试论唐代咏史赋的源流与价值

唐代咏史赋的源流与价值可以从两个方面探讨：一　为咏史赋在赋史上的渊源;另一为咏史赋与魏晋史论的渊源关系。咏史赋在形式与创作手法　上是对汉赋的继承,而咏史赋在题材上是史论的延伸。综合这两个方面,唐代咏史赋这一特　殊的文学样式实际上有两个源流;而它的价值主要体现在其形式上,即唐代律赋的价值。     

Breast Cancer:

Cancer is a major problem for elderly individuals. Overall, it is the second leading cause of death after heart disease and 50% of all documented cases occur in 12% of the population over the age 65. About 50,000 women in the United States age 65 and older are diagnosed annually with breast cancer, making it one of the most serious health oroblems for women in this age ~ O U D I. t is the second leading causk of cancer deaths after lung cancer in women. While breast cancer is not preventable, the survival rate is near 100% if detected earlv. However. late staEe of diamosis remains a concern in this age groip. ~ ~ ~ r o x & n ai0t%e lo~f women with breast cancer present with metastases as the first indication of a malignancy. Early detection and screening offer the only solution to this dreaded situation. Society must find ways to make these practices available to the elderly.     

Objective Bayesian analysis of counting experiments with correlated sources of background

Searches for faint signals in counting experiments are often encountered in particle physics and astrophysics, as well as in other fields. Many problems can be reduced to the case of a model with independent and Poisson-distributed signal and background. Often several background contributions are present at the same time, possibly correlated. We provide the analytic solution of the statistical inference problem of estimating the signal in the presence of multiple backgrounds, in the framework of objective Bayes statistics. The model can be written in the form of a product of a single Poisson distribution with a multinomial distribution. The first is related to the total number of events, whereas the latter describes the fraction of events coming from each individual source. Correlations among different backgrounds can be included in the inference problem by a suitable choice of the priors.     

Substance use disorders and referral to treatment in substantiated cases of child maltreatment

Parents with substance use disorders (SUD) require treatment and support in order to provide children with appropriate care and protection. Using the 2012 National Child Abuse and Neglect Data System (NCANDS), this paper analysed 464 313 substantiated child maltreatment reports to determine (i) the proportion and characteristics of reports involving substance abuse; and (ii) the child and caregiver/perpetrator (C/P) characteristics that predicted referral to treatment as recorded in service plans. Findings indicate that 12% (N = 53 234) of maltreatment reports involved C/P SUD. Yet, of those reports, only (19%) (N = 10 088) were referred to substance abuse treatment as part of their service plan, indicating a large gap between those who need treatment and those who receive it. This finding is important given that parental SUD is consistently linked to poorer child outcomes. Amongst other variables, reports indicate that C/P with co‐occurring emotional disturbance were three times more likely to be referred to treatment for SUD as part of service plans. Additional research is needed regarding the characteristics that distinguish C/P who receive referrals for SUD treatment in substantiated cases of child maltreatment.     

When the Norwegian child-welfare services get involved: parents making sense of referrals

There is limited research exploring parents' views and understanding of referrals to the child-welfare services (CWS). This study explores parents' understanding of the circumstances leading to a child-welfare referral, and their understanding of the reporter's objectives in making the referral. Qualitative content analysis and frequency analysis was performed on open-ended survey responses from a sample of 683 Norwegian parents in contact with the CWS. The results showed that the majority (60.2%) of the parents perceived the referral to be initiated solely because of parental difficulties and multiple family life stressors. Some of the parents (22.8%) believed the referrals were initiated exclusively because of their children's problems, whereas a few (13.3%) perceived it to be a combination of parental/familial difficulties and children's problems. The findings reveal that close to half of the parents (46.4%) felt the objective of the person making the referral was to help the child, their parents and the family. Some (36.5%) saw it as a routine or mandated action by public or official services, while others (18.7%) reported that they did not know why referrals had been made, or gave no answer to the question. A small group of parents (6%) viewed the referral as an act of harassment. The main implications of these findings are discussed.     

The Psychology of the Psychopharmacology Triangle

Abstract

The psychopharmacological triangle generated by recent changes in mental health practices requires social workers to deepen their understanding of the psychological meanings of such treatment. Many clients receive concurrent psychotherapeutic and psychopharmacological interventions from different providers, creating a triangular treatment relationship. To facilitate a successful outcome, social workers will need to understand how meaning, transference and countertransference are stimulated by this arrangement. The literature on these issues as well as clinical experience will highlight specific issues requiring attention. By attending to these dynamics, the social worker can maximize the chances for a successful treatment outcome.     

Sources,Providers and Self-Reported Complications among Indian Women Seeking Induced Abortion: Evidence from the National Family Health Survey (2015–16)

Abstract

This article attempts to find types of sources and providers, and likelihood of self-reported complication among Indian women. Fifty-three percent of abortions are done at private health facilities. Only one in every 5 women went to public health facilities, and the rest did not go anywhere (27.5%). Doctors are the major abortion service providers (52.3%) in India. Eighteen percent of women who sought abortion reported some complication. Logit regression shows that complications were 1.8 times higher in the second-trimester than the first-trimester abortion. This study suggests for addressing the demand of abortion by accessing and improving services in public health system.     

Bayesian classification with multivariate autoregressive sources that might have different orders

The main objective of this paper is to develop an exact Bayesian technique that can be used to assign a multivariate time series realization to one of several autoregressive sources, with unknown coefficients and precision, that might have different orders. The foundation of the proposed technique is to develop the posterior mass function of a classification vector, in an easy form, using the conditional likelihood function. A multivariate time series realization is assigned to the multivariate autoregressive source with the largest posterior probability. A simulation study, with uniform prior mass function, is carried out to demonstrate the performance of the proposed technique and to test its adequacy in handling the multivariate classification problems. The analysis of the numerical results supports the adequacy of the proposed technique in solving the classification problems with multivariate autoregressive sources.     

Multivariate outliers and decompositions of mahalanobis distance

Two decompositions of the Mahalanobis distance are considered. These decompositions help to explain some reasons for the outlyingness of multivari- ate observations. They also provide a graphical tool for identifying outliers including those that have a large influence on the multiple correlation coefficient, Illustrative examples are given.     

Model Averaging for Prediction With Fragmentary Data

ABSTRACT

One main challenge for statistical prediction with data from multiple sources is that not all the associated covariate data are available for many sampled subjects. Consequently, we need new statistical methodology to handle this type of “fragmentary data” that has become more and more popular in recent years. In this article, we propose a novel method based on the frequentist model averaging that fits some candidate models using all available covariate data. The weights in model averaging are selected by delete-one cross-validation based on the data from complete cases. The optimality of the selected weights is rigorously proved under some conditions. The finite sample performance of the proposed method is confirmed by simulation studies. An example for personal income prediction based on real data from a leading e-community of wealth management in China is also presented for illustration.