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The purpose of this study is to highlight the threats related to the utilization of synthetic fibers. Volatile organic compounds, particulates and acid gases are released during the production of polyester and other synthetic textiles. Polyester is problematic solid waste material as it takes centuries to break down and hence causes microplastic pollution. Biodegradable synthetic solutions for the replacement of polyester are a sustainable business marketing these days. The naNia fiber is the breakthrough product and it is claimed a biodegradable, compostable and toxin-free polymer.

In this research, fabric constructed of naNia fiber was dyed with the extract of naturally occurring Lawsonia inermis (henna) plant leaves. The henna dye was extracted in water and ethanol using different methods, and the better extract was selected by the evaluation of ultraviolet-visible spectroscopy and phytochemical analysis. Henna with ethanol extract showed more desirable results hence it was selected to dye naNia fabric. To improve dyeability, premordanting, simultaneous mordanting and postmordanting were done using chitosan, fresh lemon extract and tannic acid, respectively. The dyed fabric samples were subjected to color strength analysis and multiple colorfastness tests.

The colorfastness test has shown good to excellent results. Scanning electron microscope analysis had also shown the attachment of dye molecules to the filaments. This study revealed that henna dye is appropriate to color naNia fiber even without the aid of a mordant.

For the first time, toxicant-free, biodegradable polyester (naNia) is successfully dyed with sustainable and naturally available dyes and mordants.

Fog computing is a new field of research and has emerged as a complement to the cloud which can mitigate the problems inherent to the cloud computing model such as unreliable latency, bandwidth constraints, security and mobility. This paper aims to provide detailed survey in the field of fog computing covering the current state-of-the-art in fog computing.

Cloud was developed for IT and not for Internet of Things (IoT); as a result, cloud is unable to meet the computing, storage, control and networking demands of the IoT applications. Fog is a companion for the cloud and aims to extend the cloud capabilities to the edge of the network.

Lack of survey papers in the area of fog computing was an important motivational factor for writing this paper. This paper highlights the capabilities of the fog computing and where it fits in between IoT and cloud. This paper has also presented architecture of the fog computing model and its characteristics. Finally, the challenges in the field of fog computing have been discussed in detail which need to be overcome to realize its full potential.

This paper presents the current state-of-the-art in fog computing. Lack of such papers increases the importance of this paper. It also includes challenges and opportunities in the fog computing and various possible solutions to overcome those challenges.

The purpose of this paper is to find the response of micro‐layered rapid prototyping material under impact loading.

A modified Hopkinson Bar was used to impart impact loading in velocities ranging from 2‐7 m/s. Strain gages and stress wave theory were employed to calculate the load‐point force and displacement. Hence the dynamic crack initiation and propagation energies were calculated.

It was found that the crack deflection and inter layer delamination mechanisms lead to greater absorption of crack propagation energy and hence offer better resistance to crack propagation as compared to monolithic acrylonitrile butadiene styrene (ABS).

The finding will lead to greater confidence for the use of rapid prototypes as direct‐use parts subjected to low velocity impact.

Although the static properties of ABS material used in rapid prototyping are well documented, this paper is one of the first reported researches in measuring the impact response of the micro layered ABS.

It has been argued that failure to enlist participation in education in developing countries cannot be attributed exclusively to insufficiency of the schools. To the extent that child schooling reflects parental capacity to invest in human capital formation, there is a need to reckon with the factors bearing on the parents′ decision regarding child schooling. As an illustrative example, examines the impact of household income, household size, ownership of assets, parents′ education, parents′ socio‐economic status, area literacy level and presence of school in the area on the schooling of an individual child in Pakistan.

The intelligence in the Internet of Things (IoT) can be embedded by analyzing the huge volumes of data generated by it in an ultralow latency environment. The computational latency incurred by the cloud-only solution can be significantly brought down by the fog computing layer, which offers a computing infrastructure to minimize the latency in service delivery and execution. For this purpose, a task scheduling policy based on reinforcement learning (RL) is developed that can achieve the optimal resource utilization as well as minimum time to execute tasks and significantly reduce the communication costs during distributed execution.

To realize this, the authors proposed a two-level neural network (NN)-based task scheduling system, where the first-level NN (feed-forward neural network/convolutional neural network [FFNN/CNN]) determines whether the data stream could be analyzed (executed) in the resource-constrained environment (edge/fog) or be directly forwarded to the cloud. The second-level NN ( RL module) schedules all the tasks sent by level 1 NN to fog layer, among the available fog devices. This real-time task assignment policy is used to minimize the total computational latency (makespan) as well as communication costs.

Experimental results indicated that the RL technique works better than the computationally infeasible greedy approach for task scheduling and the combination of RL and task clustering algorithm reduces the communication costs significantly.

The proposed algorithm fundamentally solves the problem of task scheduling in real-time fog-based IoT with best resource utilization, minimum makespan and minimum communication cost between the tasks.

This paper aims to study the attenuation and dispersion phenomena of shear waves in anelastic and elastic porous strips. Numerical investigations are performed for the phase and damped velocity profiles of the wave. For numerical computation purposes, water-saturated limestone and kerosene oil saturated sandstone for the first and second porous strips, respectively. Some other peculiarities have been observed and discussed.

Dispersion and attenuation characteristic of the shear wave propagations have been studied in an inhomogeneous poro-anelastic strip of finite thickness, which is clamped between an inhomogeneous poroelastic strip of finite thickness and an elastic half-space. Both the strips are initially stressed and the half-space is self-weighted. Analytical methods are used to calculate the interior deformations of the model with the involvement of special functions. The determination of the frequency equation, which includes the Bessel’s and Whittaker functions, has been obtained using the prescribed boundary conditions.

Impacts of attenuation coefficient, dissipation factor, inhomogeneities, initial stresses, Biot’s gravity, porosity and thickness ratio parameters on the velocity profile of the wave have been demonstrated through the graphical visuals. These parameters are playing an important role and working as a catalyst in affecting the propagation behaviour of the wave.

Inclusion of the concept of doubly layered initially stressed inhomogeneous porous structure of elastic and anelastic medium bedded over a self-weighted half-space medium brings a novelty to the existing literature related to the study of shear wave. It may be helpful to geologists, seismologists and structural engineers in the development of theoretical and practical studies.

The study aims to investigate the effect of four customer relationship management (CRM) dimensions, namely, customer orientation, customer relationship management organization, managing knowledge and CRM based technology, on customer satisfaction in the hospitality sector of Kashmir.

A survey instrument with a slight modification is adapted from literature and is exercised on the customers of three- and four-star hotels operating in Kashmir. A total of 176 responses received using systematic random sampling were subjected to exploratory factor and regression analyses to uncover the underlying relationships among dependent and independent variables.

The results revealed a significant and positive relationship between CRM dimensions, namely, customer orientation, managing knowledge and CRM organization on customer satisfaction. Though the results also indicate a significant positive effect of CRM-based technology on customer satisfaction, the magnitude of this effect is very weak. This suggests that hotel organizations use technology as a mere tool to store customer information only. Thus, CRM-based technology should be used by the hotels to analyze customer information and, subsequently, design customized products. This will unravel the full potential of the technology and lead to better customer satisfaction.

The findings of this study provide significant insights to the practitioners to understand the role of successfully implementing a CRM strategy. It reflects that establishing an effective CRM strategy helps managers in improving customer satisfaction and in maintaining a long-term relationship with customers to achieve the organizational goals. Thus, establishing an efficient and effective CRM strategy should be (one of) the key objectives for all hotel managers. Moreover, the hotels that successfully implement CRM strategy and manage customer knowledge properly will reap the rewards in terms of better customer loyalty and long-term sustainable profitability.

This study approaches the implementation of CRM strategy from a customer perspective with a specific focus on investigating the effect of four CRM dimensions on customer satisfaction in the hospitality sector. This will provide a novel impetus to the hotel managers to devise and manage a CRM strategy that leads to (better) customer satisfaction.

This study quantifies empirically the induced impact of income distribution and consumption expenditure on the structures of agriculture production of Nigerian economy.

The study calibrates an extended input-output model on a social accounting matrix (SAM) for Nigeria for the year 2010. Moreover, the study conducts a dispersion analysis to identify the key agriculture sectors/subsectors both in exogenous and endogenous setup.

This study presents an empirical analysis of propagation in the structure of production particularly in the structure of agriculture sector. It combines the aggregate and the disaggregated levels of analysis and identifies the key sectors/subsectors both in the exogenous and endogenous setup. The comparison of both findings confirms that the composition of income distribution and consumption expenditure significantly influences the composition and the aggregated and disaggregated order of structure of agriculture production.

Knowledge of interindustry connections is vital in policy implications since the policy makers prefer strongly interconnected sectors to the sectors with poor industry linkages. These connections are estimated as forward and backward linkages, which provide indices to set the criteria for key sectors identification. This study presents an empirical analysis of propagation in the structure of production particularly in the structure of agriculture sector. It combines the aggregate and the disaggregated levels of analysis and identifies the key sectors/subsectors both in the exogenous and endogenous setup.

With the global outbreak of COVID-19 that has made the economic activities standstill, countries have taken immediate measures to safeguard not only the human lives but also the economies. This study investigates empirically the lockdown impact of current pandemic on the Saudi economy.

The study employs inoperability input–output model (IIOM) on the input–output table (IOT) of Saudi Arabia for the analysis.

Findings show that with the closure of few sectors for the period of two months, the GDP declined to 6.49%. Findings also show a negative impact on consumption, investments and exports.

One limitation of current study is that it uses IOTs which lack primary and secondary income distribution that is vital for presenting complete interindustry connections in the analysis. The interindustry structures relate to the consumption structures which ultimately lead to the income distribution and affect the consumption behaviors of economic agents. Hence, the complete income circular flow is not incorporated in IIOM using IOT. The findings of current study would be well grounded if it endogenized the primary and secondary income distribution.

The practical implication of this study is the use of IIOM for anticipating the potential loss against the backdrop of catastrophes and pandemics. The IIOM has the capability to predict the economic effects of disruptive events and hence the policy-makers can better predict and devise prudent policies to avoid the likely threats to the economy.

The current situation is unprecedented, and it is challenging for governments to forecast the economic repercussions. Several economic sectors have been inoperative due to lockdown implemented by the governments. This study empirically estimated the inoperability produced by the current pandemic. The findings are consistent with other estimated statistics, thereby proving the efficacy of IIOM to anticipate the economic repercussions of natural hazards.

This study aims to investigate the irreversibility associated with the Fe3O4–Co/kerosene hybrid-nanofluid past a wedge with nonlinear radiation and heat source.

This study reports the numerical analysis of the hybrid nanofluid model under the implications of the heat source and magnetic field over a static and moving wedge with slips. The second law of thermodynamics is applied with nonlinear thermal radiation. The system that comprises differential equations of partial derivatives is remodeled into the system of differential equations via similarity transformations and then solved through the Runge–Kutta–Fehlberg with shooting technique. The physical parameters, which emerges from the derived system, are discussed in graphical formats. Excellent proficiency in the numerical process is analyzed by comparing the results with available literature in limiting scenarios.

The significant outcomes of the current investigation are that the velocity field uplifts for higher velocity slip and magnetic strength. Further, the heat transfer rate is reduced with the incremental values of the Eckert number, while it uplifts with thermal slip and radiation parameters. An increase in Brinkmann’s number uplifts the entropy generation rate, while that peters out the Bejan number. The results of this study are of importance involving in the assessment of the effect of some important design parameters on heat transfer and, consequently, on the optimization of industrial processes.

This study is original work that reports the hybrid nanofluid model of Fe3O4–Co/kerosene.