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One of the greatest challenges of multi-stakeholder partnerships lies in forging a shared understanding and obtaining and sustaining commitment among parties representing different interests and goals. While studies have emphasized the importance of developing shared frames for enabling collaboration and collective action through frame alignment, scant attention has been paid to how stakeholder representatives can attain commitment from their constituents "back home" to frames negotiated on their behalf. Our longitudinal process study explores how participants in the German Partnership for Sustainable Textiles successfully confronted the challenge of aligning frames across multiple interaction arenas, highlighting how failing to tackle this "two-table problem" can risk partnership collapse. Our process model captures how back-and-forth interactions enabled the stretching of shared frames across interaction arenas, thereby propelling the partnership from near collapse to deepened commitments. While stretching frames heightens the risk of frame break, our analysis shows how such iterative ongoing efforts are essential for deepening commitments and advancing collaboration. We thus contribute to framing theory by highlighting how frame alignment can be achieved across multiple interaction arenas by "collaborating on the edge of failure." We further contribute to scholarship on multiparty collaboration by unpacking the multi-table negotiation dynamics that help explain collaborative outcomes. [ABSTRACT FROM AUTHOR]

This article contributes to explaining the rise of labor unrest in Egypt in the early 2000s, led initially by public-sector workers. Using two case studies in textile and transport, the author shows that perceptions of sector potential affected workers' ability to protest and compensated for the decline in their sectors' roles in the economy. The perceptions of underutilization due to corruption and to sector viability based on squandered profits help explain workers' militancy and capacities to mount an extended protest campaign. These perceptions build on discourses that critique the state's adoption of neoliberal policies associated with privatization. Workers could develop these perceptions because their sectors still played a role in the economy despite their decline. The analysis contributes to the Power Resource Approach by showing how perceptions of sector potential enhance capacities among Global South workers in declining sectors. To explain labor unrest, the author engages labor scholarship on Egypt that focuses on grievances rather than on workers' economic position and sources of power. [ABSTRACT FROM AUTHOR]

This study offers design of the 'socially optimal' rebate and tax structures, corresponding to the maximum expected gain and minimum risk from migration of prospective risk-averse suppliers towards supplying sustainable products. Risk-averse behaviour is caused by small and medium-sized suppliers who are financially constrained from the perspective of a textile company. This study addresses the unexplored but serious issue of suppliers' willingness-to-pay for renouncing the option of migrating towards sustainable practices under uncertain market conditions for sustainable products, by using a mean-variance utility framework. The analytical model is validated using case-based real data collected from an Indian retailer who works with two types of suppliers in India: one natural fibre supplier and another chemical-based synthetic fibre supplier. Our model helps explain the effects of loss in expected market share and sudden increase in variability in market share for sustainable products respectively on the 'socially optimal' rate of tax and rebate. Also, we establish that with rate of tax increases, the 'socially optimal' rate of rebate on sustainable product must increase at an increasing rate to induce potential migration of suppliers towards sustainable practices. The implications of our findings on academics and practice are offered. [ABSTRACT FROM AUTHOR]

The main goal of this study is to improve the effectiveness of customer prediction in order to benefit businesses. To achieve this objective, the research focuses on addressing two main challenges. Firstly, it solves the issue of clustering large business datasets. For this purpose, it introduces a novel approach called hybrid K-means++ with EM clustering. This method aims to better organize the data points into distinct clusters, enhancing the understanding of customer behaviour patterns. Secondly, the research aims to enhance the efficiency of training models for customer prediction, particularly when dealing with big data. It achieves this by employing Dynamic Adjustable Momentum Backpropagation (DAMB) within Deep Belief Networks (DBN). By utilizing DAMB, the research optimizes the training process, resulting in more accurate prediction models. In addition to these primary objectives, the study also contributes by developing and utilizing two custom datasets: the South India Visual Merchandising Survey (SIVMS) and the Global Visual Merchandising and Customer Behaviour Survey (GVMCBS). These datasets provide a broader perspective on customer behaviour in visual merchandising settings, including diverse demographics and geographical regions. To assess the effectiveness of the proposed methods, the research conducts thorough analyses in three key areas: clustering efficiency, training efficiency, and computational efficiency. The proposed method demonstrates superior clustering results compared to traditional K-means and K-means++ algorithms when applied to the SIVMS and GVMCBS datasets. Specifically, it resulted in less overlap between customer groups and greater separation between the centers of those groups. Additionally, the proposed method offers slightly improved testing efficiency. In comparison to standard Backpropagation (BP) models and DBN variants (Deep Belief Networks-Backpropagation (DBN-BP), Deep Belief Networks-Backpropagation-Adaptive Learning Rates (DBN-BP-ALR), Deep Belief Networks-Resilient Backpropagation (DBN-RBP), Deep Belief Networks-Levenberg-Marquardt Algorithm (DBN-LMA), and Deep Belief Networks-Conjugate Gradient (DBN-CG)), the proposed Deep Belief Networks-Dynamic Adjustable Momentum Backpropagation (DBN-DAMB) model yields the most favourable results. The proposed DBN-DAMB model also has the lowest computational demands, with 1.8 million parameters and 2.5 x 109) Floating-Point Operations Per Second (FLOPs). These results show that the system can accurately predict customer behavior and is efficient in terms of computation. [ABSTRACT FROM AUTHOR]

Purpose: Wool fiber is accepted as one of the natural and renewable sources and has been used in the apparel and textile industry since ancient times. However, wool fiber has the highest global warming potential value among conventional fibres due to its high land use and high methane gas generation. This study aimed to recycle the wool fabric wastes and also to create a mini eco-collection by using the produced yarns. Design/methodology/approach: This manuscript aimed to evaluate the fabric wastes of a woolen fabric producer company. Fabric wastes were opened with two different opening systems and fiber properties were determined. First, conventional ring yarns were produced in the company's own spinning mill by mixing the opened fibres with the long fiber wastes of the company. In addition, opening wastes were mixed with different fibres (polyester, long wool waste, and Tencel fibres) between 25% and 70% in the short-staple yarn spinning mill and used in the production of conventional ring and OE-rotor yarns. Most of the yarns contained waste fibres at 50%. Recycled and virgin yarns were used as a weft and warp yarn and a total of 270 woven fabric samples were obtained and fabric properties were examined. Also, a fabric collection was created. A life cycle assessment (LCA) was made for one of the selected yarns. Findings: At the end of the study, it was determined that it was possible to produce yarn and fabric samples from fiber blends containing high waste fiber ratios beyond 50%. All the woven fabric samples produced from conventional ring and OE-rotor yarns gave higher breaking, tearing and stitch slip strength values in the weft and warp direction than limit quality values of the company. In addition, abrasion resistance and WIRA steam stability properties of the fabric samples were also sufficient. Environmental analysis of the recycling of the wastes showed a possible decrease of about 9940034.3 kg CO2e per year in the global warming potential. In addition, fiber raw material expenses reduced yarn production cost about 50% in case of opened fabric waste usage. However, due to insufficient pilling resistance results, it was decided to evaluate the woven fabrics for the product groups such as shawls and blankets, where pilling resistance is less sought. Originality/value: The original aspects of the article can be summarized under two headings. First, there are limited studies on the evaluation of wool wastes compared to cotton and polyester fibres and the number of samples examined was limited. However, this study was quite comprehensive in terms of opening type (rag and tearing), spinning systems (long and short spinning processes), fiber blends (waste 100% and blends with polyester, long wool waste and Tencel fibres) and yarn counts (coarser and finer). Recycled and virgin yarns were used as a weft and warp yarn and a total of 270 woven fabric samples were obtained using different colour combinations and weave types. All processes from fabric waste to product production were followed and evaluated. Life cycle assessment (LCA) and cost analysis was also done. The second unique aspect is that the problem of a real wool company was handled by taking the waste of the woolen company and a collection was created for the customer group of the company. Production was made under real production conditions. Therefore, this study will provide important findings to the research field about recycling, sustainability etc. [ABSTRACT FROM AUTHOR]

Purpose: This study aimed to analyze the role of organizational learning capability and entrepreneurial orientation on frugal innovation and, consequently, operational performance within the Brazilian textile industry. Design/methodology/approach: The sample consisted of 257 valid questionnaires from the textile industry in the state of Santa Catarina, Brazil. Data were analyzed using structural equation modeling using SmartPLS software. Findings: The results showed that organizational learning capability is a strong driver of the operational performance when mediated by frugal innovation. Evidence also showed that relationships between entrepreneurial orientation, organizational learning capability, frugal innovation and operational performance are significant once the direct effect has more power than the indirect effect. Results elucidated different outcomes that are not in accordance with previously seen studies. Moreover, the latter shines a light on a possible interference caused by the COVID-19 pandemic. Originality/value: The study clarifies the relationship that entrepreneurial orientation and organizational learning capability unleash in frugal innovation and operational performance. It also shows a new situation when looking at the relationship between entrepreneurial orientation, organizational learning capability and operational performance. [ABSTRACT FROM AUTHOR]

Given recent breakdowns in global value chains, like the COVID-19 crisis or the conflict in Ukraine, developed economies are trying to develop resilience to address future drawbacks. Backshoring and nearshoring arise as attractive solutions to reduce exposure to global disruptions and undesirable practices such as forced labour. This study analyses the labour impacts of a hypothetical EU-driven reconfiguration of value chains of the fashion industry through a multi-regional input-output model. Using the Structural Path Analysis methodology, how forced labour is transmitted within Europe is explored. Once the forced labour hotspots are determined, we explore the socioeconomic consequences of a trade-restructuring strategy simulated through the source-shifting technique. Our results show that the forced labour embodied in the European final demand for fashion products could fall by up to 34.2%. This strategy could generate more than 190,000 jobs in Europe, while China and India could lose more than 1.5 million jobs each. [ABSTRACT FROM AUTHOR]

There is broad consensus in academia and practice that organizational resilience is a critical factor for organizations to cope with crises. However, despite considerable theoretical progress, empirical knowledge on the dynamics of organizational resilience remains limited. To explore facilitators and consequences of organizational resilience with a holistic approach, we report results of a mixed-methods multi-study throughout an ongoing crisis within the Pakistani textile industry. Qualitative findings indicate a broad set of organizational resilience facilitators, differentiated in respect to their content and temporal properties. Quantitative findings from longitudinal survey data suggest the pivotal importance of "soft" facilitators related to employee focus and learning orientation. In terms of consequences, results show that organizational resilience can reduce emotional exhaustion and contribute to business success. Overall, the findings are consistent with an integral understanding of organizational resilience as a meta-capability, building on a set of facilitators occurring at different time points throughout a crisis. [ABSTRACT FROM AUTHOR]

This research examines the impact of the Regional Comprehensive Economic Partnership (RCEP) on the textile and apparel industry within its member nations. The study seeks to understand the implications of RCEP on trade dynamics, innovation chains, and industrial integration in the textile sector. The study uses both quantitative analysis of trade data and qualitative assessment of policy frameworks to analyze changes in textile trade and patterns among RCEP members through UN Comtrade data. Qualitative analysis is conducted to examine RCEP policies related to intellectual property protection, investment regulations, and innovation cooperation. The findings reveal a significant increase in textile trade volume among RCEP member countries following the agreement's implementation. China emerges as a key player, experiencing substantial growth in textile exports to RCEP nations, particularly driven by tariff reduction initiatives. RCEP provisions stimulate demand for innovation within the textile industry, fostering collaborative efforts in scientific research and development. [ABSTRACT FROM AUTHOR]

Ammonia plays a pivotal role globally, profoundly impacting human activities, especially in agriculture, chemical production, and the textile sector. As the most efficient carbon‐free hydrogen carrier, ammonia is vital for transporting energy over long distances. Haber‐Bosch process producing ammonia from nitrogen accounts for ≈2% of global energy production. Electrochemical conversion offers a sustainable, long‐term solution for ammonia synthesis due to its environmentally friendly characteristics. This approach complements the traditional Haber‐Bosch process, known for its harsh operational conditions and significant CO2 emissions. Iron (Fe), serving as the active catalytic site in the Haber‐Bosch process and a vital nitrogenase component for biological nitrogen fixation, exhibits superiority over other non‐noble metals in catalyzing ammonia synthesis. Therefore, investigating single‐atom Fe is attracting significant attention for its potential application in electrochemical ammonia synthesis. In this review, the recent advancements in the design and synthesis of single‐atom Fe‐based catalysts for electrochemical ammonia production are summarized. The topic of synthesis and characterization of Fe single‐atom catalysts, as well as their application in the electrochemical reduction of nitrogen and nitrate to ammonia is covered. Additionally, insights are provided into the current challenges and considerations for future directions aimed at designing efficiently Fe single atom‐based catalysts. [ABSTRACT FROM AUTHOR]

Fabric Defect (FD) detection has played an important role in the process of fabric production. FDs lead to a reduction in cloth prices, causing a significant loss of 45% to 65% for the cloth manufacturer. The detection of FDs becomes a challenging task in the fabric industry due to its complicated shapes and a considerable amount of FDs. Thus, a new detection technique, which has great detection speed and accuracy, is desired to replace manual work. With the emergence of Convolution Neural Networks (CNN) and the development of machine vision and Deep Learning (DL), various detection techniques, combining the benefits of DL and machine vision, have emerged, which replace manual and image processing approaches. The study presents an Automated Fabric Defect Detection using a Hybrid Particle Cat Swarm Optimizer with a Deep Learning (AFDD-HPCSODL) algorithm. AFDD-HPCSODL method aims to detect and categorize the existence of defects in fabric production. The objective is to automate and improve the performance of fabric defect detection, addressing the complexity of different defect patterns and characteristics in textile images. In the presented AFDD-HPCSODL technique, two stages of data pre-processing take place namely contrast enhancement and bilateral filtering (BF)-based noise elimination. Besides, a fusion of feature extraction processes is carried out using Inception V3 and EfficientNetB3. Moreover, the Attention Convolutional Long Short-Term Memory (ACLSTM) network is exploited for the detection and classification of FDs. Furthermore, the HPCSO technique carries out the hyperparameter selection of the ACLSTM model. Finally, the Root Mean Square Propagation (RMSProp) optimizer with the NestNet model is utilized for the defect segmentation process. The stimulation validation of the AFDD-HPCSODL method is studied on the two FD datasets. Widespread comparative results emphasized the improved performance of the AFDD-HPCSODL technique on FD classification with maximum accuracy of 97.92% and 98.89% on the Kaggle FD dataset and the ZJU-Leaper dataset, correspondingly. [ABSTRACT FROM AUTHOR]

This study aimed to illustrate the impact of green human resources management on circular economy performance; the mediator role of green innovation; and the moderator roles of big data analytics and data-driven culture. A total of 438 survey questionnaires were collected from small and medium-sized enterprises from the Pakistani textile sector and evaluated through partial least square-structural equation modelling. The study's outcomes revealed that green human resources management significantly impacts circular economy performance. Similarly, green innovation and big data analytics mediated and moderated between green human resources management and circular economy performance. Nevertheless, data-driven culture is needed to moderate between green human resources management and circular economy performance. The study presented a unique and novel idea of green human resources management concerning circular economy performance – the best solution for sustainable environmental fortification in the current decade while enhancing circular economy performance. [ABSTRACT FROM AUTHOR]

The textile industry contributes significantly to the expansion of the world economy, however, it is also notorious for producing large amounts of trash and harming the environment. Effective waste management techniques depend on having a thorough understanding of the forms and makeup of waste from the textile sector. The objective of this paper is to study effluent wastewater technologies to efficiently treat and control the wastewater produced during textile production operations. It is well known that the textile industry generates vast amounts of wastewater, some of which may be contaminated with heavy metals, chemicals, dyes, and organic compounds. This effluent can have serious negative effects on the environment if it is not adequately treated, including contaminating soil and water sources, removing aquatic life, and possibly endangering human health. Due to the inclusion of dyes, heavy metals, and other chemicals, the discharge of untreated or improperly treated effluent from textile processes leads to water contamination. Textile waste can leak hazardous compounds into the environment and contaminate the soil, both of which have an impact on air quality. The environmental impact of the textile industry is further exacerbated by the energy and resource use involved in production. At several points in the textile supply chain, waste is generated. Fibre trimmings, fly waste, and yarn waste are produced during the fibre production, spinning, and weaving operations. There are numerous ways and technologies for treating wastewater, including advanced oxidation processes (AOPs), biological treatment systems, and membrane-based technologies. The formation of eco-friendly materials and advancements in recycling technology help to make the textile industry more closed-loop and sustainable. In conclusion, managing waste from the textile sector is a significant environmental concern that calls for creative solutions and environmentally friendly procedures. [ABSTRACT FROM AUTHOR]

This paper studies the knowledge spillover effect through industrial correlation in the process of interregional textile industry transfer and its effects on the TFP of China's textile industry. The paper calculates the industrial similarity coefficients of subdivided industries with the textile industry and identifies the related industries of China's textile industry by using the data of China's input-output table and extension tables from 2002 to 2017. Then, the paper defines the industrial correlation spillover as the weighted sum of the indirect R&D investment of one industry from its related industries and constructs a quantitative method to qualify the industrial correlation spillover. Furthermore, the paper makes two empirical analyses on the existence of industrial correlation spillover in the interregional industrial transfer and its effects on productivity using the panel data of two-digit subdivided industries in 30 provinces. The results show that the correlation spillover effect does exist and promotes the interregional textile industry transfer from the eastern coastal region to the central and the northern-coastal regions; the correlation spillover from the related tertiary industries in industrial transfer promotes the TFP of China's textile industry, but the correlation spillover from the related secondary industries impedes the TFP of the textile industry. [ABSTRACT FROM AUTHOR]

The key to high-quality development in the textile and apparel industry lies in enhancing technological innovation and optimizing the efficiency of technological innovation. Based on data from 60 A-share listed companies in the textile and apparel sector in China from 2013 to 2022, this study employs a three-stage DEA model and the Malmquist index model to measure changes in technological innovation efficiency from static and dynamic perspectives. Additionally, it uses a Tobit model to analyze the impact and mechanisms of management and financial factors on technological innovation efficiency. The results indicate that: (1) Compared to the manufacturing industry and its sub-sectors, the overall technological innovation efficiency of listed textile and apparel companies was relatively low and showed a declining trend between 2013 and 2022; (2) Over the decade, the average total factor productivity of these listed companies increased by 1.7%, exhibiting a "W" shaped fluctuation, with technological progress, pure technical efficiency, and scale efficiency all showing weak improvement; (3) Management and financial factors significantly influence technological innovation efficiency. Specifically, employee quality, profitability, and operational capability are positively correlated with technological innovation efficiency and have long-term effectiveness, while firm age, management costs, equity concentration, development ability, and debt repayment capacity are negatively correlated with technological innovation efficiency; (4) Different types of enterprises show differences in the significance of management factors, while whether the same person holds both managerial positions significantly affects financial factors. [ABSTRACT FROM AUTHOR]

This study aims to improve the fabric-cutting process of cotton garmentexporting micro and small businesses by identifying and eliminating waste, defined as the processes that do not add value in cutting area of a textile company. In addition, the lean manufacturing approach is applied by employing tools such as value stream mapping (VSM), singleminute exchange of dies (SMED), and work standardisation. The proposed philosophy is based on data analysis, economic validation, and simulation using the historical data from the company under study. Consequently, a decline in default rework and delayed processes along with an increase in the productivity index is expected. [ABSTRACT FROM AUTHOR]

Acrylic fibres, as synthetic polymers, have been used extensively in the textile industry to create a wide variety of products, ranging from apparel and home furnishings to car rooftops and carbon fibres. Their widespread application is attributed to a combination of desirable properties, including a soft, wool-like texture, chemical stability, and robust mechanical characteristics. Furthermore, the chemical structure of acrylic fibres can be modified to imbue them with additional features, such as antimicrobial properties, fire resistance, conductivity, water repellency, and ultraviolet protection. This review explores the technological methods employed to functionalise acrylic fibres and discusses future trends in their development. [ABSTRACT FROM AUTHOR]

The article discusses an exhibition titled "Remaking the Renaissance" at the Lynn Mecklenburg Textile Gallery at the University of Wisconsin-Madison. The exhibition explores the process of remaking historical textiles and objects from the Renaissance period using present-day experiments. The show emphasizes the importance of understanding historical methods and materials to gain a deeper understanding of objects and people from the past. The exhibition showcases reconstructions of textiles and objects, accompanied by contextual period objects and texts, providing an intriguing and educational experience for visitors. The exhibition also highlights the global nature of the textile industry during the Renaissance, with an emphasis on the origins of dyes and the presence of non-European textile fragments. The show aims to engage with the material loss of historical textiles while also demonstrating the power of remaking in museum contexts. [Extracted from the article]

The textile industry comprises technologies that transform synthetic or natural fibers into yarn, cloth, and felt for manufacturing clothing, upholstery, and household linens. The major public health threat in tropical and subtropical countries is mosquito‐borne malaria. Nowadays, the demand for insect repellent‐based textiles is continuously rising, as they are used for protection against diseases transmitted by mosquitoes. The present work reviews studies on the fabrication of insect repellent containing electrospun polymeric nanofibers as principal tools for protecting people against mosquito bites. Electrospinning technology is a remarkably facile technique for fabricating polymeric nanofiber devices. The technique is outlined and elucidated. The performance of insect repellent‐based polymeric nanofibers against mosquitoes is carefully reported and comprehensively reviewed in‐depth. Furthermore, the progress made on the mathematical modeling of the release rate of repellents through polymeric nanofiber devices is reviewed. The reviewed studies demonstrate that repellents can be released slowly from electrospun nanofibers, increasing the product's protection period against insects. The reviewed works suggest that electrospinning technology has led to an effective and facile methodology for fabricating functional nanofiber textiles with insect repellent. The reviewed studies showed that product‐based repellents can be effective not only against malaria but also against other mosquito‐borne diseases. [ABSTRACT FROM AUTHOR]

Textile production has received considerable attention owing to its significance in production value, the complexity of its manufacturing processes and the extensive reach of its supply chains. However, textile industry consumes substantial energy and materials and emits greenhouse gases that severely harm the environment. In addressing this challenge, the concept of sustainable production offers crucial guidance for the sustainable development of the textile industry. Low-carbon manufacturing technologies provide robust technical support for the textile industry to transition to a low-carbon model by optimizing production processes, enhancing energy efficiency and minimizing material waste. Consequently, low-carbon manufacturing technologies have gradually been implemented in sustainable textile production scenarios. However, while research on low-carbon manufacturing technologies for textile production has advanced, these studies predominantly concentrate on theoretical methods, with relatively limited exploration of practical applications. To address this gap, a thorough overview of carbon emission management methods and tools in textile production, as well as the characteristics and influencing factors of carbon emissions in key textile manufacturing processes is presented to identify common issues. Additionally, two new concepts, carbon knowledge graph and carbon traceability, are introduced, offering strategic recommendations and application directions for the low-carbon development of sustainable textile production. Beginning with seven key aspects of sustainable textile production, the characteristics of carbon emissions and their influencing factors in key textile manufacturing process are systematically summarized. The aim is to provide guidance and optimization strategies for future emission reduction efforts by exploring the carbon emission situations and influencing factors at each stage. Furthermore, the potential and challenges of carbon knowledge graph technology are summarized in achieving carbon traceability, and several research ideas and suggestions are proposed. [ABSTRACT FROM AUTHOR]

Copyright of University of Health Sciences Journal of Nursing is the property of Saglik Bilimleri Universitesi and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Brown cotton is a major cultivar of naturally colored cotton, and brown cotton fibers (BCFs) are widely utilized as raw materials for textile industry production due to their advantages of being green and dyeing-pollution-free. However, the mechanisms underlying the pigmentation in fibers are still poorly understood, which significantly limits their extensive applications in related fields. In this study, we conducted a multidimensional comparative analysis of the transcriptomes and metabolomes between brown and white fibers at different developmental periods to identify the key genes and pathways regulating the pigment deposition. The transcriptomic results indicated that the pathways of flavonoid biosynthesis and phenylpropanoid biosynthesis were significantly enriched regulatory pathways, especially in the late development periods of fiber pigmentation; furthermore, the genes distributed in the pathways of PAL, CHS, F3H, DFR, ANR, and UFGT were identified as significantly up-regulated genes. The metabolic results showed that six metabolites, namely (−)-Epigallocatechin, Apiin, Cyanidin-3-O-glucoside, Gallocatechin, Myricetin, and Poncirin, were significantly accumulated in brown fibers but not in white fibers. Integrative analysis of the transcriptomic and metabolomic data demonstrated a possible regulatory network potentially regulating the pigment deposition, in which three MYB transcription factors promote the expression levels of flavonoid biosynthesis genes, thereby inducing the content increase in (−)-Epigallocatechin, Cyanidin-3-O-glucoside, Gallocatechin, and Myricetin in BCFs. Our findings provide new insights into the pigment deposition mechanism in BCFs and offer references for genetic engineering and breeding of colored cotton materials. [ABSTRACT FROM AUTHOR]

A novel method has been explored based on the recovery of two industrial wastes V2O5 and phosphogypsum from the fertilizer production industry, which also provide a significant challenge due to their toxicity and environmental impact. To solve the problem of these two harmful wastes, these residues have been transformed into valuable resources, by the elaboration of Nanoparticles vanadate-hydroxyapatite (NPs-HAP/VAP) adsorbent, contributing a sustainable solution without requiring expensive or highly skilled work. This comprehensive investigation explores the adsorption of the reactive red 141 dye (RR 141) on Ca10(VO4) x(PO4)6-x(OH)2, with (xi = 0, 1.5, 3, 4.5, and 6). Using a Centered composite design (CCD), several parameters influencing the adsorption process were examined. The optimal adsorption capacity is 50 mg. g - 1 under optimal conditions 57.5 mg of the adsorbent dose, 152.5 mgL-1 for the RR 141, pH 8, 92.5 minutes of contact time, and incorporation ratio of 4.5 with an R2 of 0.99. These results reinforce the effectiveness of our chosen CCD model. Kinetic analysis demonstrated a pseudoorder reaction model with an R² > 0.92, while the Sips isotherm describes the adsorption process. Thermodynamic studies revealed spontaneous adsorption, suggesting a physical character enhanced by a positive entropy variation. [ABSTRACT FROM AUTHOR]

This study provides a comprehensive analysis of capital structure stability over long horizons for firms listed in India. It covers a period of 28 years from 1992 to 2019, leading to 20,371 firm-year observations to determine the relative significance of cross-firm leverage variation and time-series leverage variation. It also identifies the circumstances and industries when each type of variation emerges stronger. The study employs simple econometric tools along with financial modelling techniques in SPSS and Microsoft Excel. It was found that corporate leverages are sticky and predictable in the short run. Also, with an increase in a firm's age, leverage stability increases. This study contributes to the existing literature by empirically establishing that leverages can also be persistent at high levels and identifying industries that are persistent at low and high leverages. The results show that persistence at low leverage is a common phenomenon; however, a few industries such as textile, construction, and metals and mining are persistent in their capital structures even at higher levels of leverage. [ABSTRACT FROM AUTHOR]

The review explored the potential of cola acuminata (cola-nut) as a natural and eco-friendly dye source for textiles, taking into account its characteristics, and prospective applications on textile materials. Moreover, the review discusses the various techniques used to extract the dye from cola acuminata, the dye yield, the compound responsible for the color yield of the cola, its various applications, and prospect for sustainable management. There has been limited research on the sustainability of cola acuminata dye extract where there has also been a growing interest in the use of natural dye in the textile industry. Additionally, the production and use of synthetic dyes have been associated with several environmental issues, including water pollution, waste generation, carbon emissions, as well as health related problems for textile workers, particularly in developing countries. However, the dye extract of cola acuminata has been found to possess good color fastness properties and has proven to be a sustainable alternative to synthetic dye since it contains tannins, which are a type of polyphenolic compound that can be used as a natural dye. The tannins in the extract have been shown to have flavonoids properties, so that textiles dyed with the extract may be very resistant to microbial growth. Although, the tannin content of the seeds has been reported to be higher than that of some cola such as cola nitida, despite its lower dye yield. Moreso, the review emphasized on the importance of continued research in this field to optimize the dyeing process and contribute also to the enhancement of sustainable practice in the textile sector. It further provides valuable insights into the potential applications of cola acuminata dye extract particularly in the textile industry. [ABSTRACT FROM AUTHOR]

In order to help users in the textile industry to fully understand USTER Statistics, the USTER Statistics 2023 was interpretated. The concept, history, source of samples of USTER Statistics were introduced. Its scope, percentile curve, application of interactive table and form of publication were explained. The new changes in USTER Statistics 2023 which included the expansion of fiber quality and the quality data of recycled yarn were interpreted. Finally, from the fiber indexes change and fiber indexes change during processing and the change of yarn indexes, the change trend of cotton fiber and yarn quality in the world were analyzed. It is considered that the correct use of the USTER Statistics can help different users of textile enterprises accurately defining yarn quality specifications with a common quality language, promote production process improvement and the realization of key quality performance. And the technology development and spinning parts improvement of textile machinery producers can be proceed based on the latest quality requirements. [ABSTRACT FROM AUTHOR]

The clothing, footwear, and household textiles sectors play a significant role, providing employment opportunities on a global scale. However, they are also associated with a considerable consumption of natural resources, leading to high levels of water pollution and emissions of greenhouse gases, contributing to climate change. The carbon footprint (CF) of textiles depends generally on fabric types and production processes. Natural fibers such as cotton, wool, and silk, generally have a lower CF when compared to synthetic fabrics such as polyester and nylon, requiring more energy and chemicals during production. In addition, fabrics manufactured through eco-friendly methods, such as closed-loop systems and sustainable production processes, have a significantly lower CF than those produced using conventional means. Accordingly, there is a perceived need for comprehensive studies that investigate the environmental and climate implications of the textile sector. Considering these concerns, a study was undertaken on the topic, encompassing a literature review and data collection so as to present an overview of the environmental impacts and CF associated with the textile sector. The results from the research show that the resource consumption associated with the textile sector, particularly its CF, demands urgent action in order to reduce its impacts. Also, actionable measures are needed so as to reduce the CF of the textile industry. These are described in the paper, along with the obstacles that need to be overcome so as not only to reduce the CF of this sector, but also to pursue the objectives outlined in the sustainable development goals. [ABSTRACT FROM AUTHOR]

Purpose: The primary objective of this research is to determine critical success factors (CSFs) that enable textile enterprises to effectively implement Kaizen, a Japanese concept of continuous development, particularly during disruptive situations. The study aims to provide insights into how Kaizen is specifically employed within the textile sector and to offer guidance for addressing future crises. Design/methodology/approach: This study employs a structured approach to determine CSFs for successful Kaizen implementation in the textile industry. The Triple Helix Actors structure, comprising business, academia and government representatives, is utilized to uncover essential insights. Additionally, the Matriced Impacts Croises-Multiplication Applique and Classement (MICMAC) analysis and interpretative structural modeling (ISM) techniques are applied to evaluate the influence of CSFs. Findings: The research identifies 17 CSFs for successful Kaizen implementation in the textile industry through a comprehensive literature review and expert input. These factors are organized into a hierarchical structure with 5 distinct levels. Additionally, the application of the MICMAC analysis reveals three clusters of CSFs: linkage, dependent and independent, highlighting their interdependencies and impact. Originality/value: Major contribution of this study is understanding how Kaizen can be effectively utilized in the textile industry, especially during disruptive events. The combination of the Triple Helix Actors structure, MICMAC analysis and ISM provides a unique perspective on the essential factors driving successful Kaizen implementation. The identification of CSFs and their categorization into clusters offer valuable insights for practitioners, policymakers and academia seeking to enhance the resilience and sustainability of the textile industry. [ABSTRACT FROM AUTHOR]

The textile industry is a pillar of the manufacturing sector worldwide, but it still represents a significantly polluting production sector since it is energy-, water- and natural resource-intensive. Herein, waste wool that did not meet the technical requirements to be used for yarns and fabrics was recovered first to prepare materials for wastewater remediation, specifically for phosphate removal. The wool underwent an alkaline treatment, eventually saturated with FeCl3 and then left at room temperature or thermally treated to induce crosslinking/stabilisation, obtaining adsorbent panels. The main characterisation findings concerned the impact of alkaline treatment on morphology and structure; additionally, the samples with iron displayed a behaviour attributable to a crosslinking effect operated by Fe3+. Batch experiments showed that only samples with iron were efficient in phosphate adsorption, with a high removal percentage obtained in a wide pH range. Adsorption isotherms and kinetics were investigated, suggesting a complex system of interactions. Moreover, during the alkaline treatment necessary to prepare such wool-derived adsorbent panels, a significant amount of wool hydrolysates left in the solution was produced. These substances, in view of zero-waste procedures, were isolated and re-employed as dyeing auxiliaries. Preliminary results demonstrated that the wool hydrolysates enabled the dyeing of cotton with natural dyes, which is generally a tricky process. [ABSTRACT FROM AUTHOR]

BACKGROUND: Dyes present in textile wastewater can pose various environmental problems, including toxicity, carcinogenicity and mutagenicity, when released into receiving environments. Sulfidogenic bacteria play a crucial role in wastewater treatment by reducing sulfate and producing sulfide through the utilization of organic compounds in water. The resulting sulfide often transfers its electrons to another electron acceptor. This study focused on the treatment of real textile wastewater using an up‐flow sulfidogenic column bioreactor. RESULTS: The reactor was acclimated to sulfate‐reducing conditions when influent chemical oxygen demand and sulfate concentrations were 1742 and 2000 mg L−1, respectively. Subsequently, a gradual transition was made from sulfate‐reducing conditions to dye‐reducing conditions. Throughout the study, the hydraulic retention time was maintained at 1 day. CONCLUSION: The influent dye concentration was 2722 Pt‐Co, and an impressive dye removal efficiency of approximately 90 ± 2% was achieved. This corresponds to a removal rate of 2450 Pt‐Co L−1 day−1. Although the sulfide concentration in the reactor decreased in the last period, investigating the extent to which this sulfide participates in the dye removal may expand the use of sulfidogenic reactors in the treatment of real textile industry wastewater. © 2024 The Author(s). Journal of Chemical Technology and Biotechnology published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry (SCI). [ABSTRACT FROM AUTHOR]

Objectives: Low back pain (LBP) is an increasingly prevalent work-related condition that affects workers in manufacturing in Dhaka, Bangladesh, which often causes disability or additional problems when doing demanding physical duties. This study focused on the risk factors for LBP in the context of workers with LBP who work in the ready-made garment (RMG) factories. Methods and materials: A cross-sectional study involved 385 RMG workers, all of whom were adults with ≥ 1 year of work job experience and who typically worked in a sitting position. We use surveys method for collecting data, and a standardized questionnaire covering sociodemographic, pain, work, associated effects, and activities, as well as risk factor-related variables, was used. To evaluate the associations among categorical variables and LBP, we used the chi-square test. To identify the variables that showed strong relationships with LBP, multivariable logistic regression analysis was also carried out. Results: The participant's age (mean ± SD) is 31.27 ± 6.94. One-hundred ninety-four of the 385 participants between the ages of 30–39 years (23.9%) suffered from LBP and statistically strongly significant (χ2 = 15.187, p < 0.05). BMI, employment pattern, and specific work experience are also strongly significant. Out of all risk factors, age 40 and above (OR 1.65, 95% CI 1.53–17.78), overweight (BMI > = 25 kg/m2) (OR 10.72, 95% CI 2.16–53.5), work in an awkward position, stationary position for ling time, working beyond physical ability, incorrectly using body mechanics, repeated twisting and bending, continuously longtime sitting, and using ergonomically improper tools were found to be significantly associated with LBP. Conclusion: The point prevalence of LBP among RMG workers is 41.6%. Only male gender is associated with the presence of LBP. This study showed that working in an awkward position, stationary position for a long time, incorrectly using body mechanics, repeated twisting, and bending had significant associations with LBP. Training programs that instruct proper weight-bearing skills should be encouraged by factories. The occurrence of LBP must also be reduced by regularly performing screening activities to detect it, with a special focus on married people, overweight or obese, and older-aged people. [ABSTRACT FROM AUTHOR]

Background: The study's relevance is determined by the current desire to reduce the negative environmental impact of the textile industry. The study aims to develop and optimise dyeing processes using natural dyes in the textile industry. Results: The process of dye transfer from solution to Bombyx mori natural silk fibre can be divided into three successive kinetic stages. The first stage involves the adsorption of dye molecules on the active surface of the fibre, the second, their diffusion deep into the fibre towards its centre, and the third, the uniform distribution of dye molecules along the fibre starting from its centre. It is noticed that diffusion at the third stage slows down significantly, and the third stage lasts much longer than the first and second stages. The analysis of experimental data on dye concentration over time on dyed materials and their comparison with hypothetical data will make it possible to establish time intervals for each stage of the process and diffusion coefficients for each of them. Conclusion: This study has practical implications as it may contribute to more efficient and sustainable dyeing of textile materials using natural dyes, helping to reduce the negative environmental impact of the textile industry, and contributing to our knowledge of diffusion and dyeing processes. [ABSTRACT FROM AUTHOR]

The pick-up and transfer of easily deformable multi-layer fabrics is a challenge in the automation process of the textile industry. A transfer manipulator using interfacial adhesion forces has potential applications in the pick-up and transfer of fabrics. However, rapid adhesion and detachment cannot be achieved because of the small variability of adhesion and detachment forces between the fabric and the adhering material, which results in difficulty of picking and placing of fabric. To address this problem, in this study, an innovative pressure and strip manipulator structure is designed, utilizing the fabric gesture presented during the fabric peeling process to adjust the peel angle, and thereafter affect the adhesion force. The factors affecting the adhesion force, such as peeling speed, duration, and preload are analyzed, and a control method to regulate the adhesion force by peeling speed and the gap between the adhesion element and positioning block is proposed. Based on the interface adhesion force, the transfer manipulator can realize low-cost, high-stability, and high-efficiency fabric picking, which has good prospects for application in fabric production. [ABSTRACT FROM AUTHOR]

This study aims to identify the contextual relationships between the impact factors on Sustainability 4.0, through the principles of I4.0 in the textile industry, using interpretive structural modeling (ISM), a qualitative technique that makes it possible to understand the relationship between different factors, classifying them hierarchically based on their interdependencies. The hierarchy of the 16 (sixteen) factors proposed at different levels helps to identify critical areas to focus efforts and investments, providing data to guide strategic business planning. From the result of the Level Partition Chart, four levels were observed for the ISM diagram. The Corporate Social Responsibility factor (FIS7) was considered a dependent variable of all others. The identification of FIS4, FIS10 and FIS14 as factors with high dependence suggests key areas for strategic interventions. Thus, this study provides a solid theoretical basis and practical recommendations that help textile companies adopt sustainable and technologically advanced strategies, promoting an effective transition to Sustainability 4.0. [ABSTRACT FROM AUTHOR]

Stretchable devices have gained increasing interest in recent years, particularly in the field of wearable electronics. Among them, fiber‐type devices with high mechanical conformability hold great potential to enable next‐generation wearable and interactive applications with their special structure and high compatibility with the well‐established textile industries. In this study, a hydrogel fiber providing large moisture retention and high mechanical compliance is fabricated, with which a new approach to enable highly stretchable electromechanical sensors based on knot structures is developed. Comparative analysis with common orthogonal textile structures reveal the superior performance of sensors based on ionotronic knots. Stress sensors with the double overhand knot exhibit ≈four times greater variation in capacitance than those with orthogonal structures, and sensors with the clove hitch knot exhibit a fast response time of 57 ms. Based on the characteristics of different knots, a sensor matrix based on clove hitch knots to map the pressure distribution, and a wearable mole code generator based on reef knots to recognize and encode wrist motions are developed. These applications demonstrate the excellent performance of knot‐architecture sensors and their great potential in the fields of smart fabrics and human–machine interactions. [ABSTRACT FROM AUTHOR]

Cotton plays a crucial role in the progress of the textile industry and the betterment of human life by providing natural fibers. In our study, we explored the genetic determinants of cotton architecture and fiber yield and quality by crossbreeding Gossypium hirsutum and Gossypium barbadense, creating a recombinant inbred line (RIL) population. Utilizing SNP markers, we constructed an extensive genetic map encompassing 7,730 markers over 2,784.2 cM. We appraised two architectural and seven fiber traits within six environments, identifying 58 QTLs, of which 49 demonstrated stability across these environments. These encompassed QTLs for traits such as lint percentage (LP), boll weight (BW), fiber strength (STRENGTH), seed index (SI), and micronaire (MIC), primarily located on chromosomes chr‐A07, chr‐D06, and chr‐D07. Notably, chr‐D07 houses a QTL region affecting SI, corroborated by multiple studies. Within this region, the genes BZIP043 and SEP2 were identified as pivotal, with SEP2 particularly showing augmented expression in developing ovules. These discoveries contribute significantly to marker‐assisted selection, potentially elevating both the yield and quality of cotton fiber production. These findings provide valuable insights into marker‐assisted breeding strategies, offering crucial information to enhance fiber yield and quality in cotton production. [ABSTRACT FROM AUTHOR]

All-cellulose composites (ACCs) have been fabricated by using a variety of cellulosic sources, versatile technologies, and are sustainable alternatives for traditional composites. In this study, nonwoven-woven ACC laminates were created from wood-based Spinnova short fibers and Lyocell fabrics via partial dissolution and an NaOH-urea solvent system. The less-known wood-based Spinnova fiber is created for the textile industry, but it also has great potential for the composite industry. To identify the mechanical properties of ACCs--which greatly influence the range of material application--tensile, impact, and flexural tests were conducted. The mechanical properties indicated only moderate properties, which are influenced by high porosity and weak fiber bonding. Despite this, valuable information on the nonwoven-woven structured ACCs was obtained. To improve the ACC laminate's ability to resist moisture, biobased coatings (e.g., commercially available birch bark betulin and suberin acid mixture) were applied on the surface of ACCs and it successfully improved the wetting resistance. The results of contact angle analyses demonstrated that the highest contact angle of 128° was measured for betulin-coated laminates and the best stable hydrophobicity calculated a minute after the beginning of the experiment were observed at 109° for the uncommercial pressurized hot ethanol (PHE) extract of birch bark. [ABSTRACT FROM AUTHOR]

Engagement with socioscientific issues (SSI) is seen as an important citizenship goal of SSI-based science education. In this experimental study, Dutch students (age 8 to 13) participated in lesson series in which they learned about and discussed SSI, such as issues related to the textile industry and wastewater. Attitudes toward SSI indicating engagement were measured among relatively large experimental (n = 236) and control (n = 192) groups prior to and after the intervention. Multilevel analyses showed a positive effect of SSI-based teaching on collective efficacy and no effects on the other seven attitude components. Furthermore, we investigated whether the effects depended on students' SSI-related resources. Students' profiles for use of sources of knowledge (USK) moderated the effect of condition on self-efficacy and—depending on analysis type—on personal relevance, positive feelings, and collective efficacy. The positive impact occurred mainly for students with low USK. We discuss implications thereof for SSI education. [ABSTRACT FROM AUTHOR]

This work addresses the problem of the development of a robotic system for the picking of parts cut by a CNC machine and the optimization of the sequencing of this picking process. An automated parts collection system is optimized to reduce the time required to perform the task of both picking and the subsequent classification by the type of part. The automated picking system, which is located at the end of a cutting machine, uses a robot equipped with an additional axis to expand its working space. Therefore, in this proposal, the industrial equipment necessary to automate this process is designed and the process to be optimized is computationally modeled. In particular, three discrete optimization algorithms are analyzed, with different evolution strategies and operators, but all of them are free of specific configuration parameters. The whole process is shown in this research, from the design of the procedure to the design of the tool, the algorithm selection, and elements validation. Finally, the first steps towards its industrial implementation are presented, and the hypothesis behind this project is validated. [ABSTRACT FROM AUTHOR]

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