Since the coal mine in-pit personnel positioning system neither can effectively achieve the function to detect the uniqueness of in-pit coal-mine personnel nor can identify and eliminate violations in attendance manag...Since the coal mine in-pit personnel positioning system neither can effectively achieve the function to detect the uniqueness of in-pit coal-mine personnel nor can identify and eliminate violations in attendance management such as multiple cards for one person, and swiping one's cards by others in China at present. Therefore, the research introduces a uniqueness detection system and method for in-pit coal-mine personnel integrated into the in-pit coal mine personnel positioning system, establishing a system mode based on face recognition + recognition of personnel positioning card + release by automatic detection. Aiming at the facts that the in-pit personnel are wearing helmets and faces are prone to be stained during the face recognition, the study proposes the ideas that pre-process face images using the 2D-wavelet-transformation-based Mallat algorithm and extracts three face features: miner light, eyes and mouths, using the generalized symmetry transformation-based algorithm. This research carried out test with 40 clean face images with no helmets and 40 lightly-stained face images, and then compared with results with the one using the face feature extraction method based on grey-scale transformation and edge detection. The results show that the method described in the paper can detect accurately face features in the above-mentioned two cases, and the accuracy to detect face features is 97.5% in the case of wearing helmets and lightly-stained faces.展开更多
Objective To analyze the gamma band effective connectiviyty characteristicsof theprefrontal-striatal circuitry in bipolar disorder patients with and without a history of manic episodes,as well as in major depressive d...Objective To analyze the gamma band effective connectiviyty characteristicsof theprefrontal-striatal circuitry in bipolar disorder patients with and without a history of manic episodes,as well as in major depressive disorder patients,during the recognition of positive emotional faces,this study aims to identify unique neurophysiological features that may aid in the early detection of bipolar disorder.Methods This retrospective study collected clinical data and magnetoencephalography(MEG)imaging data from patients performing a positive emotional face recognition task at the Affiliated Brain Hospital of Nanjing Medical University from May 2009 to December 2019.The study included 75 patients with major depressive disorder and 29 patients with bipolar disorder in a depressive episode(rBD group).Concurrently,39 age-and gender-matched healthy controls(HC group)were recruited.After a follow-up period of at least 5 years,23 out of the 75 patients with major depressive disorder converted to bipolar disorder(ctBD group),while the remaining 52 who did not convert maintained a diagnosis of major depressive disorder.Results There were statistically significant differences in gamma-band effective connectivity in the prefrontal-striatal circuit when recognizing positive emotional faces among the converted to bipolar disorder(ctBD),raw bipolar disorder,major depressive disorder,and HC groups(H=9.04,10.30,8.30,13.43,14.38,12.62,9.82,8.94,24.62,7.89,18.53,9.97,9.58,12.79,P<0.05).The ctBD group,rBD group,and major depressive group all showed reduction in effective connectivity from the right orbital inferior frontal gyrus(ORBinf.R)to the left orbital inferior frontal gyrus(ORBinf.L)[Z=-1.98,-3.38,-2.88],from the right orbital inferior frontal gyrus to the right ventral striatum(VS.R)(Z=-2.05,-2.76,-2.11;P<0.05)and from the left ventral striatum(VS.L)to the left orbital middle frontal gyrus(ORBmid.L)(Z=-2.76,-1.98,-2.43;P<0.05).Among the disease groups,the ctBD group showed significantly enhanced effective connectivity strength compared to the major depressive group from the right amygdala(AMYG.R)to the left orbital inferior frontal gyrus(0.04(0.03,0.08)),from the right amygdala to the left ventral striatum(0.05(0.03,0.09)),and from the right ventral striatum to the right anterior cingulate and paracingulate gyri(ACG.R)(0.04(0.02,0.08))(Z=4.17,3.70,3.35;P<0.001).The ctBD group also exhibited enhanced effective connectivity compared to the rBD group from ORBinf.R to the ACG.R,fron the AMYG.R to the ORBinf.L,from the AMYG.R to the VS.L,and from the VS.R to the ACG.R(Z=2.05,4.61,3.60,3.04;P<0.05).The rBD group demonstrated reduced effective connectivity compared to the major depressive disorder group from the right orbital middle frontal gyrus(ORBmid.R)to the left anterior cingulate and paracingulate gyri(ACG.L),ORBinf.R to the ACG.R and from the ORBinf.R to the AMYG.R(Z=-2.12,-2.40,-2.22;P<0.05).Conclusion There are significant differences in the gamma-band effective connectivity characteristics of the prefrontal-striatal pathway when recognizing positive emotional faces between patients with bipolar disorder in depressive episodes and those with depression,as well as differences between bipolar depressed patients with and without a history of manic episodes.展开更多
Research on cells and organ-like tissues is critical in the fields of molecular biology,genetic analysis,proteomics analysis,tissue engineering,and others.In recent years,advancements in precise cell manipulation tech...Research on cells and organ-like tissues is critical in the fields of molecular biology,genetic analysis,proteomics analysis,tissue engineering,and others.In recent years,advancements in precise cell manipulation technologies have made precise positioning and batch processing of cells feasible.Various methods are used for cell recognition,positioning,manipulation,and assembly,often introducing external fields such as electric,magnetic,acoustic,or optical fields into the liquid environment to interact with cells,applying forces to induce cell movement and rearrangement.Alternatively,three-dimensional(3D)bioprinting technology is employed for precise cell positioning and assembly.This review will comprehensively assess the status,principles,advantages,disadvantages,and prospects of these precise cell manipulation technologies,covering single-cell manipulation,multicellular assembly,and biological 3D printing techniques.展开更多
The important indicators to measure the goodness of rigid fruit and vegetable picking robot have two aspects,the first is the reasonable structural design of the end-effector,and the second is having a high precision ...The important indicators to measure the goodness of rigid fruit and vegetable picking robot have two aspects,the first is the reasonable structural design of the end-effector,and the second is having a high precision positioning recognition method.Many researchers have done a lot of work in these two aspects,and a variety of end-effector structures and advanced position recognition methods are constantly appearing in people’s view.The working principle,structural characteristics,advantages and disadvantages of each end-effector are summarized to help us design better fruit and vegetable picking robot.The authors start from the rigid fruit and vegetable picking robot grasping methods,separation methods,and position recognition methods,firstly introduce three different grasping methods and the characteristics of the two separation methods,then introduce the under-driven picking robot developed on the basis of the traditional rigid picking robot,then explain the single special,multi-feature,and deep learning location position recognition methods currently used,and finally make a summary and outlook on the rigid fruit and vegetable picking robot from the structural development and position recognition methods.展开更多
基金financial supports from the National Natural Science Foundation of China (No. 51134024)the National High Technology Research and Development Program of China (No. 2012AA062203)are gratefully acknowledged
文摘Since the coal mine in-pit personnel positioning system neither can effectively achieve the function to detect the uniqueness of in-pit coal-mine personnel nor can identify and eliminate violations in attendance management such as multiple cards for one person, and swiping one's cards by others in China at present. Therefore, the research introduces a uniqueness detection system and method for in-pit coal-mine personnel integrated into the in-pit coal mine personnel positioning system, establishing a system mode based on face recognition + recognition of personnel positioning card + release by automatic detection. Aiming at the facts that the in-pit personnel are wearing helmets and faces are prone to be stained during the face recognition, the study proposes the ideas that pre-process face images using the 2D-wavelet-transformation-based Mallat algorithm and extracts three face features: miner light, eyes and mouths, using the generalized symmetry transformation-based algorithm. This research carried out test with 40 clean face images with no helmets and 40 lightly-stained face images, and then compared with results with the one using the face feature extraction method based on grey-scale transformation and edge detection. The results show that the method described in the paper can detect accurately face features in the above-mentioned two cases, and the accuracy to detect face features is 97.5% in the case of wearing helmets and lightly-stained faces.
文摘Objective To analyze the gamma band effective connectiviyty characteristicsof theprefrontal-striatal circuitry in bipolar disorder patients with and without a history of manic episodes,as well as in major depressive disorder patients,during the recognition of positive emotional faces,this study aims to identify unique neurophysiological features that may aid in the early detection of bipolar disorder.Methods This retrospective study collected clinical data and magnetoencephalography(MEG)imaging data from patients performing a positive emotional face recognition task at the Affiliated Brain Hospital of Nanjing Medical University from May 2009 to December 2019.The study included 75 patients with major depressive disorder and 29 patients with bipolar disorder in a depressive episode(rBD group).Concurrently,39 age-and gender-matched healthy controls(HC group)were recruited.After a follow-up period of at least 5 years,23 out of the 75 patients with major depressive disorder converted to bipolar disorder(ctBD group),while the remaining 52 who did not convert maintained a diagnosis of major depressive disorder.Results There were statistically significant differences in gamma-band effective connectivity in the prefrontal-striatal circuit when recognizing positive emotional faces among the converted to bipolar disorder(ctBD),raw bipolar disorder,major depressive disorder,and HC groups(H=9.04,10.30,8.30,13.43,14.38,12.62,9.82,8.94,24.62,7.89,18.53,9.97,9.58,12.79,P<0.05).The ctBD group,rBD group,and major depressive group all showed reduction in effective connectivity from the right orbital inferior frontal gyrus(ORBinf.R)to the left orbital inferior frontal gyrus(ORBinf.L)[Z=-1.98,-3.38,-2.88],from the right orbital inferior frontal gyrus to the right ventral striatum(VS.R)(Z=-2.05,-2.76,-2.11;P<0.05)and from the left ventral striatum(VS.L)to the left orbital middle frontal gyrus(ORBmid.L)(Z=-2.76,-1.98,-2.43;P<0.05).Among the disease groups,the ctBD group showed significantly enhanced effective connectivity strength compared to the major depressive group from the right amygdala(AMYG.R)to the left orbital inferior frontal gyrus(0.04(0.03,0.08)),from the right amygdala to the left ventral striatum(0.05(0.03,0.09)),and from the right ventral striatum to the right anterior cingulate and paracingulate gyri(ACG.R)(0.04(0.02,0.08))(Z=4.17,3.70,3.35;P<0.001).The ctBD group also exhibited enhanced effective connectivity compared to the rBD group from ORBinf.R to the ACG.R,fron the AMYG.R to the ORBinf.L,from the AMYG.R to the VS.L,and from the VS.R to the ACG.R(Z=2.05,4.61,3.60,3.04;P<0.05).The rBD group demonstrated reduced effective connectivity compared to the major depressive disorder group from the right orbital middle frontal gyrus(ORBmid.R)to the left anterior cingulate and paracingulate gyri(ACG.L),ORBinf.R to the ACG.R and from the ORBinf.R to the AMYG.R(Z=-2.12,-2.40,-2.22;P<0.05).Conclusion There are significant differences in the gamma-band effective connectivity characteristics of the prefrontal-striatal pathway when recognizing positive emotional faces between patients with bipolar disorder in depressive episodes and those with depression,as well as differences between bipolar depressed patients with and without a history of manic episodes.
基金National Natural Science Foundation of China,Grant/Award Numbers:52205312,52275200。
文摘Research on cells and organ-like tissues is critical in the fields of molecular biology,genetic analysis,proteomics analysis,tissue engineering,and others.In recent years,advancements in precise cell manipulation technologies have made precise positioning and batch processing of cells feasible.Various methods are used for cell recognition,positioning,manipulation,and assembly,often introducing external fields such as electric,magnetic,acoustic,or optical fields into the liquid environment to interact with cells,applying forces to induce cell movement and rearrangement.Alternatively,three-dimensional(3D)bioprinting technology is employed for precise cell positioning and assembly.This review will comprehensively assess the status,principles,advantages,disadvantages,and prospects of these precise cell manipulation technologies,covering single-cell manipulation,multicellular assembly,and biological 3D printing techniques.
基金supported by the National Natural Science Foundation of China(Grant No.51775002)the 14th Five-Year Plan of Beijing Education Science(Grant No.CDDB21173).
文摘The important indicators to measure the goodness of rigid fruit and vegetable picking robot have two aspects,the first is the reasonable structural design of the end-effector,and the second is having a high precision positioning recognition method.Many researchers have done a lot of work in these two aspects,and a variety of end-effector structures and advanced position recognition methods are constantly appearing in people’s view.The working principle,structural characteristics,advantages and disadvantages of each end-effector are summarized to help us design better fruit and vegetable picking robot.The authors start from the rigid fruit and vegetable picking robot grasping methods,separation methods,and position recognition methods,firstly introduce three different grasping methods and the characteristics of the two separation methods,then introduce the under-driven picking robot developed on the basis of the traditional rigid picking robot,then explain the single special,multi-feature,and deep learning location position recognition methods currently used,and finally make a summary and outlook on the rigid fruit and vegetable picking robot from the structural development and position recognition methods.
