Characterization of commercial double-walled carbon nanotube material: composition, structure, and heat capacity

A purified commercial double-walled carbon nanotube (DWCNT) sample was investigated by transmission electron microscopy (TEM), thermogravimetry (TG), and Raman spectroscopy. Moreover, the heat capacity of the DWCNT sample was determined by temperature-modulated differential scanning calorimetry in the range of temperature between −50 and 290 °C. The main thermo-oxidation characterized by TG occurred at 474 °C with the loss of 90 wt% of the sample. Thermo-oxidation of the sample was also investigated by high-resolution TG, which indicated that a fraction rich in carbon nanotube represents more than 80 wt% of the material. Other carbonaceous fractions rich in amorphous coating and graphitic particles were identified by the deconvolution procedure applied to the derivative of TG curve. Complementary structural data were provided by TEM and Raman studies. The information obtained allows the optimization of composites based on this nanomaterial with reliable characteristics.     

Evolution and stability of texture during thermomechanical processing of Ti-24Al-11Nb alloy

The evolution of basal texture during thermomechanical processing of Ti-24Al-11Nb alloy has been studied as a function of different processing variables like hot rolling temperature, amount of deformation, cooling conditions etc. The stability of the deformation texture during post-rolling annealing and during theα ₂→β→α ₂ phase transformation cycle was also investigated. Unrestricted rolling of primaryα ₂ to maximum thickness reduction at the lowest rolling temperature has been found to be most favourable for obtaining a good basal texture. Texture of transformed (secondary)α ₂ is generally non basal when the transformation takes place from deformedβ. Rolling texture does not seem to change during annealing leading to recrystallization. Theα ₂→β→α ₂ phase transformation cycle does not change the starting basal texture and a starting non basal texture also does not give rise to basal texture due to this treatment.     

Managing cooperation in e-business systems

E-Business management involves monitoring and controlling all forms of business transactions conducted over the Internet, extranets, and related communications technologies and services. As such, it includes the management of networks, systems, and software applications. E-Business management is beginning to depend increasingly on knowledge of the cooperative aspects of partners in a business chain and the cooperative aspects of stake-holders in e-business operations. The study of cooperation offers many opportunities to apply social network analyses to derive software solutions for the management of e-business. This article provides a methodology and case study that recognises the dimension of cooperation among a multiplicity of organisations, coined “Awareness-based Cooperative Management.” It is aimed towards the design or re-engineering of effective e-business management systems, where the key concept involves the degree of awareness held by e-business stake-holders. Awareness is defined in terms of stake-holder interactions and artefacts used in those interactions such as buyer specifications, requests for proposals, offers, service level agreements, and the like. Since awareness is an indispensable, albeit an inherently vague concept, we cast it and reason about it with the apparatus of fuzzy logic.

Development of a Mortality Prediction Model in Hospitalised SARS-CoV-2 Positive Patients Based on Routine Kidney Biomarkers

Acute kidney injury (AKI) is a prevalent complication in severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) positive inpatients, which is linked to an increased mortality rate compared to patients without AKI. Here we analysed the difference in kidney blood biomarkers in SARS-CoV-2 positive patients with non-fatal or fatal outcome, in order to develop a mortality prediction model for hospitalised SARS-CoV-2 positive patients. A retrospective cohort study including data from suspected SARS-CoV-2 positive patients admitted to a large National Health Service (NHS) Foundation Trust hospital in the Yorkshire and Humber regions, United Kingdom, between 1 March 2020 and 30 August 2020. Hospitalised adult patients (aged ≥ 18 years) with at least one confirmed positive RT-PCR test for SARS-CoV-2 and blood tests of kidney biomarkers within 36 h of the RT-PCR test were included. The main outcome measure was 90-day in-hospital mortality in SARS-CoV-2 infected patients. The logistic regression and random forest (RF) models incorporated six predictors including three routine kidney function tests (sodium, urea; creatinine only in RF), along with age, sex, and ethnicity. The mortality prediction performance of the logistic regression model achieved an area under receiver operating characteristic (AUROC) curve of 0.772 in the test dataset (95% CI: 0.694–0.823), while the RF model attained the AUROC of 0.820 in the same test cohort (95% CI: 0.740–0.870). The resulting validated prediction model is the first to focus on kidney biomarkers specifically on in-hospital mortality over a 90-day period.     

Moisture Sensitive Smart Yarns and Textiles from Self‐Balanced Silk Fiber Muscles

Smart textiles that sense, interact, and adapt to environmental stimuli have provided exciting new opportunities for a variety of applications. However, current advances have largely remained at the research stage due to the high cost, complexity of manufacturing, and uncomfortableness of environment‐sensitive materials. In contrast, natural textile materials are more attractive for smart textiles due to their merits in terms of low cost and comfortability. Here, water fog and humidity‐driven torsional and tensile actuation of thermally set twisted, coiled, plied silk fibers, and weave textiles from these silk fibers are reported. When exposed to water fog, the torsional silk fiber provides a fully reversible torsional stroke of 547° mm^?1. Coiled‐and‐thermoset silk yarns provide a 70% contraction when the relative humidity is changed from 20% to 80%. Such an excellent actuation behavior originates from water absorption‐induced loss of hydrogen bonds within the silk proteins and the associated structural transformation, which are corroborated by atomistic and macroscopic characterization of silk and molecular dynamics simulations. With its large abundance, cost‐effectiveness, and comfortability for wearing, the silk muscles will open up additional possibilities in industrial applications, such as smart textiles and soft robotics.     

聚合物波导电光调制器

尽管直接调制激光二级管控制光波是一种简单是一种简单且重要的调制方式，但光波导结构的调制器将使器件性能得到惊人的改善，本文简略介绍了聚合物波导电光调制器，并给出了制备该器件的聚合物材料及制备过程。     

Investigation of RF sputtered PSG films for MEMS and semiconductor devices

In this work, we report the preparation of phospho-silicate-glass (PSG) films using RF magnetron sputtering process and its application as a sacrificial layer in surface micromachining technology. For this purpose, a 76 mm diameter target of phosphorus-doped silicon dioxide was prepared by conventional solid-state reaction route using P₂O₅ and SiO₂ powders. The PSG films were deposited in a RF (13.56 MHz) magnetron sputtering system at 200-300 W RF power, 10-20 mTorr pressure and 45 mm target-to-substrate spacing without external substrate heating. To confirm the presence of phosphorus in the deposited films, hot-probe test and sheet resistance measurements were performed on silicon wafers following deposition of PSG film and a drive-in step. As a final confirmatory test, a p-n diode was fabricated in a p-type Si wafer using the deposited film as a source of phosphorus diffusion. The phosphorus concentration in the target and the deposited film were analyzed using energy dispersive X-rays (EDAX) tool. The etch rate of the PSG film in buffered HF was measured to be about 30 times higher as compared to that of thermally grown SiO₂ films. The application of RF sputtered PSG film as sacrificial layer in surface micromachining technology has been explored. To demonstrate the compatibility with MEMS process, micro-cantilevers and micro-bridges of silicon nitride were fabricated using RF sputtered PSG as a sacrificial layer in surface micromachining. It is envisaged that the lower deposition temperature in RF sputtering (<150 °C) compared to CVD process for PSG film preparation is advantageous, particularly for making MEMS on temperature sensitive substrates.     

Determination of IgG1 and IgG3 SARS-CoV-2 Spike Protein and Nucleocapsid Binding—Who Is Binding Who and Why?

The involvement of immunoglobulin (Ig) G3 in the humoral immune response to SARS-CoV-2 infection has been implicated in the pathogenesis of acute respiratory distress syndrome (ARDS) in COVID-19. The exact molecular mechanism is unknown, but it is thought to involve this IgG subtype’s differential ability to fix, complement and stimulate cytokine release. We examined the binding of convalescent patient antibodies to immobilized nucleocapsids and spike proteins by matrix-assisted laser desorption/ionization–time of flight (MALDI-ToF) mass spectrometry. IgG3 was a major immunoglobulin found in all samples. Differential analysis of the spectral signatures found for the nucleocapsid versus the spike protein demonstrated that the predominant humoral immune response to the nucleocapsid was IgG3, whilst for the spike protein it was IgG1. However, the spike protein displayed a strong affinity for IgG3 itself, as it would bind from control plasma samples, as well as from those previously infected with SARS-CoV-2, similar to the way protein G binds IgG1. Furthermore, detailed spectral analysis indicated that a mass shift consistent with hyper-glycosylation or glycation was a characteristic of the IgG3 captured by the spike protein.     

Autonomous clustering using rough set theory

This paper proposes a clustering technique that minimizes the need for subjective human intervention and is based on elements of rough set theory （RST）. The proposed algorithm is unified in its approach to clustering and makes use of both local and global data properties to obtain clustering solutions. It handles single-type and mixed attribute data sets with ease. The results from three data sets of single and mixed attribute types are used to illustrate the technique and establish its efficiency.