Detection of changes in literary writing style using N-grams as style markers and supervised machine learning.

The analysis of an author's writing style implies the characterization and identification of the style in terms of a set of features commonly called linguistic features. The analysis can be extrinsic, where the style of an author can be compared with other authors, or intrinsic, where the style of an author is identified through different stages of his life. Intrinsic analysis has been used, for example, to detect mental illness and the effects of aging. A key element of the analysis is the style markers used to model the author's writing patterns. The style markers should handle diachronic changes and be thematic independent. One of the most commonly used style marker in extrinsic style analysis is n-gram. In this paper, we present the evaluation of traditional n-grams (words and characters) and dependency tree syntactic n-grams to solve the task of detecting changes in writing style over time. Our corpus consisted of novels by eleven English-speaking authors. The novels of each author were organized chronologically from the oldest to the most recent work according to the date of publication. Subsequently, two stages were defined: initial and final. In each stage three novels were assigned, novels of the initial stage corresponded to the oldest and those at the final stage to the most recent novels. To analyze changes in the writing style, novels were characterized by using four types of n-grams: characters, words, Part-Of-Speech (POS) tags and syntactic relations n-grams. Experiments were performed with a Logistic Regression classifier. Dimension reduction techniques such as Principal Component Analysis (PCA) and Latent Semantic Analysis (LSA) algorithms were evaluated. The results obtained with the different n-grams indicated that all authors presented significant changes in writing style over time. In addition, representations using n-grams of syntactic relations have achieved competitive results among different authors.

Streamlining breast cancer and colorectal cancer biosimilar regulations to improve treatment access in Latin America: an expert panel perspective.

In a multiday conference, a panel of Latin American experts in biological cancer therapies and health economics were provided with questions to address the barriers restricting access to biosimilars in Latin America, specifically for patients with breast cancer and colorectal cancer, for whom biosimilars can be a path forward to increasing access to care. During the conference, responses were discussed and edited until a consensus was achieved. The regulatory challenges identified in the conference included heterogenous regulations, non-adherence to regulatory pathways, scarcity of market opportunity, inadequate naming of biosimilars by only using international non-proprietary names, imprecise use of interchangeability and substitution, and insufficient traceability and pharmacovigilance. Recommendations were developed to improve the implementation of regulatory pathways and reliable procurement strategies that increase access to these therapies with adequate traceability and outcome measures; efforts from all involved stakeholders will be crucial. These recommendations can serve as a strategy for biosimilar adoption in other countries in a similar situation.

A Systematic Review for Cognitive State-Based QoE/UX Evaluation.

Traditional evaluation of user experience is subjective by nature, for what is sought is to use data from physiological and behavioral sensors to interpret the relationship that the user's cognitive states have with the elements of a graphical interface and interaction mechanisms. This study presents the systematic review that was developed to determine the cognitive states that are being investigated in the context of Quality of Experience (QoE)/User Experience (UX) evaluation, as well as the signals and characteristics obtained, machine learning models used, evaluation architectures proposed, and the results achieved. Twenty-nine papers published in 2014-2019 were selected from eight online sources of information, of which 24% were related to the classification of cognitive states, 17% described evaluation architectures, and 41% presented correlations between different signals, cognitive states, and QoE/UX metrics, among others. The amount of identified studies was low in comparison with cognitive state research in other contexts, such as driving or other critical activities; however, this provides a starting point to analyze and interpret states such as mental workload, confusion, and mental stress from various human signals and propose more robust QoE/UX evaluation architectures.

Características clínicas de la meningitis por Criptococo en pacientes con VIH del Hospital Roosevelt durante el período de enero de 2001 a junio de 2002 / clinical characteristics of Cryptococcal meningitis in HIV infected patients, January 2001 to June 2002

El objetivo del presente estudio es establecer las características clínicas que comparten los pacientes con infección por VIH con diagnóstico de meningitis por criptococo. Dicho estudio se realizó durante el período de enero del 2001 a junio del 2002, se eligieron a 30 pacientes ingresados en el Hospital Roosevelt con diagnóstico de VIH con cultivo positivo para Cryptococcus neoformans. El 93/100 de los pacientes estudiados presentó como síntoma principal la cefalea, el signo clínico de papiledema encontrado en el 86/100, se observaron gran cantidad de pacientes con signos meningeos positivos (73/100), los pacientes en un porcentaje alto (40/100) presentaron alteración del estado de conciencia secundario...