Bounds on Quantile Treatment Effects of Job Corps on Participants' Wages

This paper assesses the effect of the U.S. Job Corps (JC), the nation's largest and most comprehensive job training program targeting disadvantaged youths, on wages. We employ partial identification techniques and construct informative nonparametric bounds for the causal effect of interest under weaker assumptions than those conventionally used for point identification of treatment effects in the presence of sample selection. In addition, we propose and estimate bounds on quantile treatment effects of the program on participants' wages. In general, we find convincing evidence of positive impacts of JC on participants' wages. Importantly, we find that estimated impacts on lower quantiles of the distribution are higher, with the highest impact being in the 5th percentile where a positive effect on wages is bounded between 8.4 and 16.1 percent. These bounds suggest that JC results in wage compression within eligible participants.Job Corps, Nonparametric Bounds, Principal Stratification, Active Labor Market Programs., Labor and Human Capital, Public Economics, Research Methods/ Statistical Methods, J24, J68, C14, C21,

Bounds on Average and Quantile Treatment Effects of Job Corps Training on Wages

We assess the effectiveness of Job Corps (JC), the largest job training program targeting disadvantaged youth in the United States, by constructing nonparametric bounds for the average and quantile treatment effects of the program on wages. Our preferred estimates point toward convincing evidence of positive effects of JC on wages both at the mean and throughout the wage distribution. For the different demographic groups analyzed, the statistically significant estimated average effects are bounded between 4.6 and 12 percent, while the quantile treatment effects are bounded between 2.7 and 11.7 percent. Furthermore, we find that the program's effect on wages varies across quantiles and groups. Blacks likely experience larger impacts in the lower part of their wage distribution, while Whites likely experience larger impacts in the upper part of their distribution. Non-Hispanic Females show statistically significant impacts in the upper part of their distribution but not in the lower part.training programs, wages, bounds, quantile treatment effects

Actualización de la colección de tipos del herbario MACB, II

CARRASCO, M. A. & MARTÍN-BLANCO, C. J. 2002. Actualización de la colección de Tipos del Herbario MACB. Bot. Complutensis, 26: 59-62. Se actualiza la Colección de Tipos del Herbario MACB, presentando los Typus de siete nombres. Señalamos la categoria de cada Tipo y los herbarios que tienen material tipo de los mismos taxones. Los nuevos Tipos son: 2 Holotypus, 4 Isotypus, 1 Isolectotypus y 2 Sintypus.CARRASCO, M. A. & MARTÍN-BLANCO, C. J. 2002. Update of the MACB type collection, II. Bot. Complutensis, 26: 59-62. In this paper the Type collection of the MACB Herbarium is update. We indicate the category of seven names (Holotypus, Isotypus Isolectotypus or Sintypus), as well as the herbariums with other type specimens of the same taxa. The new Typus are: 2 Holotypus, 4 Isotypus, 1 Isolectotypus and 2 Sintypus

Machine Learning Analysis of TCGA Cancer Data

[Abstract] In recent years, machine learning (ML) researchers have changed their focus towards biological problems that are difficult to analyse with standard approaches. Large initiatives such as The Cancer Genome Atlas (TCGA) have allowed the use of omic data for the training of these algorithms. In order to study the state of the art, this review is provided to cover the main works that have used ML with TCGA data. Firstly, the principal discoveries made by the TCGA consortium are presented. Once these bases have been established, we begin with the main objective of this study, the identification and discussion of those works that have used the TCGA data for the training of different ML approaches. After a review of more than 100 different papers, it has been possible to make a classification according to following three pillars: the type of tumour, the type of algorithm and the predicted biological problem. One of the conclusions drawn in this work shows a high density of studies based on two major algorithms: Random Forest and Support Vector Machines. We also observe the rise in the use of deep artificial neural networks. It is worth emphasizing, the increase of integrative models of multi-omic data analysis. The different biological conditions are a consequence of molecular homeostasis, driven by both protein coding regions, regulatory elements and the surrounding environment. It is notable that a large number of works make use of genetic expression data, which has been found to be the preferred method by researchers when training the different models. The biological problems addressed have been classified into five types: prognosis prediction, tumour subtypes, microsatellite instability (MSI), immunological aspects and certain pathways of interest. A clear trend was detected in the prediction of these conditions according to the type of tumour. That is the reason for which a greater number of works have focused on the BRCA cohort, while specific works for survival, for example, were centred on the GBM cohort, due to its large number of events. Throughout this review, it will be possible to go in depth into the works and the methodologies used to study TCGA cancer data. Finally, it is intended that this work will serve as a basis for future research in this field of study.This work was supported by the “Collaborative Project in Genomic Data Integration (CICLOGEN)” PI17/01826 funded by the Carlos III Health Institute from the Spanish National plan for Scientific and Technical Research and Innovation 2013–2016 and the European Regional Development Funds (FEDER)—“A way to build Europe.” and the General Directorate of Culture, Education and University Management of Xunta de Galicia (Ref. ED431D 2017/16), the “Galician Network for Colorectal Cancer Research” (Ref. ED431D 2017/23) and Competitive Reference Groups (Ref. ED431C 2018/49). CITIC, as Research Center accredited by Galician University System, is funded by “Consellería de Cultura, Educación e Universidades from Xunta de Galicia”, supported in an 80% through ERDF Funds, ERDF Operational Programme Galicia 2014–2020, and the remaining 20% by “Secretaría Xeral de Universidades” (Grant ED431G 2019/01). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscriptXunta de Galicia; ED431D 2017/16Xunta de Galicia; ED431D 2017/23Xunta de Galicia; ED431C 2018/49Xunta de Galicia; ED431G 2019/0

Effect of Two Bacillus thuringiensis1 Proteins on Development of the Fall Armyworm2 after Seven-Day Exposure Efecto en el Desarrollo del Gusano Cogollero2 Después de Ser Expuesto por Siete Días a Dos Proteínas de Bacillus thuringiensis1

Field-evolved resistance of fall armyworm, Spodoptera frugiperda (J.E. Smith) (Lepidoptera: Noctuidae), to the bacterium Bacillus thuringiensis (Bt) has been reported worldwide as one of the most serious threats to the sustainability of Bt maize crop. Therefore, it is important to assess the magnitude of adult survival and the possibility of cross-resistance of fall armyworm neonates exposed to Bt proteins. In this study, bioassays were used to examine susceptibility of two field-collected Cry1Fa-resistant strains of fall armyworm from Puerto Rico (456RR, 512RR) and their crosses with a susceptible strain (Monsanto SS) (456SR-RS, 512SR-RS). LC50 values varied in both Cry1Fa-resistant strains and in their backcrosses with the susceptible strain. The two RR strains were more tolerant to Cry1Fa and Cry1Ac proteins in earlier instars of development than were their crosses. Greater survival to the adult stage was obtained in the 512 RR strain and their RS-SR crosses when exposed to all concentrations of Cry1Ac and 1Fa. Survival to adult in the 456 RR was much greater when exposed to Cry1Fa than to Cry1Ac. Adults of 456 RR and their crosses survived only when exposed to the lowest concentrations of Cry1Ac. Our data confirmed great resistance to Cry1Fa and Cry1Ac in S. frugiperda larvae from Puerto Rico. However, based on the larvae that survived the 7-day diet bioassay and developed to pupae and adult maturity on regular diet, their LC50 values were less for both resistant strains and their crosses

Population Subset Selection for the Use of a Validation Dataset for Overfitting Control in Genetic Programming

[Abstract] Genetic Programming (GP) is a technique which is able to solve different problems through the evolution of mathematical expressions. However, in order to be applied, its tendency to overfit the data is one of its main issues. The use of a validation dataset is a common alternative to prevent overfitting in many Machine Learning (ML) techniques, including GP. But, there is one key point which differentiates GP and other ML techniques: instead of training a single model, GP evolves a population of models. Therefore, the use of the validation dataset has several possibilities because any of those evolved models could be evaluated. This work explores the possibility of using the validation dataset not only on the training-best individual but also in a subset with the training-best individuals of the population. The study has been conducted with 5 well-known databases performing regression or classification tasks. In most of the cases, the results of the study point out to an improvement when the validation dataset is used on a subset of the population instead of only on the training-best individual, which also induces a reduction on the number of nodes and, consequently, a lower complexity on the expressions.Xunta de Galicia; ED431G/01Xunta de Galicia; ED431D 2017/16Xunta de Galicia; ED431C 2018/49Xunta de Galicia; ED431D 2017/23Instituto de Salud Carlos III; PI17/0182

Empresas familiares petroleras en Latinoamérica

Los antecedentes de la industria familiar petrolera en América, se ubican con la perforación del primer pozo en Titusville, Pennsylvania, U.S.A, en 1859. Luego siguieron Texas y Oklahoma. Su crecimiento y desarrollo fue favorecido por la llegada del automóvil y los motores de combustión interna, en el siglo XX

El pacífico: Centro cultural-económico del mundo

Arturo Uslar Pietri, fue el primer intelectual venezolano en visualizar lo que acontecía en las relaciones entre Occidente y Oriente, a comienzo de la década de los 60’s dio testimonio de ello en conferencias escritas y radiales, dijo, que el escenario del mundo “estaba cambiando, el centro económico cultural y político será el Pacífico, allí se asentará el centro de los acontecimientos mundiales, el mundo del mañana, si no es ya el mundo de hoy, lo demás será periferia porque el gran centro de poder, histórico, de contacto, de comercio será el Pacífico”, de allí el título de este ensayo