Ben shu dui Luling Wang xue de yan jiu, zhu yao cong yi xia liang fang mian zhan kai: shou xian, zhong dian jie shao le ti chu Luling Wang xue de li lun yi ju he Luling Wang xue fa zhan de ge ge jie duan de jie ding, te dian ji qi zhu yao de dai biao ren wu. Qi ci, ju ti lun shu le Luling Wang xue fa zhan de ge ge jie duan de zui zhu (...) yao dai biao ren wu de zhi xue li lu, xin xue si xiang, jing xue te dian. Tong guo dui Luling Wang xue zong ti shang de yan jiu, gai kuo he zheng li yi ji dui ge ge fa zhan jie duan zhu yao de dai biao ren wu Wang xue si xiang de bu tong shi jiao de tan tao chan fa, cong zong ti shang rang shi ren jiao wei xi tong de liao jie Luling Wang xue de gai mao ji qi cao chuang, fa zhan, ding sheng ji shi wei de li shi guo cheng he zhong yao dai biao ren wu de Wang xue si xiang. Tong shi, zai qian mian yan jiu de ji chu shang, dui Luling Wang xue zai Jiang you Wang xue nai zhi Yangming hou xue fa zhan guo cheng zhong de zhong yao di wei yi ji dui zhong wan Ming ru xue si xiang fa zhan de ying xiang zuo le zong jie. (shrink)

BackgroundPrehospital delay is associated with non-modifiable factors such as age, residential region, and disease severity. However, the impact of psychosocial factors especially for job burnout on prehospital decision delay is still little understood.MethodThis internet-based survey was conducted between 14 February 2021 and 5 March 2021 in China through the Wechat platform and web page. Self-designed questionnaires about the expected and actual length of prehospital decision time and the Chinese version of Maslach Burnout Inventory-General Survey, Type D Personality Scale-14, and Social (...) Support Rating Scale were applied. A total of 1,039 general participants with a history of perceptible but tolerable body discomfort were included.ResultsThe top six reasons for prehospital decision delay were: endure until self-healing, too busy to ask for leave, process for seeing a doctor too complicated, too tired after work, worry about the expenditure, and fear of being identified as with serious problem. The univariate analyses revealed that older age, type D personality, job burnout, and worrying about expenditure were associated with prolonged prehospital decision time, while engaged in medical-related job and with more social support would shorten the delay. The multivariate analysis using logistic regression model with forward selecting method showed that age [per 10 years, odds ratio 1.19, p 7 days). Mediating effects were analyzed by using bias-corrected percentile bootstrap methods. Social support was found partially mediated the relationship between the determinants and prehospital decision time. The partial mediating effect of social support accounted for 24.0% of the total effect for job burnout and 11.6% for worrying about expenditure.ConclusionPsychosocial factors have a non-negligible impact on prehospital decision delay. The crucial part of prehospital decision delay may be the lack of motivation inside. Job burnout and lack of social support, as two commonly seen features in the modern world, should be given enough consideration in disease prevention and treatment. (shrink)

The quality and quantity of training data are crucial to the performance of a deep-learning-based brain-computer interface system. However, it is not practical to record EEG data over several long calibration sessions. A promising time- and cost-efficient solution is artificial data generation or data augmentation. Here, we proposed a DA method for the motor imagery EEG signal called brain-area-recombination. For the BAR, each sample was first separated into two ones by left/right brain channels, and the artificial samples were generated by (...) recombining the half-samples. We then designed two schemas corresponding to the single- and multi-subject scenarios. Extensive experiments using the classifier of EEGnet were conducted on two public datasets under various training set sizes. In both schemas, the BAR method can make the EEGnet have a better performance of classification. To make a comparative investigation, we selected two common DA methods, and the BAR method beat them. Further, using the proposed BAR for augmentation, EEGnet achieved up to 8.3% improvement than a typical decoding algorithm CSP-SVM, note that both the models were trained on the augmented dataset. This study shows that BAR usage can significantly improve the classification ability of deep learning to MI-EEG signals. To a certain extent, it may promote the development of deep learning technology in the field of BCI. (shrink)

本书内容包括:比例原则之界定,比例原则的回溯与前瞻,比例原则的理论基础,比例原则的功能与局限,比例原则于我国公法中适用的若干探讨.

本书共有马克思主义历史主义的基本内容、特点及理论地位;阶级、阶级斗争观点与阶级分析方法;历史主义和阶级观点的关系等四章。.

Ben shu wei "Song Ming shi qi Chang Jiang zhong you de ru xue yan jiu" cong shu zhi yi: ben cong shu shi ren wen she hui ke xue chong dian yan jiu ji di-Wuhan da xue Zhongguo chuan tong wen hua yan jiu zhong xin tou biao, jing jiao yu bu zu zhi zhuan jia ping shen tong guo, zheng shi pi zhun de jiao yu bu ren wen she hui ke xue 2001 nian du zhong da (...) yan jiu xiang mu, xiang mu pi zhun hao shi 01JAZJD720008, ding yu 2004 nian qian hou wan cheng. ke ti zu zhu chi ren wei Guo Qiyong jiao shou, "Jiangxi zhi xue"shi Zhu Xi ti chu de yi ge gai nian, zhu yao zhi chu zi yu Jiangxi Jinxi Lu shi jia zu yi men de xue shuo, qi nei he shi Lu Jiuyuan de xin xue; di 2 quan ze shi you "Song Yuan xue an" suo zai zhi Xiangshan xiong Zhangfu, Suoshan de xue shuo; di 3 quan wei Xiangshan xiong di de di zi men de si xiang. Ben shu quan mian kao cha Jiangxi zhi xue zai Song dai Chang Jiang zhong you xing qi de xue mo yuan yuan, zhu yao xue shuo, yu Luo xue Min xue Zhejiang zhu xue zhe (Lü Zuqian, Yong Shangsi xian sheng deng) zhi jian de guan xi, yi ji qi dui Wang (Yangming) xue xing qi de nei zai guan lian xing, bing yan ji dui xian dai xin ru xue de tan tao. ben shu de xie zuo jiang zhu zhong si xiang kao gu de fang fa, zai quan mian yan jiu you guan dian ji de ji chu shang, dui you guan ren wu de chu sheng di, huo dong de di qu (ru jia zu suo zai cun luo, xue zhe shu xin wang lai, jiang xue, hui jiang, shu yuan deng) jin xing shi di de kao cha, guang fan di yun yong fang zhi, nian pu, shu yuan zhi, jia pu deng cai liao, ba si xiang jia huan yuan yu ju ti huan jing zhi zhong, zai ju ti she hui de li shi de jia zu de bei jing xia kao cha qi si xiang de nei han, jie shi qi jing shen suo zai, bing jin er yin shen chu qi yi yi yu jia zhi. (shrink)

《想象与理性：中国道教文学及其思想史研究》简洁地勾勒了中国道教的次生学科——道教文学（含道教文学思想）产生、发展的历史进程，揭示了道教文学形成和兴盛的诸多因素，探讨了道教文学盛衰的内在规律。.

Ben shu yi Ming ru Li Cai de jiang xue huo dong yu xue pai jian gou wei zhong xin, tan tao cong shi liu shi ji chu dao shi qi shi ji mo li xue qun ti zhong xin xing xue shuo he xue pai de chan sheng, chuan bo, kuo zhan yu chuan cheng de mo shi, bing zhuo zhong cong si xiang shi de jiao du jie shi zhe zhong mo shi chan sheng he yun xing (...) de si xiang gen yuan yu nei zai dong li. Quan shu zheng wen gong qi zhang, zhu yao nei rong fen wei shang xia liang bian, shang bian yi hong guan zong lun de fang shi, cong li xue jing dian "Da xue" de wen ben bian dong he quan shi jing zheng qie ru, tan tao zhong wan Ming li xue xue shuo he xue pai jian gou de li lun gen ju; xia bian yi Li Cai de "zhi xiu" xue shuo ji qi jiang xue huo dong zuo wei ge an yan jiu, tan tao li xue xue shuo he xue pai de chuan bo ji chuan cheng de she hui hua tu jing. (shrink)

Wei Jin xuan xue jia de xuan lun, ru jin zhi zai zhi ben wen ju jian. Dan bing bu jing mo, na xie xuan lun zong shi dui du zhe zhan xian qi zi ji. Wei Jin zhi shi, xuan xiao rao rang, xuan si zhe huo sa tuo fang da, huo yi yu shen yin, ru he zai xian shi jian yi wei, shun ni shi Wei Jin xuan yin zhong zui shen ke de di yun. Zuo (...) zhe Lu Guizhen pan wang tou guo xiang Wei Jin xuan lun zhe de kou wen, zhi chu yi ge fang xiang,er zai ci yi fang xiang de guan zhu xia, neng gou cheng xian yi ge yu xuan lun rong he de xin shi yu, bing jie ci dui yu mou xie zhong yao de ke ti jin xing sheng si, shi quan shi de jie guo ju you yi ding cheng du de yi yi. Ben shu zhong ji lu de liu pian lun wen, ji shi zhe xie nian zuo zhe bu duan xiang Wei Jin zhe ren ti wen zhi hou suo huo zhi de da an.--. (shrink)

Ben shu tong guo dui Kang Youwei zhi "qun" yu"du" guan nian de kao cha, lai ba wo Kang Youwei dui ge ren, guo jia nai zhi tian xia zhi xu de shen ke si kao. Zhu yao nei rong you: yi, Jin dai"qun-du" guan nian de chu xian ji qi zou xiang, er, Kang Youwei "qun-du" guan nian chan sheng de si xiang bei jing, san, "Du ren" yu Kang Youwei dui xian dai xing ge ti sheng cun zhi (...) ling hui, si, "Qun" yu guo jia wei xin, wu, "qun-du" guan lian yu chong tu: min quan yu guo jia guan nian zhi jian de zhang li, liu, Shi jie fan wei zhi "du" yu "qun" : guo jia yu "da tong"deng. (shrink)

Deep learning is widely used in the fields of information technology and education innovation but there are few studies for young children in the preschool stage. Therefore, we aimed to explore factors that affect children’s learning ability through collecting relevant information from teachers in the kindergarten. Literature review, interview, and questionnaire survey methods were used to determine the influencing factors of deep learning. There were five dimensions for these factors: the level of difficulty of academic, communication skills, level of active (...) collaboration, level of in-depth processing, and reflection level evaluation. Reliability and validity tests were used to analyze the data from questionnaires. In total, 100 valid questionnaires were collected. The Cronbach coefficients for academic challenge, communication, active cooperation, deep processing, and reflective evaluation were 0.801, 0.689, 0.770, 0.758, and 0.665, respectively. Principal component analysis revealed that there were three main factors that affect children’s learning depth: the level of deep processing, the level of reflective evaluation, and the active level of collaboration. In conclusion, there were several factors affecting deep learning in children and further studies are warranted to promote the development of this field. (shrink)

ObjectiveWith the improvement in health awareness, humanistic care ability of nurses has become a focus of public attention. The aim of the study was to confirm the relationship between psychological capital and humanistic care ability of nurses, and to provide suggestions on improving the humanistic care ability of nurses.MethodsA cross-section survey was conducted. Three hundred thirty-nine nurses were recruited from a tertiary general hospital in Taizhou, China. Psychological capital and humanistic care ability were measured using a self-reported questionnaire. Correlation analysis (...) and stepwise multiple regression analysis were performed to analyze the correlation between psychological capital and humanistic care ability.ResultsThe psychological capital and humanistic care ability scores were 91.57 ± 13.96 and 189.08 ± 20.37, respectively. Differences in psychological capital scores across professional titles, departments, years of work, and marital status were statistically significant. There were statistical differences for the humanistic care ability scores among nurses based on marital status. The total psychological capital scores and the four sub-dimensions scores were positively correlated with the humanistic care ability scores among nurses. Self-efficacy was the main predictor of nurses’ humanistic care ability.ConclusionPsychological capital positively affected the humanistic care ability of nurses. Self-efficacy was the main predictor of humanistic care ability. Nursing managers can formulate strategies from the perspective of positive psychology to improve humanistic care ability of nurses. (shrink)

Although some cognitive studies provided reasons that children with low socioeconomic status (SES) showed poor mathematical achievements, there was no explicit evidence to directly explain the root of lagged performance in children with low SES. Therefore, the present study explored the differences in neural correlates in the process of symbolic magnitude comparison between children with different SES by the event-related potentials (ERP). A total of 16 second graders from low SES families and 16 from middle/high SES families participated in this (...) study. According to the results of anterior N1 (early attention) and P2 (extraction of numerical meaning) over frontal region, the differences among children with different SES were manifested as differences in general neural activities in terms of attention and top-down cognitive control. In the late stage of cognitive processing, there was no significant difference in the average amplitude of the LPC between the children with different SES, indicating that low SES did not influence the information encoding and memory updating of numerical representation responsible by the parietal lobe. The educational implications of this study were mentioned in the discussion. (shrink)

本书通过对大众传媒的女性时尚化的类型,描述和概括女性的时尚化对女性理念的影响,提出在全球消费主义的主导下,大众传媒用"现代化"话语构建的女性时尚的社会与文化的互动宣传,其裨仍是将女性"化约"为媒体娱乐 和消费市场的载体,阻碍了女性真实个性的发展,以及由女性经验主导的文化实践的呈现.

This study aimed to explore the association between self-oriented empathy and compassion fatigue, and examine the potential mediating roles of dispositional mindfulness and the counselor’s self-efficacy. A total of 712 hotline psychological counselors were recruited from the Mental Health Service Platform at Central China Normal University, Ministry of Education during the outbreak of Corona Virus Disease 2019, then were asked to complete the questionnaires measuring self-oriented empathy, compassion fatigue, dispositional mindfulness, and counselor’s self-efficacy. Structural equation modeling was utilized to analyze (...) the possible associations and explore potential mediations. In addition to reporting confidence intervals, we employed a new method named model-based constrained optimization procedure to test hypotheses of indirect effects. Results showed that self-oriented empathy was positively associated with compassion fatigue. Dispositional mindfulness and counselor’s self-efficacy independently and serially mediated the associations between self-oriented empathy and compassion fatigue. The findings of this study confirmed and complemented the etiological and the multi-factor model of compassion fatigue. Moreover, the results indicate that it is useful and necessary to add some training for increasing counselor’s self-efficacy in mindfulness-based interventions in order to decrease compassion fatigue. (shrink)

Through empirical studies or laboratory tests, previous studies have shown that sport-confidence, attention, and emotion regulation are key factors in archery performance. The present study aims to further identify the effects and pathways of sport-confidence, attention, and cognitive reappraisal on real-world archery performance by constructing a hypothesized model to provide a basis for scientific training of athletes to improve sport performance. A survey design was utilized on a sample of 61 athletes from the Chinese National Archery Team to test the (...) model. The measurement and hypothesized models were tested using partial least squares structural equation modeling. The results indicate that the model fit well and explained 33.6% of the variance in archery performance. Sport-confidence and attention were important predictive indicators of archery performance, while the relationship between cognitive reappraisal and archery performance showed considerable complexity. We conclude that the development of sport-confidence and attention of archery athletes should be strengthened, but athletes who use cognitive reappraisal in archery competition should be mindful of its potential appropriation of cognitive resources and should be directed to improve sport-confidence or develop a positive orientation to arouse excitement. (shrink)

We study a joint pricing and inventory control problem for perishables with positive lead time in a finite horizon periodic-review system. Unlike most studies considering a continuous density function of demand, in our paper the customer demand depends on the price of current period and arrives according to a homogeneous Poisson process. We consider both backlogging and lost-sales cases, and our goal is to find a simultaneously ordering and pricing policy to maximize the expected discounted profit over the planning horizon. (...) When there is no fixed ordering cost involved, we design a deep reinforcement learning algorithm to obtain a near-optimal ordering policy and show that there are some monotonicity properties in the learned policy. We also show that our deep reinforcement learning algorithm achieves a better performance than tabular-based Q-learning algorithms. When a fixed ordering cost is involved, we show that our deep reinforcement learning algorithm is effective and efficient, under which the problem of “curse of dimension” is circumvented. (shrink)

PurposeTo study the changes in functional connections between the left and right hemispheres of patients with high myopia and healthy controls by resting functional magnetic resonance imaging based on voxel-mirrored homotopic connectivity. To study the changes in resting-state functional connectivity between the left and right hemispheres of patients with HM and healthy controls at rest by using resting functional magnetic resonance imaging based on voxel-mirror homotopy connectivity.Patients and MethodsA total of 89 patients with HM and 59 HCs were collected and (...) matched according to gender, age, and education level. The VMHC method was used to evaluate the changes in rsFC between cerebral hemispheres, and a correlation analysis was carried out to understand the differences in brain functional activities between the patients with HM and the HCs.ResultsCompared with the HCs, the VMHC values of the putamen and fusiform in the HM group were significantly lower.ConclusionThis study preliminarily confirmed the destruction of interhemispheric functional connection in some brain regions of the patients with HM and provided effective information for clarifying the neural mechanism of patients with HM. (shrink)

Ben shu zhi zai yong zhe xue yan jiu de fang shi zheng ti lun shu fo xue ti xi. wei le shi pu tong da zhong neng chu kui wan zheng de fo jiao xi tong, zuo zhe fen bie cong fo jiao de ge di yu pai bie,zhe xue si xiang guan dian,si miao jian zhu yi ji fo jing shu ji lun zhu deng fang mian jin xing liao xiang jin de xu shu ji tao lun. shu (...) zhong chu le dui fo jiao wen hua zhi shi de zheng li yu chuan hang, hai hui jie he you zuo zhe zai de zhe xue ji Zhongguo wen hua ling yu zhong di yan jiu cheng guo. ben shu zun zhong zong jiao ben shen, zai xie zuo shou fa shang shi fen yan jin, fo jing ji xue zhe guan dian jie zhi yi yin yong xing shi lie chu, bing bu zuo ping lun ; dui zhuan men de shu yu hui dai you jiao zhu,jian suo shen zhi shi fan wen yuan wen de shuo ming, ke du xing qiang bing yi yu cha yue. (shrink)