Operando X-ray characterization of interfacial charge transfer and structural rearrangements

Key technologies in energy conversion and storage, sensing and chemical synthesis rely on a detailed knowledge about charge transfer processes at electrified solid-liquid interfaces. However, these interfaces continuously evolve as a function of applied potentials, ionic concentrations and time. We therefore need to characterize chemical composition, atomic arrangement and electronic structure of both the liquid and the solid side of the interface under operating conditions. In this chapter, we discuss the state-of-the-art X-ray based spectroscopy and diffraction approaches for such 'operando' characterization. We highlight recent examples from literature and demonstrate how X-ray absorption spectroscopy, X-ray photoelectron spectroscopy and surface X-ray diffraction can reveal the required interface-sensitive information

Enhancing Access to Online Education: Quality Machine Translation of MOOC Content

Contains fulltext : 162505.pdf (publisher's version ) (Open Access)The International Conference on Language Resources and Evaluation (LREC) 2016, 23 mei 201

Uncovering the language of wine experts

Talking about odors and flavors is difficult for most people, yet experts appear to be able to convey critical information about wines in their reviews. This seems to be a contradiction, and wine expert descriptions are frequently received with criticism. Here, we propose a method for probing the language of wine reviews, and thus offer a means to enhance current vocabularies, and as a by-product question the general assumption that wine reviews are gibberish. By means of two different quantitative analyses-support vector machines for classification and Termhood analysis-on a corpus of online wine reviews, we tested whether wine reviews are written in a consistent manner, and thus may be considered informative; and whether reviews feature domain-specific language. First, a classification paradigm was trained on wine reviews from one set of authors for which the color, grape variety, and origin of a wine were known, and subsequently tested on data from a new author. This analysis revealed that, regardless of individual differences in vocabulary preferences, color and grape variety were predicted with high accuracy. Second, using Termhood as a measure of how words are used in wine reviews in a domain-specific manner compared to other genres in English, a list of 146 wine-specific terms was uncovered. These words were compared to existing lists of wine vocabulary that are currently used to train experts. Some overlap was observed, but there were also gaps revealed in the extant lists, suggesting these lists could be improved by our automatic analysis

Cause-specific mortality time series analysis: a general method to detect and correct for abrupt data production changes

<p>Abstract</p> <p>Background</p> <p>Monitoring the time course of mortality by cause is a key public health issue. However, several mortality data production changes may affect cause-specific time trends, thus altering the interpretation. This paper proposes a statistical method that detects abrupt changes ("jumps") and estimates correction factors that may be used for further analysis.</p> <p>Methods</p> <p>The method was applied to a subset of the AMIEHS (Avoidable Mortality in the European Union, toward better Indicators for the Effectiveness of Health Systems) project mortality database and considered for six European countries and 13 selected causes of deaths. For each country and cause of death, an automated jump detection method called Polydect was applied to the log mortality rate time series. The plausibility of a data production change associated with each detected jump was evaluated through literature search or feedback obtained from the national data producers.</p> <p>For each plausible jump position, the statistical significance of the between-age and between-gender jump amplitude heterogeneity was evaluated by means of a generalized additive regression model, and correction factors were deduced from the results.</p> <p>Results</p> <p>Forty-nine jumps were detected by the Polydect method from 1970 to 2005. Most of the detected jumps were found to be plausible. The age- and gender-specific amplitudes of the jumps were estimated when they were statistically heterogeneous, and they showed greater by-age heterogeneity than by-gender heterogeneity.</p> <p>Conclusion</p> <p>The method presented in this paper was successfully applied to a large set of causes of death and countries. The method appears to be an alternative to bridge coding methods when the latter are not systematically implemented because they are time- and resource-consuming.</p

Transcriptome analysis reveals tumor microenvironment changes in glioblastoma

A better understanding of transcriptional evolution of IDH-wild-type glioblastoma may be crucial for treatment optimization. Here, we perform RNA sequencing (RNA-seq) (n = 322 test, n = 245 validation) on paired primary-recurrent glioblastoma resections of patients treated with the current standard of care. Transcriptional subtypes form an interconnected continuum in a two-dimensional space. Recurrent tumors show preferential mesenchymal progression. Over time, hallmark glioblastoma genes are not significantly altered. Instead, tumor purity decreases over time and is accompanied by co-increases in neuron and oligodendrocyte marker genes and, independently, tumor-associated macrophages. A decrease is observed in endothelial marker genes. These composition changes are confirmed by single-cell RNA-seq and immunohistochemistry. An extracellular matrix-associated gene set increases at recurrence and bulk, single-cell RNA, and immunohistochemistry indicate it is expressed mainly by pericytes. This signature is associated with significantly worse survival at recurrence. Our data demonstrate that glioblastomas evolve mainly by microenvironment (re-)organization rather than molecular evolution of tumor cells

La gestión académica en pandemia : adecuaciones, innovaciones y desafíos de la Universidad Nacional de Cuyo

Este libro remite a un contexto especial e inédito que surge a partir de la pandemia de covid-19. Se trata de un contexto de alcance global signado por efectos intensos y perdurables sobre diferentes aspectos de la realidad social, económica y ambiental. En general, estos efectos provocaron, por un lado, situaciones problemáticas nuevas y, por otro lado, agravaron situaciones problemáticas preexistentes que adquirieron mayor visibilidad. En el caso argentino, las restricciones derivadas de la pandemia agudizaron la brecha socioeducativa existente y, al mismo tiempo, exigieron una gestión ágil, dinámica, resolutiva, propositiva y resiliente, especialmente a las instituciones educativas con el objeto de asegurar el derecho a la educación y su calidad. Lógicamente, la provincia de Mendoza y, por tanto, la Universidad Nacional de Cuyo (UNCUYO) no quedaron exentas de los efectos mencionados. Aunque aún no resulta posible identificar con rigor el impacto concreto que ha tenido la pandemia sobre el funcionamiento del sistema educativo provincial, se pueden entrever algunos indicadores que vale la pena atender. Por ejemplo, el egreso en la oferta de educación superior de la uncuyo registró, en 2020, una caída interanual cercana al -18 % 1. Esta oscilación se torna más relevante si se considera que este indicador se mostraba estable a lo largo de los últimos años.Fil: Castañeda, Linda. Universidad de Murcia.Fil: Viñoles Cosentino, Virginia. Universidad de Murcia.Fil: Falcón, Paulo.Fil: Martínez, Ana María.Fil: Meljin Lombard, Mariela Beatriz. Universidad Nacional de Cuyo. Facultad de Artes y Diseño.Fil: Van Den Bosch, Silvia. Universidad Nacional de Cuyo. Facultad de Ciencias Agrarias.Fil: Castro, María Eugenia. Universidad Nacional de Cuyo. Facultad de Ciencias Aplicadas a la Industria.Fil: Puebla, Patricia. Universidad Nacional de Cuyo. Facultad de Ciencias Económicas.Fil: Sánchez, Esther Lucía. Universidad Nacional de Cuyo. Facultad de Ciencias Económicas.Fil: González Gaviola, Miguel. Universidad Nacional de Cuyo. Facultad de Ciencias Económicas.Fil: Tarabelli, María Florencia. Universidad Nacional de Cuyo. Facultad de Ciencias Exactas y Naturales.Fil: Rüttler, María Elena. Universidad Nacional de Cuyo. Facultad de Ciencias Médicas.Fil: Nalda, Gonzalo. Universidad Nacional de Cuyo. Facultad de Ciencias Médicas.Fil: Castiglia, Mariana. Universidad Nacional de Cuyo. Facultad de Ciencias Políticas y Sociales.Fil: Mussuto, Matías M.. Universidad Nacional de Cuyo. Facultad de Derecho.Fil: Griffouliere, María Gabriela. Universidad Nacional de Cuyo. Facultad de Educación.Fil: Verstraete, María Ana. Universidad Nacional de Cuyo. Facultad de Filosofía y Letras.Fil: Echagaray, Patricia. Universidad Nacional de Cuyo. Facultad de Odontología.Fil: Mirasso, Aníbal. Universidad Nacional de Cuyo. Facultad de Ingeniería.Fil: Molina, Fabiana. Universidad Nacional de Cuyo. Instituto Tecnológico Universitario.Fil: Corral, Patricia. Universidad Nacional de Cuyo. Instituto Universitario de Seguridad Pública.Fil: Chrabalowski, Marina. Universidad Nacional de Cuyo.Fil: Barrozo, María Ana. Universidad Nacional de Cuyo.Fil: Zabala, Cecilia. Universidad Nacional de Cuyo. Escuela de Comercio Martín Zapata.Fil: Sauer, Marcelo. Universidad Nacional de Cuyo.Fil: Romero Day, Marcela. Universidad Nacional de Cuyo. Liceo Agrícola y Enológico Domingo F. Sarmiento.Fil: Marlia, Nora. Universidad Nacional de Cuyo. Facultad de Filosofía y Letras. Departamento de Aplicación Docente.Fil: Zamorano, Cristina. Universidad Nacional de Cuyo. Colegio Universitario Central.Fil: Yapura, Susana. Universidad Nacional de Cuyo. Escuela del Magisterio.Fil: Navarro, María Fernanda. Universidad Nacional de Cuyo.Fil: Bosio, Iris Viviana. Universidad Nacional de Cuyo. EDIUNC.Fil: Degiorgi, Horacio. Universidad Nacional de Cuyo. Sistema Integrado de Documentación.Fil: Bocco, María Susana. Universidad Nacional de Cuyo.Fil: Guayco, Mariana. Universidad Nacional de Cuyo.Fil: Pizzi, Daniel. Universidad Nacional de Cuyo.Fil: Lettelier, Dolores. Universidad Nacional de Cuyo. Secretaría Académica

Maximum-Entropy Parameter Estimation for the k-nn Modified Value-Difference Kernel

We introduce an extension of the modified value-difference kernel of k-nn by replacing the kernel's default class distribution matrix with the matrix produced by the maximum-entropy learning algorithm. This hybrid algorithm is tested on fifteen machine learning benchmark tasks, comparing the hybrid to standard k-nn classifcation and maximum-entropy-based classifi- cation. Results show that the hybrid typically outperforms the lower-scoring of the two other algorithms, often significantly; in a majority of cases the hybrid yields the highest accuracy of the three algorithms. Error analysis indicates that the hybrid's errors overlap more with k-nn than with maximum entropy modeling.