Study of needle heating in industrial sewing.

With the use of synthetic fabric and thread as well as high speed sewing in sewing industry, needle heating due to friction between the needle and fabric becomes a serious problem. The high temperature in the needle can scorch the fabric as well as accelerate thread wear and damage the thread. It also causes wear at the needle eye, and may temper and weaken the needle itself. It is desirable to develop analytical computer simulation models to study the needle heating problem. In this thesis, three models are developed: a sliding model, a lumped model, and a Finite Element (FE) simulation model. In the sliding model and the lumped model, it is assumed that needle can be modeled as a cylinder and the effect of the thread can be ignored. These simplified analytical models focus on the needle-fabric interactions, especially the friction heat partition between needle and fabric. In the FE model, both the detailed needle geometry characteristics and thread effects are considered. (Abstract shortened by UMI.)Dept. of Industrial and Manufacturing Systems Engineering. Paper copy at Leddy Library: Theses & Major Papers - Basement, West Bldg. / Call Number: Thesis1998 .L5. Source: Masters Abstracts International, Volume: 39-02, page: 0576. Adviser: R. Du. Thesis (M.A.Sc.)--University of Windsor (Canada), 1998

A 2-Cys Peroxiredoxin in Response to Oxidative Stress in the Pine Wood Nematode, \u3cem\u3eBursaphelenchus xylophilus\u3c/em\u3e

The pine wood nematode, Bursaphelenchus xylophilus, is the causal agent of pine wilt disease that has devastated pine forests in Asia. Parasitic nematodes are known to have evolved antioxidant stress responses that defend against host plant defenses. In this study, the infestation of whitebark pine, Pinus bungean, with B. xylophilus led to a significant increase in plant hydrogen peroxide (H2O2) and salicylic acid levels. Correspondingly, the expression of an antioxidative enzyme, 2-Cysteine peroxiredoxin (BxPrx), was elevated in B. xylophilus following the H2O2 treatments. Recombinant BxPrx, a thermal stabile and pH tolerant enzyme, exhibited high level of antioxidant activity against H2O2, suggesting that it is capable of protecting cells from free radical attacks. Immunohistochemical localization study showed that BxPrx was broadly expressed across different tissues and could be secreted outside the nematode. Finally, the number of BxPrx homologs in both dauer-like and fungi-feeding B. xylophilus were comparable based on bioinformatics analysis of existing EST libraries, indicating a potential role of BxPrx in both propagative and dispersal nematodes. These combined results suggest that BxPrx is a key genetic factor facilitating the infestation and distribution of B. xylophilus within pine hosts, and consequently the spread of pine wilt disease

Universal approach to deterministic spatial search via alternating quantum walks

Spatial search is an important problem in quantum computation, which aims to find a marked vertex on a graph. We propose a novel and universal approach for designing deterministic quantum search algorithms on a variety of graphs via alternating quantum walks. The approach divides the search space into a series of subspaces and performs deterministic quantum searching on these subspaces. We highlight the flexibility of our approach by proving that for Johnson graphs, rook graphs, complete-square graphs and complete bipartite graphs, our quantum algorithms can find the marked vertex with $100\%$ success probability and achieve quadratic speedups over classical algorithms. This not only gives an alternative succinct way to prove the existing results, but also leads to new findings on more general graphs.Comment: The introduction has been revise

Reference Gene Selection for Transcriptional Profiling in \u3cem\u3eCryptocercus punctulatus\u3c/em\u3e, an Evolutionary Link between Isoptera and Blattodea

The subsocial life style and wood-feeding capability of Cryptocercus gives us an evolutionary key to unlock some outstanding questions in biology. With the advent of the Genomics Era, there is an unprecedented opportunity to address the evolution of eusociality and the acquisition of lignocellulases at the genetic level. However, to quantify gene expression, an appropriate normalization strategy is warranted to control for the non-specific variations among samples across different experimental conditions. To search for the internal references, 10 housekeeping genes from a gut transcriptome of a wood-feeding cockroach, Cryptocercus punctulatus, were selected as the candidates for the RT-qPCR analysis. The expression profiles of these candidates, including ACT, EF1α, GAPDH, HSP60, HSP70, αTUB, UBC, RPS18, ATPase and GST, were analyzed using a panel of analytical tools, including geNorm, NormFinder, BestKeeper, and comparative ΔCT method. RefFinder, a comprehensive ranking system integrating all four above-mentioned algorithms, rated ACT as the most stable reference gene for different developmental stages and tissues. Expression analysis of the target genes, Hex-1 and Cell-1, using the most or the least appropriate reference genes and a single or multiple normalizers signified this research. Our finding is the first step toward establishing a standardized RT-qPCR analysis in Cryptocercus

Parameter identification of the interaction body model using available measurements

This paper determines the parameters of the interaction models based on available published experimental measurements. The masses, damping ratios and stiffnesses of body models are identified by the curve fitting of the measured apparent mass curves from shaking table tests in published biomechanics studies. Then the extracted data are used to identify the parameters of the interaction models. Finally, the eigenvalue analyses of the human-structure models are calculated for comparison. In this identification process, it was identified that the quality of the curve fitting for the interaction model is as good as and even slightly better than the published results. One or two additional conditions for the interaction models would lead to several sets of parameters, but with the result of the continuous model, reasonable parameters have to be applied which can be identified and these parameters could be used in further calculations

Bio-inspired Design and Fabrication of Super-Strong and Multifunctional Carbon Nanotube Composites

Carbon nanotubes (CNTs) are ideal scaffolds to design and architect high-performance composites at high CNT volume fractions. In these composites, the CNT alignment determines the level of aggregation and the structure morphology, and thus the load transfer efficiency between neighboring CNTs. Here, we discuss two major solutions to produce high-volume fraction CNT composites, namely the layer-by-layer stacking of aligned CNT sheets and the stretching of entangled CNT webs (networks). As inspired by the growth procedure of natural composites, the aggregation of CNTs can be well controlled during the assembling process. As a result, the CNTs can be highly packed, aligned, and importantly unaggregated, with the impregnated polymers acting as interfacial adhesion or mortars to build up the composite structure. The CNT/bismaleimide composites can yield a super-high tensile strength up to 6.27–6.94 GPa and a modulus up to 315 GPa

Graph Contrastive Learning with Multi-Objective for Personalized Product Retrieval in Taobao Search

In e-commerce search, personalized retrieval is a crucial technique for improving user shopping experience. Recent works in this domain have achieved significant improvements by the representation learning paradigm, e.g., embedding-based retrieval (EBR) and collaborative filtering (CF). EBR methods do not sufficiently exploit the useful collaborative signal and are difficult to learn the representations of long-tail item well. Graph-based CF methods improve personalization by modeling collaborative signal within the user click graph. However, existing Graph-based methods ignore user's multiple behaviours, such as click/purchase and the relevance constraint between user behaviours and items.In this paper, we propose a Graph Contrastive Learning with Multi-Objective (GCL-MO) collaborative filtering model, which solves the problems of weak relevance and incomplete personalization in e-commerce search. Specifically, GCL-MO builds a homogeneous graph of items and then optimizes a multi-objective function of personalization and relevance. Moreover, we propose a modified contrastive loss for multi-objectives graph learning, which avoids the mutual suppression among positive samples and thus improves the generalization and robustness of long-tail item representations. These learned item embeddings are then used for personalized retrieval by constructing an efficient offline-to-online inverted table. GCL-MO outperforms the online collaborative filtering baseline in both offline/online experimental metrics and shows a significant improvement in the online A/B testing of Taobao search

Application of Electric Automation Technology in the Wastewater Treatment Process

With the rapid development of our economy, industrialization and urbanization, the production and life of the people create a lot of wastewater, and how to treat it has become the focus of public attention. Compared with conventional methods, the application of electrical automation technology in wastewater treatment has the characteristics of convenience and high efficiency, and its role in wastewater treatment cannot be ignored. In this paper, the problems in wastewater treatment are analyzed and discussed for reference