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This study aims to elucidate the machining properties of low-cost expanded clay-reinforced syntactic foams by using different neural network models for the first time in the literature. The main goal of this endeavor is to create a casting machining-neural network modeling flow-line for real-time foam manufacturing in the industry.

Samples were manufactured via an industry-based die-casting technology. For the slot milling tests performed with different cutting speeds, depth of cut and lubrication conditions, a 3-axis computer numerical control (CNC) machine was used and the force data were collected through a digital dynamometer. These signals were used as input parameters in neural network modelings.

Among the algorithms, the scaled-conjugated-gradient (SCG) methodology was the weakest average results, whereas the Levenberg–Marquard (LM) approach was highly successful in foreseeing the cutting forces. As for the input variables, an increase in the depth of cut entailed the cutting forces, and this circumstance was more obvious at the higher cutting speeds.

The effect of milling parameters on the cutting forces of low-cost clay-filled metallic syntactics was examined, and the correct detection of these impacts is considerably prominent in this paper. On the other side, tool life and wear analyses can be studied in future investigations.

It was indicated that the milling forces of the clay-added AA7075 syntactic foams, depending on the cutting parameters, can be anticipated through artificial neural network modeling.

It is hoped that analyzing the influence of the cutting parameters using neural network models on the slot milling forces of metallic syntactic foams (MSFs) will be notably useful for research and development (R&D) researchers and design engineers.

This work is the first investigation that focuses on the estimation of slot milling forces of the expanded clay-added AA7075 syntactic foams by using different artificial neural network modeling approaches.

This study aims to examine the impact of China's “Manufacturing and Internet Integration Development Pilot Demonstration Project” (MIP) policy on the digital transformation (DT) and labor structure optimization (LSU) of manufacturing enterprises, reveal the relationship between DT and LSU at the micro level and investigate the mechanism between them.

This study employs MIP as a quasi-natural experiment and develops a time-varying difference-in-difference (DID) model based on a sample of 2,445 Chinese A-share listed manufacturing enterprises in the Shanghai and Shenzhen markets from 2013 to 2021.

The implementation of MIP significantly increases DT by 0.4366 and optimizes LSU by 0.0507. By enhancing the two mediated variables of organizational learning inputs (SI) and employees' personal digital cognition (PDC), DT can optimize the LSU of pilot enterprises by 0.035 and 0.034, according to the results of the mechanism analysis. The study also reveals that the impact of MIP on LSU is highly heterogeneous. With effects of 0.0691 and 0.0632, the optimization effect is more pronounced in state-owned firms and firms with low ownership concentration, respectively.

This study demonstrates the dual effects of the MIP pilot on DT and LSU. In addition, this study pioneers research on the significance of optimizing the labor structure through SI and PDC on the basis of DT, which provides an empirical foundation for the Chinese Government to expand the scope of MIP pilots and revise policy content, as well as for manufacturing enterprises to upgrade the labor structure.

Face masks are the most recommended precautionary measure since the emergence of SARS-CoV-2 since 2020 and the most useful PPE against this virus and its variants so far. This study aims to develop reusable and biodegradable mask from 100% regenerated bamboo or/and its blend. Selection of natural and regenerated textile materials is to minimize generation of solid waste. This attempt will eventually protect our earth by minimizing or better discontinuing the production of the disposable nonbiodegradable face masks available worldwide.

Hundred percent regenerated bamboo and 50:50 bamboo:cotton were selected to knit plain and interlock fabrics for manufacturing of reusable sustainable face masks. A 2³ 3²-mixed-level factorial design was applied to study the effect of liquor ratio and temperatures, fabric structure, blend ratios and finishes at three different levels. Model 2³ 3² has two factors (liquor ratio and temperatures) at three levels and three factors (fabric structure, blend ratios and type of finish) at two levels. Knitted fabrics were then applied with antibacterial finishes; sanitized T99-19 and sanitized T27-22, separately at three different liquor ratios (1:10, 1:12 and 1:15) and temperatures (45, 55 and 65 °C) via exhaust method. After completing processing, fabric thickness, pilling resistance, dimensional stability, bursting strength, Berger whiteness index, air permeability and antibacterial properties of each trial were evaluated using standard test procedures.

Selected fabrics treated either by sanitized T27 or sanitized T99 in a liquor ratio of 1:15 against 65 °C, showed excellent bacteriostatic/bactericidal activity. However, 100% regenerated bamboo interlock knitted fabric treated with sanitized T99 in a liquor ratio of 1:15 at 65 °C has the most desired values of dimensional stability, pilling resistance, Berger whiteness, fabric thickness, air permeability and bursting strength which made it the best for the manufacturing of the masks. Reusable mask is comprised of three layers in which the first and the third layers were of selected 100% regenerated bamboo fabric while a PM2.5 filter was inserted in between. Bacterial filtration efficiency, particle filtration efficiency, biocompatibility and microbial cleanliness will be evaluated in future, to compare the performance of proposed reusable and biodegradable face mask with N95 masks and other fabric masks available commercially.

This study resulted in a development of reusable eco-friendly facemask which was not attempted by the preceding investigations. Outcomes of this work pave the way for a greener and safer earth by using easily obtainable regenerated bamboo fabrics, antibacterial finishes and knitted structures.

The purpose of this study is twofold. First, this research explores the level of Islamic financial literacy of customers in the context of Islamic banking. Second, this study examines the determinants of customer adoption of Islamic banking in Turkey.

This study gathered sample data from 409 participants determined using the purposive sampling method. In the study, first, the reflective measurement model is used to examine the reliability, validity and multicollinearity problems of the variables. Then, AMOS structural equation model (SEM) is used to reveal the relationship between Islamic financial literacy and Islamic banking services. Additionally, this study performed both descriptive and inferential analysis to understand customer literacy about Islamic banking and their adoption behavior of Islamic banking.

The results obtained from descriptive assessment indicate that Turkish customers of Islamic banking possess sufficient literacy about Islamic banking. Moreover, the results from SEM indicate that the adoption of Islamic banking by customers is significantly predicted by the role of Sharia Board management, Islamic banking and purpose of financial institution, religious factor and legitimacy of Islamic financial system.

This study focuses only on the level of knowledge and perceptions of customers who have accounts in Islamic banks or financial institutions in Turkey. It does not focus on the level of knowledge and perception of Muslims who do not have accounts in Islamic banks and financial institutions.

Previous studies on Islamic banking are mostly studies that investigate customers’ perceptions of the Islamic banking system and why individuals prefer Islamic banks. In particular, studies examining the relationship between individuals’ Islamic financial literacy level and Islamic banking preferences are limited. This study is considered to be an original study as it investigates the relationship between the Islamic financial literacy level of individuals and their adoption of Islamic banking services in Turkey.

The purpose of this study is to present a systematic review of the effects of COVID-19 on the conventional textile production subsector. The emergence of the COVID-19 virus in 2019 has subsequently caused many problems, such as unemployment, business closures, economic instability and high volatility in the global capital markets amongst others within the wider manufacturing industry including textile production.

Relevant secondary data are obtained from the Scopus database and Statista. Based on the data analysis of 21 seed articles, three research themes are identified: challenges in the textile industry, new material innovations or solutions and the textile industry performance.

The results reveal that the COVID-19 pandemic has affected the textile industry, disrupted the supply chains of this industry, affected profit margins, stopped employment and impacted the retail of products to customers. Aside from the negative repercussions, there are also good sides to the pandemic which, for instance, range from advanced material innovations to textiles with anti-microbial, self-cleaning and anti-bacterial properties that would limit the transfer of the virus.

Findings reinforced the need for effective strategies and investments in the research and development departments of the various firms in the textile industry to innovate operations and novel materials for the next global pandemic.

Many companies have adopted novel strategies and practices that are helping them to survive the pandemic. This study, therefore, recommends further investigation into material innovations and reimagining strategies by companies and the supply chain within the textile industry so that it is protected against future crises.