A technical review of face mask wearing in preventing respiratory COVID-19 transmission

Since the outbreak of the COVID-19 pandemic, most countries have recommended their citizens to adopt social distance, hand hygiene, and face mask wearing. However, wearing face masks has not been well adopted by many citizens. While the reasons are complex, there is a general perception that the evidence to support face mask wearing is lacking, especially for the general public in a community setting. Face mask wearing can block or filter airborne virus-carrying particles through the working of colloid and interface science. This paper assesses current knowledge behind the design and functioning of face masks by reviewing the selection of materials, mask specifications, relevant laboratory tests, and respiratory virus transmission trials, with an overview of future development of reusable masks for the general public. This review highlights the effectiveness of face mask wearing in the prevention of COVID-19 infection.     

防紫外线伞ATR-OMNI采样器的FTIR分析

本实验使用OMNI采样器，直接对伞面内外进行单反射ATR的分析，快速、简便、不破坏样品，得到分辨率很好的红外图谱，再配合红外谱库的谱图检索，可以分别得到匹配率95％以上的尼龙－6和聚酯型聚氨酯的分析结果。     

Some geometrical aspects of semidefinite linear complementarity problems

This article studies some geometrical aspects of the semidefinite linear complementarity problem (SDLCP), which can be viewed as a generalization of the well-known linear complementarity problem (LCP). SDLCP is a special case of a complementarity problem over a closed convex cone, where the cone considered is the closed convex cone of positive semidefinite matrices. It arises naturally in the unified formulation of a pair of primal-dual semidefinite programming problems. In this article, we introduce the notion of complementary cones in the semidefinite setting using the faces of the cone of positive semidefinite matrices and show that unlike complementary cones induced by an LCP, semidefinite complementary cones need not be closed. However, under R₀-property of the linear transformation, closedness of all the semidefinite complementary cones induced by L is ensured. We also introduce the notion of a principal subtransformation with respect to a face of the cone of positive semidefinite matrices and show that for a self-adjoint linear transformation, strict copositivity is equivalent to strict semimonotonicity of each principal subtransformation. Besides the above, various other solution properties of SDLCP will be interpreted and studied geometrically.     

Good match exploration for thermal infrared face recognition based on YWF-SIFT with multi-scale fusion

Stable local feature detection is a critical prerequisite in the problem of infrared (IR) face recognition. Recently, Scale Invariant Feature Transform (SIFT) is introduced for feature detection in an infrared face frame, which is achieved by applying a simple and effective averaging window with SIFT termed as Y-styled Window Filter (YWF). However, the thermal IR face frame has an intrinsic characteristic such as lack of feature points (keypoints); therefore, the performance of the YWF-SIFT method will be inevitably influenced when it was used for IR face recognition. In this paper, we propose a novel method combining multi-scale fusion with YWF-SIFT to explore more good feature matches. The multi-scale fusion is performed on a thermal IR frame and a corresponding auxiliary visual frame generated from an off-the-shelf low-cost visual camera. The fused image is more informative, and typically contains much more stable features. Besides, the use of YWF-SIFT method enables us to establish feature correspondences more accurately. Quantitative experimental results demonstrate that our algorithm is able to significantly improve the quantity of feature points by approximately 38%. As a result, the performance of YWF-SIFT with multi-scale fusion is enhanced about 12% in infrared human face recognition.     

流体静压型机械密封的三维传热数学模型及端面温度分析

建立了静环倾斜时流体静压型机械密封的三维稳态传热模型,考虑流体黏度随压力、温度的变化,建立了压力、温度的控制方程,采用有限差分法,分析研究了倾斜量、结构参数及操作参数对机械密封温度分布的影响规律.结果表明,端面的最大液膜压力和最高温度随静环倾斜量的增加而增大,倾斜量越大,压黏效应越显著;端面温升受密封的结构参数、操作参数影响明显.静环端面锥角越大,温升越小;流体注入温度越低,温升越大;动环转速越高,温升越大.     

基于小波分解系数的贝叶斯人脸识别方法

本文给出了贝叶斯人脸识别方法中匹配准则的多个近似表达式及一种实用的快速计算方法.在此基础上,利用反对称双正交小波变换的微分算子功能,提出了一种利用两幅人脸图象的小波变换系数差作为模式矢量的贝叶斯人脸识别方法,并利用AR人脸图象库进行了实验.实验结果表明本文方法与基于图象灰度的类似方法相比,识别率提高8%左右.此外本文方法也提供了一条在图象压缩数据域中实现人脸识别的可能途径.     

Quaternionic geometry of matroids

Building on a recent paper [8], here we argue that the combinatorics of matroids are intimately related to the geometry and topology of toric hyperkähler varieties. We show that just like toric varieties occupy a central role in Stanley’s proof for the necessity of McMullen’s conjecture (or g-inequalities) about the classification of face vectors of simplicial polytopes, the topology of toric hyperkähler varieties leads to new restrictions on face vectors of matroid complexes. Namely in this paper we will give two proofs that the injectivity part of the Hard Lefschetz theorem survives for toric hyperkähler varieties. We explain how this implies the g-inequalities for rationally representable matroids. We show how the geometrical intuition in the first proof, coupled with results of Chari [3], leads to a proof of the g-inequalities for general matroid complexes, which is a recent result of Swartz [20]. The geometrical idea in the second proof will show that a pure O-sequence should satisfy the g-inequalities, thus showing that our result is in fact a consequence of a long-standing conjecture of Stanley.     

Dsc Evaluations in F.c.c. Solid Solutions of Short-range-order Kinetics As Influenced by Bound Vacancies

A modified first order kinetic law, which describes the roles of bound and unbound vacancies, is proposed in order to predict defect decay and short-range-order kinetics of quenched binary alloys during linear heating experiments. The model has been applied to differential scanning calorimetry (DSC) curves of Cu–5 at%Zn quenched from different temperatures. Activation energy for migration of solute-vacancy complexes was also assessed from the kinetics of short-range-order using DSC traces. A value of 89.5±0.32 kJ mol^–1 was obtained. The relative contribution of bound and unbound vacancies to the ordering process as influenced by quenching temperature was determined. In conjunction, a parametric study of the initial total defect concentration and effective energy for defect migration was performed in order to envisage their influence on the calculated DSC profiles. This revised version was published online in August 2006 with corrections to the Cover Date.     

A Semi-Supervised Learning Algorithm for Growing Neural Gas in Face Recognition

In many classification applications and face recognition tasks, there exist unlabelled data available for training along with labelled samples. The use of unlabelled data can improve the performance of a classifier. In this paper, a semi-supervised growing neural gas is proposed for learning with such partly labelled datasets in face recognition applications. The classifier is first trained on the labelled data and then gradually unlabelled data is classified and added to the training data. The classifier is retrained; and so on. The proposed iterative algorithm conforms to the EM framework and is demonstrated, on both artificial and real datasets, to significantly boost the classification rate with the use of unlabelled data. The improvement is particularly great when the labelled dataset is small. Comparison with support vector machine classifiers is also given. The algorithm is computationally efficient and easy to implement.