Motivation, Identity and L2 Reading: Perceptions of Chinese ESL Students in Canada

This study was conducted to explore and examine whether there are different motivational tendencies among Chinese English as a Second Language (ESL) students with different reading proficiency levels, and the identity transformations they may have experienced during the process of their ESL learning. The quantitative results demonstrate statistically significant differences between two groups of participants (high proficiency vs. low proficiency), and participants’ reading motivation levels are positively correlated with their previous reading proficiency levels. Furthermore, the qualitative semi-structured interviews indicate that participants’ self-perceived motivation toward reading in English is mainly academic, and they are experiencing a certain level of identity transformation in the process of learning in an authentic English speaking environment

Firm ESG reputation risk and debt choice

Using a novel sample covering 3783 US public firms from 2007 to 2020, we examine how negative media coverage of firm‐level environmental, social, and governance (ESG) practices affects a firm's debt choice. We find that firms with higher ESG reputation risk rely more on public bond than bank loan. The social and governance components, in particular, matter. Moreover, firms that receive more negative news coverage display a higher propensity to issue new bonds as opposed to securing new bank debt. Overall, our study presents empirical evidence on the relation between firm ESG reputation risk and debt financing

Bank funding constraints and stock liquidity

This paper examines the relationship between bank marginal funding constraints and stock liquidity. Using bank credit default swap (CDS) spreads we show that increased funding constraints weaken bank stock liquidity (as measured by liquidity tightness, depth, and resilience). This effect strengthens during crises periods. Deteriorating bank stock liquidity is in turn priced into excess stock returns. In addition, we find that during liquidity crises, monetary expansion can break the relationship between funding costs and stock liquidity. Heightened monetary policy uncertainty, however, strengthens this relation

Probabilistic thresholds for landslides warning by integrating soil moisture conditions with rainfall thresholds

Various methods have been proposed to define the rainfall thresholds for the landslide prediction. Once the threshold is determined, it remains the same regardless of the antecedent soil moisture conditions. However, given the important role of the antecedent soil moisture in the initiation of landslides, it is considered if the rainfall threshold level varies according to the antecedent soil moisture conditions, the prediction performance will be improved. Therefore, in this study we propose a probabilistic threshold to integrate antecedent soil moisture conditions with rainfall thresholds. In order to take into account the conditions with landslides and without landslides, the Bayesian analysis is applied to estimate the landslide occurrence probability given the various combinations of two factors: the antecedent soil moisture and the severity of the recent rainfall event. These combinations are then divided into conditions that are likely to trigger landslides and those unlikely to trigger landslides by comparing their probabilities with a critical value. In this way, the probabilistic threshold is determined. Here the soil moisture is estimated using the distributed hydrological model, and the severity of the rainfall event is characterized by the cumulated event rainfall-rainfall duration (ED) thresholds with different exceedance probabilities. The proposed approach was applied to a sub-region of the Emilia-Romagna region in northern Italy. The results show that the probabilistic threshold has a better prediction performance than the ED rainfall threshold, especially in terms of reducing false alarms. This study provides an effective approach to improve the prediction capability of the ED rainfall threshold, benefiting its application in the landslide prediction

Estimation of soil moisture using modified antecedent precipitation index with application in landslide predictions

Soil moisture plays a key role in land-atmosphere interaction systems. Although it can be estimated through in situ measurements, satellite remote sensing, and hydrological modelling, using indicators to index soil moisture conditions is another useful way. In this study, one of these indicators, the antecedent precipitation index (API), is explored. Modifications were proposed to the conventional version of API by introducing two parameters to make it more in line with the physical process. First, the recession coefficient is allowed to vary with the change of air temperature, which could take into account the variation of the evapotranspiration process. Second, the API value is restricted by the maximum value of API, accounting for the maximum water holding capacity of the soil. The modified API was then calibrated and validated by comparing with the in situ measured soil moisture. The better correlation between these two datasets demonstrates that the modified API could better indicate soil moisture conditions, compared with the conventional API. The capability of the modified API to index soil moisture conditions was further explored by applying it to landslide predictions in the Emilia-Romagna region, northern Italy. Here, the recent 3-day rainfall vs the antecedent soil wetness thresholds (RS thresholds) were constructed, in which the soil wetness is indexed by the modified API. The validation of RS thresholds was carried out with the use of the contingency matrix and receiver operating characteristic (ROC) curves. By comparing the prediction performance between RS thresholds and rainfall thresholds, it is found that RS threshold could provide better prediction capabilities in terms of higher hit rate and lower false alarm rate. The positive results indicate that the modified API could provide superior performance of indexing soil moisture conditions, demonstrating the effectiveness of the proposed modifications

Antecedent wetness and rainfall information in landslide threshold definition

For rainfall-induced landslides, their occurrence is attributed to both the antecedent wetness condition and the recent rainfall condition. However, when defining rainfall thresholds for the landslide occurrence, these two types of information have been used incompletely or implicitly, which may affect the threshold's predictive capability. This study aims to investigate how to make a better use of these two types of information in the landslide threshold definition. Here four types of thresholds are proposed, by including different variables that are responsible for landslide occurrences, these thresholds could represent different cases, like whether to include the antecedent wetness information or whether to consider the recent rainfall condition explicitly. The predictive capability of these thresholds is then compared crossly with the help of the receiver operating characteristic (ROC) approach. We carry out this study in a northern Italian region called Emilia-Romagna. Results show that the antecedent wetness condition plays a crucial role in the occurrence of rainfall-induced landsides. It is beneficial for the threshold's predictive capability to explicitly include the antecedent wetness information and the recent rainfall in the definition of landslide thresholds. When including soil moisture information in landslide threshold, the reliability of the soil moisture measurement is a key factor affecting the threshold's prediction performance