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The Internet provides a wide variety of information that can be collected and studied, creating a massive data repository. Among the data available on the Internet, we can find articles about Violence against Women (VAW) published in the digital press, which are of great societal interest. In this work, we utilized Web scraping techniques to gather VAW-related news from the internet. Applying Text Mining techniques, we conducted a study on VAW and its characteristics. Our work comprises an exploratory analysis and the application of Topic Modelling to VAW events to identify latent topics and their semantic structures. We employed classification algorithms on a set of VAW press articles to determine the type of violence they refer to, namely physical, psychological, sexual, or a combination of them. We proposed two methodologies to target the data: the first one is based on dictionaries of VAW types, while the second approach extends the former by using the predominant violence to identify other associated types. Furthermore, we implemented two feature selection techniques: TF-IDF and Chi2. Then, we applied Support Vector Machine, Decision Tree, Bayesian Networks, XGBoost Classifier, Random Forest, and Artificial Neural Networks. The results obtained showed that the classifiers achieved better performance when using Chi2. The Boost Classifier demonstrated the best performance, followed by Random Forest.

Alemtuzumab es un fármaco de alta eficacia aprobado por la Agencia Europea de Medicamentos como tratamiento modificador de la enfermedad en pacientes con esclerosis múltiple remitente recurrente.

To study the clinico-radiological paradox in multiple sclerosis (MS) relapse by analyzing the number and location of gadolinium-enhanced (Gd+) lesions on brain MRI before methylprednisolone (MP) treatment.

Los plexos coroideos, los vasos sanguíneos y las barreras cerebrales están íntimamente relacionados tanto morfológica como funcionalmente. Por otro lado, la hipertensión produce cambios en el flujo sanguíneo y en los pequeños vasos y capilares cerebrales. El propósito de la presente revisión es estudiar los efectos de la hipertensión arterial sobre los plexos coroideos y las barreras cerebrales.

The objective of the study is to identify the risk factors associated with mortality at six weeks, especially by analyzing the role of antivirals and munomodulators.

Tunneled island flaps that transfer skin from a site adjacent to the wound are an effective way to reconstruct defects. These flaps provide good aesthetic and functional results and can be completed during a single surgical session, thus reducing complications. The procedure consists of taking an island of skin about the size of the surgical defect and moving it through a subcutaneous tunnel to cover the wound. We aimed to exemplify the use of these flaps in different regions of the face.

Hippocampal volume is recognised as a surrogate imaging biomarker for the study of Alzheimer's disease (AD). However, in Cuba there are no antecedents of its use. The objective of this research was to establish an automatic hippocampal segmentation procedure to study a sample of Cuban subjects diagnosed with possible mild or moderate AD.

In newborns, dramatic changes occur in the blood and bone marrow during the first hours; there are rapid fluctuations in the quantities of leukocytes populations. In this work, we investigated leukocytes subsets counts in two types of blood samples (cord blood and capillary blood) extracted from healthy newborns.

Interpretation of variants of unknown significance (VUS) in genetic tests is complicated in ethnically diverse populations, given the lack of information regarding the common spectrum of genetic variation in clinically relevant genes. Public availability of data obtained from high-throughput genotyping and/or exome massive parallel sequencing (MPS)-based projects from several thousands of outbred samples might become useful tools to evaluate the pathogenicity of a VUS, based on its frequency in different populations. In the case of the Mexican and other Latino populations, several thousands of samples have been genotyped or sequenced during the last few years as part of different efforts to identify common variants associated to common diseases. In this report, we analyzed Mexican population data from a sample of 3985 outbred individuals, and additional 66 hereditary breast cancer patients were analyzed in order to better define the spectrum of common genomic variation of the BRCA1and BRCA2genes. Our analyses identified the most common genetic variants in these clinically relevant genes as well as the presence and frequency of specific pathogenic mutations present in the Mexican population. Analysis of the 3985 population samples by MPS identified three pathogenic mutations in BRCA1, only one population sample showed a BRCA1exon 16–17 deletion by MLPA. This resulted in a basal prevalence of deleterious mutations of 0.10% (1:996) for BRCA1and 11 pathogenic mutations in BRCA2, resulting in a basal prevalence of deleterious mutations of 0.276% (1:362) for BRCA2, combined of 0.376% (1:265). Separate analysis of the breast cancer patients identified the presence of pathogenic mutations in 18% (12 pathogenic mutations in 66 patients) of the samples by MPS and 13 additional alterations by MLPA. These results will support a better interpretation of clinical studies focused on the detection of BRCA mutations in Mexican and Latino populations and will help to define the general prevalence of deleterious mutations within these populations.

El último documento de consenso del Grupo de Estudio de Enfermedades Desmielinizantes de la Sociedad Española de Neurología sobre el tratamiento de la esclerosis múltiple (EM) data del año 2016. Aunque muchas consideraciones continúan todavía vigentes, desde entonces se han producido cambios significativos en el manejo y tratamiento de esta enfermedad, motivados no solo por la aprobación de nuevos fármacos con diferentes mecanismos de acción, sino también por la evolución de conceptos otrora consolidados. Esto ha permitido abordar situaciones especiales como el embarazo y la vacunación desde otra perspectiva, e incluir nuevas variables en la toma de decisiones en práctica clínica, como plantear tratamiento modificador de la enfermedad (TME) de alta eficacia en fases tempranas, considerar la perspectiva del paciente y utilizar nuevas tecnologías como monitorización remota.

An integrated ecohydrological modeling approach was deployed in three long‐term critical zone (CZ) observatories of the French CZ network (CZ Observatories—Application and Research) to better understand how the CZ heterogeneity modulates the water cycle within territories. Ecohydrological simulations with the physically based model EcH2O‐iso constrained by a wide range of observations crossing several disciplines (meteorology, hydrology, geomorphology, geophysics, soil sciences, and satellite imagery) are able to capture stream water discharges, evapotranspiration fluxes, and piezometric levels in the Naizin, Auradé, and Strengbach watersheds. In Naizin, an agricultural watershed in northwestern France with a schist bedrock underlying deep weathered materials (5–15 m) along gentle slopes, modeling results reveal a deep aquifer with a large total water storage (1,080–1,150 mm), an important fraction of inactive water storage (94%), and relatively long stream water transit times (0.5–2.5 years). In the Auradé watershed, representative of agricultural landscapes of the southwestern France developed on molasse, a relatively shallow regolith (1–8 m) is observed along hilly slopes. Simulations indicate a shallow aquifer with moderate total water storage (590–630 mm), an important fraction of inactive water storage (91%), and shorter stream water transit times (0.1–1.3 years). In the Strengbach watershed, typical of mid‐mountain forested landscapes developed on granite, CZ evolution implies a shallow regolith (1–5 m) along steep slopes. Modeling results infer a shallow aquifer with the smallest total water storage (475–575 mm), the shortest stream water transit times (0.1–0.7 years), but also the highest fraction of active water storage (18%). Understanding how water is stored and released in landscapes is essential for predicting water availability in a changing world. It is of course driven by the local climate, but also by the landscape settings, from the vegetation to the belowground structure inherited from the geological history. In three intensively studied observatories across France, we used numerous field measurements and a numerical model of water‐vegetation‐subsurface interactions to better depict how differences between landscapes shape the water cycle. We found that the geological history determines how much water is stored in watersheds, through the thickness of water‐holding rocks and soils. How this storage contributes to surface processes (including river flow) is modulated by more recent changes, from valley morphology and tectonics to agricultural practices and precipitation patterns. This study highlights that considering the continuity between long and short‐term landscape processes is key to a detailed understanding of the water cycle. The long‐term critical zone (CZ) evolution controlling the regolith thickness strongly impacts the total water storage in watersheds, while the Quaternary geomorphological evolution influences the current hydrological partitioning and the separation of hydrologically active and inactive water storageBoth internal watershed characteristics and external forcings, such as current atmospheric forcing and recent land use need to be considered to infer stream persistence and to understand hydrological diversityThe observed hydrological diversity cannot be fully understood without considering a continuum of time scales in CZ evolution The long‐term critical zone (CZ) evolution controlling the regolith thickness strongly impacts the total water storage in watersheds, while the Quaternary geomorphological evolution influences the current hydrological partitioning and the separation of hydrologically active and inactive water storage Both internal watershed characteristics and external forcings, such as current atmospheric forcing and recent land use need to be considered to infer stream persistence and to understand hydrological diversity The observed hydrological diversity cannot be fully understood without considering a continuum of time scales in CZ evolution

Quantum Machine Learning was born during the past decade as the intersection of Quantum Computing and Machine Learning. Today, advances in quantum computer hardware and the design of simulation frameworks able to run quantum algorithms in classic computers make it possible to extend classic artificial intelligence models to a quantum environment. Despite these achievements, several questions regarding the whole quantum machine learning pipeline remain unanswered, for instance the problem of classical data representation on quantum hardware, or the methodologies for designing and evaluating quantum models for common learning tasks such as classification, function approximation, clustering, etc. These problems become even more difficult to solve in the case of Time Series processing, where the context of past historical data may influence the behavior of the decision-making model. In this piece of research, we address the problem of Time Series classification using quantum models, and propose an efficient and compact representation of time series in quantum data using amplitude embedding. The proposal is capable of representing a time series of length nin log2(n)computational units, and experiments conducted on benchmark time series classification problems show that quantum models designed for classification can also outperform the accuracy of classic methods.

Andean glaciers are among the fastest shrinking and largest contributors to sea level rise on Earth. They also represent crucial water resources in many tropical and semi-arid mountain catchments. Yet the magnitude of the recent ice loss is still debated. Here we present Andean glacier mass changes (from 10° N to 56° S) between 2000 and 2018 using time series of digital elevation models derived from ASTER stereo images. The total mass change over this period was −22.9 ± 5.9 Gt yr−1(−0.72 ± 0.22 m w.e. yr−1(m w.e., metres of water equivalent)), with the most negative mass balances in the Patagonian Andes (−0.78 ± 0.25 m w.e. yr−1) and the Tropical Andes (−0.42 ± 0.24 m w.e. yr−1), compared to relatively moderate losses (−0.28 ± 0.18 m w.e. yr−1) in the Dry Andes. Subperiod analysis (2000–2009 versus 2009–2018) revealed a steady mass loss in the tropics and south of 45° S. Conversely, a shift from a slightly positive to a strongly negative mass balance was measured between 26 and 45° S. In the latter region, the drastic glacier loss in recent years coincides with the extremely dry conditions since 2010 and partially helped to mitigate the negative hydrological impacts of this severe and sustained drought. These results provide a comprehensive, high-resolution and multidecadal data set of recent Andes-wide glacier mass changes that constitutes a relevant basis for the calibration and validation of hydrological and glaciological models intended to project future glacier changes and their hydrological impacts.

Common variable immunodeficiency (CVID) is a heterogeneous group of primary antibody deficiencies defined by marked reductions in serum IgG, IgA and/or IgM levels and recurrent bacterial infections. Some patients are associated with defects in T cells and regulatory T cells (Tregs), resulting in recurrent viral infections and early-onset autoimmune disease.

The use of hydraulic fracturing for production of petroleum and natural gas has increased dramatically in the past decade, but the environmental impacts of this technology remain unclear. Experiments were conducted to quantify airborne emissions from 12 samples of hydraulic fracturing flowback wastewater collected in the Permian Basin, as well as the photochemical processing of these emissions leading to the formation of particulate matter (PM). The concentration of total volatile carbon (hydrocarbons evaporating at room temperature) averaged 29 mg of carbon per liter. After photochemical oxidation under high NOxconditions, the amount of organic PM formed per milliliter of wastewater evaporated averaged 24 μg; the amount of ammonium nitrate formed averaged 262 μg. Based on the mean PM formation observed in these experiments, the estimated formation of PM from evaporated flowback wastewater in the state of Texas is in the range of estimated PM emissions from diesel engines used in oil rigs. Evaporation of flowback wastewater, a hitherto unrecognized source of secondary pollutants, could significantly contribute to ambient PM concentrations.

Pressure-driven shock waves in solid materials can cause extreme damage and deformation. Understanding this deformation and the associated defects that are created in the material is crucial in the study of a wide range of phenomena, including planetary formation and asteroid impact sites, the formation of interstellar dust clouds, ballistic penetrators, spacecraft shielding and ductility in high-performance ceramics. At the lattice level, the basic mechanisms of plastic deformation are twinning (whereby crystallites with a mirror-image lattice form) and slip (whereby lattice dislocations are generated and move), but determining which of these mechanisms is active during deformation is challenging. Experiments that characterized lattice defects have typically examined the microstructure of samples after deformation, and so are complicated by post-shock annealing and reverberations. In addition, measurements have been limited to relatively modest pressures (less than 100 gigapascals). In situ X-ray diffraction experiments can provide insights into the dynamic behaviour of materials, but have only recently been applied to plasticity during shock compression and have yet to provide detailed insight into competing deformation mechanisms. Here we present X-ray diffraction experiments with femtosecond resolution that capture in situ, lattice-level information on the microstructural processes that drive shock-wave-driven deformation. To demonstrate this method we shock-compress the body-centred-cubic material tantalum—an important material for high-energy-density physics owing to its high shock impedance and high X-ray opacity. Tantalum is also a material for which previous shock compression simulations and experiments have provided conflicting information about the dominant deformation mechanism. Our experiments reveal twinning and related lattice rotation occurring on the timescale of tens of picoseconds. In addition, despite the common association between twinning and strong shocks, we find a transition from twinning to dislocation-slip-dominated plasticity at high pressure (more than 150 gigapascals), a regime that recovery experiments cannot accurately access. The techniques demonstrated here will be useful for studying shock waves and other high-strain-rate phenomena, as well as a broad range of processes induced by plasticity.

ABSTRACTThe sources of submicrometer particulate matter (PM1) remain poorly characterized in the industrialized city of Houston, TX. A mobile sampling approach was used to characterize PM1composition and concentration across Houston based on high-time-resolution measurements of nonrefractory PM1and trace gases during the DISCOVER-AQ Texas 2013 campaign. Two pollution zones with marked differences in PM1levels, character, and dynamics were established based on cluster analysis of organic aerosol mass loadings sampled at 16 sites. The highest PM1mass concentrations (average 11.6 ± 5.7 µg/m3) were observed to the northwest of Houston (zone 1), dominated by secondary organic aerosol (SOA) mass likely driven by nighttime biogenic organonitrate formation. Zone 2, an industrial/urban area south/east of Houston, exhibited lower concentrations of PM1(average 4.4 ± 3.3 µg/m3), significant organic aerosol (OA) aging, and evidence of primary sulfate emissions. Diurnal patterns and backward-trajectory analyses enable the classification of airmass clusters characterized by distinct PM sources: biogenic SOA, photochemical aged SOA, and primary sulfate emissions from the Houston Ship Channel. Principal component analysis (PCA) indicates that secondary biogenic organonitrates primarily related with monoterpenes are predominant in zone 1 (accounting for 34% of the variability in the data set). The relevance of photochemical processes and industrial and traffic emission sources in zone 2 also is highlighted by PCA, which identifies three factors related with these processes/sources (~50% of the aerosol/trace gas concentration variability). PCA reveals a relatively minor contribution of isoprene to SOA formation in zone 1 and the absence of isoprene-derived aerosol in zone 2. The relevance of industrial amine emissions and the likely contribution of chloride-displaced sea salt aerosol to the observed variability in pollution levels in zone 2 also are captured by PCA.Implications: This article describes an urban-scale mobile study to characterize spatial variations in submicrometer particulate matter (PM1) in greater Houston. The data set indicates substantial spatial variations in PM1sources/chemistry and elucidates the importance of photochemistry and nighttime oxidant chemistry in producing secondary PM1. These results emphasize the potential benefits of effective control strategies throughout the region, not only to reduce primary emissions of PM1from automobiles and industry but also to reduce the emissions of important secondary PM1precursors, including sulfur oxides, nitrogen oxides, ammonia, and volatile organic compounds. Such efforts also could aid in efforts to reduce mixing ratios of ozone.

This paper presents the implementation and analysis of two approaches (fuzzy and conventional). Using hourly data from buildings at the University of Granada, we have examined their electricity demand and designed a model to predict energy consumption. Our proposal was conducted with the aid of time series techniques as well as the combination of artificial neural networks and clustering algorithms. Both approaches proved to be suitable for energy modelling although nonfuzzy models provided more variability and less robustness than fuzzy ones. Despite the relatively small difference between fuzzy and nonfuzzy estimates, the results reported in this study show that the fuzzy solution may be useful to enhance and enrich energy predictions.

AbstractWe explored templating effects of various materials for hydrogen (H2and D2) solidification by measuring the degree of supercooling required for liquid hydrogen to solidify below each triple point. The results show high supercooling (>100 mK) for most metallic, covalent, and ionic solids, and low supercooling (<100 mK) for van der Waals (vdW) solids. We attribute the low supercooling of vdW solids to the weak interaction of the substrate and hydrogen. Highly ordered pyrolytic graphite showed the lowest supercooling among materials that are solid at room temperature, but did not exhibit a templating effect within a fill-tube and capsule assembly.

If $$\left( \Omega ,\Sigma ,\mu \right) $$ Ω,Σ,μ is a finite measure space and $$X$$ X a Banach space whose dual has a countable norming set we provide a proof of the fact that the space of all weakly $$\mu $$ μ -measurable (classes of scalarly equivalent) Pettis integrable functions $$f$$ f : $$\Omega \rightarrow X$$ Ω→X of finite variation, equipped with the variation norm, contains a copy of $$c_0$$ c0 if and only if $$X$$ X does.

AbstractVerticillium leaf mottle and wilt caused by the fungus Verticillium dahliaeis a major disease of sunflower in Argentina and the USA. In the summer of 2013, an important outbreak of the disease occurred in one field in the Southwest of Spain. The determination of vegetative compatibility groups (VCGs) of V. dahliaeis used in the genetic characterization of the fungus. Molecular markers have also been developed and applied for the analysis of V. dahliae, particularly for those isolates infecting artichoke, cotton and olive tree. The objective of this work was to determine the genetic and molecular features of V. dahliaeof sunflower. Three V. dahliaeisolates, one from Argentina collected in 2012 and two collected in Spain in 2013, were analysed. The VCGs were determined by complementation between nitmutants of the isolates from sunflower and the VCGs reference strains. Molecular characterization was conducted by polymerase chain reaction using primer pairs that are diagnostic of either V. dahliaespecies, defoliating or non-defoliating pathotypes, or VCGs. Complementation tests between nitmutants and reference strains clearly showed that the three isolates from sunflower belong to the VCG2B. The VCG2B has been identified in V. dahliaefrom crops as cotton, artichoke, eggplant, pepper and tomato among others. When molecularly analysed, the three V. dahliaeisolates infecting sunflower had the same molecular pattern than the one found for non-defoliating isolates of V. dahliaepathogenic to artichoke or cotton. The results of this work show the closeness between non-defoliating isolates of V. dahliaeinfecting artichoke, cotton and sunflower and suggest that any of these three species can serve as carrier and source of inoculum for Verticillium outbreaks in them.