183 research outputs found
Cold Regions Ice/Snow Actions in Hydrology, Ecology and Engineering
No full textThis is a reprint of the articles gathered through a Special Issue on the topic of "Cold Regions Ice/Snow Actions in Hydrology, Ecology, and Engineering". In total, 12 articles have been published in the Special Issue, covering topics including identification of snow and ice through image analysis, snow and sea ice formation processes, physical and mechanical properties of snow and ice, ice flood disasters, changes in sea ice characteristics, and ecosystems under ice
Two Essays in Asset Pricing and FinTech: Out-of-Sample Equity Premium Predictability and Stock Co-jump Networks with Mixed Membership
No full textIn Chapter 1, we introduce a new method for forecasting stock returns. Despite exhibiting strong in-sample predictive power, a wide range of predictors proposed in the literature are shown by Goyal and Welch [2008] to underperform the historical average in out-of-sample forecasts of the equity premium. We propose an unconventional approach for out-of-sample equity premium prediction that avoids parameter estimation, adopting a conservative constant as the predictive coefficient. Our methodology retains the same zero-variance advantage as the historical average, while achieving lower bias, thereby outperforming the benchmark. We show that our forecast first-order stochastically dominates the historical average. Using our methodology, we reveal that many predictors exhibit statistically and economically significant out-of-sample gains for the market return. We also compare our method with machine learning models and apply our framework to out-of-sample bond return predictability. In Chapter 2, we study stock dependence across many firms using pairwise co-jump networks with high-frequency data. Stock cojumps contain important information about the risk linkage among stocks. Ding et al. [2024] discovered a block structure among stocks based on their co-jumps and proposed a model DCBM-DMP. In this paper, we exhibit that this structure can greatly benefit from an essentially additional component: mixed membership. Specifically, we propose a Degree Corrected Mixed Membership network model with Dependent Multivariate Poisson edges (DCMM-DMP) and develop a Mixed Spectral Clustering On Ratios-of-Eigenvectors for networks with Dependent Multivariate Poisson edges (Mixed-SCORE-DMP) algorithm. We show that Mixed-SCORE-DMP is asymptotically consistent in estimating the mixed membership structures. Empirically, we show that (1) the mixed membership network DCMM-DMP enhances DCBM-DMP by providing a more precise risk structure; (2) “peers” defined by our mixed membership model offer significant advantages in return prediction over benchmarks, such as GICS, self-grouping, or counting analyst coverage linkage; (3) a “purity” measure based on our model provides insightful perspectives about stocks’ risk profile and investment opportunities. We also construct a lead-lag jump network to study the leading and lagging group effect.</p
Highly Sensitive Low-Bandgap Perovskite Photodetectors with Response from Ultraviolet to the Near-Infrared Region
No full textPhysicochemical and biological properties of a novel injectable polyurethane system for root canal filling
No full textJian Wang,1 Yi Zuo,1 Minghui Zhao,1 Jiaxing Jiang,1 Yi Man,2 Jun Wu,3 Yunjiu Hu,3 Changlei Liu,4 Yubao Li,1 Jidong Li11Research Center for Nano-Biomaterials, Analytical and Testing Center, Sichuan University, Chengdu, Sichuan, People’s Republic of China; 2College of Stomatology, Sichuan University, Chengdu, Sichuan, People’s Republic of China; 3Department of Orthopedics, Chongqing Medical University, Chongqing, People’s Republic of China; 4College of Chemistry, Sichuan University, Chengdu, Sichuan, People’s Republic of ChinaAbstract: A root canal sealer with antibacterial activity can be efficacious in preventing reinfection that results from residual microorganisms and/or the leakage of microorganisms. In the present study, a series of injectable, self-curing polyurethane (PU)-based antibacterial sealers with different concentrations of silver phosphate (Ag3PO4) were fabricated. Subsequently, their physicochemical properties, antibacterial abilities, and preliminary cytocompatibilities were evaluated. The results indicated that the fabricated PU-based sealers can achieve a high conversion rate in a short amount of time. More than 95% of the isocyanate group of PU sealers with 3 wt% (PU3) and 5 wt% (PU5) concentrations of Ag3PO4 were included in the curing reaction after 7 hours. With the exception of those for film thickness for PU5, the results of setting time, film thickness, and solubility were able to meet the requirements of the International Organization for Standardization. The antibacterial tests showed that PU3 and PU5 exhibit stronger antimicrobial effects than that achieved with 1 wt% Ag3PO4 (PU1) and AH Plus (positive control) against Streptococcus mutans. The cytocompatibility evaluation revealed that the PU1 and PU3 sealers possess good cytocompatibility and low cytotoxicity. These results demonstrate that the PU3 sealer offers good physicochemical and antimicrobial properties along with cytocompatibility, which may hold great application potential in the field of root canal fillings.Keywords: root canal sealer, polyurethane, silver phosphate, antibacterial properties, direct contact tes
Comparative analysis of seepage simulation for embankment in cold area during ice flood season and non-ice flood season
No full textInfluenced by meteorological and environmental factors, ice flood is easy to occur in cold areas, causing the flood level to rise substantially and threatening the safety of embankments. Based on the analysis of the influencing factors of the seepage of the dike in the cold region, the seepage simulation model of the dike is constructed and solved by the SEEP/W module of Geo-studio software. The seepage of the Dike Section in the ice flood season and non-ice flood season under the scenario of 100-year flood level is compared and analyzed. The results show that, (1) The seepage path of non-ice flood dike mainly passes through the base layer of the dike, and the seepage path of the dike is affected by the frozen shell during the ice flood season, and the seepage path of the dike mainly passes through the frozen shell. (2) The maximum velocity of Dike Seepage in the season of ice flood is higher than that in non-ice flood season, which is easy to cause piping and collapse. (3) the maximum gradient of the embankment during the flood season has also increased, exceeding the allowable slope value of the project. During the season of ice flood, the embankment is unstable, and the embankment protection should be strengthened during the flood season
Lithium battery parameter identification and SOC estimation based on dual-polarized model
No full textAn equivalent circuit model of dual polarization (DP) of lithium battery was established according to the application characteristics of lithium battery under the standby condition of 5G base station. On the basis of the model, recursive least square method with forgetting factor (RLS) was used to identify the model parameters. Finally, the Unscented Kalman filtering (UKF) was used to estimate the SOC of lithium battery in real time with the identified model parameters. The simulation and experimental results showed that the combined estimation using recursive least square method with forgetting factor (RLS) and UKF could greatly improve the estimation accuracy of lithium battery SOC, reduce the estimation error, and further verify the accuracy and effectiveness of the whole modeling
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