Resources Protection: Towards Replacement of Cotton Fiber with Polyester

L'abstract è presente nell'allegato / the abstract is in the attachmen

Fit evaluation of virtual garment try-on by learning from digital pressure data

Presently, garment fit evaluation mainly focuses on real try-on, and rarely deals with virtual try-on. With the rapid development of E-commerce, there is a profound growth of garment purchases through the internet. In this context, fit evaluation of virtual garment try-on is vital in the clothing industry. In this paper, we propose a Naive Bayes-based model to evaluate garment fit. The inputs of the proposed model are digital clothing pressures of different body parts, generated from a 3D garment CAD software; while the output is the predicted result of garment fit (fit or unfit). To construct and train the proposed model, data on digital clothing pressures and garment real fit was collected for input and output learning data respectively. By learning from these data, our proposed model can predict garment fit rapidly and automatically without any real try-on; therefore, it can be applied to remote garment fit evaluation in the context of e-shopping. Finally, the effectiveness of our proposed method was validated using a set of test samples. Test results showed that digital clothing pressure is a better index than ease allowance to evaluate garment fit, and machine learning-based garment fit evaluation methods have higher prediction accuracies

Applications of Silk in Biomedical and Healthcare Textiles

Global trends are shifting towards environmental friendly materials and manufacturing methods. Therefore, natural fiber applications are gaining traction globally. Silk, a natural protein fiber is one of the textile fibers that have recently received more attention due to the new frontiers brought about by technological advancement that has expanded the use of silk fiber beyond the conventional textile industry. The simple and versatile nature of silk fibroin process-ability has made silk appealing in wide range of applications. Silk is biocompatible, biodegradable, easy to functionalize and has excellent mechanical properties, in addition to optical transparency. This review chapter explores the use of silk in biomedical applications and healthcare textiles. Future trends in silk applications are also highlighted

Protection des ressources : vers le remplacement du coton par du polyester

La demande annuelle de coton augmente en raison de la croissance démographique mondiale et de l’évolution des comportements d’achat des consommateurs. D'autres options de fibres naturelles telles que la laine, le lin et la soie, entre autres, sont produites dans des proportions très maigres. Le polyester (poly (téréphtalate d’éthylène) (PET) présente des qualités qui pourraient répondre à cette préoccupation pour les vêtements. Malheureusement, les consommateurs hésitent à porter des vêtements 100% polyester, principalement en raison d’un confort sensoriel inférieur, du toucher et parfois de leur apparence. Cette étude visait à améliorer le tissu en PET caractéristiques afin de réduire l'écart entre la perception humaine et la performance hydrophile du coton par rapport au PET Pour déterminer la disparité existant entre le coton et les tissus tissés en PET, une étude multisensorielle a été réalisée à l'aide d'un panel de 12 juges formés sur 11 descripteurs sensoriels. Des algorithmes de Monte Carlo, des algorithmes génétiques et la technique de Borda Count (BK) ont été utilisés pour la fusion de rangs .L'analyse en composantes principales (PCA) et la classification hiérarchique par agglomération (AHC) ont été utilisées pour créer des profils sensoriels. Tissus en PET et en coton (p = 0,05). Il a été déduit que l’aspect visuel et esthétique peut être utilisé pour distinguer le PET du tissus de coton. Pour remplacer le coton par du PET via cette approche sensorielle, la modification de la rigidité des tissus en polyester a été judicieusement réalisée à l'aide de NaOH et d'un adoucissant en silicium, avec une pré-oxydation au plasma atmosphérique. Les tissus en PET traités avec NaOH et l’adoucissant en silicone ont été perçus comme étant doux, lisses, moins nets et moins raides par rapport à certains tissus en coton et en PET non traité. Le profilage des tissus indique que les tissus en PET conventionnels peuvent être distingués des tissus en coton conventionnels en utilisant une évaluation à la fois subjective et objective. Il est également avancé que la perception sensorielle humaine sur textile ne peut être directement représentée par des mesures instrumentales. La dernière partie de l’étude compare le potentiel hydrophile et l’efficacité de deux monomères vinyliques: le poly- (éthylène glycol) diacrylate (PEGDA) et le chlorure de [2- (méthacryloyloxy) éthyl] triméthylammonium (METAC) radicalement photo-greffé sur la surface de Tissu en PET. Une étude de surface utilisant la spectroscopie photoélectronique à rayons X (XPS) et la spectroscopie à dispersion d'énergie (EDS) a confirmé le greffage. Les tests d'humidité indiquent que PEGDA et METAC induisent un mouillage complet du PET à des concentrations de 0,1 à 5% (V: V). Les mesures colorimétriques (K/S et CIELAB/CH) et la stabilité de la couleur sur les tissus teints en PET suggèrent que les deux monomères améliorent considérablement l'efficacité de la teinture du PET. Il est suggéré que PEGDA et METAC génèrent des groupes hydrophiles sur le PET; les macroradicaux sont sous la forme de structures vinyliques qui forment des greffes à chaîne courte et démontrent une fonction hydrophile. Les résultats de cette recherche peuvent jouer un rôle directeur pratique dans la conception des tissus, la conception des propriétés sensorielles et contribuer au développement de tissus en polyester de type coton.There is increasing annual demand for cotton due to world population growth and changes in consumers’ purchasing behavior. Other natural fiber options such as wool, linen and silk among others, are produced in very meager proportions. Polyester (poly(ethylene terephthalate) (PET) has qualities that could address this concern for apparel. Unfortunately, consumers are reluctant to wear 100% polyester clothing mainly due to inferior sensory comfort, touch and sometimes appearance. This study sought to improve PET fabric characteristics in order to decrease the gap between human perception and hydrophilic performance of cotton vs. PET. To determine the disparity between cotton and PET woven fabrics, a multisensory study was undertaken using a panel of 12 trained judges against 11 sensory descriptors. Cross-entropy Monte Carlo algorithms, Genetic algorithms, and the Borda Count (BK) technique were used for rank fusion. Principle component analysis (PCA) and agglomerative hierarchical clustering (AHC) were used to create sensory profiles. The descriptor crisp accounted for the highest variability between PET and cotton fabrics (p˂0.05). It was deduced that visual and aesthetics can be used to distinguish between PET and cotton fabrics. To replace cotton with PET via this sensory approach, the modification of stiffness of polyester fabrics was judiciously carried out using NaOH and a silicon softener, with atmospheric air plasma pre-oxidation. PET fabrics treated with NaOH and the silicon softener were perceived soft, smooth, less crisp, and less stiff compared to some cotton and untreated PET fabrics. The profiling of fabrics indicates that conventional PET fabrics can be distinguished from conventional cotton fabrics using both subjective and objective evaluation. It is also argued that textile human sensory perception cannot be directly represented by instrumental measurements. The final part of the study compares the hydrophilic potential and efficacy of two vinyl monomers: Poly-(ethylene glycol) diacrylate (PEGDA) and [2-(methacryloyloxy) ethyl]-trimethylammonium chloride (METAC) radically photo-grafted on the surface of PET fabric. Surface study using X-ray photoelectron spectroscopy (XPS) and Energy Dispersive Spectroscopy (EDS) confirmed the grafting. Moisture tests indicate that PEGDA and METAC induce complete wetting of PET at concentrations 0.1-5% (V:V). Colorimetric measurements (K/S and CIELAB/CH) and colorfastness on dyed PET fabrics suggest that both monomers greatly improve the dyeing efficiency of PET. It is suggested that PEGDA and METAC generate hydrophilic groups on PET; the macroradicals are in a form of vinyl structures which form short chain grafts and demonstrate hydrophilic function. The results of this research can play a practical guiding role in the design of fabrics, sensory property design and contribute to the development of cotton-like polyester fabrics

CLASSIFICATION AND MEASURE OF QUANTITATIVE DIFFERENCE BETWEEN POLYESTER AND COTTON FABRICS BASED ON SENSORY ANALYSIS

In this study we compare cotton and polyester (Polyethylene terephthalate) (PET) sensory attributes, as a precursor for sensory modification of polyester, for cotton replacement. We systematically identify the key sensory attributes that distinguish cotton from polyester fabrics. Rank Aggregation, Principal Component Analysis (PCA), Agglomerative Hierarchical Clustering (AHC), and the measure of distances are used to process elicited dat

Helicobacter pylori among patients with symptoms of gastroduodenal ulcer disease in rural Uganda

Introduction: To meet key millennium development goals, the rural population needs to be reached for health assessment and service delivery. Gastroduodenal ulcer disease is a common ailment affecting the health of people in Uganda. A cross-sectional study was conducted at Bwera Hospital in Kasese district of western Uganda, to establish the prevalence and predisposing factors of Helicobacter pylori among gastroduodenal ulcer disease patients. Methods: A sample of 174 patients with symptoms of gastroduodenal ulcer disease was purposively obtained. Using two laboratory test methods, the prevalence of H. pylori among these patients was determined. A structured questionnaire was administered to participants to establish their demographic background and selected aspects of their lifestyle. Finally, the results obtained by enzyme-linked immunosorbent assay (ELISA) and immunochromatographic rapid test (IRT) were compared. Results: We established the prevalence of H. pylori as 29.9% (52/174) by ELISA and 37.4% (65/174) by IRT. Cigarette smoking, poor sanitation, and lack of formal education were the significant predisposing factors with p-values <0.05. The two tests gave identical results in 87.9% of the patients. Discussion: The prevalence of H. pylori by IRT and ELISA test methods was similar to what has been reported elsewhere in developed countries; but was lower than previously reported in developing countries including Uganda. The previous studies in Uganda were carried out in the urban population and on young children; and some used antibody-detection methods only, therefore leading to different prevalence as a result of difference in study population and methods

Optimization design of cycling clothesâ patterns based on digital clothing pressures

Enormous research has focused on the analysis of garment wear-comfort using clothing pressure; however, optimization of clothing pressure based garment comfort has remained elusive. In this context, we propose a new method to optimize cycling clothes’ patterns based on the difference of static-to-dynamic clothing pressure (DSDCP). Firstly, we mapped 53 measuring points on an upper cycling garment on which we measured garment pressures in both static and dynamic conditions. We then analyzed DSDCP to find the rightful garment patterns to adjust according to the analyzed results. A garment optimization degree (OD) is proposed to carry out a quantitative analysis for garment comfort optimization. Finally, two upper cycling garments were made according to the original patterns and optimized patterns. A comparative analysis through cyclist wear trials of the cycling garments to test the optimization effect was done. Results show that our proposed method improves dynamic wear comfort significantly. Moreover, the optimized upper cycling garment, offers additional improvement of dynamic wear comfort

Construction of a prediction model for body dimensions used in garment pattern making based on anthropometric data learning

Using artificial intelligence to predict body dimensions rather than measuring them physically is a new research direction in apparel industry. If implemented, this technology can reduce costs and improve efficiency. In this paper, we proposed a back propagation artificial neural network (BP-ANN) model to predict pattern making-related body dimensions by inputting few key human body dimensions. In order to construct the proposed model, anthropometric measurements of 120 young females from the northeastern region of China were collected. The data were then used for training and the proposed model. The results showed that the prediction of the developed BP-ANN model is more accurate and stable than that of linear regression (LR) model. As great as the LR model was at pattern making, the BP-ANN model is even better. In the future, the precision of the proposed model can be further improved if the size of the learning data increases. The proposed method can be especially useful in making garment pattern for form-fitting clothing