大学生就业心理障碍的成因与对策分析

在严峻的就业形势面前,部分毕业生心理压力过大,产生了就业心理障碍,影响了他们的顺利就业。通过对大学生就业心理的研究,分析产生障碍的原因,探索克服障碍的对策措施,对促进大学生顺利就业,具有十分重要的现实意义。     

师范院校体育系、科学生必须注重训练和竞赛实践

师范院校体育系、科学生加强课外训练与竞赛 ,不仅能理论联系实际 ,积累较多的实践经验 ,而且可以在将来的教学工作中成为学校体育带头人     

Can We Perceive Near Miss? An Empirical Study

Near misses are a special kind of reinforcement which increases one’s desire to play. The aim of this paper is to examine the perception of near misses in normal population. We used a slot machine simulation running on a PC, where participants had to play four rounds with different near miss ratios (0, 15, 30 and 45%). Our sample consisted of 159 individuals with mean age of 22.8 and with no or little gambling experience. For data analysis we used chi-squared goodness-of-fit test and exact binomial test. Despite the fact, that there was a notable effect of near misses results showed that the subjects could not perceive trials of them.     

朱光潜《诗论》的诗学原理建构

通过苏州轨道交通1号线土建I TS 05标塔园路站～滨河路站区间隧道盾构施工，介绍在苏州富水粉砂地层中盾构综合施工技术。施工中，克服了富水砂层下盾构到达加固区水平长度不足的困难，使用了在加固区外再施工一圈止水帷幕桩的地基加固技术，该技术可以使三轴加固土体与止水帷幕桩组合形成一个范围更大的端头地基加固区域，并在盾构到达段掘进中合理使用管片壁后二次注浆和聚氨酯，成功地阻断微承压水在盾构到达时涌出的路径，从而解决了富水砂层下盾构到达施工的涌水、涌砂问题。通过使用,该技术保证了2台盾构安全成功接收，在富水粉砂地层具有适用性广、安全可控等优点。     

Graphical and Numerical Methods for Detecting Influential Observations in Complex Bingham Data

We describe methods to detect influential observations in a sample of pre-shapes when the underlying distribution is assumed to be complex Bingham. One of these methods is based on Cook's distance, which is derived from the likelihood of the complex Bingham distribution. Other method is related to the tangent space, which is based on the local influence for the multivariate normal distribution. A method to detect outliers is also explained. The application of the methods is illustrated in both a real dataset and a simulated sample.     

New Shrinkage Parameters for the Liu-type Logistic Estimators

The binary logistic regression is a widely used statistical method when the dependent variable has two categories. In most of the situations of logistic regression, independent variables are collinear which is called the multicollinearity problem. It is known that multicollinearity affects the variance of maximum likelihood estimator (MLE) negatively. Therefore, this article introduces new shrinkage parameters for the Liu-type estimators in the Liu (2003) in the logistic regression model defined by Huang (2012) in order to decrease the variance and overcome the problem of multicollinearity. A Monte Carlo study is designed to show the goodness of the proposed estimators over MLE in the sense of mean squared error (MSE) and mean absolute error (MAE). Moreover, a real data case is given to demonstrate the advantages of the new shrinkage parameters.     

Different Pathways from Transformational Leadership to Job Satisfaction

Transformational leaders are known to inspire and motivate their followers, thereby leading to enhanced job satisfaction. Job satisfaction is an intellectual concept regarding individuals’ attitudes toward their jobs. This study asserts that the underlying mechanisms for transformational leadership to affect employee satisfaction are trust in the community, including the leader (that is, organization) and trust in the self, namely self‐efficacy. Leadership is specifically associated with continual transformations in the higher educational context, and collectivist cultures may manifest different processes underlying the transformational leadership–satisfaction relationship. This study investigated the mediating effects of trust and self‐efficacy on the relationship between transformational leadership and job satisfaction. The study sample included academicians from a nonprofit higher education institution in Turkey. The data were analyzed using structural equation modeling. The results showed that the relationship between transformational leadership and job satisfaction is fully mediated by both trust and self‐efficacy. The mediator effect of trust was shown to be stronger than self‐efficacy, which is assumed to be the result of the cultural context. The results are discussed in the context of employee satisfaction and cultural determinants of employee satisfaction.     

Usability in product design--the importance and need for systematic assessment models in product development--Usa-Design Model (U-D) ©

In product design, human factors are considered as an element of differentiation given that today's consumer demands are increasing. Safety, wellbeing, satisfaction, health, effectiveness, efficiency, and other aspects must be effectively incorporated into the product development process. This work proposes a usability assessment model that can be incorporated as an assessment tool. The methodological approach is settled in two stages. First a literature review focus specifically on usability and developing user-centred products. After this, a model of usability named Usa-Design (U-D?) is presented. Consisted of four phases: understanding the use context, pre-preliminary usability assessment (efficiency/effectiveness/satisfaction); assessment of usability principles and results, U-D? features are modular and flexible, allowing principles used in Phase 3 to be changed according to the needs and scenario of each situation. With qualitative/quantitative measurement scales of easy understanding and application, the model results are viable and applicable throughout all the product development process.     

A copula-based Markov chain model for the analysis of binary longitudinal data

A fully parametric first-order autoregressive (AR(1)) model is proposed to analyse binary longitudinal data. By using a discretized version of a copula, the modelling approach allows one to construct separate models for the marginal response and for the dependence between adjacent responses. In particular, the transition model that is focused on discretizes the Gaussian copula in such a way that the marginal is a Bernoulli distribution. A probit link is used to take into account concomitant information in the behaviour of the underlying marginal distribution. Fixed and time-varying covariates can be included in the model. The method is simple and is a natural extension of the AR(1) model for Gaussian series. Since the approach put forward is likelihood-based, it allows interpretations and inferences to be made that are not possible with semi-parametric approaches such as those based on generalized estimating equations. Data from a study designed to reduce the exposure of children to the sun are used to illustrate the methods.     

A new generalized two-sided class of distributions with an emphasis on two-sided generalized normal distribution

The ordinary-G class of distributions is defined to have the cumulative distribution function (cdf) as the value of the cdf of the ordinary distribution F whose range is the unit interval at G, that is, F(G), and it generalizes the ordinary distribution. In this work, we consider the standard two-sided power distribution to define other classes like the beta-G and the Kumaraswamy-G classes. We extend the idea of two-sidedness to other ordinary distributions like normal. After studying the basic properties of the new class in general setting, we consider the two-sided generalized normal distribution with maximum likelihood estimation procedure.