The long way to bilingualism: the peculiar case of multilingual South Tyrol

In the present contribution we discuss the challenges and the results of learning a second language in South Tyrol, the multilingual border region in northern Italy where the autochthonous German- and Ladinspeaking communities have cohabited with the Italian-speaking community since the end of the First World War. The picture resulting from the data collected in the Kolipsi project (Eurac/DiScoF), an extensive linguistic and psychosocial investigation about South Tyrolean secondary school pupils now in its second edition, gives precious inputs to all entities that intervene in the process of attitude formation and change, ranging from the family environment to politics.En el presente trabajo, debatimos los retos y los resultados del proceso de aprendizaje de segundas lenguas en el Tirol del Sur, la región fronteriza multilingüe del norte de Italia donde las comunidades autóctonas hablantes de alemán y ladino han convivido con la comunidad italohablante desde el fin de la Primera Guerra Mundial. La imagen resultante de los datos recogidos en el proyecto Kolipsi (Eurac/DiScoF), una investigación abarcadora tanto lingüística como psicosocial sobre alumnado de secundaria del Tirol del Sur, proporciona información muy valiosa a todas las entidades que intervienen en el proceso de la formación y el cambio de las actitudes, desde el entorno familiar hasta el ámbito de la política

Capecitabine from X-ray powder synchrotron data

In the title compound [systematic name 5-de­oxy-5-fluoro-N-(pent­yloxycarbon­yl)cytidine], C15H22FN3O6, the pentyl chain is disordered over two positions with refined occupancies of 0.53 (5) and 0.47 (5). The furan ring assumes an envelope conformation. In the crystal, inter­molecular N—H⋯O hydrogen bonds link the mol­ecules into chains propagating along the b axis. The crystal packing exhibits electrostatic inter­actions between the 5-fluoro­pyrimidin-2(1H)-one fragments of neighbouring mol­ecules as indicated by short O⋯C [2.875 (3) and 2.961 (3) Å] and F⋯C [2.886 (3) Å] contacts

Communications Biophysics

Contains research objectives and reports on six research projects split into three sections.National Institutes of Health (Grant 5 P01 NS13126-07)National Institutes of Health (Training Grant 5 T32 NS07047-05)National Institutes of Health (Training Grant 2 T32 NS07047-06)National Science Foundation (Grant BNS 77-16861)National Institutes of Health (Grant 5 R01 NS1284606)National Institutes of Health (Grant 5 T32 NS07099)National Science Foundation (Grant BNS77-21751)National Institutes of Health (Grant 5 R01 NS14092-04)Gallaudet College SubcontractKarmazin Foundation through the Council for the Arts at M.I.T.National Institutes of Health (Grant 1 R01 NS1691701A1)National Institutes of Health (Grant 5 R01 NS11080-06)National Institutes of Health (Grant GM-21189

Communications Biophysics

Contains reports on ten research projects.National Institutes of Health (Grant 5 P01 NS13126)National Institutes of Health (Training Grant 5 T32 NS0704)National Science Foundation (Grant BNS80-06369)National Institutes of Health (Grant 5 R01 NS11153)National Science Foundation (Grant BNS77-16861)National Institutes of Health (Grant 5 RO1 NS12846)National Science Foundation (Grant BNS77-21751)National Institutes of Health (Grant 1 P01 NS14092)Karmazin Foundation through the Council for the Arts at MITNational Institutes of Health (Fellowship 5 F32 NS06386)National Science Foundation (Fellowship SP179-14913)National Institutes of Health (Grant 5 RO1 NS11080

Communications Biophysics

Contains reports on seven research projects split into three sections.National Institutes of Health (Grant 5 PO1 NS13126)National Institutes of Health (Grant 1 RO1 NS18682)National Institutes of Health (Training Grant 5 T32 NS07047)National Science Foundation (Grant BNS77-16861)National Institutes of Health (Grant 1 F33 NS07202-01)National Institutes of Health (Grant 5 RO1 NS10916)National Institutes of Health (Grant 5 RO1 NS12846)National Institutes of Health (Grant 1 RO1 NS16917)National Institutes of Health (Grant 1 RO1 NS14092-05)National Science Foundation (Grant BNS 77 21751)National Institutes of Health (Grant 5 R01 NS11080)National Institutes of Health (Grant GM-21189

Systemic Maternal Inflammation and Neonatal Hyperoxia Induces Remodeling and Left Ventricular Dysfunction in Mice

The impact of the neonatal environment on the development of adult cardiovascular disease is poorly understood. Systemic maternal inflammation is linked to growth retardation, preterm birth, and maturation deficits in the developing fetus. Often preterm or small-for-gestational age infants require medical interventions such as oxygen therapy. The long-term pathological consequences of medical interventions on an immature physiology remain unknown. In the present study, we hypothesized that systemic maternal inflammation and neonatal hyperoxia exposure compromise cardiac structure, resulting in LV dysfunction during adulthood.Pregnant C3H/HeN mice were injected on embryonic day 16 (E16) with LPS (80 µg/kg; i.p.) or saline. Offspring were placed in room air (RA) or 85% O(2) for 14 days and subsequently maintained in RA. Cardiac echocardiography, cardiomyocyte contractility, and molecular analyses were performed. Echocardiography revealed persistent lower left ventricular fractional shortening with greater left ventricular end systolic diameter at 8 weeks in LPS/O(2) than in saline/RA mice. Isolated cardiomyocytes from LPS/O(2) mice had slower rates of contraction and relaxation, and a slower return to baseline length than cardiomyocytes isolated from saline/RA controls. α-/β-MHC ratio was increased and Connexin-43 levels decreased in LPS/O(2) mice at 8 weeks. Nox4 was reduced between day 3 and 14 and capillary density was lower at 8 weeks of life in LPS/O(2) mice.These results demonstrate that systemic maternal inflammation combined with neonatal hyperoxia exposure induces alterations in cardiac structure and function leading to cardiac failure in adulthood and supports the importance of the intrauterine and neonatal milieu on adult health

Automatic summarization of voicemail messages using lexical and prosodic features

This article presents trainable methods for extracting principal content words from voicemail messages. The short text summaries generated are suitable for mobile messaging applications. The system uses a set of classifiers to identify the summary words with each word described by a vector of lexical and prosodic features. We use an ROC-based algorithm, Parcel, to select input features (and classifiers). We have performed a series of objective and subjective evaluations using unseen data from two different speech recognition systems as well as human transcriptions of voicemail speech

Feature analysis for discriminative confidence estimation in spoken term detection

This is the author’s version of a work that was accepted for publication in Computer Speech & Language. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Computer Speech & Language, 28, 5, (2014) DOI: 10.1016/j.csl.2013.09.008Discriminative confidence based on multi-layer perceptrons (MLPs) and multiple features has shown significant advantage compared to the widely used lattice-based confidence in spoken term detection (STD). Although the MLP-based framework can handle any features derived from a multitude of sources, choosing all possible features may lead to over complex models and hence less generality. In this paper, we design an extensive set of features and analyze their contribution to STD individually and as a group. The main goal is to choose a small set of features that are sufficiently informative while keeping the model simple and generalizable. We employ two established models to conduct the analysis: one is linear regression which targets for the most relevant features and the other is logistic linear regression which targets for the most discriminative features. We find the most informative features are comprised of those derived from diverse sources (ASR decoding, duration and lexical properties) and the two models deliver highly consistent feature ranks. STD experiments on both English and Spanish data demonstrate significant performance gains with the proposed feature sets.This work has been partially supported by project PriorSPEECH (TEC2009-14719-C02-01) from the Spanish Ministry of Science and Innovation and by project MAV2VICMR (S2009/TIC-1542) from the Community of Madrid