Code-Switching in Portuguese Print Media of Brazilian Immigrant Communities in Massachusetts

This study focuses on the phenomenon of code-switching (CS) which is the alternating use of two or more languages in written or spoken form (Poplack 1980). These instances of CS are collected from Brazilian Portuguese print media published by immigrant communities in Massachusetts. Print material in Brazilian Portuguese was gathered from townships and cities in the South Shore of Massachusetts, which have been documented as having large Portuguese-speaking populations. The data were analyzed by tabulating orthographic errors, examples of code-switching, false cognates and language anomalies. The results were compared to those found in Poplack (1980), Gardner-Chloros (2009), and Hill (1993), among others. The results revealed a clear relationship between the presence of CS and the instability of immigrants’ first language with possible evidence of attrition and language shift. The paper also advances the idea that the presence of CS in the community’s media is a prominent indicator of the emerging identity of immigrants in Southeastern Massachusetts

Carbon nanotubes induce inflammation but decrease the production of reactive oxygen species in lung

With the rapid spread of carbon nanotubes (CNTs) applications, the respiratory toxicity of these compounds has attracted the attention of many scientists. Several studies have reported that after lung administration, CNTs could induce granuloma, fibrosis, or inflammation. By comparison with the mechanisms involved with other toxic particles such as asbestos, this effect could be attributed to an increase of oxidative stress. The aim of the present work was to test this hypothesis in vivo. Mice were intranasally instilled with 1.5 mg/kg of double walled carbon nanotubes (DWCNTs). Six, 24, or 48 h after administration, inflammation and localisation of DWCNTs in lungs were microscopically observed. Local oxidative perturbations were investigated using ESR spin trapping experiments, and systemic inflammation was assessed by measuring the plasma concentration of cytokines TNF-α, IL-1α, IL-1β, IL-6, IGF-1, Leptin, G-CSF, and VEGF. Examination of lungs and the elevation of proinflammatory cytokines in the plasma (Leptin and IL-6 at 6 h) confirmed the induction of an inflammatory reaction. This inflammatory reaction was accompanied by a decrease in the local oxidative stress. This effect could be attributed to the scavenger capability of pure CNTs

Regional parent flood frequency distributions in Europe – Part 1: Is the GEV model suitable as a pan-European parent?

Abstract. This study addresses the question of the existence of a parent flood frequency distribution on a European scale. A new database of L-moment ratios of flood annual maximum series (AMS) from 4105 catchments was compiled by joining 13 national data sets. Simple exploration of the database presents the generalized extreme value (GEV) distribution as a potential pan-European flood frequency distribution, being the three-parameter statistical model that with the closest resemblance to the estimated average of the sample L-moment ratios. Additional Monte Carlo simulations show that the variability in terms of sample skewness and kurtosis present in the data is larger than in a hypothetical scenario where all the samples were drawn from a GEV model. Overall, the generalized extreme value distribution fails to represent the kurtosis dispersion, especially for the longer sample lengths and medium to high skewness values, and therefore may be rejected in a statistical hypothesis testing framework as a single pan-European parent distribution for annual flood maxima. The results presented in this paper suggest that one single statistical model may not be able to fit the entire variety of flood processes present at a European scale, and presents an opportunity to further investigate the catchment and climatic factors controlling European flood regimes and their effects on the underlying flood frequency distributions

Predictive Modeling of Envelope Flood Extents Using Geomorphic and Climatic-Hydrologic Catchment Characteristics

A topographic index (flood descriptor) that combines the scaling of bankfull depth with morphology was shown to describe the tendency of an area to be flooded. However, this approach depends on the quality and availability of flood maps and assumes that outcomes can be directly extrapolated and downscaled. This work attempts to relax these problems and answer two questions: (1) Can functional relationships be established between a flood descriptor and geomorphic and climatic-hydrologic catchment characteristics? (2) If so, can they be used for low-complexity predictive modeling of envelope flood extents? Linear stepwise and random forest regressions are developed based on classification outcomes of a flood descriptor, using high-resolution flood modeling results as training benchmarks, and on catchment characteristics. Elementary catchments of four river basins in Europe (Thames, Weser, Rhine, and Danube) serve as training data set, while those of the Rh\uf4ne river basin in Europe serve as testing data set. Two return periods are considered, the 10- and 10,000-year. Prediction of envelope flood extents and flood-prone areas show that both models achieve high hit rates with respect to testing benchmarks. Average values were found to be above 60% and 80% for the 10- and the 10,000-year return periods, respectively. In spite of a moderate to high false discovery rate, the critical success index value was also found to be moderate to high. It is shown that by relating classification outcomes to catchment characteristics, the prediction of envelope flood extents may be achieved for a given region, including ungauged basins

Smooth regional estimation of low-flow indices: physiographical space based interpolation and top-kriging

Recent studies highlight that spatial interpolation techniques of point data can be effectively applied to the problem of regionalization of hydrometric information. This study compares two innovative interpolation techniques for the prediction of low-flows in ungauged basins. The first one, named Physiographical-Space Based Interpolation (PSBI), performs the spatial interpolation of the desired streamflow index (e.g., annual streamflow, low-flow index, flood quantile, etc.) in the space of catchment descriptors. The second technique, named Topological kriging or Top-kriging, predicts the variable of interest along river networks taking both the area and nested nature of catchments into account. PSBI and Top-kriging are applied for the regionalization of <i>Q</i><sub>355</sub> (i.e., a low-flow index that indicates the streamflow that is equalled or exceeded 355 days in a year, on average) over a broad geographical region in central Italy, which contains 51 gauged catchments. The two techniques are cross-validated through a leave-one-out procedure at all available gauges and applied to a subregion to produce a continuous estimation of <i>Q</i><sub>355</sub> along the river network extracted from a 90m elevation model. The results of the study show that Top-kriging and PSBI present complementary features. Top-kriging outperforms PSBI at larger river branches while PSBI outperforms Top-kriging for headwater catchments. Overall, they have comparable performances (Nash-Sutcliffe efficiencies in cross-validation of 0.89 and 0.83, respectively). Both techniques provide plausible and accurate predictions of <i>Q</i><sub>355</sub> in ungauged basins and represent promising opportunities for regionalization of low-flows

Machine-learning blends of geomorphic descriptors: value and limitations for flood hazard assessment across large floodplains

Recent literature shows several examples of simplified approaches that perform flood hazard (FH) assessment and mapping across large geographical areas on the basis of fast-computing geomorphic descriptors. These approaches may consider a single index (univariate) or use a set of indices simultaneously (multivariate). What is the potential and accuracy of multivariate approaches relative to univariate ones? Can we effectively use these methods for extrapolation purposes, i.e., FH assessment outside the region used for setting up the model? Our study addresses these open problems by considering two separate issues: (1) mapping flood-prone areas and (2) predicting the expected water depth for a given inundation scenario. We blend seven geomorphic descriptors through decision tree models trained on target FH maps, referring to a large study area (∼ 105 km2). We discuss the potential of multivariate approaches relative to the performance of a selected univariate model and on the basis of multiple extrapolation experiments, where models are tested outside their training region. Our results show that multivariate approaches may (a) significantly enhance flood-prone area delineation (accuracy: 92%) relative to univariate ones (accuracy: 84%), (b) provide accurate predictions of expected inundation depths (determination coefficient ∼0.7), and (c) produce encouraging results in extrapolation

Prediction of streamflow regimes over large geographical areas: interpolated flow–duration curves for the Danube region

ABSTRACTFlow–duration curves (FDCs) are essential to support decisions on water resources management, and their regionalization is fundamental for the assessment of ungauged basins. In comparison with calibrated rainfall–runoff models, statistical methods provide data-driven estimates representing a useful benchmark. The objective of this work is the interpolation of FDCs from ~500 discharge gauging stations in the Danube. To this aim we use total negative deviation top-kriging (TNDTK), as multi-regression models are shown to be unsuitable for representing FDCs across all durations and sites. TNDTK shows a high accuracy for the entire Danube region, with overall Nash-Sutcliffe efficiency values computed in a leave-p-out cross-validation scheme (p equal to one site, one-third and half of the sites), all above 0.88. A reliability measure based on kriging variance is attached to each interpolated FDC at ~4000 prediction nodes. The GIS layer of regionalized FDCs is made available for broader use in the region

Streamflow data availability in Europe: a detailed dataset of interpolated flow-duration curves

For about 24 000 river basins across Europe, we provide a continuous representation of the stream-flow regime in terms of empirical flow-duration curves (FDCs), which are key signatures of the hydrological behaviour of a catchment and are widely used for supporting decisions on water resource management as well as for assessing hydrologic change. In this study, FDCs are estimated by means of the geostatistical procedure termed total negative deviation top-kriging (TNDTK), starting from the empirical FDCs made available by the Joint Research Centre of the European Commission (DG-JRC) for about 3000 discharge measurement stations across Europe. Consistent with previous studies, TNDTK is shown to provide high accuracy for the entire study area, even with different degrees of reliability, which varies significantly over the study area. In order to provide this kind of information site by site, together with the estimated FDCs, for each catchment we provide indicators of the accuracy and reliability of the performed large-scale geostatistical prediction. The dataset is freely available at the PANGAEA open-access library (Data Publisher for Earth & Environmental Science) at https://doi.org/10.1594/PANGAEA.938975 (Persiano et al., 2021b)

Panta Rhei: an evolving scientific decade with a focus on water systems

Abstract. The paper presents an overview of the activity of Panta Rhei, the research decade launched in 2013 by the International Association of Hydrological Sciences. After one year of activity Panta Rhei has already stimulated several initiatives and a worldwide involvement of researchers in hydrology and sister disciplines. Providing an overview of the status of Panta Rhei is essential to further promote the participation of scientists and the completion of its structure, which is currently being shaped by receiving Research Theme and Working Group proposals from the community

From grape berries to wines: Drought impacts on key secondary metabolites

Aim: We aimed to study the impact of water deficit on the concentration of key flavour and phenolic secondary metabolites of wines. Methods and results: A drought-stress field trial was conducted on Vitis vinifera cv. Merlot and Tocai Friulano for two seasons. Fully irrigated (C) and deficit irrigated (D) grapes were microvinified and the resulting wines were analysed to determine the concentrations of anthocyanins, tannins, and free and glycosidically-bound Volatile Organic Compounds (VOCs). A descriptive sensory test was undertaken on the same wines. Water stressed grapes produced wines with higher concentrations of anthocyanins in Merlot and of free and glycosidically-bound monoterpenes in Tocai Friulano. Both cultivars displayed higher amounts of glycosidically-bound C13-norisoprenoids. Conclusions: Previously observed drought-induced compositional changes to the grapes were transfered to the wines, with an increase in polyphenols and VOCs. However, the timing and the duration of the water stress in the field only heavily impacted the final wine composition with major metabolic modification when the severe water deficit started early (at approximately 40 days after anthesis) and lasted over the entire season until harvest. Significance and impact of the study: This study highlights the positive role of a controlled water deficit on the composition of the wines in terms of secondary metabolites