Effects of the Particle Size of BaTiO₃ Fillers on Fabrication and Dielectric Properties of BaTiO₃/Polymer/Al Films for Capacitor Energy-Storage Application

BaTiO3/polymer/Al (BPA) composite films for energy storage were fabricated by way of a roll coating and thermal curing process. The coating slurry consisted of silicon-containing heat-resistant resin (CYN-01) and BaTiO3 particles with various particle sizes obtained from commercial BaTiO3 powders processed at different durations of wet sand grinding in the presence of silane coupling agent (KH550), which not only improves the dielectric performance of the BPA films but also facilitates its production in a large scale. The major influence factors, such as the ratio between BaTiO3 and resin and the size of BaTiO3 particles, were investigated and their related mechanisms were discussed. The results show that modifying BaTiO3 particles (D90 = 0.83 μm) with the silane coupling agent of KH550 enhances the dielectric properties of the BPA films. The typical BPA films obtained exhibit a high dielectric constant of 32, a high break strength of 20.8 V/μm and a low dielectric loss of 0.014. The present work provides a simple and convenient way to prepare high-quality ceramic/polymer composite films for energy-storage application in a large scale

A LightGBM-based landslide susceptibility model considering the uncertainty of non-landslide samples

AbstractThe quality of samples is crucial in constructing a data-driven landslide susceptibility model. This article aims to construct a data-driven landslide susceptibility model that takes into account the selection of non-landslide samples. First, 21 conditioning factors are selected, including four types of topography and landform, geological conditions, environmental conditions, and human activities. Grid units with 30 m resolution are established by combining 942 historical landslide events in study area. Second, non-landslide samples are selected using both the traditional method and the information quantity method. Two landslide susceptibility models are established using the Bayesian optimization-LightGBM model. The accuracy of the model is evaluated by significance test and the area under curve (AUC). Finally, the SHAP algorithm is used to analyse the internal mechanism of the model’s decision-making. Based on the information quantity method, the LightGBM model identifies very high-high susceptibility areas that account for 77.92% of the total number of landslides. Additionally, the AUC of test set and the AUC of training set are 23.2% and 17.1% higher, respectively, compared to the traditional model. The selection of different sample data, whether landslide or non-landslide, impacts the factor rank, model accuracy, and the interal decision-making mechanism of the model. This finding provides valuable for the selection of sample data in the binary classification model

TiO2-Seeded Hydrothermal Growth of Spherical BaTiO3 Nanocrystals for Capacitor Energy-Storage Application

Simple but robust growth of spherical BaTiO3 nanoparticles with uniform nanoscale sizes is of great significance for the miniaturization of BaTiO3-based electron devices. This paper reports a TiO2-seeded hydrothermal process to synthesize spherical BaTiO3 nanoparticles with a size range of 90–100 nm using TiO2 (Degussa) and Ba(NO3)2 as the starting materials under an alkaline (NaOH) condition. Under the optimum conditions ([NaOH] = 2.0 mol L−1, RBa/Ti = 2.0, T = 210 °C and t = 8 h), the spherical BaTiO3 nanoparticles obtained exhibit a narrow size range of 91 ± 14 nm, and the corresponding BaTiO3/polymer/Al film is of a high dielectric constant of 59, a high break strength of 102 kV mm−1, and a low dielectric loss of 0.008. The TiO2-seeded hydrothermal growth has been proved to be an efficient process to synthesize spherical BaTiO3 nanoparticles for potential capacitor energy-storage applications

A Hybrid Landslide Warning Model Coupling Susceptibility Zoning and Precipitation

Landslides are one of the most severe and common geological hazards in the world. The purpose of this research is to establish a coupled landslide warning model based on random forest susceptibility zoning and precipitation. The 1520 landslide events in Fengjie County, Chongqing, China, before 2016 are taken as research cases. We adapt the random forest model to build a landslide susceptibility model. The antecedent effective precipitation model, based on the fractal relationship, is used to calculate the antecedent effective precipitation in the 10 days before the landslide event. Based on different susceptibility zones, the effective precipitation corresponding to different cumulative frequencies is counted as the threshold, and the threshold is adjusted according to the fitted curve. Finally, according to the daily precipitation, the rain warning levels in susceptibility zones are further adjusted, and the final prewarning model of the susceptibility zoning and precipitation coupling is obtained. The results show that the random forest model has good prediction ability for landslide susceptibility zoning, and the precipitation warning model that couples landslide susceptibility, antecedent effective precipitation, and the daily precipitation threshold has high early warning ability. At the same time, it was found that the precipitation warning model coupled with antecedent effective precipitation and the daily precipitation threshold has more accurate precipitation warning ability than the precipitation warning model coupled with the antecedent effective precipitation only; the coupling of the two can complement each other to better characterize the occurrence of landslides triggered by rainfall. The proposed coupled landslide early warning model based on random forest susceptibility and rainfall inducing factors can provide scientific guidance for landslide early warning and prediction, and improve the manageability of landslide risk

Resection of Liver Metastases: A Treatment Provides a Long-Term Survival Benefit for Patients with Advanced Pancreatic Neuroendocrine Tumors: A Systematic Review and Meta-Analysis

Purpose. Nonsurgical therapies, including biotherapy, chemotherapy, and liver-directed therapy, provided a limit survival benefit for PNET patients with hepatic metastases. With the development of liver resection technique, there was a controversy on whether to perform a liver resection for these patients. Methods. A computerized search was made of the Medline/PubMed, EMbase, Cochrane Library, and SinoMed (CBM) before March 2018. A meta-analysis was performed to investigate the differences in the efficacy of liver resection and nonliver resection treatments based on the evaluation of morbidity, 30-day mortality, symptom relief rate, and 1-, 3-, and 5-year survival. Two investigators reviewed all included articles and extracted the data of them. The meta-analysis was performed via Review Manager 5.3 software. Results. A total of 13 cohort studies with 1524 patients were included in this meta-analysis. Compared with the nonliver resection group, liver resection group had a longer 1-, 3-, and 5-year survival time and a higher symptom relief with an acceptable mortality and morbidity. Conclusions. Liver resection is a safe treatment and could significantly prolong the long-term prognosis for highly selected patients with resectable liver metastases from PNET. Further randomized, controlled trials are needed

Different Effects of Three Selected Lactobacillus Strains in Dextran Sulfate Sodium-Induced Colitis in BALB/c Mice.

To analyze the changes of different Lactobacillus species in ulcerative colitis patients and to further assess the therapeutic effects of selected Lactobacillus strains on dextran sulfate sodium (DSS)-induced experimental colitis in BALB/c mice.Forty-five active ulcerative colitis (UC) patients and 45 population-based healthy controls were enrolled. Polymerase chain reaction (PCR) amplification and real-time PCR were performed for qualitative and quantitative analyses, respectively, of the Lactobacillus species in UC patients. Three Lactobacillus strains from three species were selected to assess the therapeutic effects on experimental colitis. Sixty 8-week-old BALB/c mice were divided into six groups. The five groups that had received DSS were administered normal saline, mesalazine, L. fermentum CCTCC M206110 strain, L. crispatus CCTCC M206119 strain, or L. plantarum NCIMB8826 strain. We assessed the severity of colitis based on disease activity index (DAI), body weight loss, colon length, and histologic damage.The detection rate of four of the 11 Lactobacillus species decreased significantly (P < 0.05), and the detection rate of two of the 11 Lactobacillus species increased significantly (P < 0.05) in UC patients. Relative quantitative analysis revealed that eight Lactobacillus species declined significantly in UC patients (P < 0.05), while three Lactobacillus species increased significantly (P < 0.05). The CCTCC M206110 treatment group had less weight loss and colon length shortening, lower DAI scores, and lower histologic scores (P < 0.05), while the CCTCC M206119 treatment group had greater weight loss and colon length shortening, higher histologic scores, and more severe inflammatory infiltration (P < 0.05). NCIMB8826 improved weight loss and colon length shortening (P < 0.05) with no significant influence on DAI and histologic damage in the colitis model.Administration of an L. crispatus CCTCC M206119 supplement aggravated DSS-induced colitis. L. fermentum CCTCC M206110 proved to be effective at attenuating DSS-induced colitis. The potential probiotic effect of L. plantarum NCIMB8826 on UC has yet to be assessed