Subjects: Digital Publishing >> New Media submitted time 2023-10-08 Cooperative journals: 《中国传媒科技》
Abstract：全媒体时代来临,给新闻宣传带来了良好的机遇,同时伴随新的挑战,特别是让媒体人面临空前未有的生存考验。本文提出新形势下传统媒体人如何创新报道,新媒体人如何提高新闻写作能力,并树立新闻理想,做个全能的新闻工作者,适应新闻报道的需求。
Subjects: Psychology >> Social Psychology submitted time 2023-03-28 Cooperative journals: 《心理科学进展》
Abstract： As an important predictor of violent crime, recidivism, and juvenile delinquency, psychopathy has received extensive attention in clinical psychology and justice research. Recent studies have conceptualized psychopathy as multidimensional constructs, proposed to further understand various phenotypic constructs of psychopathy through the interaction of distinct psychopathic dispositions. The Triarchic Model of Psychopathy (TriPM) conceptualizing psychopathy as three phenotypic structures (boldness, meanness, and disinhibition) with independent etiologic pathways, provides a framework for integrating the previous findings of the assessment, development trajectory, and neurobiological process of psychopathy.At first, the TriPM boldness includes the characteristics of stress immunity, low fear, and insensitivity to punishment. It is an adaptive expression of fearlessness genotype, which corresponds to the neurobiological dimension of low threat sensitivity. Previous studies have shown that psychopathic individuals with high affective-interpersonal (Factor 1) or boldness features are expected to exhibit reduced aversive startle potentiation, difficulty in establishing threat-related conditioning, abnormal amygdala volume, and lower levels of amygdala activation in threat context. These findings reflect the core defensive system of psychopathy—based in the amygdala and affiliated structures—is insensitive to threat or punishment cues.Second, individuals with high levels of trait disinhibition are characterized by lack of planning and foresight, poor regulation of emotion and impulse, insistence on immediate gratification, and lack of behavioral restraint. They showed reduced P3 and ERN amplitudes in go/no-go tasks and flanker tasks, fail to process and attend to contextual or environmental cues when engaged in a dominant response set (e.g., goal-directed behavior). Give the evidence that individuals with high disinhibition tend to exhibit poor performance in various cognitive tasks, it can be speculated that the impairment of executive function, in particular the impaired ability of attentional modulation, is closely associated with psychopathic disinhibition. Moreover, the motivational system (i.e., reward-seeking) may exacerbate the deficits of executive function in individuals with high disinhibition disposition. Finally, as the maladaptive expression of the fearless genotype, meanness describes a constellation of various phenotypic attributes including arrogance, rebelliousness, lack of intimacy, excitement seeking, and empowerment through cruelty. On the one hand, impaired emotional processes will lead to an empathic deficit, which may contribute to the development of psychopathic meanness. Extensive research has shown that abnormalities in physiological structures such as the insula and anterior cingulate cortex in psychopathy are associated with reduced subjective emotional experience and poor ability to recognize other’s distress cues. On the other hand, insecure attachment associated with empathic deficit may be an important environmental factor that exacerbates individual meanness disposition.By integrating the low threat sensitivity, impaired executive function, and empathic deficit of psychopathy with the boldness, disinhibition, and meanness of the TriPM model, the current study establishes a relatively complete cognition-affective processing framework of psychopathy, provides some useful information for theoretical research and clinical treatment about this personality disorder. However, this framework can not account for all the clinical conditions of psychopathy, as the factors that influence the phenotype of psychopathy are diverse. For example, previous research has demonstrated that gender, race, age, sample type, and psychopathic measures are all important moderators in the study of psychopathy. There are also controversies about the conceptualization of psychopathic variants or subtypes. In addition, the exclusivity of psychopathic phenotypes and their underlying neurobiological processes is still unclear.Therefore, future research should consider the influence of these moderators on the explanation of the results. And greater attention should be paid to the underlying etiological pathways among different psychopathic constructs, it is also a verification of the discriminative validity among three dimensions of the TriPM model. Moreover, further exploration of the precursors of adult psychopathic traits will provide important information about the development of psychopathic deviant behavior, which does great help for the early treatment and intervention of this disorder.
Subjects: Psychology >> Personality Psychology submitted time 2021-04-22
Abstract： As an important predictor of violent crime, recidivism, and juvenile delinquency, psychopathy has received extensive attention in clinical psychology and justice research. The Triarchic Model of Psychopathy conceptualized psychopathy as three phenotypic structures include boldness, meanness, and disinhibition, which counterpart to distinct cognitive and affective processing defects in neurobiological dimensions. In particular, low threat sensitivity is the main etiological basis of boldness; the impairment of executive function, especially the impaired attentional modulation will lead to disinhibition; and the empathy deficits associated with emotion recognition may contribute to the development of meanness. Future research still needs to focus on the conceptualization of psychopathy and to further investigate whether there is a common underlying etiological basis between different psychopathic variants. Meanwhile, it is necessary to explore the precursors of adult psychopathic traits for early treatment and intervention.
Peer Review Status:
Awaiting Review
Subjects: Linguistics and Applied Linguistics >> Linguistics and Applied Linguistics submitted time 2020-11-10
Abstract：本文通过声学实验提取基频数据，研究了天柱方言的单字调和双字调的声调模式。实验数据表明天柱方言有4个单字调：1个平调，1个降调，2个升调，其中阴平、阳平、上声和去声的五度值分别为12、11、32、45。理论上，天柱方言双字调共有16种组合模式，经过实验数据分析后，双字调只有14种组合模式。天柱方言双字调中，后字较易变调；作为后字的阴平、上声和去声较易发生变调，阳平极为稳定，没有发生变调；只有上声和去声相配时，前后两字都变调。
Peer Review Status:Awaiting Review
Subjects: Environmental Sciences, Resource Sciences >> Basic Disciplines of Environmental Science and Technology submitted time 2019-03-07 Cooperative journals: 《干旱区地理》
Abstract：以新疆74个县域单元为研究对象选取多个指标，利用ESDA、ArcGIS和GeoDa等分析方法和手段及动态面板数据模型，分析2008—2017年新疆县域单元旅游经济空间格局演变特征地域差异及驱动机制。结果表明：（1）县域旅游经济集聚特征呈“下降―上升―下降―上升”的态势，彼此之间差异明显，集聚性存在显著的由北向南梯度增强的格局特征。（2）县域旅游经济的“多核心、多条带”分布逐渐形成，但并未改变“北热南冷”的分布格局。（3）受“东北-西南”方向牵引力影响，旅游经济重心轨迹变化呈多个“V”字型重叠分布，也使标准差椭圆的覆盖范围也在此方向上逐渐增大。（4）旅游资源禀赋和政策支持是影响县域旅游经济格局演变的主要驱动因素。交通条件的改善和人力资本水平的提高并非都能促进各县域旅游经济的发展，各影响因素在不同区域间存在明显的强度差异。
Subjects: Computer Science >> Integration Theory of Computer Science submitted time 2019-01-03 Cooperative journals: 《计算机应用研究》
Abstract： To handle the issues of low accuracy and lacking training samples in abnormal crowd behavior detection in public places, this paper proposes a method based on deep spatial-temporal convolutional neural networks in this paper. In view of the characteristics of crowd behavior in monitoring videos, a deep spatial-temporal convolution neural network for detecting abnormal crowd behavior is first designed by extending 2D convolution to the 3D space according to spatial features of static images and temporal features between the frames before and after the current frame. To locating abnormal crowd, this paper divides video frames into a number of subregions that obtain spatial-temporal samples. Then, the samples are input into the designed deep spatial-temporal convolutional neural network for training and classification, whose results are used to detect and locate abnormal crowd. In the meanwhile, this paper utilizes a transfer learning method to deal with the issue of lacking training samples when training the deep spatial-temporal convolutional neural network, where datasets with more training samples are used to pre-train the network which is fine-tuned and optimized on testing datasets with fewer samples. Experimental results show that the detection accuracies on UCSD and Subway open datasets are greater than 99% and 93%, respectively.
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