A primal-dual approximation algorithm for the Asymmetric Prize-Collecting TSP

We present a primal-dual ?log(n)?-approximation algorithm for the version of the asymmetric prize collecting traveling salesman problem, where the objective is to find a directed tour that visits a subset of vertices such that the length of the tour plus the sum of penalties associated with vertices not in the tour is as small as possible. The previous algorithm for the problem (V.H. Nguyen and T.T Nguyen in Int. J. Math. Oper. Res. 4(3):294–301, 2012) which is not combinatorial, is based on the Held-Karp relaxation and heuristic methods such as the Frieze et al.’s heuristic (Frieze et al. in Networks 12:23–39, 1982) or the recent Asadpour et al.’s heuristic for the ATSP (Asadpour et al. in 21st ACM-SIAM symposium on discrete algorithms, 2010). Depending on which of the two heuristics is used, it gives respectively 1+?log(n)? and $3+ 8\frac{\log(n)}{\log(\log(n))}$ as an approximation ratio. Our algorithm achieves an approximation ratio of ?log(n)? which is weaker than $3+ 8\frac{\log(n)}{\log(\log(n))}$ but represents the first combinatorial approximation algorithm for the Asymmetric Prize-Collecting TSP.     

A pragmatic adaptive enrichment design for selecting the right target population for cancer immunotherapies

One of the challenges in the design of confirmatory trials is to deal with uncertainties regarding the optimal target population for a novel drug. Adaptive enrichment designs (AED) which allow for a data-driven selection of one or more prespecified biomarker subpopulations at an interim analysis have been proposed in this setting but practical case studies of AEDs are still relatively rare. We present the design of an AED with a binary endpoint in the highly dynamic setting of cancer immunotherapy. The trial was initiated as a conventional trial in early triple-negative breast cancer but amended to an AED based on emerging data external to the trial suggesting that PD-L1 status could be a predictive biomarker. Operating characteristics are discussed including the concept of a minimal detectable difference, that is, the smallest observed treatment effect that would lead to a statistically significant result in at least one of the target populations at the interim or the final analysis, respectively, in the setting of AED.     

Young people's decision making involvement and educational attainment

Increasing participation in family decision making is an integral part of adolescent development. This paper uses longitudinal data from four low and middle income countries—Ethiopia, India, Peru and Vietnam—to assess the relationship between young people's involvement in schooling decision making and schooling outcomes. In the pooled sample, compared to young adults who indicate to have no say in educational choices at age 19, adolescents who make these decisions unilaterally or jointly with parents are on average 17%–23% more likely to drop out by age 22. The effects are, however, heterogenous across countries.     

Credit and Ethnic Consumption Inequality in the Central Highlands of Vietnam

Social Indicators Research - Credit is commonly considered an important instrument to relieve financial capital constraints of poor households and subsequently to improve their welfare. However,...     

COMPUTER-AIDED CONSTRUCTION OF SMALL (M, S)-OPTIMAL INCOMPLETE BLOCK DESIGNS

A new exchange algorithm for the construction of (M, S)-optimal incomplete block designs (IBDS) is developed. This exchange algorithm is used to construct 973 (M, S)-optimal IBDs (v, k, b) for v= 4,…,12 (varieties) with arbitrary v, k (block size) and b (number of blocks). The efficiencies of the “best” (M, S)-optimal IBDs constructed by this algorithm are compared with the efficiencies of the corresponding nearly balanced incomplete block designs (NBIBDs) of Cheng(1979), Cheng & Wu (1981) and Mitchell & John(1976).     

A new diagnostic tool for VARMA(p,q) models

A new diagnostic method for VARMA(p,q) time series models is introduced. The procedure is based on a statistic that generalizes to a multivariate setting the properties of the usual univariate ARMA(p,q) residual correlations. A multiple version of the cumulative periodogram statistic is also suggested. Simulation studies and one real data application are presented.     

Leadership and Stress Orientations of Germans: An Examination Based on Gender, Age, and Government Work Experience

Today??s working adults often display different leadership orientations, as well as moderate to severe levels of stress depending on the situation and various demographic traits. In order to explore the stress, task orientation and relationship orientation variables of German people, this study examined the differences of 232 respondents in Germany based on their gender, age, and public sector work experience. The results showed that respondents had dissimilar scores on their leadership orientations. Younger respondents had significantly lower task and relationship orientation scores. Furthermore, females reported having a significantly higher level of stress perception. These findings are useful for expatriate managers and professionals who work with German-born workers. Besides, relevant literature on the German culture, suggestions and implications for future studies are presented.     

Depressive Symptoms in Mothers of Recently Adopted Post-Institutionalized Children

To determine whether depressive symptoms are elevated within months of adoption, we compared women who had recently adopted a toddler from an overseas orphanage to women with children of the same age who adopted more than a year before or were raising a child they birthed. The groups did not differ significantly in means or in percentage with elevated symptoms (Session 1, χ²(2) = 2.5, ns; Session 2, χ²(2) = 1.38, ns). The results provided no evidence of elevated symptoms in the first months following adoption for women who adopted internationally relative to other women with toddler-aged children.     

Mixture Multi-state Markov Regression Model

Although heterogeneity across individuals may be reduced when a two-state process is extended into a multi-state process, the discrepancy between the observed and the predicted for some states may still exist owing to two possibilities, unobserved mixture distribution in the initial state and the effect of measured covariates on subsequent multi-state disease progression. In the present study, we developed a mixture Markov exponential regression model to take account of the above-mentioned heterogeneity across individuals (subject-to-subject variability) with a systematic model selection based on the likelihood ratio test. The model was successfully demonstrated by an empirical example on surveillance of patients with small hepatocellular carcinoma treated by non-surgical methods. The estimated results suggested that the model with the incorporation of unobserved mixture distribution behaves better than the one without. Complete and partial effects regarding risk factors on different subsequent multi-state transitions were identified using a homogeneous Markov model. The combination of both initial mixture distribution and homogeneous Markov exponential regression model makes a significant contribution to reducing heterogeneity across individuals and over time for disease progression.