A comparison of conditional predictive ability of implied volatility and realized measures in forecasting volatility

In a conditional predictive ability test framework, we investigate whether market factors influence the relative conditional predictive ability of realized measures (RMs) and implied volatility (IV), which is able to examine the asynchronism in their forecasting accuracy, and further analyze their unconditional forecasting performance for volatility forecast. Our results show that the asynchronism can be detected significantly and is strongly related to certain market factors, and the comparison between RMs and IV on average forecast performance is more efficient than previous studies. Finally, we use the factors to extend the empirical similarity (ES) approach for combination of forecasts derived from RMs and IV.     

Incorporating textual and management factors into financial distress prediction: A comparative study of machine learning methods

Financial distress prediction (FDP) has been widely considered as a promising approach to reducing financial losses. While financial information comprises the traditional factors involved in FDP, nonfinancial factors have also been examined in recent studies. In light of this, the purpose of this study is to explore the integrated factors and multiple models that can improve the predictive performance of FDP models. This study proposes an FDP framework to reveal the financial distress features of listed Chinese companies, incorporating financial, management, and textual factors, and evaluating the prediction performance of multiple models in different time spans. To develop this framework, this study employs the wrapper-based feature selection method to extract valuable features, and then constructs multiple single classifiers, ensemble classifiers, and deep learning models in order to predict financial distress. The experiment results indicate that management and textual factors can supplement traditional financial factors in FDP, especially textual ones. This study also discovers that integrated factors collected 4 years prior to the predicted benchmark year enable a more accurate prediction, and the ensemble classifiers and deep learning models developed can achieve satisfactory FDP performance. This study makes a novel contribution as it expands the predictive factors of financial distress and provides new findings that can have important implications for providing early warning signals of financial risk.     

A new DFM flow for sub-100nm standard cells

DFM （Design-For-Manufacturability） method, which aims to improve manufacturability of ICs through specific design considerations, is becoming important nowadays. In particular, standard cells now should be designed by DFM method. This paper reports a new DFM flow for sub-100 nm standard cell design with a group of technologies for process modeling, manufacturability simulation and trial RETs. Based on this flow, a set of DFM-friendly 90nm standard cells were designed.     

国际重要检索系统与甘肃省科技期刊

对国际重要检索系统进行了论述,并对甘肃省科技期刊被国际重要检索系统收录情况进行了统计与分析。     

Germline-specific dgcr8 knockout in zebrafish using a BACK approach

Zebrafish is an important model to study developmental biology and human diseases. However, an effective approach to achieve spatial and temporal gene knockout in zebrafish has not been well established. In this study, we have developed a new approach, namely bacterial artificial chromosome-rescue-based knockout (BACK), to achieve conditional gene knockout in zebrafish using the Cre/loxP system. We have successfully deleted the DiGeorge syndrome critical region gene 8 (dgcr8) in zebrafish germ line and demonstrated that the maternal-zygotic dgcr8 (MZdgcr8) embryos exhibit MZdicer-like phenotypes with morphological defects which could be rescued by miR-430, indicating that canonical microRNAs play critical role in early development. Our findings establish that Cre/loxP-mediated tissue-specific gene knockout could be achieved using this BACK strategy and that canonical microRNAs play important roles in early embryonic development in zebrafish.     

Overactive bone morphogenetic protein signaling in heterotopic ossification and Duchenne muscular dystrophy

Bone morphogenetic proteins (BMPs) are important extracellular cytokines that play critical roles in embryogenesis and tissue homeostasis. BMPs signal via transmembrane type I and type II serine/threonine kinase receptors and intracellular Smad effector proteins. BMP signaling is precisely regulated and perturbation of BMP signaling is connected to multiple diseases, including musculoskeletal diseases. In this review, we will summarize the recent progress in elucidation of BMP signal transduction, how overactive BMP signaling is involved in the pathogenesis of heterotopic ossification and Duchenne muscular dystrophy, and discuss possible therapeutic strategies for treatment of these diseases.     

Indirect adaptive fuzzy control for a class of nonlinear discrete-time systems

An indirect adaptive fuzzy control scheme is developed for a class of nonlinear discrete-time systems. In this method, two fuzzy logic systems are used to approximate the unknown functions, and the parameters of membership functions in fuzzy logic systems are adjusted according to adaptive laws for the purpose of controlling the plant to track a reference trajectory. It is proved that the scheme can not only guarantee the boundedness of the input and output of the closed-loop system, but also make the tracking error converge to a small neighborhood of the origin. Simulation results indicate the effectiveness of this scheme.     

交通荷载作用下低路堤动力特性试验研究

结合连盐高速低路堤,对路堤进行了动应力、振动响应等现场测试,分析了路基中附加动应力及振动位移的变化规律.并且通过应力控制的室内动三轴试验,采用一定的动应力频率、不同的循环应力比来模拟交通荷载,研究了在循环荷载作用下,连盐高速公路饱和软粘土的轴向累计应变、孔隙水压力和轴向周期应变软化的变化规律.实验结果表明:路堤中动应力和振动位移随行车速度和车重的增加而增加,随深度的增加而降低,有效影响深度达2.5 m;原状土的临界循环应力比远大于重塑土,承受循环应力能力高于重塑土.因此,要加强浅层路基强度,同时要减少对底部下卧层软粘土的扰动.其结果可为在软土地基上设计和施工低路堤高速公路提供有益的参考.