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The paper aims to use the Trilobal® polyester (Y cross-section) for producing fabrics suitable for fencing suits and evaluating their various properties.

Double weave structure was chosen to produce the samples by using six different face structures and two back structures divided into two groups according to the back structures. They were evaluated by their physical and mechanical properties such as tensile strength, puncture resistance, air permeability and humidity properties in horizontal and vertical wicking, drying rate and water vapor transmission.

Fencing sport recently is one of the most growing sports in the world, which necessitates special requirements and properties of fencing suit, either mechanical properties, which allow the easily and freely movement for the athlete, or the comfort properties that save the player’s effort and energy for a long time to improve his performance.

ANOVA test analysis showed highly significant results in some properties comparing back and face structures of the double weave fabric high correlation coefficient were found between packing density factor of produced fabric and the weft material types. The final results showed the produced sample that weaved with plain 1/1 for back structure and warp rib 2/2 for face structure achieved the best results, followed by the produced sample weaved with plain 1/1 for back structure and weft rib 2/2 for face structure compared with the other produced samples.

Mechanical properties of 100% polyester and polyester-viscose (P/V) blended yarns produced from polyester fibres which vary in denier and cross-sectional shape have been analyzed. It is observed that fibre fineness and cross-sectional shape play a significant role in the translation of fibre properties to the respective yarn properties. As the fibre linear density decreases, fibre strength translation efficiency increases. In the case of trilobal fibre, translation efficiency is observed to be lower, but yarn breaking elongation is higher in comparison to the corresponding circular fibre. Scalloped oval fibre contributes more towards yarn strength and elongation versus the equivalent circular and tetraskelion fibres. In the P/V blended form, a decrease in yarn tenacity does not affect fibre fineness, but is substantially influenced by changes in the fibre profile. Contribution of broken viscose fibres (comparatively weaker component) at the point of actual breaking of yarn, i.e. Z-value, is altered depending on the polyester fibre profile, which is higher in trilobal and scalloped oval fibres in comparison to the corresponding circular ones, but the role of fibre linear density in this regard is rendered insignificant.

The purpose of this paper is to show how shape analysis and quantitative characterization of fiber cross sections, with the aid of image analysis techniques, provide a quick, powerful approach to automated profiled fiber identification.

In this paper, an effective method of cross‐sectional shape characterization for profiled fiber identification is reported with extraction of the distance fluctuation curve of fiber cross‐sectional boundary to the centroid. By calculating their cross‐correlations using signal processing techniques, the authors tackle the problem of calibrating the starting points of fiber objects orientated arbitrarily in image successfully, which are difficult to deal with by means of image processing, to finish the normalization of distance fluctuation curves. For two fiber cross‐sections, the similarity degree of their boundary fluctuation curves normalized can effectively reflect the similarity degree of themselves.

Based on this, the method presented extracts the curves of all fiber cross‐sections in one sample, compares the similarity degrees between each other, and creates clusters to identify profiled fiber.

Experimental results validate that this curve can effectively characterize profiled fiber cross‐sectional contour for profiled fiber identification and the normalization method is feasible.

Firefighter Personal Protective Equipment (PPE) is the only barrier between the firefighter and hazardous environment. Gloves are a crucial component of the multi-component PPE. Over time the gloves have reduced the intensity of hand injuries, yet further improvement in terms of material selection and glove design is required to strike the balance between protection and comfort. Focusing on the material aspect, the purpose of this study is to present literature analysis on material selection and testing for firefighter gloves.

The study conducted a literature analysis on material selection and characterization of firefighter PPE. The review summarizes and evaluates past work addressing the characterization of firefighter gloves in accordance with NFPA 1971 requirements and points out found research gaps to aid with foundation of future research.

The study summarizes several research works to inform readers about the material selection and characterization of firefighter gloves. Based on the analyzed literature, the study resulted in material specification sheets for firefighter gloves. The developed material specification sheets provide information in terms of crucial material properties to be incorporated for accurate functioning of firefighter gloves, testing methods to validate those material properties and materials from analyzed literature exhibiting desired properties.

With large research addressing firefighter PPE, only limited studies focus specifically on gloves. Thus, this study provides a literature analysis covering material selection and testing for gloves. A consolidated firefighter gloves material specification document, which does not appear to be available in the literature, will provide a foundation for the development and characterization of firefighter gloves to better serve the functions along with ensuring user comfort.

The textile industry holds immense significance in the economy of any nation, particularly in the production of synthetic yarn and fabrics. Consequently, the pursuit of acquiring high-quality products at a reduced cost has become a significant concern for countries. The primary objective of this research is to leverage data mining and data intelligence techniques to enhance and refine the production process of texturized yarn by developing an intelligent operating guide that enables the adjustment of production process parameters in the texturized yarn manufacturing process, based on the specifications of raw materials.

This research undertook a systematic literature review to explore the various factors that influence yarn quality. Data mining techniques, including deep learning, K-nearest neighbor (KNN), decision tree, Naïve Bayes, support vector machine and VOTE, were employed to identify the most crucial factors. Subsequently, an executive and dynamic guide was developed utilizing data intelligence tools such as Power BI (Business Intelligence). The proposed model was then applied to the production process of a textile company in Iran 2020 to 2021.

The results of this research highlight that the production process parameters exert a more significant influence on texturized yarn quality than the characteristics of raw materials. The executive production guide was designed by selecting the optimal combination of production process parameters, namely draw ratio, D/Y and primary temperature, with the incorporation of limiting indexes derived from the raw material characteristics to predict tenacity and elongation.

This paper contributes by introducing a novel method for creating a dynamic guide. An intelligent and dynamic guide for tenacity and elongation in texturized yarn production was proposed, boasting an approximate accuracy rate of 80%. This developed guide is dynamic and seamlessly integrated with the production database. It undergoes regular updates every three months, incorporating the selected features of the process and raw materials, their respective thresholds, and the predicted levels of elongation and tenacity.

Perspiration and heat are produced by the body and must be eliminated to maintain a stable body temperature. Sweat, heat and air must pass through the fabric to be comfortable. The cloth absorbs sweat and then releases it, allowing the body to chill down. By capillary action, moisture is driven away from fabric pores or sucked out of yarns. Convectional air movement improves sweat drainage, which may aid in body temperature reduction. Clothing reduces the skin's ability to transport heat and moisture to the outside. Excessive moisture makes clothing stick to the skin, whereas excessive heat induces heat stress, making the user uncomfortable. Wet heat loss is significantly more difficult to understand than dry heat loss. The purpose of this study is to provided a good compilation of complete information on wet thermal comfort of textile and technological elements to be consider while constructing protective apparel.

This paper aims to critically review studies on the thermal comfort of textiles in wet conditions and assess the results to guide future research.

Several recent studies focused on wet textiles' impact on comfort. Moisture reduces the fabric's thermal insulation value while also altering its moisture characteristics. Moisture and heat conductivity were linked. Sweat and other factors impact fabric comfort. So, while evaluating a fabric's comfort, consider both external and inside moisture.

The systematic literature review in this research focuses on wet thermal comfort and technological elements to consider while constructing protective apparel.