Polymerization Catalyst[(BDI)ZnN(TMS)2] Synthesis

The goal of this project was to synthesize [(BDI)ZnN(TMS)2], a catalyst for a ring-opening trans-esterification polymerization reactions. The BDI ligand was synthesized from the reaction of 2,6-diisopropylaniline and 2,4-pentanedione; four trials resulted in an average yield of 12.5%. The ligand formation was confirmed by the appearance of peaks at 3.481 ppm in the 1H NMR spectrum, indicating the — CH2 group. After recrystallization from methanol, the zinc complex was formed by treating Zn[N(TMS)2] with BDI, resulting in a yield of 38.5%

Large-scale Multi-Modal Pre-trained Models: A Comprehensive Survey

With the urgent demand for generalized deep models, many pre-trained big models are proposed, such as BERT, ViT, GPT, etc. Inspired by the success of these models in single domains (like computer vision and natural language processing), the multi-modal pre-trained big models have also drawn more and more attention in recent years. In this work, we give a comprehensive survey of these models and hope this paper could provide new insights and helps fresh researchers to track the most cutting-edge works. Specifically, we firstly introduce the background of multi-modal pre-training by reviewing the conventional deep learning, pre-training works in natural language process, computer vision, and speech. Then, we introduce the task definition, key challenges, and advantages of multi-modal pre-training models (MM-PTMs), and discuss the MM-PTMs with a focus on data, objectives, network architectures, and knowledge enhanced pre-training. After that, we introduce the downstream tasks used for the validation of large-scale MM-PTMs, including generative, classification, and regression tasks. We also give visualization and analysis of the model parameters and results on representative downstream tasks. Finally, we point out possible research directions for this topic that may benefit future works. In addition, we maintain a continuously updated paper list for large-scale pre-trained multi-modal big models: https://github.com/wangxiao5791509/MultiModal_BigModels_SurveyComment: Accepted by Machine Intelligence Researc

Talbot Effect for Exciton Polaritons

e demonstrate, experimentally and theoretically, a Talbot effect for hybrid light-matter waves—an exciton-polariton condensate formed in a semiconductor microcavity with embedded quantum wells. The characteristic “Talbot carpet” is produced by loading the exciton-polariton condensate into a microstructured one-dimensional periodic array of mesa traps, which creates an array of phase-locked sources for coherent polariton flow in the plane of the quantum wells. The spatial distribution of the Talbot fringes outside the mesas mimics the near-field diffraction of a monochromatic wave on a periodic amplitude and phase grating with the grating period comparable to the wavelength. Despite the lossy nature of the polariton system, the Talbot pattern persists for distances exceeding the size of the mesas by an order of magnitude. Thus, our experiment demonstrates efficient shaping of the two-dimensional flow of coherent exciton polaritons by a one-dimensional “flat lens.

Hypoglycemic Effects of Crude Polysaccharide from Purslane

The effects of crude polysaccharide from Purslane (CPP) on body weight (bw), blood glucose, total cholesterol (TC), high-density lipoprotein cholesterol (HDL-c), triglyceride (TG) and serum insulin levels were studied in diabetes mellitus mice. CPP treatment (200, 400 mg/kg bw) for 28 days resulted in a significant decrease in the concentrations of fasting blood glucose (FBG), TC and TG. Furthermore, CPP significantly increased the concentration of HDL-c, body weight and serum insulin level in the mice. In addition, according to acute toxicity studies and single cell gel electrophoresis analysis, CPP did not produce any physical or behavioral signs of toxicity. More significantly, our data demonstrated CPP exhibited the best effects at the dose of 400 mg/kg bw. The above results suggest that CPP can control blood glucose and modulate the metabolism of glucose and blood lipids in diabetes mellitus mice, so we conclude that CPP should be evaluated as a candidate for future studies on diabetes mellitus

Comparing the effectiveness of long-term use of daily and weekly glucagon-like peptide-1 receptor agonists treatments in patients with nonalcoholic fatty liver disease and type 2 diabetes mellitus: a network meta-analysis

ObjectiveIn the present network meta-analysis (NMA), we aimed to compare the effectiveness of daily and weekly treatment with glucagon-like peptide-1 receptor agonists for patients with nonalcoholic fatty liver disease (NAFLD) and type 2 diabetes mellitus (T2DM).MethodWe used Stata 17.0 for the NMA. Eligible Randomized controlled trials (RCTs) were searched in PubMed, Cochrane, and Embase databases until December 2022. Two researchers independently screened the available studies. The Cochrane Risk of Bias tool was used to assess the risk of bias in the included studies. We used GRADEprofiler (version3.6) to analyze the evidence certainty. Primary outcomes such as liver fat content (LFC), aspartate aminotransferase (AST), and alanine aminotransferase (ALT) levels, as well as secondary outcomes such as γ-glutamyltransferase (γGGT) and body weight, were evaluated. Then, each intervention was ranked by the surface under the cumulative ranking curve (SUCRA). As a supplement, we drew forest plots of subgroup using RevMan (version 5.4).ResultsFourteen RCTs involving 1666 participants were included in the present study. The NMA results showed that exenatide (bid) was the best treatment for improving LFC compared with other agents, liraglutide, dulaglutide, semaglutide (qw) and placebo), and the SUCRA values were 66.8%. Among five interventions (except exenatide (bid) and semaglutide (qw)) evaluated for AST outcome, and six interventions (except exenatide (bid)) evaluated for ALT outcome, semaglutide (qd) was the most effective drug (SUCRA (AST) = 100%, SUCRA (ALT) = 95.6%). The result of LFC in daily group was MD = -3.66, 95% CI [-5.56, -1.76] and in weekly GLP-1RAs group, it was MD = -3.51, 95% CI [-4, -3.02]. As to AST and ALT, the results in daily group versus weekly group were AST: MD = -7.45, 95% CI [-14.57, -0.32] versus MD= -0.58, 95% CI [-3.18, 2.01] and ALT: MD = -11.12, 95% CI [-24.18, 1.95] versus MD = -5.62, 95% CI [-15.25, 4]. The quality of evidence was assessed as moderate or low.ConclusionThe daily GLP-1RAs may be more effective in primary outcomes. And the daily semaglutide may be the most effective treatment for NAFLD and T2DM among the six interventions

Assessing Temporal Trade-Offs of Ecosystem Services by Production Possibility Frontiers

Ecosystems provide multiple valuable services that play an essential role in preventing meteorological risks, combating sandy land expansion, and ensuring sustainable development in the West Liao River Basin. The trade-off among ecosystem services (ES) is inevitable because of biophysical constraints and societal preferences. The production possibility frontier (PPF) is increasingly deemed an appropriate tool for representing trade-off relationships among ES. In this study, we developed a feasible approach for estimating PPF, which includes three steps. First, the annual water yield model, the sediment delivery ratio model, the carbon storage and sequestration model, and the habitat quality model of InVEST models were used to quantify temporal changes in four key ES, including water retention, soil conservation, carbon sequestration, and habitat improvement, in five-year periods from 1990 to 2020. Second, after the standardization of ES quantities, the functional forms of PPF curves for six pairs of ES trade-offs were derived by adopting a two-term exponential function of the curve fitting tool in MATLAB. Third, the trade-off intensity for each ES pair was defined and calculated based on the distance from the mean point to the PPF curve. Compared to the existing approaches, our approach has the advantage of fitting functional forms of PPF curves, handling both positive and negative values of ES, and calculating trade-off intensities. This study has three implications. First, showing the trade-offs between ES by PPF is helpful for providing knowledge on the existence of turning points and a complex relationship between certain ES pairs, thus avoiding unintended and large-scale shifts in the provision of ES. Second, PPF curves are a useful tool for visualizing the nature of ES relationships and the changes in trade-off intensity, thus supporting decision-makers to identify optimal solutions and make land use planning that can increase the overall efficiency over multiple ES. Third, socioeconomic components should be integrated into the assessment of ES trade-offs in order to understand the influences of societal choices on and examine stakeholders’ preferences regarding efficient ES combinations

Inter-and intra-event rainfall partitioning dynamics of two typical xerophytic shrubs in the Loess Plateau of China

Rainfall is known as the main water replenishment in dryland ecosystems, and rainfall partitioning by vegetation reshapes the spatial and temporal distribution patterns of rainwater entry into the soil. The dynamics of rainfall partitioning have been extensively studied at the inter-event scale, yet very few studies have explored its finer intra-event dynamics and the relating driving factors for shrubs. Here, we conducted a concurrent in-depth investigation of all rainfall partitioning components at inter-and intra-event scales for two typical xerophytic shrubs (Caragana korshinskii and Salix psammophila) in the Liudaogou catchment of the Loess Plateau, China. The event throughfall (TF), stemflow (SF), and interception loss (IC), and their temporal variations within the rainfall event, as well as the meteorological factors and vegetation characteristics, were systematically measured during the 2014-2015 rainy seasons. Our results showed that C. korshinskii had significantly higher SF percentage (9.2%) and lower IC percentage (21.4%) compared to S. psammophila (3.8% and 29.5%, respectively), but their TF percentages were not significantly different (69.4% vs. 66.7%). At the intra-event scale, TF and SF of S. psammophila were initiated (0.1 vs. 0.3h and 0.7 vs. 0.8h) and peaked (1.8 vs. 2.0h and 2.1 vs. 2.2h) more quickly, and TF of S. psammophila lasted longer (5.2 vs. 4.8h) and delivered more intensely (4.3 vs. 3.8mmh-1), whereas SF of C. korshinskii lasted longer (4.6 vs. 4.1h) and delivered more intensely (753.8 vs. 471.2mmh-1). For both shrubs, rainfall amount was the most significant factor influencing inter-event rainfall partitioning, and rainfall intensity and duration controlled the intra-event TF and SF variables. The C. korshinskii with larger branch angle, more small branches, and smaller canopy area, has an advantage over S. psammophila to produce SF more efficiently. The S. psammophila has lower canopy water storage capacity to generate and peak TF and SF earlier, and it has larger aboveground biomass and total canopy water storage of individual plants to produce higher IC compared to C. korshinskii. These findings contribute to the fine characterization of shrub-dominated ecohydrological processes, and improve the accuracy of water balance estimation in dryland ecosystems.This research has been supported by the National Natural Science Foundation of China (grant nos. 41991233 and 41822103) and the Youth Innovation Promotion Association of the Chinese Academy of Sciences (grant no. Y202013).Peer reviewe