI) approach. Necessary and sufficient conditions for the existence of...This paper considers the design problem of static output feedback H ∞ controllers for descriptor linear systems with linear matrix inequality (LMI) approach. Necessary and sufficient conditions for the existence of a static output feedback H ∞ controller are given in terms of LMIs. Furthermore, the design method of H ∞ controllers is provided using the solutions to the LMIs.展开更多
The precondition of realizing feedback controlling DC DC converter to avoid chaotic state is to judge the behavior of the converter and take corresponding measures. In this paper, the output signals under different ci...The precondition of realizing feedback controlling DC DC converter to avoid chaotic state is to judge the behavior of the converter and take corresponding measures. In this paper, the output signals under different circuit parameters of the PWM buck converter have been analyzed. The method of using Fourier descriptor to extract output signals characteristics is put forward and proved to be a gist of identifying and classifying the behavior of DC DC converter. This method can establish a good foundation fo...展开更多
基金Supported by the Major Funded Project of National Natural Science Foundation of China (No. 70890083)
文摘To achieve online automatic classification of product is a great need of e-commerce de-velopment. By analyzing the characteristics of product images, we proposed a fast supervised image classifier which is based on class-specific Pyramid Histogram Of Words (PHOW) descriptor and Im-age-to-Class distance (PHOW/I2C). In the training phase, the local features are densely sampled and represented as soft-voting PHOW descriptors, and then the class-specific descriptors are built with the means and variances of distribution of each visual word in each labelled class. For online testing, the normalized chi-square distance is calculated between the descriptor of query image and each class-specific descriptor. The class label corresponding to the least I2C distance is taken as the final winner. Experiments demonstrate the effectiveness and quickness of our method in the tasks of product clas-sification.
基金supported by the National Natural Science Foundation of China (Grant Nos.T2325004 and 52161160330)the National Natural Science Foundation of China (Grants No.12504233)+2 种基金Advanced MaterialsNational Science and Technology Major Project (Grant No.2024ZD0606900)the Talent Hub for “AI+New Materials” Basic Researchthe Key Research and Development Program of Ningbo (Grant No.2025Z088)。
文摘The functional properties of glasses are governed by their formation history and the complex relaxation processes they undergo.However,under extreme conditions,glass behaviors are still elusive.In this study,we employ simulations with varied protocols to evaluate the effectiveness of different descriptors in predicting mechanical properties across both low-and high-pressure regimes.Our findings demonstrate that conventional structural and configurational descriptors fail to correlate with the mechanical response following pressure release,whereas the activation energy descriptor exhibits robust linearity with shear modulus after correcting for pressure effects.Notably,the soft mode parameter emerges as an ideal and computationally efficient alternative for capturing this mechanical behavior.These findings provide critical insights into the influence of pressure on glassy properties,integrating the distinct features of compressed glasses into a unified theoretical framework.
基金Project supported by the Henan Innovation Project for University Prominent Research Talents(No.2010HASTIT026)the Key Scientific & Technological Project of Education Department in Henan Province of China(No.2011A230003)
文摘Modified 1-ethyl-3-(3-dimethylaminopropyl)carbodiimide(EDC)method was employed to synthesize the artificial antigen of norfloxacin(NOR),and New Zealand rabbits were used to produce anti-NOR polyclonal antibody(pAb).Based on the checkerboard titration,an indirect competitive enzyme-linked immunosorbent assay(icELISA) standard curve was established.This assay was sensitive and had a working range from 0.12 to 68.40 ng/ml,with the half maximal inhibitory concentration(IC50)and limit of detection(LOD)values of 2.7 ng/ml and 0.06 ng/ml,respectively.The produced pAb exhibited high cross-reactivity to fluoroquinolones(FQs)tested,and the IC50 values to enoxacin,ciprofloxacin,and pefloxacin were 3.1,3.4,and 4.1 ng/ml,respectively.It also indicated that the concentrations of NaOH and methanol in assay buffer should not be higher than 10%and 30%.When spiked in milk at 5,20,and 50 ng/ml,the recoveries for NOR,enoxacin,ciprofloxacin,and pefloxacin ranged 90.5%-98.0%,84.0%-95.2%,94.0%-106.0%,and 89.5%-100.0%,respectively.The results suggest that this class-specific pAb-based icELISA could be utilized for the primary screening of FQ residues in animal-original products.
基金support from the National Natural Science Foundation of China(Nos.22173034,11974128,52130101)the Opening Project of State Key Laboratory of High Performance Ceramics and Superfine Microstructure(No.SKL202206SIC)+2 种基金the Program of Innovative Research Team(in Science and Technology)in University of Jilin Province,the Program for JLU(Jilin University)Science and Technology Innovative Research Team(No.2017TD-09)the Fundamental Research Funds for the Central Universitiesthe computing resources of the High Performance Computing Center of Jilin University,China.
文摘The control of solute segregation at grain boundaries is of significance in engineering alloy properties.However,there is currently a lack of a physics-informed predictive model for estimating solute segre-gation energies.Here we propose novel electronic descriptors for grain-boundary segregation based on the valence,electronegativity and size of solutes.By integrating the non-local coordination number of surfaces,we build a predictive analytic framework for evaluating the segregation energies across various solutes,grain-boundary structures,and segregation sites.This framework uncovers not only the coupling rule of solutes and matrices,but also the origin of solute-segregation determinants,which stems from the d-and sp-states hybridization in alloying.Our scheme establishes a novel picture for grain-boundary segregation and provides a useful tool for the design of advanced alloys.
基金supported by the Natural Science Foundation of China(Grant No.:21505009)the Natural Science Foundation of Chongqing,China(Grant No.:2023NSCQ-MSX0140)the Open Project of Central Nervous System Drug Key Laboratory of Sichuan Province,China(Grant No.:230012-01SZ).
文摘Computational approaches,encompassing both physics-based and machine learning(ML)methodologies,have gained substantial traction in drug repurposing efforts targeting specific therapeutic entities.The human dopamine(DA)transporter(hDAT)is the primary therapeutic target of numerous psychiatric medications.However,traditional hDAT-targeting drugs,which interact with the primary binding site,encounter significant limitations,including addictive potential and stimulant effects.In this study,we propose an integrated workflow combining virtual screening based on weighted holistic atom localization and entity shape(WHALES)descriptors with in vitro experimental validation to repurpose novel hDAT-targeting drugs.Initially,WHALES descriptors facilitated a similarity search,employing four benztropine-like atypical inhibitors known to bind hDAT's allosteric site as templates.Consequently,from a compound library of 4,921 marketed and clinically tested drugs,we identified 27 candidate atypical inhibitors.Subsequently,ADMETlab was employed to predict the pharmacokinetic and toxicological properties of these candidates,while induced-fit docking(IFD)was performed to estimate their binding affinities.Six compounds were selected for in vitro assessments of neurotransmitter reuptake inhibitory activities.Among these,three exhibited significant inhibitory potency,with half maximal inhibitory concentration(IC_(50))values of 0.753μM,0.542μM,and 1.210μM,respectively.Finally,molecular dynamics(MD)simulations and end-point binding free energy analyses were conducted to elucidate and confirm the inhibitory mechanisms of the repurposed drugs against hDAT in its inward-open conformation.In conclusion,our study not only identifies promising active compounds as potential atypical inhibitors for novel therapeutic drug development targeting hDAT but also validates the effectiveness of our integrated computational and experimental workflow for drug repurposing.
基金Deanship of Research and Graduate Studies at King Khalid University funded this work through Large Research Project under grant number RGP2/54/45.
文摘Retinal Optical Coherence Tomography (OCT) images, a non-invasive imaging technique, have become a standard retinal disease detection tool. Due to disease, there are morphological and textural changes in the layers of the retina. Classifying OCT images is challenging, as the morphological manifestations of different diseases may be similar. The OCT images capture the reflectivity characteristics of the retinal tissues. Retinal diseases change the reflectivity property of retinal tissues, resulting in texture variations in OCT images. We propose a hybrid approach to OCT image classification in which the Convolution Neural Network (CNN) model is trained using Multiple Neighborhood Local Ternary Pattern (MNLTP) texture descriptors of the OCT images dataset for a robust disease prediction system. Parallel deep CNN (PDCNN) is proposed to improve feature representation and generalizability. The MNLTP-PDCNN model is tested on two publicly available datasets. The parameter values Accuracy, Precision, Recall, and F1-Score are calculated. The best accuracy obtained specifying the model’s overall performance is 93.98% and 99% for the NEH and OCT2017 datasets, respectively. With the proposed architecture, comparable performance is obtained with a subset of the original OCT2017 data set and a comparatively smaller number of trainable parameters (1.6 million, 1.8 million, and 2.3 million for a single CNN branch, two parallel CNN branches, and three parallel network branches, respectively), compared to off-the-shelf CNN models. Hence, the proposed approach is suitable for real-time OCT image classification systems with fast training of the CNN model and reduced memory requirement for computations.
基金founded by the National Science and Technology Council(Taiwan)under contract NSTC113-2221-E-019-032.
文摘An optimal fuzzy tracking synthesis for nonlinear discrete-time descriptor systems is discussed through the Parallel Distributed Compensation(PDC)approach and the Proportional-Difference(P-D)feedback framework.Based on the Takagi-Sugeno Fuzzy Descriptor Model(T-SFDM),a nonlinear discrete-time descriptor system is represented as several linear fuzzy subsystems,which facilitates the linear P-D feedback technique and streamlines the fuzzy controller design process.Leveraging the P-D feedback fuzzy controller,the closed-loop T-SFDM can be transformed into a standard system that guarantees non-impulsiveness and causality for the nonlinear discrete-time descriptor system.In view of the disturbance problems,a passive performance constraint is incorporated into the fuzzy tracking synthesis to achieve dissipativity of disturbance energy.To achieve a better balance between state and control responses,the H2 performance requirement is considered and a minimization constraint is applied to optimize the H2 index.It is observed that there is a lack of research focusing on both disturbance and control input issues in nonlinear descriptor systems.Extending the Lyapunov theory,a stability analysis method is proposed for the tracking purpose with the combination of the free-weighting matrix to relax the analysis process while complying multiple performance constraints.Finally,two simulation examples are presented to demonstrate the feasibility and applicability of the proposed approach in practical control scenarios for nonlinear descriptor systems.
基金supported partially by the National Key Research and Development Program of China(No.2023YFF1303901)the National Natural Science Foundation of China(Nos.32171789,12411530088,and 32371654)the Joint Open Funded Project of State Key Laboratory of Geo-Information Engineering and Key Laboratory of the Ministry of Natural Resources for Surveying and Mapping Science and Geo-spatial Information Technology(No.2022-02-02).
文摘Unmanned aerial vehicle laser scanning(ULS)and terrestrial laser scanning(TLS)systems are effective ways to capture forest structures from top and side views,respectively.The registration of TLS and ULS data is a prerequisite for a comprehensive forest structure representation.Conventional registration methods based on geometric features(e.g.,points,lines,and planes)are likely to fail due to the irregular natural point distributions of forest point clouds.Currently,automatic registration methods for forest point clouds typically rely on tree attributes(such as tree position and stem diameter).However,these methods are often unsuitable for forests with diverse compositions,complex terrains,irregular tree layouts,and insufficient common trees.In this study,an automated method is proposed to register ULS and TLS forest point clouds using ground points as registration primitives,which operates independently of tree attribute extraction and is estimated to reduce processing time by over 50%.A new evaluation method for registration accuracy evaluation is proposed,where transformation parameters from each TLS scan to the ULS obtained by the proposed registration algorithm are used to derive transformation parameters between TLS scans,which are then compared to reference parameters obtained using artificial spherical targets.Conventional ULS-TLS registration evaluation methods mostly rely on the manual corresponding points selection that is subject to inherent subjective errors,or control points in both TLS and ULS data that are difficult to collect.The proposed method presents an objective and accurate solution for ULS-TLS registration accuracy evaluation that effectively eliminates these limitations.The proposed method was tested on 12 plots with diverse stem densities,tree species,and altitudes located in a mountain forest.A total of 124 TLS scans were successfully registered to ULS data.The registration accuracy was assessed using both the conventional evaluation method and the proposed new evaluation method,with average rotation errors of 2.03 and 2.06 mrad,and average translation errors of 7.63 and 6.51 cm,respectively.The registration accuracies demonstrate that the proposed algorithm effectively and accurately registers TLS to ULS point clouds.
基金National High-tech Research and Development Program (2007AA01Z314)National Natural Science Foundation of China (60873085)
文摘In order to obtain a large number of correct matches with high accuracy,this article proposes a robust wide baseline point matching method,which is based on Scott s proximity matrix and uses the scale invariant feature transform (SIFT). First,the distance between SIFT features is included in the equations of the proximity matrix to measure the similarity between two feature points; then the normalized cross correlation (NCC) used in Scott s method,which has been modified with adaptive scale and orientation,...
文摘This paper considers the design problem of static output feedback H ∞ controllers for descriptor linear systems with linear matrix inequality (LMI) approach. Necessary and sufficient conditions for the existence of a static output feedback H ∞ controller are given in terms of LMIs. Furthermore, the design method of H ∞ controllers is provided using the solutions to the LMIs.
文摘The precondition of realizing feedback controlling DC DC converter to avoid chaotic state is to judge the behavior of the converter and take corresponding measures. In this paper, the output signals under different circuit parameters of the PWM buck converter have been analyzed. The method of using Fourier descriptor to extract output signals characteristics is put forward and proved to be a gist of identifying and classifying the behavior of DC DC converter. This method can establish a good foundation fo...
