Testicular descent occurs in two consecutive stages:the transabdominal stage and the inguinoscrotal stage.Androgens play a crucial role in the second stage by influencing the development of the gubernaculum,a structur...Testicular descent occurs in two consecutive stages:the transabdominal stage and the inguinoscrotal stage.Androgens play a crucial role in the second stage by influencing the development of the gubernaculum,a structure that pulls the testis into the scrotum.However,the mechanisms of androgen actions underlying many of the processes associated with gubernaculum development have not been fully elucidated.To identify the androgen-regulated genes,we conducted large-scale gene expression analyses on the gubernaculum harvested from luteinizing hormone/choriogonadotropin receptor knockout(Lhcgr KO)mice,an animal model of inguinoscrotal testis maldescent resulting from androgen deficiency.We found that the expression of secreted protein acidic and rich in cysteine(SPARC)-related modular calcium binding 1(Smoc1)was the most severely suppressed at both the transcript and protein levels,while its expression was the most dramatically induced by testosterone administration in the gubernacula of Lhcgr KO mice.The upregulation of Smoc1 expression by testosterone was curtailed by the addition of an androgen receptor antagonist,flutamide.In addition,in vitro studies demonstrated that SMOC1 modestly but significantly promoted the proliferation of gubernacular cells.In the cultures of myogenic differentiation medium,both testosterone and SMOC1 enhanced the expression of myogenic regulatory factors such as paired box 7(Pax7)and myogenic factor 5(Myf5).After short-interfering RNA-mediated knocking down of Smoc1,the expression of Pax7 and Myf5 diminished,and testosterone alone did not recover,but additional SMOC1 did.These observations indicate that SMOC1 is pivotal in mediating androgen action to regulate gubernaculum development during inguinoscrotal testicular descent.展开更多
Sentiment analysis plays an important role in distilling and clarifying content from movie reviews,aiding the audience in understanding universal views towards the movie.However,the abundance of reviews and the risk o...Sentiment analysis plays an important role in distilling and clarifying content from movie reviews,aiding the audience in understanding universal views towards the movie.However,the abundance of reviews and the risk of encountering spoilers pose challenges for efcient sentiment analysis,particularly in Arabic content.Tis study proposed a Stochastic Gradient Descent(SGD)machine learning(ML)model tailored for sentiment analysis in Arabic and English movie reviews.SGD allows for fexible model complexity adjustments,which can adapt well to the Involvement of Arabic language data.Tis adaptability ensures that the model can capture the nuances and specifc local patterns of Arabic text,leading to better performance.Two distinct language datasets were utilized,and extensive pre-processing steps were employed to optimize the datasets for analysis.Te proposed SGD model,designed to accommodate the nuances of each language,aims to surpass existing models in terms of accuracy and efciency.Te SGD model achieves an accuracy of 84.89 on the Arabic dataset and 87.44 on the English dataset,making it the top-performing model in terms of accuracy on both datasets.Tis indicates that the SGD model consistently demonstrates high accuracy levels across Arabic and English datasets.Tis study helps deepen the understanding of sentiments across various linguistic datasets.Unlike many studies that focus solely on movie reviews,the Arabic dataset utilized here includes hotel reviews,ofering a broader perspective.展开更多
An optimal feedback guidance law with disturbance rejection objective is proposed for endoatmospheric powered descent.This guidance law with an affine form is derived by solving a novel problem called Endoatmospheric ...An optimal feedback guidance law with disturbance rejection objective is proposed for endoatmospheric powered descent.This guidance law with an affine form is derived by solving a novel problem called Endoatmospheric Powered Descent Guidance with Disturbance Rejection(Endo-PDG-DR).The key idea of formulating the Endo-PDG-DR problem is dividing disturbances into two parts,modeled and unmodeled disturbances:the modeled disturbance is proactively exploited by augmenting it as a new state of a dynamics model;the unmodeled disturbance is reactively attenuated in terms of its effect on the guidance performance by adjoining a parameterized time-varying quadratic performance index in the proposed optimal guidance problem.A Pseudospectral Differential Dynamic Programming(PDDP)method is developed to solve the Endo-PDG-DR problem,and correspondingly a robust neighboring optimal state feedback law is obtained,which has two synergistic functionalities.One is adaptive optimal steering to accommodate the modeled disturbance,and the other is disturbance attenuation to compensate for the state perturbation effect induced by the unmodeled disturbance.Using the derived feedback guidance law,a disturbance rejection level is quantified,and is correspondingly optimized by designing a quadratic weighting parameter tuning law.The numerical computations of interest are performed within a pseudospectral setting,ensuring polynomial analytical solution,high computational efficiency,and reliable convergence.展开更多
In order to obtain a high-quality weld during the laser welding process, extracting the characteristic parameters of weld pool is an important issue for automated welding. In this paper, the type 304 austenitic stainl...In order to obtain a high-quality weld during the laser welding process, extracting the characteristic parameters of weld pool is an important issue for automated welding. In this paper, the type 304 austenitic stainless steel is welded by a 5 kW high-power fiber laser and a high-speed camera is employed to capture the topside images of weld pools. Then we propose a robust visual-detection approach for the molten pool based on the supervised descent method. It provides an elegant framework for representing the outline of a weld pool and is especially efficient for weld pool detection in the presence of strong uncertainties and disturbances. Finally, welding experimental results verified that the proposed approach can extract the weld pool boundary accurately, which will lay a solid foundation for controlling the weld quality of fiber laser welding process.展开更多
This paper presents a coordinate gradient descent approach for minimizing the sum of a smooth function and a nonseparable convex function.We find a search direction by solving a subproblem obtained by a second-order a...This paper presents a coordinate gradient descent approach for minimizing the sum of a smooth function and a nonseparable convex function.We find a search direction by solving a subproblem obtained by a second-order approximation of the smooth function and adding a separable convex function.Under a local Lipschitzian error bound assumption,we show that the algorithm possesses global and local linear convergence properties.We also give some numerical tests(including image recovery examples) to illustrate the efficiency of the proposed method.展开更多
The original free vortex wake model was used for numerical investigation.Calculation of the aerodynamic characteristics in hover and vertical descent modes in the range of vertical descent speed of 0–30 m/s including...The original free vortex wake model was used for numerical investigation.Calculation of the aerodynamic characteristics in hover and vertical descent modes in the range of vertical descent speed of 0–30 m/s including the Vortex Ring State(VRS)area was performed.The calculations were carried out under the condition of variable blade pitch angle values providing a fixed timeaverage thrust value.Visualization data of free vortex wake shapes,flow structures,and velocity fields were obtained and analyzed.The time-dependences of the rotor’s thrust and torque coefficients were obtained and analyzed.The obtained data allows determining the boundaries of the VRS area by various criteria such as rotor thrust and torque pulsations,growth of rotor power consumption relative to the hover,growth of rotor induced velocities relative to the hover,and growth of the required rotor blade pitch angles values.The results of the study are compared with experimental and calculated data of other authors and can significantly supplement the available results of experimental and computational studies in this area.展开更多
A recommender system(RS)relying on latent factor analysis usually adopts stochastic gradient descent(SGD)as its learning algorithm.However,owing to its serial mechanism,an SGD algorithm suffers from low efficiency and...A recommender system(RS)relying on latent factor analysis usually adopts stochastic gradient descent(SGD)as its learning algorithm.However,owing to its serial mechanism,an SGD algorithm suffers from low efficiency and scalability when handling large-scale industrial problems.Aiming at addressing this issue,this study proposes a momentum-incorporated parallel stochastic gradient descent(MPSGD)algorithm,whose main idea is two-fold:a)implementing parallelization via a novel datasplitting strategy,and b)accelerating convergence rate by integrating momentum effects into its training process.With it,an MPSGD-based latent factor(MLF)model is achieved,which is capable of performing efficient and high-quality recommendations.Experimental results on four high-dimensional and sparse matrices generated by industrial RS indicate that owing to an MPSGD algorithm,an MLF model outperforms the existing state-of-the-art ones in both computational efficiency and scalability.展开更多
Mathematical models for burden descending process have been applied to obtain whole burden structures in blast furnace,whereas the accuracy of those burden descent models has not been sufficiently investigated.Special...Mathematical models for burden descending process have been applied to obtain whole burden structures in blast furnace,whereas the accuracy of those burden descent models has not been sufficiently investigated.Special evaluation method based on timeline burden profiles was established to quantitatively evaluate the error between experimental and modeled burden structures.Four existing burden descent models were utilized to describe the burden structure of a 1/20 scaled warm blast furnace.Input modeling conditions including initial burden profile,descending volumes in each time interval,and normalized descending velocity distribution were determined via special image processing technology.Modeled burden structures were evaluated combined with the published experimental data.It is found that all the models caught the main profile of the burden structure.Furthermore,the improved nonuniform descent model（Model IV）shows the highest level of precision especially when burden descends with unstable velocity distribution tendency.Meanwhile,the traditional nonuniform descent model（Model III）may also be desirable to model the burden descending process when the burden descending velocity presents a linear tendency.Finally,the uniform descent model（Model I）might be the first option for roughly predicting burden structure.展开更多
In this paper,we consider a distributed resource allocation problem of minimizing a global convex function formed by a sum of local convex functions with coupling constraints.Based on neighbor communication and stocha...In this paper,we consider a distributed resource allocation problem of minimizing a global convex function formed by a sum of local convex functions with coupling constraints.Based on neighbor communication and stochastic gradient,a distributed stochastic mirror descent algorithm is designed for the distributed resource allocation problem.Sublinear convergence to an optimal solution of the proposed algorithm is given when the second moments of the gradient noises are summable.A numerical example is also given to illustrate the effectiveness of the proposed algorithm.展开更多
基金supported in part by the Department of OB/GYN research funds(University of Louisville,Louisville,KY,USA)Jilin Province Health Technology Capability Enhancement funds(No.2022JC055).
文摘Testicular descent occurs in two consecutive stages:the transabdominal stage and the inguinoscrotal stage.Androgens play a crucial role in the second stage by influencing the development of the gubernaculum,a structure that pulls the testis into the scrotum.However,the mechanisms of androgen actions underlying many of the processes associated with gubernaculum development have not been fully elucidated.To identify the androgen-regulated genes,we conducted large-scale gene expression analyses on the gubernaculum harvested from luteinizing hormone/choriogonadotropin receptor knockout(Lhcgr KO)mice,an animal model of inguinoscrotal testis maldescent resulting from androgen deficiency.We found that the expression of secreted protein acidic and rich in cysteine(SPARC)-related modular calcium binding 1(Smoc1)was the most severely suppressed at both the transcript and protein levels,while its expression was the most dramatically induced by testosterone administration in the gubernacula of Lhcgr KO mice.The upregulation of Smoc1 expression by testosterone was curtailed by the addition of an androgen receptor antagonist,flutamide.In addition,in vitro studies demonstrated that SMOC1 modestly but significantly promoted the proliferation of gubernacular cells.In the cultures of myogenic differentiation medium,both testosterone and SMOC1 enhanced the expression of myogenic regulatory factors such as paired box 7(Pax7)and myogenic factor 5(Myf5).After short-interfering RNA-mediated knocking down of Smoc1,the expression of Pax7 and Myf5 diminished,and testosterone alone did not recover,but additional SMOC1 did.These observations indicate that SMOC1 is pivotal in mediating androgen action to regulate gubernaculum development during inguinoscrotal testicular descent.
文摘Sentiment analysis plays an important role in distilling and clarifying content from movie reviews,aiding the audience in understanding universal views towards the movie.However,the abundance of reviews and the risk of encountering spoilers pose challenges for efcient sentiment analysis,particularly in Arabic content.Tis study proposed a Stochastic Gradient Descent(SGD)machine learning(ML)model tailored for sentiment analysis in Arabic and English movie reviews.SGD allows for fexible model complexity adjustments,which can adapt well to the Involvement of Arabic language data.Tis adaptability ensures that the model can capture the nuances and specifc local patterns of Arabic text,leading to better performance.Two distinct language datasets were utilized,and extensive pre-processing steps were employed to optimize the datasets for analysis.Te proposed SGD model,designed to accommodate the nuances of each language,aims to surpass existing models in terms of accuracy and efciency.Te SGD model achieves an accuracy of 84.89 on the Arabic dataset and 87.44 on the English dataset,making it the top-performing model in terms of accuracy on both datasets.Tis indicates that the SGD model consistently demonstrates high accuracy levels across Arabic and English datasets.Tis study helps deepen the understanding of sentiments across various linguistic datasets.Unlike many studies that focus solely on movie reviews,the Arabic dataset utilized here includes hotel reviews,ofering a broader perspective.
基金co-supported by the National Natural Science Foundation of China(No.62103014)。
文摘An optimal feedback guidance law with disturbance rejection objective is proposed for endoatmospheric powered descent.This guidance law with an affine form is derived by solving a novel problem called Endoatmospheric Powered Descent Guidance with Disturbance Rejection(Endo-PDG-DR).The key idea of formulating the Endo-PDG-DR problem is dividing disturbances into two parts,modeled and unmodeled disturbances:the modeled disturbance is proactively exploited by augmenting it as a new state of a dynamics model;the unmodeled disturbance is reactively attenuated in terms of its effect on the guidance performance by adjoining a parameterized time-varying quadratic performance index in the proposed optimal guidance problem.A Pseudospectral Differential Dynamic Programming(PDDP)method is developed to solve the Endo-PDG-DR problem,and correspondingly a robust neighboring optimal state feedback law is obtained,which has two synergistic functionalities.One is adaptive optimal steering to accommodate the modeled disturbance,and the other is disturbance attenuation to compensate for the state perturbation effect induced by the unmodeled disturbance.Using the derived feedback guidance law,a disturbance rejection level is quantified,and is correspondingly optimized by designing a quadratic weighting parameter tuning law.The numerical computations of interest are performed within a pseudospectral setting,ensuring polynomial analytical solution,high computational efficiency,and reliable convergence.
基金Project was supported by the National Key R&D Program of China(Grant No.2017YFB1104404)
文摘In order to obtain a high-quality weld during the laser welding process, extracting the characteristic parameters of weld pool is an important issue for automated welding. In this paper, the type 304 austenitic stainless steel is welded by a 5 kW high-power fiber laser and a high-speed camera is employed to capture the topside images of weld pools. Then we propose a robust visual-detection approach for the molten pool based on the supervised descent method. It provides an elegant framework for representing the outline of a weld pool and is especially efficient for weld pool detection in the presence of strong uncertainties and disturbances. Finally, welding experimental results verified that the proposed approach can extract the weld pool boundary accurately, which will lay a solid foundation for controlling the weld quality of fiber laser welding process.
基金supported by NSFC Grant 10601043,NCETXMUSRF for ROCS,SEM+2 种基金supported by RGC 201508HKBU FRGssupported by the Hong Kong Research Grant Council
文摘This paper presents a coordinate gradient descent approach for minimizing the sum of a smooth function and a nonseparable convex function.We find a search direction by solving a subproblem obtained by a second-order approximation of the smooth function and adding a separable convex function.Under a local Lipschitzian error bound assumption,we show that the algorithm possesses global and local linear convergence properties.We also give some numerical tests(including image recovery examples) to illustrate the efficiency of the proposed method.
文摘The original free vortex wake model was used for numerical investigation.Calculation of the aerodynamic characteristics in hover and vertical descent modes in the range of vertical descent speed of 0–30 m/s including the Vortex Ring State(VRS)area was performed.The calculations were carried out under the condition of variable blade pitch angle values providing a fixed timeaverage thrust value.Visualization data of free vortex wake shapes,flow structures,and velocity fields were obtained and analyzed.The time-dependences of the rotor’s thrust and torque coefficients were obtained and analyzed.The obtained data allows determining the boundaries of the VRS area by various criteria such as rotor thrust and torque pulsations,growth of rotor power consumption relative to the hover,growth of rotor induced velocities relative to the hover,and growth of the required rotor blade pitch angles values.The results of the study are compared with experimental and calculated data of other authors and can significantly supplement the available results of experimental and computational studies in this area.
基金supported in part by the National Natural Science Foundation of China(61772493)the Deanship of Scientific Research(DSR)at King Abdulaziz University(RG-48-135-40)+1 种基金Guangdong Province Universities and College Pearl River Scholar Funded Scheme(2019)the Natural Science Foundation of Chongqing(cstc2019jcyjjqX0013)。
文摘A recommender system(RS)relying on latent factor analysis usually adopts stochastic gradient descent(SGD)as its learning algorithm.However,owing to its serial mechanism,an SGD algorithm suffers from low efficiency and scalability when handling large-scale industrial problems.Aiming at addressing this issue,this study proposes a momentum-incorporated parallel stochastic gradient descent(MPSGD)algorithm,whose main idea is two-fold:a)implementing parallelization via a novel datasplitting strategy,and b)accelerating convergence rate by integrating momentum effects into its training process.With it,an MPSGD-based latent factor(MLF)model is achieved,which is capable of performing efficient and high-quality recommendations.Experimental results on four high-dimensional and sparse matrices generated by industrial RS indicate that owing to an MPSGD algorithm,an MLF model outperforms the existing state-of-the-art ones in both computational efficiency and scalability.
基金Item Sponsored by National Natural Science Foundation of China(61290325)
文摘Mathematical models for burden descending process have been applied to obtain whole burden structures in blast furnace,whereas the accuracy of those burden descent models has not been sufficiently investigated.Special evaluation method based on timeline burden profiles was established to quantitatively evaluate the error between experimental and modeled burden structures.Four existing burden descent models were utilized to describe the burden structure of a 1/20 scaled warm blast furnace.Input modeling conditions including initial burden profile,descending volumes in each time interval,and normalized descending velocity distribution were determined via special image processing technology.Modeled burden structures were evaluated combined with the published experimental data.It is found that all the models caught the main profile of the burden structure.Furthermore,the improved nonuniform descent model（Model IV）shows the highest level of precision especially when burden descends with unstable velocity distribution tendency.Meanwhile,the traditional nonuniform descent model（Model III）may also be desirable to model the burden descending process when the burden descending velocity presents a linear tendency.Finally,the uniform descent model（Model I）might be the first option for roughly predicting burden structure.
基金the National Key Research and Development Program of China(No.2016YFB0901900)the National Natural Science Foundation of China(No.61733018)the China Special Postdoctoral Science Foundation Funded Project(No.Y990075G21).
文摘In this paper,we consider a distributed resource allocation problem of minimizing a global convex function formed by a sum of local convex functions with coupling constraints.Based on neighbor communication and stochastic gradient,a distributed stochastic mirror descent algorithm is designed for the distributed resource allocation problem.Sublinear convergence to an optimal solution of the proposed algorithm is given when the second moments of the gradient noises are summable.A numerical example is also given to illustrate the effectiveness of the proposed algorithm.
