基于琥珀酸衍生物为单体的聚酯的合成与表征

以1,4-环己二酮-2,5-二甲酸二甲酯(DMSS)为起始原料,采用两步法成功制备了2,5-二甲氧基对苯二甲酸二甲酯(DMDMT)。分别以DMDMT和不同碳链的脂肪二醇为单体,在三氧化二锑的催化作用下,采用熔融共聚酯交换法合成了4种由脂肪族二元醇-芳香族二元酸构成的聚酯。经过溶解、沉淀、离心等分离手段,得到目标聚酯a^d。通过红外光谱、核磁共振氢谱、凝胶渗透色谱、差示扫描量热分析和热重分析对其进行表征和分析。聚酯a^d的PDI在1.95~2.70之间,数均相对分子质量(Mn)在10000~15200之间。研究了聚合物中分子主链柔顺性对聚合物的热性能的影响,其中,聚酯a的熔点(Tm)较高,达到90℃,其初始分解温度(T5%)高达363℃;随着脂肪族碳链的碳数增加,所合成的聚酯a^d的熔点和初始分解温度(T5%)下降,这为新型脂肪族-芳香族聚酯的分子设计与合成提供了有益的参考。

PA66/PA6I6T共混物非等温结晶动力学及性能

将PA66与PA6I6T以不同配比进行熔融共混,通过差示扫描量热分析对所制备的尼龙66(PA66)与半芳香尼龙(PA6I6T)共混物在不同降温速率下的非等温结晶行为进行了研究。利用Jeziorny法及Mo方法对共混物的非等温结晶动力学数据进行了分析,并采用Kissinger方法计算了共混体系的结晶活化能;考察了PA6I6T含量对共混物力学性能、耐热性及加工流动性的影响。研究发现,PA66与PA6I6T具有良好的相容性,少量的PA6I6T会促进PA66的结晶,随着PA6I6T含量的进一步增加,PA66的结晶速率及结晶度呈下降趋势,PA66的结晶活化能的绝对值随PA6I6T含量的增加表现为先增大后减小。共混物的拉伸强度和冲击强度随PA6I6T含量的增加而增加,其中拉伸强度在PA6I6T达到一定含量后趋于平缓。PA6I6T的引入提高了共混物的耐热性和热稳定性,但加工流动性较纯PA66材料有一定程度降低。

Comparison of acute pneumonia caused by SARS-CoV-2 and other respiratory viruses in children:a retrospective multi-center cohort study during COVID-19 outbreak

Background:Until January 18,2021,coronavirus disease-2019(COVID-19)has infected more than 93 million individuals and has caused a certain degree of panic.Viral pneumonia caused by common viruses such as respiratory syncytial virus,rhinovirus,human metapneumovirus,human bocavirus,and parainfluenza viruses have been more common in children.However,the incidence of COVID-19 in children was significantly lower than that in adults.The purpose of this study was to describe the clinical manifestations,treatment and outcomes of COVID-19 in children compared with those of other sources of viral pneumonia diagnosed during the COVID-19 outbreak.Methods:Children with COVID-19 and viral pneumonia admitted to 20 hospitals were enrolled in this retrospective multi-center cohort study.A total of 64 children with COVID-19 were defined as the COVID-19 cohort,of which 40 children who developed pneumonia were defined as the COVID-19 pneumonia cohort.Another 284 children with pneumonia caused by other viruses were defined as the viral pneumonia cohort.The epidemiologic,clinical,and laboratory findings were compared by Kolmogorov-Smirnov test,t-test,Mann-Whitney U test and Contingency table method.Drug usage,immunotherapy,blood transfusion,and need for oxygen support were collected as the treatment indexes.Mortality,intensive care needs and symptomatic duration were collected as the outcome indicators.Results:Compared with the viral pneumonia cohort,children in the COVID-19 cohort were mostly exposed to family members confirmed to have COVID-19(53/64 vs.23/284),were of older median age(6.3 years vs.3.2 years),and had a higher proportion of ground-glass opacity(GGO)on computed tomography(18/40 vs.0/38,P<0.001).Children in the COVID-19 pneumonia cohort had a lower proportion of severe cases(1/40 vs.38/284,P=0.048),and lower cases with high fever(3/40 vs.167/284,P<0.001),requiring intensive care(1/40 vs.32/284,P<0.047)and with shorter symptomatic duration(median 5d vs.8d,P<0.001).The proportion of cases with evaluated inflammatory indicators,biochemical indicators related to organ or tissue damage,D-dimer and secondary bacterial infection were lower in the COVID-19 pneumonia cohort than those in the viral pneumonia cohort(P<0.05).No statistical differences were found in the duration of positive PCR results from pharyngeal swabs in 25 children with COVID-19 who received antiviral drugs(lopinavir-ritonavir,ribavirin,and arbidol)as compared with duration in 39 children without antiviral therapy(median 10d vs.9d,P=0.885).Conclusions:The symptoms and severity of COVID-19 pneumonia in children were no more severe than those in children with other viral pneumonia.Lopinavir-ritonavir,ribavirin and arbidol do not shorten the duration of positive PCR results from pharyngeal swabs in children with COVID-19.During the COVID-19 outbreak,attention also must be given to children with infection by other pathogens infection.

Development of innovative tools for investigation of nutrient-gut interaction

The gastrointestinal tract is the key interface between the ingesta and the human body.There is wide recognition that the gastrointestinal response to nutrients or bioactive compounds,particularly the secretion of numerous hormones,is critical to the regulation of appetite,body weight and blood glucose.This concept has led to an increasing focus on“gut-based”strategies for the management of metabolic disorders,including type 2 diabetes and obesity.Understanding the underlying mechanisms and downstream effects of nutrient-gut interactions is fundamental to effective translation of this knowledge to clinical practice.To this end,an array of research tools and platforms have been developed to better understand the mechanisms of gut hormone secretion from enteroendocrine cells.This review discusses the evolution of in vitro and in vivo models and the integration of innovative techniques that will ultimately enable the development of novel therapies for metabolic diseases.

糖尿病状态下肾小管葡萄糖转运蛋白表达和功能的变化以及影响因素的研究进展

肾小管上皮富有多种葡萄糖转运蛋白(GLUT),包括钠-葡萄糖共转运蛋白(SGLT)2、SGLT1、GLUT2和GLUT1,共同调控葡萄糖在肾脏的重吸收。近年来研究发现,肾小管GLUT的表达和功能失调可能是导致糖代谢失衡的重要因素。该文着重探讨糖尿病状态下GLUT的表达变化,以及饮食、药物和交感神经等因素对SGLT2表达水平或功能的影响,为后续对基于肾脏的2型糖尿病的治疗研究提供新思路。

SuPoolVisor:a visual analytics system for mining pool surveillance

Cryptocurrencies represented by Bitcoin have fully demonstrated their advantages and great potential in payment and monetary systems during the last decade.The mining pool,which is considered the source of Bitcoin,is the cornerstone of market stability.The surveillance of the mining pool can help regulators effectively assess the overall health of Bitcoin and issues.However,the anonymity of mining-pool miners and the difficulty of analyzing large numbers of transactions limit in-depth analysis.It is also a challenge to achieve intuitive and comprehensive monitoring of multi-source heterogeneous data.In this study,we present SuPoolVisor,an interactive visual analytics system that supports surveillance of the mining pool and de-anonymization by visual reasoning.SuPoolVisor is divided into pool level and address level.At the pool level,we use a sorted stream graph to illustrate the evolution of computing power of pools over time,and glyphs are designed in two other views to demonstrate the influence scope of the mining pool and the migration of pool members.At the address level,we use a force-directed graph and a massive sequence view to present the dynamic address network in the mining pool.Particularly,these two views,together with the Radviz view,support an iterative visual reasoning process for de-anonymization of pool members and provide interactions for cross-view analysis and identity marking.Effectiveness and usability of SuPoolVisor are demonstrated using three cases,in which we cooperate closely with experts in this field.

Spatiotemporal change patterns of urban lakes in China’s major cities between 1990 and 2015

China has experienced unprecedented urbanization in the past decades,resulting in dramatic changes in the physical,limnological,and hydrological characteristics of lakes in urban landscapes.However,the spatiotemporal dynamics in distribution and abundance of urban lakes in China remain poorly understood.Here,we characterized the spatiotemporal change patterns of urban lakes in China’s major cities between 1990 and 2015 using remote-sensing data and landscape metrics.The results showed that the urban lake landscape patterns have experienced drastic changes over the past 25 years.The total surface area of the urban lakes has decreased by 17,620.02 ha,a decrease of 24.22%,with a significant increase in the landscape fragmentation and a reduction in shape complexity.We defined three lake-shrinkage types and found that vanishment was the most common lake-shrinkage pattern,followed by edge-shrinkage and tunneling in terms of lake area.Moreover,we also found that urban sprawl was the dominant driver of the lake shrinkage,accounting for 67.89%of the total area loss,and the transition from lakes to cropland was also an important factor(19.86%).This study has potential for providing critical baseline information for government decision-making in lake resources management and urban landscape design.

A novel water index for urban high-resolution eight-band WorldView-2 imagery

Land surface water mapping is one of the most important remote-sensing applications.However,water areas are spectrally similar and overlapped with shadow,making accurate water extraction from remote-sensing images still a challenging problem.This paper develops a novel water index named as NDWI-MSI,combining a new normalized difference water index(NDWI)and a recently developed morphological shadow index(MSI),to delineate water bodies from eight-band WorldView-2 imagery.The newly available bands(e.g.coastal,yellow,red-edge,and near-infrared 2)of WorldView-2 imagery provide more potential for constructing new NDWIs derived from various band combinations.Through our testing,a new NDWI is defined in this study.In addition,MSI,a recently developed automatic shadow extraction index from high-resolution imagery can be used to indicate shadow areas.The NDWI-MSI is created by combining NDWI and MSI,which is able to highlight water bodies and simultaneously suppress shadow areas.In experiments,it is shown that the new water index can achieve better performance than traditional NDWI,and even supervised classifiers,for example,maximum likelihood classifier,and support vector machine.

An Online Visualization System for Streaming Log Data of Computing Clusters

Monitoring a computing cluster requires collecting and understanding log data generated at the core, computer, and cluster levels at run time. Visualizing the log data of a computing cluster is a challenging problem due to the complexity of the underlying dataset： it is streaming, hierarchical, heterogeneous, and multi-sourced. This paper presents an integrated visualization system that employs a two-stage streaming process mode. Prior to the visual display of the multi-sourced information, the data generated from the clusters is gathered, cleaned, and modeled within a data processor. The visualization supported by a visual computing processor consists of a set of multivariate and time variant visualization techniques, including time sequence chart, treemap, and parallel coordinates. Novel techniques to illustrate the time tendency and abnormal status are also introduced. We demonstrate the effectiveness and scalability of the proposed system framework on a commodity cloud-computing platform.

Elemental mercury removal from coal gas by CeMnTi sorbents and their regeneration performance

Ce and Mn modified TiO_(2) sorbents(CeMnTi) were prepared by a co-precipitation method,and their ability to remove elemental mercury from coal gas in a fixed bed reactor was studied.Based on results of Brunauer-Emmett-Teller(BET),X-ray diffraction(XRD),scanning electron microscope(SEM),and X-ray photoelectron spectroscopy(XPS) studies,the modification mechanisms of the CeMnTi sorbents are discussed.Mn doping improved the specific surface area and dispersion of cerium oxides on the sorbent surface,while Ce doping increased the proportion of Mn^(4+)in manganese oxides by a synergetic effect between manganese oxides and cerium oxides.The effects of the active component,temperature,and coal gas components on the mercury removal performance of the sorbents were investigated.The results showed that the CeMnTi sorbents exhibited high mercury removal efficiency.Ce_(0.2)Mn_(0.1)Ti adsorbed 91.55% elemental mercury from coal gas at 160℃.H2 S and O2 significantly improved the ability of sorbents to remove mercury.Part of the H2_(S) formed stable sulfates or sulfites through a series of oxidation reaction chains on the sorbent surface.HCl also improved the mercury removal performance,but reduced the promotion effect of H2_(S) for mercury removal when coexisting with H2_(S).CO and H2 had a minor inhibitory effect on mercury adsorption.The recycling performance of the sorbents was investigated by thermal regeneration.The thermal decomposition of the used sorbents indicated that mercury compounds were present mainly in the form of HgO and HgS,and higher temperature was beneficial for regeneration.The formation of sulfates and sulfites in the presence of H2_(S) led to a decrease in mercury removal efficiency.

Stochastic Volatility Modeling based on Doubly Truncated Cauchy Distribution and Bayesian Estimation for Chinese Stock Market

In order to measure the uncertainty of financial asset returns in the stock market, this paper presents a new model, called SV-dt C model, a stochastic volatility(SV) model assuming that the stock return has a doubly truncated Cauchy distribution, which takes into account the high peak and fat tail of the empirical distribution simultaneously. Under the Bayesian framework, a prior and posterior analysis for the parameters is made and Markov Chain Monte Carlo(MCMC) is used for computing the posterior estimates of the model parameters and forecasting in the empirical application of Shanghai Stock Exchange Composite Index(SSECI) with respect to the proposed SV-dt C model and two classic SV-N(SV model with Normal distribution)and SV-T(SV model with Student-t distribution) models. The empirical analysis shows that the proposed SV-dt C model has better performance by model checking, including independence test(Projection correlation test), Kolmogorov-Smirnov test(K-S test) and Q-Q plot. Additionally, deviance information criterion(DIC) also shows that the proposed model has a significant improvement in model fit over the others.

Benzobisthiazole Polymer with Resonance-assisted Hydrogen Bonds for High-performance Transistor and Solar Cell Applications

Benzobisthiazole polymer with resonance-assisted hydrogen bonds(RAHBs)has been synthesized for both organic field-effect transistor and polymer solar cell applications.The properties of the hydrogen bonded polymer are compared with the reference polymer without RAHBs.Single-crystal X-ray diffraction analyses of the building block reveal that the RAHB interactions are formed between the carbamate hydrogen and imine nitrogen of the thiazoles.The hydrogen donor and acceptor are connected byπ-conjugated molecular framework and the hydrogen-bridged quasi aromatic rings lock the conformation of the building block.The building block adopted a layered sandwich packing in crystal instead of slipped herringbone stacking which was often found in the crystal of benzobisthiazole derivatives.The polymer PCBTZ-TT with RAHBs showed deeper HOMO/LUMO energy level(about 0.2 eV)than reference polymer.The PCBTZ-TT demonstrated the hole mobility of0.96 cm^(2)·V^(-1)·s^(-1) in field-effect transistor devices and achieved power conversion efficiency of 13.6%in solar cell devices with Y6 as acceptor without any additive.

A Posteriori Error Estimate for Stabilized Low-Order Mixed FEM for the Stokes Equations

This paper is concerned with a stabilized approach to low-order mixed finite element methods for the Stokes equations.We will provide a posteriori error analysis for the method.We present two a posteriori error indicators which will be demonstrated to be globally upper and locally lower bounds for the error of the finite element discretization.Finally two numerical experiments will be carried out to show the efficiency on constructing adaptive meshes.

MultiSciView: Multivariate Scientific X-ray Image Visual Exploration with Cross-Data Space Views

X-ray images obtained from synchrotron beamlines are large-scale,high-resolution and high-dynamic-range grayscale data encoding multiple complex properties of the measured materials.They are typically associated with a variety of metadata which increases their inherent complexity.There is a wealth of information embedded in these data but so far scientists lack modem exploration tools to unlock these hidden treasures.To bridge this gap,we propose MultiSciView,a multivariate scientific x-ray image visualization and exploration system for beamline-generated x-ray scattering data.Our system is composed of three complementary and coordinated interactive visualizations to enable a coordinated exploration across the images and their associated attribute and feature spaces.The first visualization features a multi-level scatterplot visualization dedicated for image exploration in attribute,image,and pixel scales.The second visualization is a histogram-based attribute cross filter by which users can extract desired subset patterns from data.The third one is an attribute projection visualization designed for capturing global attribute correlations.We demonstrate our framework by ways of a case study involving a real-world material scattering dataset.We show that our system can efficiently explore large-scale x-ray images,accurately identify preferred image patterns,anomalous images and erroneous experimental settings,and effectively advance the comprehension of material nanostructure properties.