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This work aims to investigate the feasibility of recycling waste plastic (polyethylene terephthalate) as a coarse aggregate for producing blended cement concrete modified with fly ash and pond ash.

The low, medium and high controlled strength blended cement concrete modified with varied proportions of fly and pond ashes were produced. Manufactured sand and recycled plastic coarse aggregate (RPCA) replaced normal fine and coarse aggregates. Concrete samples were tested for workability, mechanical and durability characteristics. Microstructural analysis was performed on cement concrete blended with fly and pond ashes and compared to conventional concrete samples.

All concrete mixes showed better flowability with values greater than 200 mm. Besides, the maximum flow time was approximately 8 s. The wet density of blended cement concrete-RPCA-based concretes was approximately 30% lower than that of conventional concrete. The compressive strengths of the controlled strength mix at 7 and 28 days were within the specified ranges. While the conventional concrete had slightly higher permeability, the blended cement concrete-RPCA-based concretes had better thermal resistivity and lower thermal conductivity. The scanning electron microscopy analysis revealed the densification of the microstructure due to the filler effects of fly and pond ashes.

This study establishes the prospects of substituting RPCA with normal coarse aggregate in the production of controlled low-strength blended cement concrete, offering benefits of structural fill concrete, lower permeability and thermal conductivity, higher thermal resistivity and reduced density and shrinkage.

In recent times, ternary hybrid nanofluid has garnered attention from scientist and researchers due to its improved thermal efficiency. This study aims to delve into the examination of ternary hybrid nanofluid (Al₂O₃–Cu–TiO₂/water), particularly concerning axisymmetric flow over a nonlinearly permeable stretching/shrinking disk. In addition, the investigation of convective boundary conditions and thermal radiation effects is also considered within the context of the described flow problem.

Mathematical formulations representing this problem are reduced into a set of ordinary differential equations (ODEs) using similarity transformation. The MATLAB boundary value problem solver is then used to solve the obtained set of ODEs. The impact of considered physical parameters such as suction parameter, radiation parameter, nonlinear parameter, nanoparticle volumetric concentration and Biot number on the flow profiles as well as the physical quantities is illustrated in graphical form.

The findings revealed the thermal flux for the nonlinearly shrinking disk is approximately 1.33%, significantly higher when compared to the linearly shrinking disk. Moreover, the existence of dual solutions attributed to the nonlinear stretching/shrinking disk is unveiled, with the first solution being identified as the stable and reliable solution through temporal stability analysis.

Understanding ternary hybrid nanofluid behavior and flow has applications in engineering, energy systems and materials research. This study may help develop and optimize nanofluid systems like heat exchangers and cooling systems.

The study of flow dynamics across nonlinear stretching/shrinking disk gains less attention compared to linear stretching/shrinking geometries. Many natural and industrial processes involve nonlinear changes in boundary shapes or sizes. Understanding flow dynamics over nonlinear shrinking/stretching disks is therefore essential for applications in various fields such as materials processing, biomedical engineering and environmental sciences. Hence, this study highlights the axisymmetric flow over a nonlinear stretching/shrinking disk using ternary hybrid nanofluid composed of alumina (Al₂O₃), copper (Cu) and titania (TiO₂). Besides, this study tackles a complex problem involving multiple factors such as suction, radiation and convective boundary conditions. Analyzing such complex systems can provide valuable insights into real-world phenomena where multiple factors interact.

In the process of providing quality healthcare services, identifying the important healthcare attributes and their operational performance is crucial in the healthcare industry. Highlighting this, the authors have aimed to find the importance of certain healthcare attributes and their respective performance from the customers’ perspective in the Indian private tertiary healthcare facilities by conducting an importance-performance analysis (IPA).

For this study, the authors have derived 10 healthcare attributes from the literature and responses regarding their importance and performance were taken from 350 inpatients from 6 hospitals.

The analysis resulted in identification of the most and least important, high and low performing healthcare attributes as perceived by the patients. In terms of attribute importance, the doctors’ competencies and provision of safe and effective patient care have been ranked most important, whereas the doctors’ competencies and accessibility have been rated high in terms of performance. In addition, the importance ranks and performance scores helped in the development of a two-dimensional IPA grid.

The IPA grid helped in identifying the areas for improvement, hence determining the need for implementation of significant strategies in the process of cost-effective high-quality healthcare service provision.

There is a paucity of IPA studies with a focus on the Indian healthcare system in identifying and demonstrating the healthcare components that need to be addressed for improvement. Emphasizing the gap, this is one of the pioneering studies that captured various healthcare attributes’ importance and their respective performance from the lens of hospital inpatients, which helped in the development of an IPA grid by clearly outlining the areas that need attention, especially in the post-pandemic scenario.

Borrowing from the dynamic capabilities theory and augmented by the relational view, the study investigates the criticality of supply chain agility in delivering operational performance while understanding the determinant role of key cross-firm resources. Additionally, based on the contingency theory, the interactive influence of two critical context factors, supply uncertainty and product complexity, is examined to enrich the understanding of the contingent nature of the operational performance implications.

The study draws its conclusions from the survey data collected from a 152-respondent sample of executives from US manufacturing firms. The empirical data analyses using partial least square structural equation modeling (PLS-SEM) relate agility to operational performance enhancements while incorporating the moderating effects of contextual factors.

The study relates agility capability to operational performance enhancements, while resource specificity and resource complementarity emerge as significant determinants of the capability. Results on the contingent impact of contextual factors suggest differential influences of supply uncertainty and product complexity on the agility–performance relationship: while the former enhances, the latter detracts from the relationship.

The study’s contributions suggest theory extensions into supply chains as contexts, reinforcing the importance of market-responsive capabilities and the foundational nature of supply chains as repositories of vital cross-firm resources. The contingent nature of the agility–performance relationship accents the importance of market context factors.

The textile industry is evolving toward nanotechnology, which provides materials with self-cleaning properties. This paper aims to provide a thorough explanation of the green synthesis and mechanism of ZnO nanoparticles, with prospective applications of zinc oxide nanoparticles (ZnO NPs) in self-cleaning textiles.

This review introduces a green mechanism for the synthesis of ZnO NPs using plant extracts, their self-cleaning properties and the mechanisms of physical, chemical and biological self-cleaning actions for textile applications.

ZnO NPs are among the several nanoparticles that are beneficial for self-cleaning textiles because of their exceptional physical and chemical properties, although review publications addressing the use of ZnO NPs in textiles for self-cleaning are uncommon. These results indicate that the plant-synthesized ZnO NPs display excellent biological, physical and chemical self-cleaning properties, the mechanism of which involves photocatalysis, surface roughness and interactions between ZnO NPs and bacterial surfaces.

Nanoformulations of plant-synthesized ZnO have been reviewed to achieve promising self-cleaning textile properties and have not been reviewed earlier.

Globally, postnatal women endure a prominent issue caused by midline separation of abdominal recti muscles, characterized by a sagging and pouch-like appearance of the belly termed as Diastasis Recti Abdominis (DRA). The necessity of ensuring the efficacy of rehabilitative workouts for individuals with DRA cannot be overstated, as inaccurate exercises can exacerbate the condition and deteriorate the health of affected women. The purpose of these exercises is to specifically focus on the rectus abdominis muscles to facilitate the reapproximation of the linea alba. The primary aim of this research work is to assess the effectiveness of rehabilitation exercises for DRA women obtained from Inertial Measurement Unit (IMU) and Electromyography (EMG) sensors.

Convolutional neural networks (CNN) employs convolutional activation functions and pooling layers. Recently, 1D CNNs have emerged as a promising approach used in various applications, including personalized biomedical data classification and early diagnosis, structural health monitoring and anomaly detection. Yet another significant benefit is the feasibility of a real-time and cost-effective implementation of 1D CNN. The EMG and IMU signals serve as inputs for the 1D CNN. Features are then extracted from the fully connected layer of the CNN and fed into a boosting machine learning algorithm for classification.

The findings demonstrate that a combination of sensors provides more details about the exercises, thereby contributing to the classification accuracy.

In real time, collecting data from postnatal women was incredibly challenging. The process of examining these women was time-consuming, and they were often preoccupied with their newborns, leading to a reluctance to focus on their own health. Additionally, postnatal women might not be fully aware of the implications of DRA and the importance of rehabilitation exercises. Many might not realize that neglecting DRA can lead to long-term issues such as back pain, pelvic floor dysfunction, and compromised core strength.

During our data collection camps, there were educational sessions to raise awareness about the DRA problem and the benefits of rehabilitation exercises. This dual approach helped in building trust and encouraging participation. Moreover, the use of wearable sensors in this study provided a non-invasive and convenient way for new mothers to engage in rehabilitation exercises without needing frequent visits to a clinic, which is often impractical for them.

The utilization of discriminating features retrieved from the output layer of 1D CNN is a significant contribution to this work. The responses of this study indicate that 1D convolutional neural network (1D CNN) and Boosting algorithms used in a transfer learning strategy produce successful discrimination between accurate and inaccurate performance of exercises by achieving an accuracy of 96%.

The study aims to investigate the relationship between certain key attributes of the board of directors as their international experience, tenure, age, independence and size and internationalization strategies of firms in an emerging economy.

The study uses random effects panel Tobit regression on a data set of 418 Indian companies spanning over a time frame of nine years from fiscal year (F.Y.) 2009–2010 to F.Y. 2017–2018.

Board members substantially associate with internationalization choices of emerging economy firms. Specifically, board members with extensive international experience, shorter tenure, higher age, greater independence and larger board size are associated with high level of internationalization in these firms.

The study advocates that Indian companies should focus on recruiting board members with international experience, periodically refreshing their boards, valuing wisdom and experience, adhering to regulatory requirements of independent directors and increase the number of board members to expand internationally. By following this, Indian companies can successfully expand into international markets.

The study’s originality lies in its focus on the role of board members in the internationalization strategy of emerging economy firms, which remains an under-researched area.

Considering both the current opportunities of the Internet of things (IoT) and aviation, as well as the potential opportunities they may offer for the future, it is understood that they are among the important issues that need to be examined in the literature. This study aims to provide an idea by conducting bibliometric and visualization analyses of the current trends and development opportunities of IoT and aviation.

In this study, descriptive and bibliometric analyses within the framework of co-author, co-citation, bibliographic coupling, and keyword co-occurrence analysis were carried out for publications found to be published between 2007 and 2023 in the Web of Science (WoS) database related to IoT and aviation. VOSviewer (ver. 1.6.18) program and the Biblioshiny application were used to create bibliometric networks and provide visualization.

As a result of some descriptive and visualization analyses, the current trend of publications on IoT and aviation and future publication opportunities has been revealed. It has been understood that the subject of IoT and aviation is one of the subjects whose number of publications has increased in recent years and has not yet fully matured in terms of the number of publications and has the potential to make new publications.

In this study, bibliometric analysis of IoT and aviation, which could not be found examined before in the literature, and the creation of existing bibliometric networks by visualizing were carried out.

In the denim industry, enzyme washing and its combination with stone washing are generally used to get the desired worn-out look. However, these conventional methods include high water, energy and time consumption. Nowadays, laser fading, which is a computer-controlled, dry, ecological finishing method, is preferred in the denim fading process. The purpose of this study is to observe the effects of chemical pretreatment applications on laser-faded denim fabric in terms of color and mechanical properties. To eliminate the enzyme washing process in denim fading and to minimize the disadvantages of laser fading, such as decreased mechanical properties and increased fabric yellowness, various chemical pretreatment applications were applied to the denim fabric before laser fading, followed by simple rinsing instead of enzyme washing.

Two different indigo-dyed, organic cotton denim fabrics with different unit weights were exposed to pretreatment processes and then laser treatment, followed by simple rinsing. Polysilicic acid, boric acid, borax and bicarbonate were used for pretreatment processes, and laser treatment was carried out under optimized laser parameters (40 dpi resolution and 300 µs pixel time). Tensile strength was tested, and color values (CIE L*, a*, b*, ΔE*, C* and h), color yield (K/S), yellowness and whiteness indexes were measured to identify the color differences.

Before laser fading, 30 g/L and 40 g/L polysilicic acid pretreatments for sulfur-indigo-dyed fabric and a mixture of 10 g/L boric acid and 10 g/L borax pretreatments for the fabric only indigo-dyed were recommended for the laser fading with sufficient mechanical properties and good color values.

With the chemical pretreatments defined in this study, it was possible to reduce yellowness and maintain the mechanical properties after laser fading, thus minimizing the disadvantages of laser treatment and also eliminating enzyme washing.

Technological start-ups are significant contributor to the innovation and employment provider in an economy. Numerous technological start-ups are established every year; however, only a miniscule percentage of these technological start-ups sustain and scale up in the long run. The aim of this study is to investigate the factors that affect Indian technological start-ups’ competitiveness.

Case study analysis of two technological start-ups (namely, WayCool and Moglix) is undertaken to study the factors affecting the competitiveness of technological start-ups in India. Being a relatively underexplored theme of study in entrepreneurship and strategy, case analysis facilitates exploration and validation of factors influencing competitiveness. Information for case study analysis is drawn from secondary sources of information. The collected data undergoes deductive thematic analysis to systematically identify and examine recurring themes and patterns relevant to the competitiveness of Indian technological start-ups.

Case analysis reveals that innovation intensity, organisational agility and internationalisation influence competitiveness of technological start-ups. The importance of the role of each of these factors for entrepreneurial ventures has been highlighted in literature; however, their effect on competitiveness has not been examined in extant literature.

Being among the few studies on the competitiveness of technological start-ups in specific and start-ups in general, this study highlights the gap in the literature and suggests the need for examining the competitiveness of technological start-ups.

For the practitioners, this study reinforces the need for entrepreneurs to emphasise fundamental factors that build competitiveness. Subsequently, the sources of competitiveness shall enable the start-up to gain a competitive advantage.

This is among the few studies to have explored the competitiveness of technological start-ups in the Indian context.