Mathematical analysis of the dynamics of COVID-19 in Africa under the influence of asymptomatic cases and re-infection

Coronavirus pandemic (COVID-19) hit the world in December 2019, and only less than 5% of the 15 million cases were recorded in Africa. A major call for concern was the significant rise from 2% in May 2020 to 4.67% by the end of July 15, 2020. This drastic increase calls for quick intervention in the transmission and control strategy of COVID-19 in Africa. A mathematical model to theoretically investigate the consequence of ignoring asymptomatic cases on COVID-19 spread in Africa is proposed in this study. A qualitative analysis of the model is carried out with and without re-infection, and the reproduction number is obtained under re-infection. The results indicate that increasing case detection to detect asymptomatically infected individuals will be very effective in containing and reducing the burden of COVID-19 in Africa. In addition, the fact that it has not been confirmed whether a recovered individual can be re-infected or not, then enforcing a living condition where recovered individuals are not allowed to mix with the susceptible or exposed individuals will help in containing the spread of COVID-19.     

高速公路PPP项目股权结构、质量水平与VFM的关系研究

高速公路PPP项目属于具有经营收益的准经营性项目,政府制定有效的激励措施,可以鼓励项目公司发挥专业的建设和运营能力,提高项目质量和收益水平。本文以VFM作为政府绩效评价指标,通过构建完全信息静态博弈模型,研究了PPP项目股权结构、质量水平与VFM之间的关系,结果发现:虽然社会资本较多持有项目公司股份有助于提高VFM水平,但随着社会资本方股权比例的增加,项目质量水平在不断降低,所以政府应该将社会资本方的持股比例控制在一定范围内,在保证项目质量的同时达到VFM最大化,从而降低政府方风险,提高社会效益。在高速公路PPP项目中,政府应优化股权决策,激励项目公司改善项目质量和水平,为公私双方带来良好的绩效水平。     

Mechanical and electrical response variation of the polyurethane–tin oxide–carbon nanotube composite microfiber depending on the chemical solution

Toward the goal of smart sensor systems for wearable electronics, polymer microfiber‐based free‐standing sensors benefit from excellent flexibility, decent ductility, and easy wearability in comparison with thin‐film‐based sensing devices. Herein, we report a hydrophobic and conducting single‐strand microfiber‐based liquid‐phase chemical sensor consisting of polyurethane (PU), tin oxide (SnO₂), and carbon nanotube (CNT) composites with applying a (1H,1H,2H,2H‐heptadecafluorodec‐1‐yl) phosphonic acid (HDF‐PA)‐based self‐assembled monolayer. The free‐standing HDF‐PA‐treated PU–SnO₂–CNT composite microfiber showing selective filtering properties with the repellency of water and the penetration of an organic solvent is electrically and mechanically characterized. Finally, the single‐strand HDF‐PA‐treated PU–SnO₂–CNT composite microfiber‐based chemical sensor, which shows excellent mechanical properties and aqueous stability, is demonstrated to detect the presence of a chemical in pure water or counterfeit gasoline in pure gasoline by observing mechanical changes, especially variations in the length and diameter of the fiber, and monitoring the electrical resistance change. © 2018 Wiley Periodicals, Inc. J. Polym. Sci., Part A: Polym. Chem. 2019 , 57, 495–502     

Stochastic modeling of quality of systems operating in a heterogeneous environment

We consider systems that are subject to an external mixed Poisson shock process. Each shock can result in a failure of a system with a given probability and is survived with the complementary probability. Each shock additionally decreases the quality function that describes the performance of a system, thus forming the corresponding stochastic process. Expectations (unconditional and conditional on survival) and relevant variability characteristics for the stochastic quality function are derived. Some monotonicity properties of the conditional quality function are investigated and the future values of this function are derived.     

非正态变异下的非线性轮廓异常点识别方法研究

在质量控制领域,非线性轮廓异常点识别问题是重点研究问题之一。本文综合运用了小波分析、数据深度、聚类分析等数据分析处理技术,提出了一种新的非正态变异的异常点识别方法。文章通过仿真分析技术,将新方法χ²与控制图方法进行性能对比,结果证实新方法能够以更高的准确率和稳定性识别异常点,表现出更好的异常点识别性能。最后将新方法应用于木板垂直密度轮廓实例对新方法进行验证,分析结果表明本方法能够有效识别出异常轮廓数据。     

Melting thermodynamics of oligonucleic acids conjugated with relatively solvophobic linear polymers: A coarse‐grained molecular simulation study

Oligonucleic acids (ONAs), such as DNA and RNA, are used in various biotechnology and nanotechnology applications due to their ability to form a double helix that is stable at low temperature and melts at high temperatures. The melting temperature (T_m) of ONA duplexes can be tuned by the ONA composition, sequence, length and concentration, solvent quality, and salt concentration and by conjugation to other macromolecules. In this article, we use coarse‐grained (CG) molecular simulations to study ONAs conjugated with linear homopolymers that are relatively more solvophobic than the ONA. We study charged and stiff 8‐mer ONAs (e.g., DNA) and neutral and flexible 8‐mer ONAs (e.g., peptide nucleic acids or PNA), and vary the composition (or G‐C content) and sequence of ONA, conjugated homopolymer lengths and solvent quality for the polymer. For neutral and flexible ONAs, as the solvent quality worsens for the polymer, the ONA melting temperature increases from that of unconjugated ONA. The melting curves broaden with polymer length and worsening solvent quality, especially for ONAs with higher G‐C content. For charged and stiff ONAs, as the solvent quality worsens, the ONA melting temperature decreases compared to unconjugated ONA while the width of the melting curve remains the same. © 2019 Wiley Periodicals, Inc. J. Polym. Sci., Part B: Polym. Phys. 2019 , 57, 1196–1208     

QUANTIS: Data quality assessment tool by clustering analysis

Automatically generated kinetic networks are ideally validated against a large set of accurate, reproducible, and easy-to-model experimental data. However, although this might seem simple, it proves to be quite challenging. QUANTIS, a publicly available Python package, is specifically developed to evaluate both the precision and accuracy of experimental data and to ensure a uniform, quick processing, and storage strategy that enables automated comparison of developed kinetic models. The precision is investigated with two clustering techniques, PCA and t-SNE, whereas the accuracy is probed with checks for the conservation laws. First, the developed tool processes, evaluates, and stores experimental yield data automatically. All data belonging to a given experiment, both unprocessed and processed, are stored in the form of an HDF5 container. The demonstration of QUANTIS on three different pyrolysis cases showed that it can help in identifying and overcoming instabilities in experimental datasets, reduce mass and molar balance closure discrepancies, and, by evaluating the visualized correlation matrices, increase understanding in the underlying reaction pathways. Inclusion of all experimental data in the HDF5 file makes it possible to automate simulating the experiment with CHEMKIN. Because of the employed InChI string identifiers for molecules, it is possible to automate the comparison experiment/simulation. QUANTIS and the concepts demonstrated therein is a potentially useful tool for data quality assessment, kinetic model validation, and refinement.     

An Intrinsic Photothermal Liquid for Light Detection and Energy Storage

Photothermal materials (PTMs) have been intensively investigated in the fields of photothermal conversion. Superior to solid PTMs, liquid PTMs are leading the trends in satisfying the demands of high flexibility and easy recycling. Successful examples of liquid PTMs are mostly formulated by dispersing solid PTMs in solvents, but suffer from the problems of phase segregation and solvent pollution. In this work, a low-cost formulation is proposed, which involves an oxidative product of ethyl oleate by iodine. It is an intrinsic liquid PTM, preserving the fluidic nature as well as possessing considerable ability for photothermal conversion. In addition to understanding the mechanism of light absorption in the visible and even near infrared windows, two examples are presented to demonstrate the great potential of liquid PTMs in broad areas such as light sensing and energy storage.     

[2]Pseudorotaxane-Based Supramolecular Optical Indicator for the Visual Detection of Cellular Cyanide Excretion

Cyanide is extremely hazardous to living organisms and the environment. Owing to its wide range of applications and high toxicity, the development of functional materials for cyanide detection and sensing is highly desirable. Host–guest complexation between bis(p-phenylene)-34-crown-10 H and N-methylacridinium salt G remarkably decreases the detection limit for cyanide anions compared with that of the guest itself. The [2]pseudorotaxane selectively recognizes the cyanide anion with high optical sensitivity as a result of the nucleophilic addition of the cyanide anion at the 9-position of G . The host–guest complexation is further incorporated into supramolecular materials for the visual detection of cyanide anions, especially the detection of cellular cyanide excretion with a detection limit of 0.6 μm . This supramolecular method provides an extremely distinct strategy for the visual detection of cyanide anions.