Teachers’ Knowledge and Beliefs About Child Sexual Abuse

Child sexual abuse is one of the main types of abuse still to be addressed within the field of education, yet the education system itself can serve as a primary tool for its prevention. A better understanding of teachers’ knowledge and beliefs about child sexual abuse will allow us to establish key starting points from which to utilize the system for prevention. Four hundred and fifty teachers participated in this study, completing a questionnaire regarding their knowledge and beliefs about child sexual abuse. The study revealed that over half the teachers, 65.3% (n = 294), had never received any type of training in child sexual abuse education and that the majority were not familiar with methods of identifying child sexual abuse, 90.7% (n = 279). Various mistaken beliefs were identified among the participating teachers, such as pathological profiles of abusers, that the vast majority of child sexual abuse implies violent behavior, and that there cannot be abusers the same age as the victim. These results indicate that knowledge deficiencies do exist about child sexual abuse among teachers and highlight the need for training in this field.     

FDR control of detected regions by multiscale matched filtering

Feature extraction from observed noisy samples is a common important problem in statistics and engineering. This paper presents a novel general statistical approach to the region detection problem in long data sequences. The proposed technique is a multiscale kernel regression in conjunction with statistical multiple testing for region detection while controlling the false discovery rate (FDR) and maximizing the signal-to-noise ratio via matched filtering. This is achieved by considering a one-dimensional region detection problem as its equivalent zero-dimensional peak detection problem. The detection method does not require a priori knowledge of the shape of the nonzero regions. However, if the shape of the nonzero regions is known a priori, e.g., rectangular pulse, the signal regions can also be reconstructed from the detected peaks, seen as their topological point representatives. Simulations show that the method can effectively perform signal detection and reconstruction in the simulated data under high noise conditions, while controlling the FDR of detected regions and their reconstructed length.     

高等学校校院两级教学督导体系的探讨

从完善现代大学制度、建立高校内部监控机制等视角，分析了高校校院两级教学督导体系的组织架构、职能定位和运行机制，提出了高校教学督导工作新的管理理念和实施方法。     

互联网环境下学术期刊防范学术不端行为技术研究

利用互联网环境，从技术的角度出发，对一稿多投、抄袭行为、剽窃行为以及捏造行为等学术不端行为的检测与防范进行研究，提出了各种操作上可行的方法。实践证明，运用这些方法，可有效地防范有学术不端行为的文章在学术期刊上发表。     

德、位张力与先秦儒家的性命之学——对楚简《唐虞之道》第14至29号简的思想解读

文章系统解读了楚简《唐虞之道》第14至29号简的思想内涵及脉络,认为这部分简文首先通过尧成为天子之原因的追问,突出了德与位的张力问题,即在应然之理上,有位必当有德,但就实然之事看,有德未必有位.简文对这一德位张力有两个层面的解决方案:一方面,要求有德无位者全力修德,谨守性命,安于时命,养成恒常如一的圆满德行,从而能在得位而治时能“利天下而弗利”；另一方面,要求有位者透悟性命之正,从而能主动尚德授贤、退而养生,这既能使贤者居位而利天下,又能退而养生以自利.简文将“七十致政”之礼普遍化,试图断绝天子终身制的构想,也具有深刻的政治哲学意义.     

Retrospective change detection in categorical time series

The aim of this paper is to propose methods of detecting change in the coefficients of a multinomial logistic regression model for categorical time series offline. The alternatives to the null hypothesis of stationarity can be either the hypothesis that it is not true, or that there is a temporary change in the sequence. We use the efficient score vector of the partial likelihood function. This has several advantages. First, the alternative value of the parameter does not have to be estimated; hence, we have a procedure that has a simple structure with only one parameter estimation using all available observations. This is in contrast with the generalized likelihood ratio-based change point tests. The efficient score vector is used in various ways. As a vector, its components correspond to the different components of the multinomial logistic regression model’s parameter vector. Using its quadratic form a test can be defined, where the presence of a change in any or all parameters is tested for. If there are too many parameters one can test for any subset while treating the rest as nuisance parameters. Our motivating example is a DNA sequence of four categories, and our test result shows that in the published data the distribution of the four categories is not stationary.     

Variable selection for semiparametric proportional hazards model under progressive Type-II censoring

Variable selection is an effective methodology for dealing with models with numerous covariates. We consider the methods of variable selection for semiparametric Cox proportional hazards model under the progressive Type-II censoring scheme. The Cox proportional hazards model is used to model the influence coefficients of the environmental covariates. By applying Breslow’s “least information” idea, we obtain a profile likelihood function to estimate the coefficients. Lasso-type penalized profile likelihood estimation as well as stepwise variable selection method are explored as means to find the important covariates. Numerical simulations are conducted and Veteran’s Administration Lung Cancer data are exploited to evaluate the performance of the proposed method.     

浅谈行动导向教学法在教学中的实践

主要以怠速控制阀的结构、原理及检测学习任务为例,阐述了如何在教学中实践以培养关键能力为核心的"行动导向教学法"。     

白居易融会三教的“中隐”思想及其仕隐心态

白居易的"中隐"思想是对传统仕隐观念的继承、整合和发展,其本质上既区别于隐于山林的"小隐",也与隐于朝市的"大隐"不同,而是隐于地方官、散官、闲官。它巧妙地平衡了集权专制与士大夫独立意识之间的矛盾,是一种能在入世与出世间进退裕如的处世哲学和生活方式。这一以仕求隐的隐逸观,较之魏晋时期"居官无官官之事,处事无事事之心"的仕宦态度要积极得多,它更圆融通达地调谐了身与心、职与事、仕与隐的矛盾,是白居易以儒治身、以佛道修心的人生哲学的具体体现。     

Outlier detection in high-dimensional regression model

An outlier is defined as an observation that is significantly different from the others in its dataset. In high-dimensional regression analysis, datasets often contain a portion of outliers. It is important to identify and eliminate the outliers for fitting a model to a dataset. In this paper, a novel outlier detection method is proposed for high-dimensional regression problems. The leave-one-out idea is utilized to construct a novel outlier detection measure based on distance correlation, and then an outlier detection procedure is proposed. The proposed method enjoys several advantages. First, the outlier detection measure can be simply calculated, and the detection procedure works efficiently even for high-dimensional regression data. Moreover, it can deal with a general regression, which does not require specification of a linear regression model. Finally, simulation studies show that the proposed method behaves well for detecting outliers in high-dimensional regression model and performs better than some other competing methods.