Heart disease includes a multiplicity of medical conditions that affect the structure,blood vessels,and general operation of the heart.Numerous researchers have made progress in correcting and predicting early heart d...Heart disease includes a multiplicity of medical conditions that affect the structure,blood vessels,and general operation of the heart.Numerous researchers have made progress in correcting and predicting early heart disease,but more remains to be accomplished.The diagnostic accuracy of many current studies is inadequate due to the attempt to predict patients with heart disease using traditional approaches.By using data fusion from several regions of the country,we intend to increase the accuracy of heart disease prediction.A statistical approach that promotes insights triggered by feature interactions to reveal the intricate pattern in the data,which cannot be adequately captured by a single feature.We processed the data using techniques including feature scaling,outlier detection and replacement,null and missing value imputation,and more to improve the data quality.Furthermore,the proposed feature engineering method uses the correlation test for numerical features and the chi-square test for categorical features to interact with the feature.To reduce the dimensionality,we subsequently used PCA with 95%variation.To identify patients with heart disease,hyperparameter-based machine learning algorithms like RF,XGBoost,Gradient Boosting,LightGBM,CatBoost,SVM,and MLP are utilized,along with ensemble models.The model’s overall prediction performance ranges from 88%to 92%.In order to attain cutting-edge results,we then used a 1D CNN model,which significantly enhanced the prediction with an accuracy score of 96.36%,precision of 96.45%,recall of 96.36%,specificity score of 99.51%and F1 score of 96.34%.The RF model produces the best results among all the classifiers in the evaluation matrix without feature interaction,with accuracy of 90.21%,precision of 90.40%,recall of 90.86%,specificity of 90.91%,and F1 score of 90.63%.Our proposed 1D CNN model is 7%superior to the one without feature engineering when compared to the suggested approach.This illustrates how interaction-focused feature analysis can produce precise and useful insights for heart disease diagnosis.展开更多
Coenzyme Q10 is widely used in food,cosmetics and pharmaceuticals,possessing a broad market.Rhodobacter sphaeroides is enriched in natural coenzyme Q10 and is becoming an important microorganism for producing natural ...Coenzyme Q10 is widely used in food,cosmetics and pharmaceuticals,possessing a broad market.Rhodobacter sphaeroides is enriched in natural coenzyme Q10 and is becoming an important microorganism for producing natural coenzyme Q10.The paper reviewed the biosynthesis pathways of coenzyme Q10 in R.sphaeroides and the advances in enhancement of coenzyme Q10 production in R.sphaeroides based on metabolic engineering.展开更多
In this paper, preparation of nano-biphasic calcium phosphate （nBCP）, mechanical behavior and load-bearing of poly （lactide-co-glycolide） （PLGA） and PLGA/nBCP are presented. The nBCP with composition of 63/37 （...In this paper, preparation of nano-biphasic calcium phosphate （nBCP）, mechanical behavior and load-bearing of poly （lactide-co-glycolide） （PLGA） and PLGA/nBCP are presented. The nBCP with composition of 63/37 （w/w） HA/-TCP （hydroxyapatite/fl-tricalcium phosphate） was produced by heating of bovine bone at 700℃. Composite scaffolds were made by using PLGA matrix and 10-50 wt% nBCP powders as reinforcement material. All scaffolds were prepared by thermally induced solid-liquid phase separation （TIPS） at -60~C under 4 Pa （0.04 mbar） vacuum. The results of elastic modulus testing were adjusted with Ishai-Cohen and Narkis models for rigid polymeric matrix and compared to each other. PLGA/nBCP scaffolds with 30 wt% nBCP showed the highest value of yield strength among the scaffolds. In addition, it was found that by increasing the nBCP in scaffolds to 50 wt%, the modulus of elasticity was highly enhanced. However, the optimum value of yield strength was obtained at 30 wt% nBCP, and the agglomeration of reinforcing particles at higher percentages caused a reduction in yield strength. It is clear that the elastic modulus of matrix has the significant role in elastic modulus of scaffolds, as also the size of the filler particles in the matrix.展开更多
Novel bioengineering functional organoboron polymers were synthesized by 1) amidolysis of poly(acrcylic acid) (PAA) with 2-aminoethyldiphenyl borinate (2-AEPB), 2) esterification of organoboron PAA polymer (PAA-B) wit...Novel bioengineering functional organoboron polymers were synthesized by 1) amidolysis of poly(acrcylic acid) (PAA) with 2-aminoethyldiphenyl borinate (2-AEPB), 2) esterification of organoboron PAA polymer (PAA-B) with a-hydroxy-methoxypoly(ethylene oxide) (PEO) as a compatibilizer and 3) conjugation of organoboron PEO branches (PAA-B-PEO) with folic acid (FA) as a targeting agent. Structure and composition of the synthesized polymers were characterized by FTIR-ATR and 1H (13C) NMR spectroscopy, chemical and physical analysis methods. Anti-tumor activity of organoboron functional polymer and its complex with FA (PAA-B-PEO-F) against cancer and normal cells were evaluated by using different biochemical methods such as cytotoxicity, statistical, apoptotic and necrotic cell indexes, double staining and caspase-3 immune staining, light and fluorescence inverted microscope analyses. It was found that citotoxicity and apoptotic/necrotic effects of polymers significantly depend on the structure and composition of studied polymers, and increase the following raw: PAA << PAA-B < PAA-B-PEO < PAA-B-PEO-F. Among them, PAA-B-PEO-F complex at 400 mg mL–1 concentration as a therapeutic drug exhibits minimal toxicity toward the nor-mal cells, but influential for HeLa cancer cells.展开更多
In this research paper, we evaluate an assortment of tools and intend to investigate multifarious characteristic of Imagix-4D Reverse Engineering Tool and on the basis of investigation find out inadequacy of Imagix-4D...In this research paper, we evaluate an assortment of tools and intend to investigate multifarious characteristic of Imagix-4D Reverse Engineering Tool and on the basis of investigation find out inadequacy of Imagix-4D Reverse Engineering Tool (illustrate only abstract Class Diagram, and it has no support to illustrate ER-Diagram and Sequence Diagram) and propose a Reverse Engineering Tool based on Unified Mapping Method (RETUM) for prominence of Class Diagram Visualizations which surmount the limitation (class diagram which is intricate in visualization) of Imagix-4D Reverse Engineering Tool.展开更多
One application of software engineering is the vast and widely popular video game entertainment industry. Success of a video game product depends on how well the player base receives it. Of research towards understand...One application of software engineering is the vast and widely popular video game entertainment industry. Success of a video game product depends on how well the player base receives it. Of research towards understanding factors of success behind releasing a video game, we are interested in studying a factor known as Replayability. Towards a software engineering oriented game design methodology, we collect player opinions on Replayability via surveys and provide methods to analyze the data. We believe these results can help game designers to more successfully produce entertaining games with longer lasting appeal by utilizing our software engineering techniques.展开更多
The combination of the dipping effect and hydromechanical(H-M)coupling effect can easily lead to water inrush disasters in water-rich roadways with different dip angles in coal mines.Therefore,H-M coupling tests of be...The combination of the dipping effect and hydromechanical(H-M)coupling effect can easily lead to water inrush disasters in water-rich roadways with different dip angles in coal mines.Therefore,H-M coupling tests of bedded sandstones under identical osmotic pressure and various confining pressures were conducted.Then,the evolution curves of stress-strain,permeability and damage,macro-and mesoscopic failure characteristics were obtained.Subsequently,the mechanical behaviour was characterized,and finally the failure mechanism was revealed.The results showed that:(1)The failure of the sandstone with the bedding angle of 45°or 60°was the structure-dominant type,while that with the bedding angle of 0°,30°or 90°was the force-dominant type.(2)When the bedding angle was in the range of(0°,30°)or(45°,90°),the confining pressure played a dominant role in influencing the peak strength.However,withinβ∈(30°,45°),the bedding effect played a dominant role in the peak strength.(3)With the increase in bedding angle,the cohesion increased first,then decreased and finally increased,while the internal friction angle was the opposite.(4)When the bedding angle was 0°or 30°,the“water wedging”effect and the“bedding buckling”effect would lead to the forking or converging shear failure.When the bedding angle was 45°or 60°,the sliding friction effect would lead to the shear slipping failure.When the bedding angle was 90°,the combination of the“bedding buckling”effect and shear effect would lead to the mixed tension-shear failure.The above conclusions obtained are helpful for the prevention of water inrush disasters in water-rich roadways with different dips in coal mines.展开更多
Materials with both large magnetocaloric response and high thermoelectric performance are of vital importance for all-solid-state thermoelectromagnetic cooling.These two properties,however,hardly coexist in single pha...Materials with both large magnetocaloric response and high thermoelectric performance are of vital importance for all-solid-state thermoelectromagnetic cooling.These two properties,however,hardly coexist in single phase materials except previously reported hexagonal Cr_(1-x)Te half metal where a relatively high magnetic entropy change(-△S_(M))of~2.4 J·kg^(-1)·K^(-1)@5 T and a moderate thermoelectric figure of merit(ZT)of~1.2×10^(-2)@300 K are simultaneously recorded.Herein we aim to increase the thermoelectric performance of Cr_(1-x)Te by compositing with semiconducting Ag_(2)Te.It is discovered that the in-situ synthesis of Cr_(1-x)Te/Ag_(2)Te composites by reacting their constitute elements above melting temperatures is unsuccessful because of strong phase competition.Specifically,at elevated temperatures(T>800 K),Cr_(1-x)Te has a much lower deformation energy than Ag_(2)Te and tends to become more Cr-deficient by capturing Te from Ag_(2)Te.Therefore,Ag is insufficiently reacted and as a metal it deteriorates ZT.We then rationalize the synthesis of Cr_(1-x)Te/Ag_(2)Te composites by ex-situ mix of the pre-prepared Cr_(1-x)Te and Ag_(2)Te binary compounds followed by densification at a low sintering temperature of 573 K under a pressure of 3.5 GPa.We show that by compositing with 7 mol%Ag_(2)Te,the Seebeck coefficient of Cr_(1-x)Te is largely increased while the lattice thermal conductivity is considerably reduced,leading to 72%improvement of ZT.By comparison,-△S_(M)is only slightly reduced by 10%in the composite.Our work demonstrates the potential of Cr_(1-x)Te/Ag_(2)Te composites for thermoelectromagnetic cooling.展开更多
The neuron model has been widely employed in neural-morphic computing systems and chaotic circuits.This study aims to develop a novel circuit simulation of a three-neuron Hopfield neural network(HNN)with coupled hyper...The neuron model has been widely employed in neural-morphic computing systems and chaotic circuits.This study aims to develop a novel circuit simulation of a three-neuron Hopfield neural network(HNN)with coupled hyperbolic memristors through the modification of a single coupling connection weight.The bistable mode of the hyperbolic memristive HNN(mHNN),characterized by the coexistence of asymmetric chaos and periodic attractors,is effectively demonstrated through the utilization of conventional nonlinear analysis techniques.These techniques include bifurcation diagrams,two-parameter maximum Lyapunov exponent plots,local attractor basins,and phase trajectory diagrams.Moreover,an encryption technique for color images is devised by leveraging the mHNN model and asymmetric structural attractors.This method demonstrates significant benefits in correlation,information entropy,and resistance to differential attacks,providing strong evidence for its effectiveness in encryption.Additionally,an improved modular circuit design method is employed to create the analog equivalent circuit of the memristive HNN.The correctness of the circuit design is confirmed through Multisim simulations,which align with numerical simulations conducted in Matlab.展开更多
With the development of virtual reality (VR) technology, more and more industries are beginning to integrate with VR technology. In response to the problem of not being able to directly render the lighting effect of C...With the development of virtual reality (VR) technology, more and more industries are beginning to integrate with VR technology. In response to the problem of not being able to directly render the lighting effect of Caideng in digital Caideng scenes, this article analyzes the lighting model. It combines it with the lighting effect of Caideng scenes to design an optimized lighting model algorithm that fuses the bidirectional transmission distribution function (BTDF) model. This algorithm can efficiently render the lighting effect of Caideng models in a virtual environment. And using image optimization processing methods, the immersive experience effect on the VR is enhanced. Finally, a Caideng roaming interactive system was designed based on this method. The results show that the frame rate of the system is stable during operation, maintained above 60 fps, and has a good immersive experience.展开更多
Gesture detection is the primary and most significant step for sign language detection and sign language is the communication medium for people with speaking and hearing disabilities. This paper presents a novel metho...Gesture detection is the primary and most significant step for sign language detection and sign language is the communication medium for people with speaking and hearing disabilities. This paper presents a novel method for dynamic hand gesture detection using Hidden Markov Models (HMMs) where we detect different English alphabet letters by tracing hand movements. The process involves skin color-based segmentation for hand isolation in video frames, followed by morphological operations to enhance image trajectories. Our system employs hand tracking and trajectory smoothing techniques, such as the Kalman filter, to monitor hand movements and refine gesture paths. Quantized sequences are then analyzed using the Baum-Welch Re-estimation Algorithm, an HMM-based approach. A maximum likelihood classifier is used to identify the most probable letter from the test sequences. Our method demonstrates significant improvements over traditional recognition techniques in real-time, automatic hand gesture recognition, particularly in its ability to distinguish complex gestures. The experimental results confirm the effectiveness of our approach in enhancing gesture-based sign language detection to alleviate the barrier between the deaf and hard-of-hearing community and general people.展开更多
One exciting area within computer vision is classifying human activities, which has diverse applications like medical informatics, human-computer interaction, surveillance, and task monitoring systems. In the healthca...One exciting area within computer vision is classifying human activities, which has diverse applications like medical informatics, human-computer interaction, surveillance, and task monitoring systems. In the healthcare field, understanding and classifying patients’ activities is crucial for providing doctors with essential information for medication reactions and diagnosis. While some research methods already exist, utilizing machine learning and soft computational algorithms to recognize human activity from videos and images, there’s ongoing exploration of more advanced computer vision techniques. This paper introduces a straightforward and effective automated approach that involves five key steps: preprocessing, feature extraction technique, feature selection, feature fusion, and finally classification. To evaluate the proposed approach, two commonly used benchmark datasets KTH and Weizmann are employed for training, validation, and testing of ML classifiers. The study’s findings show that the first and second datasets had remarkable accuracy rates of 99.94% and 99.80%, respectively. When compared to existing methods, our approach stands out in terms of sensitivity, accuracy, precision, and specificity evaluation metrics. In essence, this paper demonstrates a practical method for automatically classifying human activities using an optimal feature fusion and deep learning approach, promising a great result that could benefit various fields, particularly in healthcare.展开更多
The numerical approach for finding the solution of fractional order systems of boundary value problems (BPVs) is derived in this paper. The implementation of the weighted residuals such as Galerkin, Least Square, and ...The numerical approach for finding the solution of fractional order systems of boundary value problems (BPVs) is derived in this paper. The implementation of the weighted residuals such as Galerkin, Least Square, and Collocation methods are included for solving fractional order differential equations, which is broadened to acquire the approximate solutions of fractional order systems with differentiable polynomials, namely Legendre polynomials, as basis functions. The algorithm of the residual formulations of matrix form can be coded efficiently. The interpretation of Caputo fractional derivatives is employed here. We have demonstrated these methods numerically through a few examples of linear and nonlinear BVPs. The results in absolute errors show that the present method efficiently finds the numerical solutions of fractional order systems of differential equations.展开更多
The purpose of this paper is to investigate the spatial interpolation of rainfall variability with deterministic and geostatic inspections in the Prefecture of Kilkis (Greece). The precipitation data where recorded fr...The purpose of this paper is to investigate the spatial interpolation of rainfall variability with deterministic and geostatic inspections in the Prefecture of Kilkis (Greece). The precipitation data where recorded from 12 meteorological stations in the Prefecture of Kilkis for 36 hydrological years (1973-2008). The cumulative monthly values of rainfall were studied on an annual and seasonal basis as well as during the arid-dry season. In the deterministic tests, the I.D.W. and R.B.F. checks were inspected, while in the geostatic tests, Ordinary Kriging and Universal Kriging respectively. The selection of the optimum method was made based on the least Root Mean Square Error (R.M.S.E.), as well as on the Mean Error (M.E.), as assessed by the cross validation analysis. The geostatical Kriging also considered the impact of isotropy and anisotropy across all time periods of data collection. Moreover, for Universal Kriging, the study explored spherical, exponential and Gaussian models in various combinations. Geostatistical techniques consistently demonstrated greater reliability than deterministic techniques across all time periods of data collection. Specifically, during the annual period, anisotropy was the prevailing characteristic in geostatistical techniques. Moreover, the results for the irrigation and seasonal periods were generally comparable, with few exceptions where isotropic methods yielded lower (R.M.S.E.) in some seasonal observations.展开更多
In this paper, we explore the classification of vibration modes generated by handwriting on an optical desk using deep learning architectures. Three deep learning models—Long Short-Term Memory (LSTM) networks with at...In this paper, we explore the classification of vibration modes generated by handwriting on an optical desk using deep learning architectures. Three deep learning models—Long Short-Term Memory (LSTM) networks with attention mechanism, Video Vision Transformer (ViViT), and Long-term Recurrent Convolutional Network (LRCN)—were evaluated to determine the most effective method for analyzing time series patterns generated by a Michelson interferometer. The interferometer was used to detect vibration modes created by handwriting, capturing time-series data from the diffraction patterns. Among these models, the LSTM-Attention network achieved the highest validation accuracy, reaching up to 92%, outperforming both ViViT and LRCN. These findings highlight the potential of deep learning in material science for detecting and classifying vibration patterns. The powerful performance of the LSTM-Attention model suggests that it could be applied to similar classification tasks in related fields.展开更多
This study proposes a facile, but precise method to back-calculate the effective modulus of nanocomposite interleaving plies. Adaptation of a conventional dry-reinforcement resin film infusion (RFI) approach allows in...This study proposes a facile, but precise method to back-calculate the effective modulus of nanocomposite interleaving plies. Adaptation of a conventional dry-reinforcement resin film infusion (RFI) approach allows interleaving neat epoxy layers (NE) with the epoxy-infused nanofibrous plies (XE) of constant thickness. The final cured nanocomposite laminate thus has the form (NE/XE)n, where “n” denotes the number of the repeats and enables clear distinction of the nanocomposite interlayers through the thickness. Mechanical testing of neat epoxy and laminated nanocomposite specimens can be coupled with the classical lamination theory for back-calculating in-plane elastic modulus of the individual epoxy-infused nanofibrous plies (EXE). Finite element analysis (FEA) and testing the laminated nanocomposite subject to flexural loading (3-point bending) are proposed to validate the analytically back-calculated EXE. It is shown that the FEA prediction incorporating EXE and testing for flexural modulus of (NE/XE)20 laminated nanocomposites correlate well and the results are within 5%. This finding suggests that the back-calculation scheme reported herein would be attractive for accurately determining the properties of an individual nanocomposite building block layer. The proposed framework is beneficial for modelling laminated structural composites incorporating XE-like nanocomposite interlayers.展开更多
基金supported by the Competitive Research Fund of the University of Aizu,Japan(Grant No.P-13).
文摘Heart disease includes a multiplicity of medical conditions that affect the structure,blood vessels,and general operation of the heart.Numerous researchers have made progress in correcting and predicting early heart disease,but more remains to be accomplished.The diagnostic accuracy of many current studies is inadequate due to the attempt to predict patients with heart disease using traditional approaches.By using data fusion from several regions of the country,we intend to increase the accuracy of heart disease prediction.A statistical approach that promotes insights triggered by feature interactions to reveal the intricate pattern in the data,which cannot be adequately captured by a single feature.We processed the data using techniques including feature scaling,outlier detection and replacement,null and missing value imputation,and more to improve the data quality.Furthermore,the proposed feature engineering method uses the correlation test for numerical features and the chi-square test for categorical features to interact with the feature.To reduce the dimensionality,we subsequently used PCA with 95%variation.To identify patients with heart disease,hyperparameter-based machine learning algorithms like RF,XGBoost,Gradient Boosting,LightGBM,CatBoost,SVM,and MLP are utilized,along with ensemble models.The model’s overall prediction performance ranges from 88%to 92%.In order to attain cutting-edge results,we then used a 1D CNN model,which significantly enhanced the prediction with an accuracy score of 96.36%,precision of 96.45%,recall of 96.36%,specificity score of 99.51%and F1 score of 96.34%.The RF model produces the best results among all the classifiers in the evaluation matrix without feature interaction,with accuracy of 90.21%,precision of 90.40%,recall of 90.86%,specificity of 90.91%,and F1 score of 90.63%.Our proposed 1D CNN model is 7%superior to the one without feature engineering when compared to the suggested approach.This illustrates how interaction-focused feature analysis can produce precise and useful insights for heart disease diagnosis.
基金Supported by Talent Project of Sichuan University of Science&Engineering(2015RC27)Meat Processing Key Laboratory of Sichuan Province(16R-27)
文摘Coenzyme Q10 is widely used in food,cosmetics and pharmaceuticals,possessing a broad market.Rhodobacter sphaeroides is enriched in natural coenzyme Q10 and is becoming an important microorganism for producing natural coenzyme Q10.The paper reviewed the biosynthesis pathways of coenzyme Q10 in R.sphaeroides and the advances in enhancement of coenzyme Q10 production in R.sphaeroides based on metabolic engineering.
基金supported by Isfahan University of Technology and Ministry of Sciences, Research & Technology in Iran and Materials Science & Engineering School of Nanyang Technological University in Singapore
文摘In this paper, preparation of nano-biphasic calcium phosphate （nBCP）, mechanical behavior and load-bearing of poly （lactide-co-glycolide） （PLGA） and PLGA/nBCP are presented. The nBCP with composition of 63/37 （w/w） HA/-TCP （hydroxyapatite/fl-tricalcium phosphate） was produced by heating of bovine bone at 700℃. Composite scaffolds were made by using PLGA matrix and 10-50 wt% nBCP powders as reinforcement material. All scaffolds were prepared by thermally induced solid-liquid phase separation （TIPS） at -60~C under 4 Pa （0.04 mbar） vacuum. The results of elastic modulus testing were adjusted with Ishai-Cohen and Narkis models for rigid polymeric matrix and compared to each other. PLGA/nBCP scaffolds with 30 wt% nBCP showed the highest value of yield strength among the scaffolds. In addition, it was found that by increasing the nBCP in scaffolds to 50 wt%, the modulus of elasticity was highly enhanced. However, the optimum value of yield strength was obtained at 30 wt% nBCP, and the agglomeration of reinforcing particles at higher percentages caused a reduction in yield strength. It is clear that the elastic modulus of matrix has the significant role in elastic modulus of scaffolds, as also the size of the filler particles in the matrix.
文摘Novel bioengineering functional organoboron polymers were synthesized by 1) amidolysis of poly(acrcylic acid) (PAA) with 2-aminoethyldiphenyl borinate (2-AEPB), 2) esterification of organoboron PAA polymer (PAA-B) with a-hydroxy-methoxypoly(ethylene oxide) (PEO) as a compatibilizer and 3) conjugation of organoboron PEO branches (PAA-B-PEO) with folic acid (FA) as a targeting agent. Structure and composition of the synthesized polymers were characterized by FTIR-ATR and 1H (13C) NMR spectroscopy, chemical and physical analysis methods. Anti-tumor activity of organoboron functional polymer and its complex with FA (PAA-B-PEO-F) against cancer and normal cells were evaluated by using different biochemical methods such as cytotoxicity, statistical, apoptotic and necrotic cell indexes, double staining and caspase-3 immune staining, light and fluorescence inverted microscope analyses. It was found that citotoxicity and apoptotic/necrotic effects of polymers significantly depend on the structure and composition of studied polymers, and increase the following raw: PAA << PAA-B < PAA-B-PEO < PAA-B-PEO-F. Among them, PAA-B-PEO-F complex at 400 mg mL–1 concentration as a therapeutic drug exhibits minimal toxicity toward the nor-mal cells, but influential for HeLa cancer cells.
文摘In this research paper, we evaluate an assortment of tools and intend to investigate multifarious characteristic of Imagix-4D Reverse Engineering Tool and on the basis of investigation find out inadequacy of Imagix-4D Reverse Engineering Tool (illustrate only abstract Class Diagram, and it has no support to illustrate ER-Diagram and Sequence Diagram) and propose a Reverse Engineering Tool based on Unified Mapping Method (RETUM) for prominence of Class Diagram Visualizations which surmount the limitation (class diagram which is intricate in visualization) of Imagix-4D Reverse Engineering Tool.
文摘One application of software engineering is the vast and widely popular video game entertainment industry. Success of a video game product depends on how well the player base receives it. Of research towards understanding factors of success behind releasing a video game, we are interested in studying a factor known as Replayability. Towards a software engineering oriented game design methodology, we collect player opinions on Replayability via surveys and provide methods to analyze the data. We believe these results can help game designers to more successfully produce entertaining games with longer lasting appeal by utilizing our software engineering techniques.
基金supported by the National Natural Science Foundation of China(Grant Nos.52034009 and 51974319)the Yue Qi Distinguished Scholar Project(Grant No.2020JCB01).
文摘The combination of the dipping effect and hydromechanical(H-M)coupling effect can easily lead to water inrush disasters in water-rich roadways with different dip angles in coal mines.Therefore,H-M coupling tests of bedded sandstones under identical osmotic pressure and various confining pressures were conducted.Then,the evolution curves of stress-strain,permeability and damage,macro-and mesoscopic failure characteristics were obtained.Subsequently,the mechanical behaviour was characterized,and finally the failure mechanism was revealed.The results showed that:(1)The failure of the sandstone with the bedding angle of 45°or 60°was the structure-dominant type,while that with the bedding angle of 0°,30°or 90°was the force-dominant type.(2)When the bedding angle was in the range of(0°,30°)or(45°,90°),the confining pressure played a dominant role in influencing the peak strength.However,withinβ∈(30°,45°),the bedding effect played a dominant role in the peak strength.(3)With the increase in bedding angle,the cohesion increased first,then decreased and finally increased,while the internal friction angle was the opposite.(4)When the bedding angle was 0°or 30°,the“water wedging”effect and the“bedding buckling”effect would lead to the forking or converging shear failure.When the bedding angle was 45°or 60°,the sliding friction effect would lead to the shear slipping failure.When the bedding angle was 90°,the combination of the“bedding buckling”effect and shear effect would lead to the mixed tension-shear failure.The above conclusions obtained are helpful for the prevention of water inrush disasters in water-rich roadways with different dips in coal mines.
基金Project supported by the National Key Research and Development Program of China(Grant No.2019YFA0704900)the National Natural Science Foundation of China(Grant No.52171221)。
文摘Materials with both large magnetocaloric response and high thermoelectric performance are of vital importance for all-solid-state thermoelectromagnetic cooling.These two properties,however,hardly coexist in single phase materials except previously reported hexagonal Cr_(1-x)Te half metal where a relatively high magnetic entropy change(-△S_(M))of~2.4 J·kg^(-1)·K^(-1)@5 T and a moderate thermoelectric figure of merit(ZT)of~1.2×10^(-2)@300 K are simultaneously recorded.Herein we aim to increase the thermoelectric performance of Cr_(1-x)Te by compositing with semiconducting Ag_(2)Te.It is discovered that the in-situ synthesis of Cr_(1-x)Te/Ag_(2)Te composites by reacting their constitute elements above melting temperatures is unsuccessful because of strong phase competition.Specifically,at elevated temperatures(T>800 K),Cr_(1-x)Te has a much lower deformation energy than Ag_(2)Te and tends to become more Cr-deficient by capturing Te from Ag_(2)Te.Therefore,Ag is insufficiently reacted and as a metal it deteriorates ZT.We then rationalize the synthesis of Cr_(1-x)Te/Ag_(2)Te composites by ex-situ mix of the pre-prepared Cr_(1-x)Te and Ag_(2)Te binary compounds followed by densification at a low sintering temperature of 573 K under a pressure of 3.5 GPa.We show that by compositing with 7 mol%Ag_(2)Te,the Seebeck coefficient of Cr_(1-x)Te is largely increased while the lattice thermal conductivity is considerably reduced,leading to 72%improvement of ZT.By comparison,-△S_(M)is only slightly reduced by 10%in the composite.Our work demonstrates the potential of Cr_(1-x)Te/Ag_(2)Te composites for thermoelectromagnetic cooling.
基金Project supported by the National Nature Science Foundation of China(Grant Nos.51737003 and 51977060)the Natural Science Foundation of Hebei Province(Grant No.E2011202051).
文摘The neuron model has been widely employed in neural-morphic computing systems and chaotic circuits.This study aims to develop a novel circuit simulation of a three-neuron Hopfield neural network(HNN)with coupled hyperbolic memristors through the modification of a single coupling connection weight.The bistable mode of the hyperbolic memristive HNN(mHNN),characterized by the coexistence of asymmetric chaos and periodic attractors,is effectively demonstrated through the utilization of conventional nonlinear analysis techniques.These techniques include bifurcation diagrams,two-parameter maximum Lyapunov exponent plots,local attractor basins,and phase trajectory diagrams.Moreover,an encryption technique for color images is devised by leveraging the mHNN model and asymmetric structural attractors.This method demonstrates significant benefits in correlation,information entropy,and resistance to differential attacks,providing strong evidence for its effectiveness in encryption.Additionally,an improved modular circuit design method is employed to create the analog equivalent circuit of the memristive HNN.The correctness of the circuit design is confirmed through Multisim simulations,which align with numerical simulations conducted in Matlab.
文摘With the development of virtual reality (VR) technology, more and more industries are beginning to integrate with VR technology. In response to the problem of not being able to directly render the lighting effect of Caideng in digital Caideng scenes, this article analyzes the lighting model. It combines it with the lighting effect of Caideng scenes to design an optimized lighting model algorithm that fuses the bidirectional transmission distribution function (BTDF) model. This algorithm can efficiently render the lighting effect of Caideng models in a virtual environment. And using image optimization processing methods, the immersive experience effect on the VR is enhanced. Finally, a Caideng roaming interactive system was designed based on this method. The results show that the frame rate of the system is stable during operation, maintained above 60 fps, and has a good immersive experience.
文摘Gesture detection is the primary and most significant step for sign language detection and sign language is the communication medium for people with speaking and hearing disabilities. This paper presents a novel method for dynamic hand gesture detection using Hidden Markov Models (HMMs) where we detect different English alphabet letters by tracing hand movements. The process involves skin color-based segmentation for hand isolation in video frames, followed by morphological operations to enhance image trajectories. Our system employs hand tracking and trajectory smoothing techniques, such as the Kalman filter, to monitor hand movements and refine gesture paths. Quantized sequences are then analyzed using the Baum-Welch Re-estimation Algorithm, an HMM-based approach. A maximum likelihood classifier is used to identify the most probable letter from the test sequences. Our method demonstrates significant improvements over traditional recognition techniques in real-time, automatic hand gesture recognition, particularly in its ability to distinguish complex gestures. The experimental results confirm the effectiveness of our approach in enhancing gesture-based sign language detection to alleviate the barrier between the deaf and hard-of-hearing community and general people.
文摘One exciting area within computer vision is classifying human activities, which has diverse applications like medical informatics, human-computer interaction, surveillance, and task monitoring systems. In the healthcare field, understanding and classifying patients’ activities is crucial for providing doctors with essential information for medication reactions and diagnosis. While some research methods already exist, utilizing machine learning and soft computational algorithms to recognize human activity from videos and images, there’s ongoing exploration of more advanced computer vision techniques. This paper introduces a straightforward and effective automated approach that involves five key steps: preprocessing, feature extraction technique, feature selection, feature fusion, and finally classification. To evaluate the proposed approach, two commonly used benchmark datasets KTH and Weizmann are employed for training, validation, and testing of ML classifiers. The study’s findings show that the first and second datasets had remarkable accuracy rates of 99.94% and 99.80%, respectively. When compared to existing methods, our approach stands out in terms of sensitivity, accuracy, precision, and specificity evaluation metrics. In essence, this paper demonstrates a practical method for automatically classifying human activities using an optimal feature fusion and deep learning approach, promising a great result that could benefit various fields, particularly in healthcare.
文摘The numerical approach for finding the solution of fractional order systems of boundary value problems (BPVs) is derived in this paper. The implementation of the weighted residuals such as Galerkin, Least Square, and Collocation methods are included for solving fractional order differential equations, which is broadened to acquire the approximate solutions of fractional order systems with differentiable polynomials, namely Legendre polynomials, as basis functions. The algorithm of the residual formulations of matrix form can be coded efficiently. The interpretation of Caputo fractional derivatives is employed here. We have demonstrated these methods numerically through a few examples of linear and nonlinear BVPs. The results in absolute errors show that the present method efficiently finds the numerical solutions of fractional order systems of differential equations.
文摘The purpose of this paper is to investigate the spatial interpolation of rainfall variability with deterministic and geostatic inspections in the Prefecture of Kilkis (Greece). The precipitation data where recorded from 12 meteorological stations in the Prefecture of Kilkis for 36 hydrological years (1973-2008). The cumulative monthly values of rainfall were studied on an annual and seasonal basis as well as during the arid-dry season. In the deterministic tests, the I.D.W. and R.B.F. checks were inspected, while in the geostatic tests, Ordinary Kriging and Universal Kriging respectively. The selection of the optimum method was made based on the least Root Mean Square Error (R.M.S.E.), as well as on the Mean Error (M.E.), as assessed by the cross validation analysis. The geostatical Kriging also considered the impact of isotropy and anisotropy across all time periods of data collection. Moreover, for Universal Kriging, the study explored spherical, exponential and Gaussian models in various combinations. Geostatistical techniques consistently demonstrated greater reliability than deterministic techniques across all time periods of data collection. Specifically, during the annual period, anisotropy was the prevailing characteristic in geostatistical techniques. Moreover, the results for the irrigation and seasonal periods were generally comparable, with few exceptions where isotropic methods yielded lower (R.M.S.E.) in some seasonal observations.
文摘In this paper, we explore the classification of vibration modes generated by handwriting on an optical desk using deep learning architectures. Three deep learning models—Long Short-Term Memory (LSTM) networks with attention mechanism, Video Vision Transformer (ViViT), and Long-term Recurrent Convolutional Network (LRCN)—were evaluated to determine the most effective method for analyzing time series patterns generated by a Michelson interferometer. The interferometer was used to detect vibration modes created by handwriting, capturing time-series data from the diffraction patterns. Among these models, the LSTM-Attention network achieved the highest validation accuracy, reaching up to 92%, outperforming both ViViT and LRCN. These findings highlight the potential of deep learning in material science for detecting and classifying vibration patterns. The powerful performance of the LSTM-Attention model suggests that it could be applied to similar classification tasks in related fields.
文摘This study proposes a facile, but precise method to back-calculate the effective modulus of nanocomposite interleaving plies. Adaptation of a conventional dry-reinforcement resin film infusion (RFI) approach allows interleaving neat epoxy layers (NE) with the epoxy-infused nanofibrous plies (XE) of constant thickness. The final cured nanocomposite laminate thus has the form (NE/XE)n, where “n” denotes the number of the repeats and enables clear distinction of the nanocomposite interlayers through the thickness. Mechanical testing of neat epoxy and laminated nanocomposite specimens can be coupled with the classical lamination theory for back-calculating in-plane elastic modulus of the individual epoxy-infused nanofibrous plies (EXE). Finite element analysis (FEA) and testing the laminated nanocomposite subject to flexural loading (3-point bending) are proposed to validate the analytically back-calculated EXE. It is shown that the FEA prediction incorporating EXE and testing for flexural modulus of (NE/XE)20 laminated nanocomposites correlate well and the results are within 5%. This finding suggests that the back-calculation scheme reported herein would be attractive for accurately determining the properties of an individual nanocomposite building block layer. The proposed framework is beneficial for modelling laminated structural composites incorporating XE-like nanocomposite interlayers.
