Simulation of the climatic effects of natural forcings during the pre-industrial era

The MPM-2, an Earth system model of intermediate complexity, is employed to study the climate system response to natural forcings during the pre-industrial era (1000-1800 AD), with a special focus on the surface air temperature (SAT) evolution. Solar radiation and volcanism are the primary natural forcings during this period. In the MPM-2, the solar radiation forcing determines the long-term trend of the climate system change, and the volcanic forcing intensifies (weakens) this trend. Ultimately, the combination of solar and volcanic forcings dominates the long-term changes of the climate system. These results aro in good agreement with other model data or temperature reconstructions. Natural forcings can well explain the Little Ice Age (LIA) and the Medieval Warm Period (MWP). At the large regional scale, the SAT response to natural forcings is almost coincident with that of the Northern Hemisphere. Based on MPM-2 model results, it is concluded that the global climate gradually became cold during the pre-industrial era. However, MPM-2 model results substantially correlate with reconstructed solar and volcanic forcings. Namely, to some great extent, these results strongly rely on the forcing series data we choose. Therefore, in order to accurately simulate the secular variation of the historical climate, it is very important to reconstruct well the solar radiation change and volcanic forcing data are well reconstructed for the past 10000 years, at least for the past 2000 years, in addition to the model improvements. The sensitivity study on the abrupt solar radiation change indicates that the increased solar radiation not only strengthens the nonlinear response of SAT, but intensifies the global hydrological cycle. At the same time, the biosphere is also affected obviously

Assessment of the feasibility of TACE combined with intratumoral injection of cisplatin in hepatocellular carcinoma

The feasibility of transcatheter arterial chemoembolization (TACE) combined with intratumoral injection of cisplatin as treatment for hepatocellular carcinoma. 30 cases receiving TACE were denoted the TACE group, another 30 cases receiving TACE combined with an intratumoral multi-point injection of cisplatin were denoted the TACE/cisplatin group. Cases with partial remission/complete remission (PR/CR) were analyzed using 2 tests; alpha fetoprotein (AFP), aspartate amino transferase (AST), total bilirubin (TBIL), erythrocyte, and platelet levels were detected and the differences between two groups were analyzed using the Student’s t-test; cases with complications, including intrahepatic metastasis (IM), upper gastrointestinal bleeding (UGB), and liver failure were also counted. The correlation of clinical parameters with PR/CR was analyzed using multifactorial correlation analysis. Cases with PR/CR in the TACE/cisplatin group were significantly more than in TACE group, accompanied by significant declination in FAP. There were no significant differences of AST, ALT, TBIL, blood urea nitrogen (BUN), white blood cells (WBC), red blood cells (RBC), and platelets (PLT) between two groups; 3 cases with IM, one case with UGB and one case with LF were found in the TACE group, but only 1 case with IM was found in the TACE/cisplatin group. In addition, tumor stage was correlated with PR/CR. We concluded that TACE combined with intratumoral injection of cisplatin was more effective than TACE, and with fewer complications and side effects

Effect of volume ratio on the performance of mid-wave infrared transparent Gd2O3–MgO composite ceramics

Gd2O3–MgO composite ceramics are promising candidates for preparing protective mid-wave infrared (MWIR) windows. However, owing to the different crystal structures of Gd2O3 and MgO after the sintering process, the volume ratio of the two phases must be controlled more precisely to achieve optimum performance. In this study, a nitrate-citrate combustion method was used to prepare Gd2O3–MgO nanopowders with different volume ratios, and composite ceramics were then fabricated via low-temperature pre-sintering and subsequent hot isostatic pressing (HIP). The effect of the Gd2O3:MgO volume ratio on the sintering behaviour, microstructures and optical, thermal and mechanical properties of the composite ceramics was studied in detail. A comprehensive assessment of the above-mentioned properties indicated that the Gd2O3–MgO composite ceramic with a volume ratio of 2:3, which exhibited a transmittance of 80.1–85.8% in the range of 3–5 μm, thermal conductivity of 17.5 W m−1 K−1, Vickers hardness of 9.8 GPa and toughness of 1.84 MPa m1/2, displays the optimum application performance for MWIR windows

Changes in Mental Health and Preventive Behaviors before and after COVID-19 Vaccination: A Propensity Score Matching (PSM) Study

Mass vaccination against the COVID-19 pandemic is ongoing worldwide to achieve herd immunity among the general population. However, little is known about how the COVID-19 vaccination would affect mental health and preventive behaviors toward the COVID-19 pandemic. In this study, we conducted a cross-sectional survey to address this issue among 4244 individuals at several COVID-19 vaccination sites in Guangzhou, China. Using univariate analysis and multiple linear regression models, we found that major demographic characteristics, such as biological sex, age, education level, and family per capita income, are the dominant influencing factors associated with health beliefs, mental health, and preventive behaviors. After propensity score matching (PSM) treatment, we further assessed the changes in the scores of health belief, mental health, and preventive behaviors between the pre-vaccination group and the post-vaccination group. When compared to individuals in the pre-vaccination group, a moderate but statistically significant lower score was observed in the post-vaccination group (p = 0.010), implying possibly improved psychological conditions after COVID-19 vaccination. In addition, there was also a moderate but statistically higher score of preventive behaviors in the post-vaccination group than in the pre-vaccination group (p < 0.001), suggesting a higher probability to take preventive measures after COVID-19 vaccination. These findings have implications for implementing non-pharmaceutical interventions combined with mass vaccination to control the rebound of COVID-19 outbreaks

Shrinkage features, microstructure evolution and properties of Gd2O3-MgO optical composite ceramics with Zr as phase stabilizer

A novel composite ceramic, composed of equal-volumetric Zr-stabilized Gd2O3 and MgO phases, was prepared to be transparent in mid-wave infrared range. Zr stabilized Gd2O3 is proved to have a lower lattice parameter (10.7516Å) using XRD refinement. Pressureless sintering behavior of Gd2O3-MgO with/without 2at.% Zr-doping (naming ZGM and GM) was studied via the real-time observation technique. The shrinkage of ZGM green body proceeds steadily up to 1400°C while that of the undoped one shrinks sharply at 1250°C due to Gd2O3 phase transition. The segregation of Zr element along the grain boundaries of Zr-Gd2O3 creates a synergized effect on the grain refinement with pinning effect. Dense ZGM ceramics exhibit superior transmittance of 78.3%‐85.6% at 3-5 μm, which show good consistency with the calculated values. The refractive index of Zr- Gd2O3 varies from 1.87 at 3 μm to 1.80 at 5 μm, which is smaller than those of monoclinic Gd2O3

Enantioselective α‑Benzoyloxylation of β‑Keto Esters by <i>N</i>‑Oxide Phase-Transfer Catalysts

An efficient and enantioselective α-benzoyloxylation of β-keto esters has been achieved by phase-transfer catalysis. This simple catalytic procedure is applicable to a range of β-keto esters with cinchona-derived <i>N</i>-oxide asymmetric phase-transfer catalysts and gives the corresponding products in good enantiopurity (up to 95% ee) and yield (up to 99%). This simple and effective oxyfunctionalization is a useful synthetic strategy for introducing an oxygen-containing functional group at the α position of β-dicarbonyl compounds

Factors associated with COVID-19 vaccination acceptance among industrial workers in the post-vaccination era: a large-scale cross-sectional survey in China

Background COVID-19 pandemic continues to pose a huge threat to public health. Mass vaccination is needed to achieve herd immunity against SARS-CoV-2. Currently, several vaccines are being inoculated on a large-scale. The willingness of COVID-19 vaccination had been well investigated in the pre-vaccination era, but no reported data in the post-vaccination era yet. Methods We conducted a large-scale survey among industrial workers during the vaccination campaign in China. Chi-square test and rank sum test were used to identify differences for various intentions regarding COVID-19 vaccination. Univariate analysis and multivariate regression models were utilized to analyze the relationship among demographic factors, related influencing factors and acceptance of COVID-19 vaccination. Results A total of 23,940 industrial workers were included, 66.0% were willing to take COVID-19 vaccine, 16.6% were unwilling, and 17.4% were unsure. Participants were more likely to get vaccinated if they were male, aged 45–65, being good educated, married, or being recommended by doctors or nurses. Participants with strong risk perception of COVID-19 infection, strong confidence in COVID-19 vaccine, high attention to COVID-19 vaccine, good health status, bad health habit, and a history of vaccination within three months were also more likely to be vaccinated. Conclusions This study calls for more attention and health-related education among industrial workers to improve their acceptance of COVID-19 vaccination

Learning-based fully automated prediction of lumbar disc degeneration progression with specified clinical parameters and preliminary validation

Abstract Background: Lumbar disc degeneration (LDD) may be related to aging, biomechanical and genetic factors. Despite the extensive work on understanding its etiology, there is currently no automated tool for accurate prediction of its progression. Purpose: We aim to establish a novel deep learning-based pipeline to predict the progression of LDD-related findings using lumbar MRIs. Materials and methods: We utilized our dataset with MRIs acquired from 1,343 individual participants (taken at the baseline and the 5-year follow-up timepoint), and progression assessments (the Schneiderman score, disc bulging, and Pfirrmann grading) that were labelled by spine specialists with over ten years clinical experience. Our new pipeline was realized by integrating the MRI-SegFlow and the Visual Geometry Group-Medium (VGG-M) for automated disc region detection and LDD progression prediction correspondingly. The LDD progression was quantified by comparing the Schneiderman score, disc bulging and Pfirrmann grading at the baseline and at follow-up. A fivefold cross-validation was conducted to assess the predictive performance of the new pipeline. Results: Our pipeline achieved very good performances on the LDD progression prediction, with high progression prediction accuracy of the Schneiderman score (Accuracy: 90.2 ± 0.9%), disc bulging (Accuracy: 90.4% ± 1.1%), and Pfirrmann grading (Accuracy: 89.9% ± 2.1%). Conclusions: This is the first attempt of using deep learning to predict LDD progression on a large dataset with 5-year follow-up. Requiring no human interference, our pipeline can potentially achieve similar predictive performances in new settings with minimal efforts