Dynamic Sight Translation: A Simultaneous Interpreting Strategies Driver

This paper reports on eliciting anticipation strategy, a common strategy in simultaneous interpreting (SI) via sight translation (ST). A new ST variant, the dynamic type, was designed in a modular and progressive manner to facilitate the trainees’ transition into SI at the early stage of learning. The new tool was used and tested under a framework of action research that was conducted continuously over 3 years. Despite some limitations, the longitudinal study finds that the newly designed set of exercises is not only a skill development and transfer enabler but also a contributor to eliciting SI-related strategies. This article explains the validity of the exercise design for SI teaching. It then presents data analysis indicating the efficacy of dynamic ST in helping students draw on anticipation strategy

Insights into the Nature of Synergistic Effects in Proton-Conducting 4,4−1H,1H-Bitriazole-Poly(ethylene oxide) Composites

A nitrogen-containing heterocycle (NCH), 4,4-1H-1H-bi-1,2,3-triazole (bitriazole), capable of mimicking the hydrogen bonding of water in the solid state is synthesized and its ability to conduct protons in the presence of poly(ethylene oxides) under anhydrous conditions is investigated. Bitriazole is shown to have sufficient thermal and electrochemical stability for fuel cell applications. The composites formed between bitriazole and poly(ethylene oxides) give proton conductivities that can be described by the Vogel−Tamman−Fulcher (VTF) equation. These characteristics suggest coupling between polymer segmental motion and ion transport. The bitriazole N-H proton is shown to be the source of conductivity, and bitriazole and poly(ethylene oxides) function synergistically through specific intermolecular interactions and polymer-induced segmental motion to create a pathway for proton transport via structural diffusion

Potential predictability of seasonal extreme precipitation accumulation in China

Abstract The potential predictability of seasonal extreme precipitation accumulation (SEPA) across mainland China is evaluated, based on daily precipitation observations during 1960–2013 at 675 stations. The potential predictability value (PPV) of SEPA is calculated for each station by decomposing the observed SEPA variance into a part associated with stochastic daily rainfall variability and another part associated with longer-time-scale climate processes. A Markov chain model is constructed for each station and a Monte Carlo simulation is applied to estimate the stochastic part of the variance. The results suggest that there are more potentially predictable regions for summer than for the other seasons, especially over southern China, the Yangtze River valley, the north China plain, and northwestern China. There are also regions of large PPVs in southern China for autumn and winter and in northwestern China for spring. The SEPA series for the regions of large PPVs are deemed not entirely stochastic, either with long-term trends (e.g., increasing trends in inland northwestern China) or significant correlation with well-known large-scale climate processes (e.g., East Asian winter monsoon for southern China in winter and El Niño for the Yangtze River valley in summer). This fact not only verifies the claim that the regions have potential predictability but also facilitates predictive studies of the regional extreme precipitation associated with large-scale climate processes.</jats:p

Further-Adjusted Long-Term Temperature Series in China Based on MASH

A set of homogenized monthly mean surface air temperature (SAT) series at 32 stations in China back to the 19th century had previously been developed based on the RHtest method by Cao et al., but some inhomogeneities remained in the dataset. The present study produces a further-adjusted and updated dataset based on the Multiple Analysis of Series for Homogenization (MASH) method. The MASH procedure detects 33 monthly temperature records as erroneous outliers and 152 meaningful break points in the monthly SAT series since 1924 at 28 stations. The inhomogeneous parts are then adjusted relative to the latest homogeneous part of the series. The new data show significant warming trends during 1924–2016 at all the stations, ranging from 0.48 to 3.57°C (100 yr)−1, with a regional mean trend of 1.65°C (100 yr)−1; whereas, the previous results ranged from a slight cooling at two stations to considerable warming, up to 4.5°C (100 yr)−1. It is suggested that the further-adjusted data are a better representation of the large-scale pattern of climate change in the region for the past century. The new data are available online at http://www.dx.doi.org/10.11922/sciencedb.516

A New Finite-Time Bounded Control of Stochastic Itô Systems with ( x

This paper addresses the finite-time bounded control problem of linear stochastic systems with state, control input, and external disturbance-dependent noise ((x,u,v)-dependent noise for short). The notion of finite-time boundedness of linear stochastic systems is first introduced. Then a different quadratic function approach is proposed to give a sufficient condition for finite-time boundedness of such a class of systems, and its superiority to common quadratic approach is shown. Moreover, the finite-time bounded controller design problem is studied and two sufficient conditions for the existence of state and output feedback controllers are presented in terms of nonlinear matrix inequalities. An algorithm is given for solving the obtained nonlinear matrix inequalities. Finally, an example is employed to illustrate the effectiveness of our obtained results

Changes in regional wet heatwave in Eurasia during summer (1979–2017)

Wet heatwaves can have more impact on human health than hot dry heatwaves. However, changes in these have received little scientific attention. Using the ECMWF Reanalysis v5 reanalysis dataset, wet-bulb temperatures ( T _w ) were used to investigate the spatial-temporal variation of wet heatwaves in Eurasia for 1979–2017. Wet heatwaves were defined as three day or longer periods when T _w was above the 90th percentile of the summer distribution and characterized by amplitude, duration and frequency. Maximum values of amplitude, close to 31 °C, occur in the Indus–Ganges plain, the lower Yangtze valley, and the coasts of the Persian Gulf and Red Sea. Significant positive trends in the frequency and amplitude of wet heatwaves have occurred over most of Eurasia though with regional variations. Changes in heatwave amplitude (HWA) are largely driven by changes in summer mean T _w . For Eurasia as a whole, increases in temperature contribute more than six times the impact of changes in relative humidity (RH) to changes in T _w HWA. Changes in T _w have a strong dependence on climatological RH with an increase in RH of 1% causing a T _w increase of 0.2 °C in arid regions, and only increasing T _w by 0.1 °C in humid regions. During T _w heatwaves in Europe, parts of Tibet, India, East Asia and parts of the Arabian Peninsula both temperature and humidity contribute to the increase in T _w , with temperature the dominant driver. During wet heatwaves in part of Russia, changes in humidity are weak and the increase in T _w is mainly caused by an increase in temperature. In the Mediterranean and Central Asia, RH has fallen reducing the increase in T _w from general warming

Have human activities changed the frequencies of absolute extreme temperatures in eastern China?

Extreme temperatures affect populous regions, like eastern China, causing substantial socio-economic losses. It is beneficial to explore whether the frequencies of absolute or threshold-based extreme temperatures have been changed by human activities, such as anthropogenic emissions of greenhouse gases (GHGs). In this study, we compared observed and multi-model-simulated changes in the frequencies of summer days, tropical nights, icy days and frosty nights in eastern China for the years 1960–2012 by using an optimal fingerprinting method. The observed long-term trends in the regional mean frequencies of these four indices were +2.36, +1.62, −0.94, −3.02 days decade−1. The models performed better in simulating the observed frequency change in daytime extreme temperatures than nighttime ones. Anthropogenic influences are detectable in the observed frequency changes of these four temperature extreme indices. The influence of natural forcings could not be detected robustly in any indices. Further analysis found that the effects of GHGs changed the frequencies of summer days (tropical nights, icy days, frosty nights) by +3.48 ± 1.45 (+2.99 ± 1.35, −2.52 ± 1.28, −4.11 ± 1.48) days decade−1. Other anthropogenic forcing agents (dominated by anthropogenic aerosols) offset the GHG effect and changed the frequencies of these four indices by −1.53 ± 0.78, −1.49 ± 0.94, +1.84 ± 1.07, +1.45 ± 1.26 days decade−1, respectively. Little influence of natural forcings was found in the observed frequency changes of these four temperature extreme indices