Balanced bilinguals favor lexical processing in their opaque language and conversion system in their shallow language

Referred to as orthographic depth, the degree of consistency of grapheme/phoneme correspondences varies across languages from high in shallow orthographies to low in deep orthographies. The present study investigates the impact of orthographic depth on reading route by analyzing evoked potentials to words in a deep (French) and shallow (German) language presented to highly proficient bilinguals. ERP analyses to German and French words revealed significant topographic modulations 240-280ms post-stimulus onset, indicative of distinct brain networks engaged in reading over this time window. Source estimations revealed that these effects stemmed from modulations of left insular, inferior frontal and dorsolateral regions (German>French) previously associated to phonological processing. Our results show that reading in a shallow language was associated to a stronger engagement of phonological pathways than reading in a deep language. Thus, the lexical pathways favored in word reading are reinforced by phonological networks more strongly in the shallow than deep orthography.

Atomic force microscopy for the study of membrane proteins

Fundamental biological processes such as cell-cell communication, signal transduction, molecular transport and energy conversion are performed by membrane proteins. These important proteins are studied best in their native environment, the lipid bilayer. The atomic force microscope (AFM) is the instrument of choice to determine the native surface structure, supramolecular organization, conformational changes and dynamics of membrane-embedded proteins under near-physiological conditions. In addition, membrane proteins are imaged at subnanometer resolution and at the single molecule level with the AFM. This review highlights the major advances and results achieved on reconstituted membrane proteins and native membranes as well as the recent developments of the AFM for imaging.

Electrochemical CO2 Reduction - A Critical View on Fundamentals, Materials and Applications

The electrochemical reduction of CO2 has been extensively studied over the past decades. Nevertheless, this topic has been tackled so far only by using a very fundamental approach and mostly by trying to improve kinetics and selectivities toward specific products in half-cell configurations and liquid-based electrolytes. The main drawback of this approach is that, due to the low solubility of CO2 in water, the maximum CO2 reduction current which could be drawn falls in the range of 0.01–0.02 A cm–2. This is at least an order of magnitude lower current density than the requirement to make CO2-electrolysis a technically and economically feasible option for transformation of CO2 into chemical feedstock or fuel thereby closing the CO2 cycle. This work attempts to give a short overview on the status of electrochemical CO2 reduction with respect to challenges at the electrolysis cell as well as at the catalyst level. We will critically discuss possible pathways to increase both operating current density and conversion efficiency in order to close the gap with established energy conversion technologies.

Endocrine changes and liver mRNA abundance of somatotropic axis and insulin system constituents during negative energy balance at different stages of lactation in dairy cows

The liver has an important role in metabolic regulation and control of the somatotropic axis to adapt successfully to physiological and environmental changes in dairy cows. The aim of this study was to investigate the adaptation to negative energy balance (NEB) at parturition and to a deliberately induced NEB by feed restriction at 100 days in milk. The hepatic gene expression and the endocrine system of the somatotropic axis and related parameters were compared between the early and late NEB period. Fifty multiparous cows were subjected to 3 periods (1=early lactation up to 12 wk postpartum, 2=feed restriction for 3 wk beginning at around 100 days in milk with a feed-restricted and a control group, and 3=subsequent realimentation period for the feed-restricted group for 8 wk). In period 1, plasma growth hormone reached a maximum in early lactation, whereas insulin-like growth factor-I (IGF-I), leptin, the thyroid hormones, insulin, and the revised quantitative insulin sensitivity check index increased gradually after a nadir in early lactation. Three days after parturition, hepatic mRNA abundance of growth hormone receptor 1A, IGF-I, IGF-I receptor and IGF-binding protein-3 (IGFBP-3) were decreased, whereas mRNA of IGFBP-1 and -2 and insulin receptor were upregulated as compared with wk 3 antepartum. During period 2, feed-restricted cows showed decreased plasma concentrations of IGF-I and leptin compared with those of control cows. The revised quantitative insulin sensitivity check index was lower for feed-restricted cows (period 2) than for control cows. Compared with the NEB in period 1, the changes due to the deliberately induced NEB (period 2) in hormones were less pronounced. At the end of the 3-wk feed restriction, the mRNA abundance of IGF-I, IGFBP-1, -2, -3, and insulin receptor was increased as compared with the control group. The different effects of energy deficiency at the 2 stages in lactation show that the endocrine regulation changes qualitatively and quantitatively during the course of lactation.

NodePM: A Remote Monitoring Alert System for Energy Consumption Using Probabilistic Techniques

In this paper, we propose an intelligent method, named the Novelty Detection Power Meter (NodePM), to detect novelties in electronic equipment monitored by a smart grid. Considering the entropy of each device monitored, which is calculated based on a Markov chain model, the proposed method identifies novelties through a machine learning algorithm. To this end, the NodePM is integrated into a platform for the remote monitoring of energy consumption, which consists of a wireless sensors network (WSN). It thus should be stressed that the experiments were conducted in real environments different from many related works, which are evaluated in simulated environments. In this sense, the results show that the NodePM reduces by 13.7% the power consumption of the equipment we monitored. In addition, the NodePM provides better efficiency to detect novelties when compared to an approach from the literature, surpassing it in different scenarios in all evaluations that were carried out.