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141.
Acute bouts of exercise have the potential to benefit children’s cognition. Inconsistent evidence on the role of qualitative exercise task characteristics calls for further investigation of the cognitive challenge level in exercise. Thus, the study aim was to investigate which “dose” of cognitive challenge in acute exercise benefits children’s cognition, also exploring the moderating role of individual characteristics. In a within-subject experimental design, 103 children (Mage = 11.1, SD = 0.9, 48% female) participated weekly in one of three 15-min exergames followed by an Attention Network task. Exergame sessions were designed to keep physical intensity constant (65% HRmax) and to have different cognitive challenge levels (low, mid, high; adapted to the ongoing individual performance). ANOVAs performed on variables that reflect the individual functioning of attention networks revealed a significant effect of cognitive challenge on executive control efficiency (reaction time performances; p = .014, ƞ2p = .08), with better performances after the high-challenge condition compared to lower ones (ps < .015), whereas alerting and orienting were unaffected by cognitive challenge (ps > .05). ANOVAs performed on variables that reflect the interactive functioning of attention networks revealed that biological sex moderated cognitive challenge effects. For males only, the cognitive challenge level influenced the interactive functioning of executive control and orienting networks (p = .004; ƞ2p = .07). Results suggest that an individualized and adaptive cognitively high-challenging bout of exercise is more beneficial to children’s executive control than less challenging ones. For males, the cognitive challenge in an acute bout seems beneficial to maintain executive control efficiency also when spatial attention resources cannot be validly allocated in advance. Results are interpreted referring to the cognitive stimulation hypothesis and arousal theory.  相似文献   
142.
Complex simulator-based models with non-standard sampling distributions require sophisticated design choices for reliable approximate parameter inference. We introduce a fast, end-to-end approach for approximate Bayesian computation (ABC) based on fully convolutional neural networks. The method enables users of ABC to derive simultaneously the posterior mean and variance of multidimensional posterior distributions directly from raw simulated data. Once trained on simulated data, the convolutional neural network is able to map real data samples of variable size to the first two posterior moments of the relevant parameter's distributions. Thus, in contrast to other machine learning approaches to ABC, our approach allows us to generate reusable models that can be applied by different researchers employing the same model. We verify the utility of our method on two common statistical models (i.e., a multivariate normal distribution and a multiple regression scenario), for which the posterior parameter distributions can be derived analytically. We then apply our method to recover the parameters of the leaky competing accumulator (LCA) model and we reference our results to the current state-of-the-art technique, which is the probability density estimation (PDA). Results show that our method exhibits a lower approximation error compared with other machine learning approaches to ABC. It also performs similarly to PDA in recovering the parameters of the LCA model.  相似文献   
143.
Religious congregations are social settings where people gather together in community to pursue the sacred (Pargament, 2008). Such settings are important to understand as they provide a context for individuals to develop relationships, share ideas and resources, and connect individuals to larger society (Todd, 2017a). Yet, research to date has not deeply examined the inherently relational nature of religious congregations. Thus, in this study, we used social settings theory (Seidman, 2012; Tseng & Seidman, 2007) to develop and test hypotheses about relationships within one Christian religious congregation. In particular, we used social network analysis to test hypotheses about relational activity, popularity, and homophily for friendship and spiritual support types of relational links. Our findings demonstrate how relational patterns may be linked to participation in congregational activities, occupying a leadership role, a sense of community and spiritual satisfaction, stratification, socialization, and spiritual support. Overall, this advances theory and research on the relational aspects of religious congregations, and more broadly to the literature on social settings. Limitations, directions for future research, and implications for theory and religious congregations also are discussed.  相似文献   
144.
This article looks at cultural models in the light of human development, and neurobiological findings in motivation, learning, and cognition. It is argued that at the individual level, the acquisition of cultural models relies on several innate, neurobiologically based motivational, learning, and cognitive systems. These are: (a) a primary motivation to form social bonds which is driven by affect; (b) highly specialized social learning circuits, involving, but not limited to, mirror neuron systems, that facilitate the encoding of social information through implicit, embodied, imitational learning processes; and (c) the formation of culturally based templates for behavior and cognition centered around structures, collectively known as the “default mode network,” which is essential to self‐understanding, autobiographical memory, social cognition, prospection, and theory‐of‐mind. Cultural models, it is argued, are acquired through innate motivational processes that tie the individual emotionally to a secure base of familiar people and customs. This instinctual desire for proximity to others facilitates the efficient, largely implicit, patterning of knowledge and expectations. Shared knowledge and expectations, in turn, create a common, mostly implicit or unconscious, experience of subjectivity within groups. This allows each individual to automatically and effortlessly interact with similarly enculturated others.  相似文献   
145.
With the increasing popularity of social media and web-based forums, the distribution of fake news has become a major threat to various sectors and agencies. This has abated trust in the media, leaving readers in a state of perplexity. There exists an enormous assemblage of research on the theme of Artificial Intelligence (AI) strategies for fake news detection. In the past, much of the focus has been given on classifying online reviews and freely accessible online social networking-based posts. In this work, we propose a deep convolutional neural network (FNDNet) for fake news detection. Instead of relying on hand-crafted features, our model (FNDNet) is designed to automatically learn the discriminatory features for fake news classification through multiple hidden layers built in the deep neural network. We create a deep Convolutional Neural Network (CNN) to extract several features at each layer. We compare the performance of the proposed approach with several baseline models. Benchmarked datasets were used to train and test the model, and the proposed model achieved state-of-the-art results with an accuracy of 98.36% on the test data. Various performance evaluation parameters such as Wilcoxon, false positive, true negative, precision, recall, F1, and accuracy, etc. were used to validate the results. These results demonstrate significant improvements in the area of fake news detection as compared to existing state-of-the-art results and affirm the potential of our approach for classifying fake news on social media. This research will assist researchers in broadening the understanding of the applicability of CNN-based deep models for fake news detection.  相似文献   
146.
ObjectiveThis study examined the role of the Five Factor Model and grandiose narcissism in players’ positive (i.e., constructive voice, supportive voice) and negative voice (i.e., defensive voice, destructive voice) in elite sport teams.MethodPlayers from six field hockey and seven korfball teams from the two highest national levels were assessed for four weeks. Using social network analyses, players’ personality was related to their self-reported voice frequency, their voice frequency as perceived by all teammates (other-ratings), and the extent to which they pass on voice.ResultsExtraversion was positively related to players’ frequency of positive and negative voice. Other traits such as conscientiousness and emotional stability were only related to, respectively, positive or negative types of voice. Not all personalities (e.g., extraversion) were consistent in how they assess their own voice versus how others perceive this. Interestingly, traits such as extraversion, emotional stability and the agentic facet of narcissism were found to predict the passing on of voice.ConclusionThis study explored the importance of personality for (a) players’ frequency of a differentiated set of positive and negative voice and (b) the extent to which they function as ‘gates’ that more covertly pass on voice. Further, the results provide perspective on how specific personalities view their voice behavior versus how their teammates perceive their voice behavior. In this way, this study is a first step in identifying players who have the potential to endanger or strengthen a team in a clear or subtle, yet influential way.  相似文献   
147.
何铨  江程铭 《心理科学》2020,(2):430-437
老年人意外伤害保险作为应对人口老龄化带来的意外风险的措施之一,能够有效缓解老年人意外伤害给其和家庭造成的经济负担。然而该险种购买不足的现状有可能影响其持续运营。本研究试图通过四个子研究探讨默认选项的助推方式是否能够促进老年人意外伤害险在线购买额。研究1通过实际销售数据分析,研究2~4通过实验发现:把默认选项设置在最高份数上能够有效地促进保险的购买份额。研究表明应用行为科学的发现可以有效促进公共政策的实施。  相似文献   
148.
In the hope of complementing the structural perspective in upper echelon research and advancing a fine-grained understanding of dyadic leadership influence in management teams, the current study combines two types of intrateam structures—leadership network and friendship network—to create a multidimensional conceptualization of leadership structure in management teams. Specifically, we propose that management teams with a denser singular leadership network (i.e., a network consisting of many leadership ties that are not coupled with friendship ties) should have lower management team cohesion, which subsequently renders worse business unit performance. To contrast, management teams with a denser multiplex network (i.e., a network consisting of many leadership ties that are coupled with friendship ties) should have higher management team cohesion, which subsequently renders better business unit performance. Guided by structural contingency perspective, we further propose that management team task interdependence will strengthen team cohesion's positive impact on business unit performance. To test the hypothesized model, we collected team-level social network data and multiple-wave survey data from 697 managers nested in 148 hotels (i.e., 148 management teams) owned by a large hospitality company. We also obtained objective performance data for each hotel (i.e., occupancy percentage rate and revenue per available room per day) as the criterion measure. The data supported our hypotheses. The theoretical and practical implications of our findings are discussed.  相似文献   
149.
This article reviews the causal implications of latent variable and psychometric network models for the validation of personality trait questionnaires. These models imply different data generating mechanisms that have important consequences for the validity and validation of questionnaires. From this review, we formalize a framework for assessing the evidence for the validity of questionnaires from the psychometric network perspective. We focus specifically on the structural phase of validation, where items are assessed for redundancy, dimensionality, and internal structure. In this discussion, we underline the importance of identifying unique personality components (i.e. an item or set of items that share a unique common cause) and representing the breadth of each trait's domain in personality networks. After, we argue that psychometric network models have measures that are statistically equivalent to factor models but we suggest that their substantive interpretations differ. Finally, we provide a novel measure of structural consistency, which provides complementary information to internal consistency measures. We close with future directions for how external validation can be executed using psychometric network models. © 2020 European Association of Personality Psychology  相似文献   
150.
This study investigated the perceived sources of happiness among young men and women. Rank scores of the perceived reasons for happiness were compared between the two groups and seven significant differences were discerned. Men ranked “sexual activity”, “sports”, being “liked” and having a “good social life” significantly higher than women. Women ranked “helping others”, having a “close family” and being “loved by loved ones” significantly higher than men. A modified form of network analysis was also conducted. Both networks demonstrated similar core representations of happiness with a focus on self-confidence, being free of stress, occupational and social factors, family support and personal relationships. However, the networks show an association between sexual activity and male personal relationships, whereas emotional factors are associated with female personal relationships. The male network also demonstrates the importance of sports and physical activity in male happiness. Despite some gender differences, it is suggested that the similarities within the mean rank scores and networks form the core elements of a shared social representation of happiness.  相似文献   
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