BackgroundThe Basal ganglia (BG) played a crucial role in the brain-level mechanisms of chronic pain disorders. However, the functional changes of BG in chronic prostatitis/chronic pelvic pain syndrome (CP/CPPS) are still poorly understood. This study investigated the BG subregions’ resting-state functional connectivity (rs-FC) in CP/CPPS patients compared with healthy controls.MethodsTwenty eight patients with CP/CPPS and 28 age- and education-matched healthy males underwent clinical measurements and 3T brain MR imaging, including T1-weighted structural images and resting-state functional imaging. The data were analyzed (...) by the seeded-based rs-FC analysis. Then, a machine learning method was applied to assess the feasibility of detecting CP/CPPS patients through the changed rs-FC.ResultsCompared with healthy males, patients presented decreased rs-FC between the BG subregions and right middle cingulate cortex, and correlated with pain (r = 0.51, p-uncorrected = 0.005) and urinary symptoms (r = –0.4, p-uncorrected = 0.034). The left superior temporal gyrus and right supramarginal gyrus showed decreased rs-FC with the BG subregions as well. The area under the receiver operating characteristic curve of 0.943 (accuracy = 80%, F1-score = 80.6%) was achieved for the classification of CP/CPPS patients and healthy males with support vector machine (SVM) based on the changed rs-FC.ConclusionThese findings provide evidence of altered BG subregions’ rs-FC in CP/CPPS, which may contribute to our understanding of the BG’s role in CP/CPPS. (shrink)

Understanding the implication of point cloud is still challenging in the aim of classification or segmentation for point cloud due to its irregular and sparse structure. As we have known, PointNet architecture as a ground-breaking work for point cloud process can learn shape features directly on unordered 3D point cloud and has achieved favorable performance, such as 86% mean accuracy and 89.2% overall accuracy for classification task, respectively. However, this model fails to consider the fine-grained semantic information of local structure (...) for point cloud. Then, a multiscale receptive fields graph attention network by means of semantic features of local patch for point cloud is proposed in this paper, and the learned feature map for our network can well capture the abundant features information of point cloud. The proposed MRFGAT architecture is tested on ModelNet datasets, and results show it achieves state-of-the-art performance in shape classification tasks, such as it outperforms GAPNet model by 0.1% in terms of OA and compete with DGCNN model in terms of MA. (shrink)

Understanding the neural basis of schizophrenia (SZ) is important for shedding light on the neurobiological mechanisms underlying this mental disorder. Structural and functional alterations in the anterior cingulate cortex (ACC), dorsolateral prefrontal cortex (DLPFC), hippocampus, and medial prefrontal cortex (MPFC) have been implicated in the neurobiology of SZ. However, the effective connectivity among them in SZ remains unclear. The current study investigated how neuronal pathways involving these regions were affected in first-episode SZ using functional magnetic resonance imaging (fMRI). Forty-nine patients (...) with a first-episode of psychosis and diagnosis of SZ—according to the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition, Text Revision—were studied. Fifty healthy controls (HCs) were included for comparison. All subjects underwent resting state fMRI. We used spectral dynamic causal modeling (DCM) to estimate directed connections among the bilateral ACC, DLPFC, hippocampus, and MPFC. We characterized the differences using Bayesian parameter averaging (BPA) in addition to classical inference (t-test). In addition to common effective connectivity in these two groups, HCs displayed widespread significant connections predominantly involved in ACC not detected in SZ patients, but SZ showed few connections. Based on BPA results, SZ patients exhibited anterior cingulate cortico-prefrontal-hippocampal hyperconnectivity, as well as ACC-related and hippocampal-dorsolateral prefrontal-medial prefrontal hypoconnectivity. In summary, spectral DCM revealed the pattern of effective connectivity involving ACC in patients with first-episode SZ. This study provides a potential link between SZ and dysfunction of ACC, creating an ideal situation to associate mechanisms behind SZ with aberrant connectivity among these cognition and emotion-related regions. (shrink)

The development of artificial intelligence technology has brought changes to various industries. Under the concept of green sustainable development, how to use the progress of science and technology to implement low-carbon strategies is a problem that every enterprise should consider. Aiming at the problem of picking up goods in logistics industry, this paper proposed a secondary task assignment theory for multiple unmanned aerial vehicle based on green scheduling. The theory greatly improves the utilization rate of unmanned aerial vehicle and reduces (...) the energy consumption. We analyzed the advantages and disadvantages of local optimal algorithm and global optimal algorithm in time and energy consumption. Through repeated experiments in different ranges, we have well verified the high efficiency and general applicability of this theory, which can provide theoretical and practical implications for logistics enterprises using UAV to achieve low-carbon sustainable development in the future. (shrink)

The aberrations of a gene can influence it and the functions of its neighbour genes in gene interaction network, leading to the development of carcinogenesis of normal cells. In consideration of gene interaction network as a complex network, previous studies have made efforts on the driver attribute filling of genes via network properties of nodes and network propagation of mutations. However, there are still obstacles from problems of small size of cancer samples and the existence of drivers without property of (...) network neighbours, limiting the discovery of cancer driver genes. To address these obstacles, we propose an efficient modularity subspace based concept learning model. Our model can overcome the curse of dimensionality due to small samples via dimension reduction in the task of attribute concept learning and explore the features of genes through modularity subspace beyond the network neighbours. The evaluation analysis also demonstrates the superiority of our model in the task of driver attribute filling on two gene interaction networks. Generally, our model shows a promising prospect in the application of interaction network analysis of tumorigenesis. (shrink)

BackgroundUp-to-date information about the trends of age-related hearing loss and how this varies between countries is essential to plan for an adequate health-system response. Therefore, this study aimed to assess the research hotpots and trends in ARHL and to provide the basis and direction for future research.Materials and methodsThe Web of Science Core Collection database was searched and screened according to the inclusion criteria during 2002–2021. Bibliometric analyses were conducted by CiteSpace software and VOSviewer software.ResultsThe query identified 1,496 publications, which (...) showed a growth trend of this filed. These publications were from 62 countries, the United States of America showed its tremendous impact on this field in publication outputs, total citations, and international collaborations, China following in second. The Journal of Hearing Research was the most productive journal. Weijia Kong published the most papers, and the most productive institution was Washington University. The keyword “presbycusis” ranked first in research frontiers and appeared earlier, and the keywords “age-related hearing loss,” “risk,” “dementia,” “auditory cortex,” “association,” and “decline” began to appear in recent years.ConclusionThe annual number of publications has grown rapidly in the past two decades and will continue to grow. Epidemiological investigation and laboratory research are lasting hot spots, besides future research will focus on the association between ARHL and cognitive decline, dementia, and Alzheimer’s disease. (shrink)

GraphicalPatients with early- to middle-stage PD were enrolled for C-Gait assessment and traditional walking ability assessments. The correlation of C-Gait assessment and traditional walking tests were studied. Two models were established based on C-Gait assessment and traditional walking tests to explore the value of C-Gait assessment in predicting freezing of gait.ObjectiveEfficient methods for assessing walking adaptability in individuals with Parkinson’s disease are urgently needed. Therefore, this study aimed to assess C-Gait for detecting freezing of gait in patients with early- to (...) middle-stage PD.MethodPeople with PD diagnosis were recruited from April 2019 to November 2019 in Beijing Rehabilitation Hospital. The participants performed six items of walking adaptability on an instrumented treadmill augmented with visual targets and obstacles. The patient’s walking adaptability was evaluated by C-Gait assessment and traditional walking tests, and FOG-related indexes were collected as outcome measures. Two discriminant models were established by stepwise discriminant analysis; area under the receiver operating characteristic curve was used to validate the models.ResultIn total, 53 patients were included in this study. Most C-Gait assessment items had no or low correlations with traditional walking tests. The obstacle avoidance and speed of adaptation items could lead to FOG with high sensitivity. In addition, the C-Gait assessment model had slightly better discrimination of freezers from non-freezers compared with traditional walking test models ; specifically, obstacle avoidance and speed of adaptation have uniquely discriminant potential.ConclusionC-gait assessment could provide additional value to the traditional walking tests for PD. Gait adaptability assessment, as measured by C-Gait, may be able to help identify freezers in a PD population. (shrink)

Researches on science and social system theory.

Brain structural covariance network can delineate the brain synchronized alterations in a long-range time period. It has been used in the research of cognition or neuropsychiatric disorders. Recently, causal analysis of structural covariance network, winner-take-all and cortex–subcortex covariance network, and modulation analysis of structural covariance network have expended the technology breadth of SCN. However, the lack of user-friendly software limited the further application of SCN for the research. In this work, we developed the graphical user interface toolkit of brain structural (...) covariance connectivity based on MATLAB platform. The software contained the analysis of SCN, CaSCN, MOD-SCN, and WTA-CSSCN. Also, the group comparison and result-showing modules were included in the software. Furthermore, a simple showing of demo dataset was presented in the work. We hope that the toolkit could help the researchers, especially clinical researchers, to do the brain covariance connectivity analysis in further work more easily. (shrink)

Ben shu yi jian ming e yao de bi chu xiang du zhe ti gong le yi fu quan jing shi de xi fang mei xue li shi hua juan.Qi nei rong han gai cong gu xi la,Luo ma zhi dao 20 shi ji de xi fang mei xue si xiang he li lun cheng guo,Qi zhong yi li lun xing tai de mei xue si xiang wei zhu gan,Tong shi she ji wen xue yi shu yi ji she hui (...) feng shang suo ti xian de shen mei yi shi. (shrink)

英文题名:A reconstruction of man as freedom.

本书共分5章。主要内容包括:明末清初西学东来及其对于中国思想文化的影响、鸦片战争前后的西学输入与国人的反应、洋务时期的西学输入等.

“国家教育部人文社会科学重点研究基地山西大学科学技术哲学研究中心”基金资助出版.

本书具有总论的性质,主要是从宏观上阐明和论述20世纪西方哲学东渐史的下述论题,全面展示20世纪西方哲学东渐的整体面貌,提示了20世纪西方哲学东渐的规律性。.

本书以独特的视角,将孙中山建设哲学置于世界自经典物理学转向现代科学、中国从革命转向建设的新时代大视野中,进行审视。采用宏观、中观与微观相结合、自然科学与人文科学相结合、理论与实践相结合、历史与现实相结 合的方法,通过对大量史料的梳理、缕析、归纳,对现实社会的观察、调查与综合分析,而后对孙中山的以系统、开放、协调、均衡与和谐为基调的建设哲学,进行全方位、多视角的透视和深刻剖析,高度肯定其对开启中国现代 思维的历史意义,及其在中国现代化建设中的当代意义.

Ben shu fen " zhong guo zhe xue " " wai guo zhe xue " " ma ke si zhu yi zhe xue " " ke xue ji shu zhe xue " " lun li xue " " mei xue " liu ge lan mu, shou lu " zhu xi yan jiu de shi lun " " guan yu zhe xue de kai duan wen ti " deng wen zhang.