Saddlepoint Approximations to the Probability of Ruin in Finite Time for the Compound Poisson Risk Process Perturbed by Diffusion

A large deviations type approximation to the probability of ruin within a finite time for the compound Poisson risk process perturbed by diffusion is derived. This approximation is based on the saddlepoint method and generalizes the approximation for the non-perturbed risk process by Barndorff-Nielsen and Schmidli (Scand Actuar J 1995(2):169–186, 1995). An importance sampling approximation to this probability of ruin is also provided. Numerical illustrations assess the accuracy of the saddlepoint approximation using importance sampling as a benchmark. The relative deviations between saddlepoint approximation and importance sampling are very small, even for extremely small probabilities of ruin. The saddlepoint approximation is however substantially faster to compute.

The timing of extraction of non-restorable first permanent molars: a systematic review.

AIM To identify the ideal timing of first permanent molar extraction to reduce the future need for orthodontic treatment. MATERIALS AND METHODS A computerised database and subsequent manual search was performed using Medline database, Embase and Ovid, covering the period from January 1946 to February 2013. Two reviewers (JE and ME) extracted the data independently and evaluated if the studies matched the inclusion criteria. Inclusion criteria were specification of the follow-up with clinical examination or analysis of models, specification of the chronological age or dental developmental stage at the time of extraction, no treatment in between, classification of the treatment result into perfect, good, average and poor. The search was limited to human studies and no language limitations were set. RESULTS The search strategy resulted in 18 full-text articles, of which 6 met the inclusion criteria. By pooling the data from maxillary sites, good to perfect clinical outcome was estimated in 72% (95% confidence interval 63%-82%). Extractions at the age of 8-10.5 years tended to show better spontaneous clinical outcomes compared to the other age groups. By pooling the data from mandibular sites, extractions performed at the age of 8-10.5 and 10.5-11.5 years showed significantly superior spontaneous clinical outcome with a probability of 50% and 59% likelihood, respectively, to achieve good to perfect clinical result (p<0.05) compared to the other age groups (<8 years of age: 34%, >11.5 years of age: 44%). CONCLUSION Prevention of complications after first permanent molars extractions is an important issue. The overall success rate of spontaneous clinical outcome for maxillary extraction of first permanent molars was superior to mandibular extraction. Extractions of mandibular first permanent molars should be performed between 8 and 11.5 years of age in order to achieve a good spontaneous clinical outcome. For the extraction in the maxilla, no firm conclusions concerning the ideal extraction timing could be drawn.

The information bottleneck method for genome-wide association studies

In population studies, most current methods focus on identifying one outcome-related SNP at a time by testing for differences of genotype frequencies between disease and healthy groups or among different population groups. However, testing a great number of SNPs simultaneously has a problem of multiple testing and will give false-positive results. Although, this problem can be effectively dealt with through several approaches such as Bonferroni correction, permutation testing and false discovery rates, patterns of the joint effects by several genes, each with weak effect, might not be able to be determined. With the availability of high-throughput genotyping technology, searching for multiple scattered SNPs over the whole genome and modeling their joint effect on the target variable has become possible. Exhaustive search of all SNP subsets is computationally infeasible for millions of SNPs in a genome-wide study. Several effective feature selection methods combined with classification functions have been proposed to search for an optimal SNP subset among big data sets where the number of feature SNPs far exceeds the number of observations. ^ In this study, we take two steps to achieve the goal. First we selected 1000 SNPs through an effective filter method and then we performed a feature selection wrapped around a classifier to identify an optimal SNP subset for predicting disease. And also we developed a novel classification method-sequential information bottleneck method wrapped inside different search algorithms to identify an optimal subset of SNPs for classifying the outcome variable. This new method was compared with the classical linear discriminant analysis in terms of classification performance. Finally, we performed chi-square test to look at the relationship between each SNP and disease from another point of view. ^ In general, our results show that filtering features using harmononic mean of sensitivity and specificity(HMSS) through linear discriminant analysis (LDA) is better than using LDA training accuracy or mutual information in our study. Our results also demonstrate that exhaustive search of a small subset with one SNP, two SNPs or 3 SNP subset based on best 100 composite 2-SNPs can find an optimal subset and further inclusion of more SNPs through heuristic algorithm doesn't always increase the performance of SNP subsets. Although sequential forward floating selection can be applied to prevent from the nesting effect of forward selection, it does not always out-perform the latter due to overfitting from observing more complex subset states. ^ Our results also indicate that HMSS as a criterion to evaluate the classification ability of a function can be used in imbalanced data without modifying the original dataset as against classification accuracy. Our four studies suggest that Sequential Information Bottleneck(sIB), a new unsupervised technique, can be adopted to predict the outcome and its ability to detect the target status is superior to the traditional LDA in the study. ^ From our results we can see that the best test probability-HMSS for predicting CVD, stroke,CAD and psoriasis through sIB is 0.59406, 0.641815, 0.645315 and 0.678658, respectively. In terms of group prediction accuracy, the highest test accuracy of sIB for diagnosing a normal status among controls can reach 0.708999, 0.863216, 0.639918 and 0.850275 respectively in the four studies if the test accuracy among cases is required to be not less than 0.4. On the other hand, the highest test accuracy of sIB for diagnosing a disease among cases can reach 0.748644, 0.789916, 0.705701 and 0.749436 respectively in the four studies if the test accuracy among controls is required to be at least 0.4. ^ A further genome-wide association study through Chi square test shows that there are no significant SNPs detected at the cut-off level 9.09451E-08 in the Framingham heart study of CVD. Study results in WTCCC can only detect two significant SNPs that are associated with CAD. In the genome-wide study of psoriasis most of top 20 SNP markers with impressive classification accuracy are also significantly associated with the disease through chi-square test at the cut-off value 1.11E-07. ^ Although our classification methods can achieve high accuracy in the study, complete descriptions of those classification results(95% confidence interval or statistical test of differences) require more cost-effective methods or efficient computing system, both of which can't be accomplished currently in our genome-wide study. We should also note that the purpose of this study is to identify subsets of SNPs with high prediction ability and those SNPs with good discriminant power are not necessary to be causal markers for the disease.^

Estrategias para la reinserción social de jóvenes en conflicto con la ley

La justicia penal adolescente es un sistema de administración judicial que extiende los derechos y garantías del debido proceso a los adolescentes a quienes se acuse de haber participado en la comisión de una infracción a la ley penal. Se podría decir que las finalidades de la justicia penal juvenil, por orden de importancia son: Administrar justicia de forma democrática. Fomentando la responsabilización del adolescente que ha cometido una infracción penal; promoviendo su integración social y favoreciendo la participación de la comunidad en el proceso de reinserción social, mediante la oferta de servicios y programas para el cumplimiento de medidas socio-educativas. Cabe preguntarse ¿Las instituciones correccionales son coadyuvantes en la reinserción de los jóvenes en conflicto con la ley de tal modo que no vuelvan a confrontar con el orden jurídico vigente cuando egresen? La respuesta es muy compleja porque si bien desde la situación de las instituciones el aislamiento que sufre el joven no les da defensas para poder cambiar sus circunstancias de vida a la hora de reingresar a la sociedad y esto lleva a una alta probabilidad de volver a delinquir. Sin embargo las Ciencias Sociales plantean otras alternativa para logran la inserción de los jóvenes, una de ellas, se inclina a la estimulación de la resiliencia. Esta implica: sobreponerse a las dificultades y tener éxito a pesar de estar expuestos a situaciones de alto riesgo; mantener la competencia bajo presión, esto significa adaptarse con éxito y recuperarse de un trauma ajustándose de forma exitosa a los acontecimientos negativos de la vida.