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This paper aims to investigate the influence of picking sequence, weave design and weft yarn material on the thermal conductivity of the woven fabrics.

This work includes the development of 36 woven samples with two weave designs (1/1 plain and 3/1 twill), three picking sequences (single, double and three pick insertion) and six different weft yarn materials (cotton, polyester having 48 filaments, polyester with 144 filaments, spun coolmax having Lycra in core and coolmax in sheath, filament coolmax and polypropylene). The thermal conductivity was measured using ALAMBETA tester.

The results showed that weft yarn material, weave design and picking sequence have a meaningful impact on the thermal conductivity of woven fabric. The value of thermal conductivity was lowest for the fabrics with three pick insertion and 3/1 twill weave in all weft yarn materials.

Plain woven fabric with single pick insertion is feasible for summer wear to enhance the comfort of wearer. By changing the warp yarn grouping and material, improved thermal conductivity/resistance can also be achieved.

The authors have studied the combined effect of different weft yarn materials with different picking sequences and different weave designs on thermal conductivity of the woven fabrics.

The purpose of the study is to optimize the blending ratio of Arecanut and cotton fibers to create yarn with the best quality for various applications, particularly home furnishings. The study aims to determine the effect of different blend ratios on the physical and mechanical properties of the yarn.

The study involves blending Arecanut and cotton fibers in various ratios (90:10, 75:25, 50:50, 25:75 and 10:90) at two different yarn counts (10/1 and 5/1). Various physical and mechanical properties of the blended yarn are analyzed, including unevenness, coefficient of mass variation (cvm%), imperfection, hairiness, breaking strength, elongation, tenacity and breaking work.

The research findings suggest that the blend ratio of 10:90 (10% cotton and 90% Arecanut fiber) produced the best results in terms of physical and mechanical properties for both yarn counts. This blend ratio resulted in reduced unevenness, cvm% and imperfection, while also exhibiting good mechanical properties such as breaking strength, elongation, tenacity and breaking work. The blend with a higher concentration of cotton generally showed better properties due to the coarseness of Arecanut fiber. As the goal of the study was to determine the best blend ratio that included the most Arecanut fiber based on its physical and mechanical properties, which is suitable for home furnishing applications, 75:25 Areca cotton blend ratio of yarn count 5/1 proved to be the best.

The study acknowledges that Arecanut fiber must be blended with other commercially used fibers like cotton due to its coarseness. While the study provides insights into optimizing blend ratios for home furnishings and packaging, further research may be needed to make the material suitable for clothing applications.

The research has practical implications for industries interested in utilizing Arecanut and cotton blends for various applications, such as home furnishings and packaging materials. It suggests that specific blend ratios can result in yarn with desirable properties for these purposes.

The study mentions that the increased use of Arecanut fibers can benefit the growers of Arecanut, potentially providing economic opportunities for communities engaged in Arecanut farming.

The research explores the utilization of Arecanut fibers, an underutilized resource, in combination with cotton to create sustainable yarn. It assesses various blend ratios and their impact on yarn properties, contributing to the understanding of eco-friendly textile materials.

The consideration of alternative sources of material for construction is imperative to reduce the environmental impacts as two-fifths of the carbon footprint of materials is attributed to the construction industry. One alternative material with improved biodegradable attributes which can contribute to carbon offset is bamboo. The commercialisation of bamboo in modern infrastructures has significant potential to address few of the Sustainable Development Goals (SDGs) itemised by the United Nations, namely SDG 9 about industry, innovation and infrastructure. Other SDGs covering sustainable cities and communities, responsible consumption and production and climate action are also indirectly addressed when utilising sustainable construction materials. Being a natural material however, the full commercialisation of materials such as bamboo is constrained by a lack of durability. Besides fracture mechanisms arising from load-induced cracks and thermal modification, the durability of bamboo material is greatly impaired by biotic and abiotic factors, which equally affect its natural rate of degradation, hence fracture behaviour. In first instance, this chapter outlines the various factors leading to the durability limitations in bamboo material due to load-induced cracks and natural degradation based on recent findings in this field from the author's own work and from past literature. Secondly, part of this chapter is devoted to a new approach of processing the surge of information about the varied aspects of bamboo durability by considering the powerful technique of artificial intelligence (AI), specifically the artificial neural network (ANN) for prediction modelling. Further use of AI-enabled technologies could have an impactful outcome on the life cycle assessment of bamboo-based structures to address the growing challenges outlined by the United Nations.

Through this study, four different types of woven fabric structures were created by using cotton/banana blends with a 70:30 ratio by varying the weaving specifications. This study aims to investigate the comfort and mechanical properties of these woven materials.

Taguchi L16 experimental design (5 factors and 4 levels) with response surface methodology tool was used to optimize mechanical and comfort characteristics. The yarn samples used in this study are cotton/banana with a blend ratio of 70:30. Fabric type (A), grams per square metre (GSM; B), yarn count (C), fabric thickness (D) and cloth cover factor (E) are the chosen process characteristics.

The highest tensile strength and tearing strength of the cotton/banana blended fabric samples were obtained as 326.3 N and 90.3 k.gf/cm, respectively. Similarly, the highest thermal conductivity and overall moisture management capacity values were found to be 0.6628 and 3.06 W/mK X10⁻⁴, respectively. The optimized process parameters for obtaining maximum mechanical properties were using canvas fabric structure, 182 GSM, 36^s Ne yarn count, 0.48 mm fabric thickness and 23.5 cloth cover factor. Similarly, the optimized process parameters for obtaining maximum comfort properties were achieved using a twill fabric structure, 182 GSM, 32^s Ne yarn count, 0.4 mm fabric thickness and 23 cloth cover factor.

In contrast to synthetic fabrics, banana fibre and its blended materials are significant ecological solutions for apparel and functional clothing. Products made from banana fibre are a sustainable and green alternative to conventional fabrics. Banana fibre obtained from the pseudostem of the plant has an appearance similar to ramie and bamboo fibres. Numerous studies showed that banana fibre could absorb significant moisture and be spun into yarn through ring and rotor spinning technology. On the other hand, this fibre can be easily combined with cotton, jute, wool and synthetic fibre. The present utilization of pseudostem of banana plant fibre is very minimal. This type of research improves the usability of bananas their blended fabrics as apparel and functional wear.

Circular supply chain management (CSCM) is considered a promising solution to attain sustainability in the current industrial system. Despite the exigency of this approach, its application in the food industry is a challenge because of the nature of the industry and CSCM being a novel approach. The purpose of this study is to develop an industry-based systematic analysis of CSCM by examining the challenges for its application, exploring the effects of recognised challenges on various food supply chain (FSC) stages and investigating the business processes as drivers.

Stakeholder theory guided the need to consider stakeholders’ views in this research and key stakeholders directly from the food circular supply chain were identified and interviewed (n = 36) following qualitative methods.

Overall, the study reveals that knowledge, perception towards environmental initiatives and economic viability are the major barriers to circular supply chain transition in the UK FSC.

This research provides a holistic perspective analysing the loopholes in different stages of the supply chain and investigating the way a particular circular supply chain stage is affected by recognised challenges through stakeholder theory, which will be a contribution to designing management-level strategies. Reconceptualising this practice would be beneficial in bringing three-tier (economic, environmental and social) benefits and will be supportive to engage stakeholders in the sustainability agenda.

The essential properties of active sports fabrics are moisture management, quick-drying, body heat management and thermal regulations. Fibre type, blending nature, yarn and fabric structure and the finishing treatment are the key parameters that influenced the performance of the clothing meant for sportswear. This study aims to investigate the effect of fibre blending and structural tightness factors on bi-layer sport fabric's dimensional, moisture management and thermal properties.

In this study, 12 different bi-layer inter-lock fabrics were produced. Polyester filament (120 Denier) yarn was fed to form the backside of the fabric, and the face side was varied with cotton, modal, wool and soya spun yarns of 30sNe. Three different types of structural tightness factors were considered, such as low, medium and high were taken for sample development. The assessment towards dimensional, moisture management and thermal properties was carried out on all the samples.

The polyester-modal blend with a high tightness factor has shown maximum overall moisture management capability (OMMC) values of 0.73 and air permeability of 205.3 cm³/cm²/s. The same sample has shown comparatively higher thermal conductivity of 61.72 × 10^–3 W m^-1 °C^-1(Under compression state) and 58.45 × 10^–3 W m^-1 °C^-1 (under recovery state). In the case of surface roughness is concerned, polyester-modal blends have shown the lowest surface roughness, surface roughness amplitude and surface friction co-efficient. Among the selected fibre combinations, the overall comfort level of polyester-modal bi-layer knitted structure with a higher tightness factor is appreciable. Polyester-modal is more suitable for active sportswear among the four fiber blend combinations.

The outcome of this study will help to gain a better understanding of fibre blends, structural tightness factor and other process specifications for the development of bi-layer fabric for active sportswear applications. The dynamic functional testing methods (Moisture management and Thermal properties) were carried out to simulate the actual wearing environment of the sports clothing. This study will create a new scope of research opportunities in the field of bi-layer sports textiles.

This study was conducted to explore the influence of fibre blend and structural tightness factor on the comfort level of sportswear and to find the suitable fibre blend for active sportswear clothing.

The purpose of this paper is to review cases of artificial reefs built through additive manufacturing (AM) technologies and analyse their ecological goals, fabrication process, materials, structural design features and implementation location to determine predominant parameters, environmental impacts, advantages, and limitations.

The review analysed 16 cases of artificial reefs from both temperate and tropical regions. These were categorised based on the AM process used, the mortar material used (crucial for biological applications), the structural design features and the location of implementation. These parameters are assessed to determine how effectively the designs meet the stipulated ecological goals, how AM technologies demonstrate their potential in comparison to conventional methods and the preference locations of these implementations.

The overview revealed that the dominant artificial reef implementation occurs in the Mediterranean and Atlantic Seas, both accounting for 24%. The remaining cases were in the Australian Sea (20%), the South Asia Sea (12%), the Persian Gulf and the Pacific Ocean, both with 8%, and the Indian Sea with 4% of all the cases studied. It was concluded that fused filament fabrication, binder jetting and material extrusion represent the main AM processes used to build artificial reefs. Cementitious materials, ceramics, polymers and geopolymer formulations were used, incorporating aggregates from mineral residues, biological wastes and pozzolan materials, to reduce environmental impacts, promote the circular economy and be more beneficial for marine ecosystems. The evaluation ranking assessed how well their design and materials align with their ecological goals, demonstrating that five cases were ranked with high effectiveness, ten projects with moderate effectiveness and one case with low effectiveness.

AM represents an innovative method for marine restoration and management. It offers a rapid prototyping technique for design validation and enables the creation of highly complex shapes for habitat diversification while incorporating a diverse range of materials to benefit environmental and marine species’ habitats.

This research aims to explore people management (PM) dimensions in Nepalese recycling startups (R-startups).

It follows a case study and qualitative research approach. Information is collected from Internet searches and R-startups’ blogs. For research purposes, 12 cases out of 30 R-startups are selected using convenient and purposeful non-probability sampling methods.

Three major findings are as follows: (1) the founders of R-startups have become more environmentally aware and motivated to source materials, manufacture products and deliver them without harming the environment; (2) the founders are establishing work-flow to create future employment opportunities and (3) the PM dimensions in R-startups appear to be sustainable and apparently linked with Sustainable Development Goal (SDG) 12.5, which aims to reduce waste generation substantially through prevention, reduction, recycling and reuse.

Since researchers use widely accessible internet information, there is no possibility of interfering with the website's text and data. The analysis is solely based on the opinions of founders/co-founders of R-startups.

This research presents PM dimensions in R-startups and contributes to the literature in this new field of study. Although on a small scale, this research can provide a basis for minimizing circulatory gaps and closing the loop through circular business (CB). It also provides insights into managing waste in order to create opportunities and wealth.

This is one of the few unexplored areas of academic research. The critical PM dimensions investigated in this study can serve as a baseline for future theoretical development in the context of a specific country.

This paper aims to integrate the consumption perspective within the Industrial Marketing and Purchasing (IMP) debate. The study delves into how consumer communities can be conceived like other network business actors. The perspective of sustainable new ventures (SNVs) in the fashion industry is adopted, considering their specific connection with consumer communities.

Adopting a multiple case study methodology, this paper uses a qualitative approach. Data collection mainly relies on interviews conducted with 10 SNVs in the fashion industry; this sector is a fertile ground for studying sustainability and consumer communities. For data analysis, the abductive approach of systematic combining is applied.

The paper identifies four distinct types of consumer communities and four roles that they can assume as business actors in the business network. Owing to their engagement in these specific roles, consumer communities become part of the SNVs’ network, akin to other business-to-business players.

This study represents one of the initial endeavors to introduce consumption into the IMP theoretical framework. In this paper’s conceptualization, consumer communities are groups of consumers and collective actors in the business network. Additionally, this study advances the research on sustainability as a network concept by including consumer communities’ roles in business networks.