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Iron deficiency anaemia and zinc deficiency are major public health problems across the globe. Cereals and pulses are important vegetarian source of minerals like zinc (Zn) and iron (Fe), however, poor digestibility impairs proper availability of micro minerals in the body. Chickpea (Cicer arietinum L.) and cowpea (Vigna unguiculata L. Walp) were selected for study as they are important pulse crops consumed worldwide. Therefore, in order to remove antinutrients and enhance bioavailability of nutrients in chickpea and cowpea, extrusion cooking was selected as a technology and its impact was studied by an in vitro method. The paper aims to discuss this issue.

Four chickpea cultivars, two desi (K 850 and PUSA 362) and two kabuli (PUSA 1108 and PUSA 1053) and one cowpea (Gomati) cultivars were selected for the study. Pulses were processed in a laboratory using a single screw food extruder. Raw and extruded pulses were analysed for antinutrients content, micronutrients content (Fe, Zn) and their bioavailability.

Extrusion cooking significantly decreased phytate in all cultivars of chick pea and cowpea with highest reduction (72.92 per cent) in PUSA 362; similarly, tannin and trypsin inhibitor decreased by 87.5 and 71.54 per cent, respectively, in Gomati cultivar of cowpea. All cultivars showed significant increase in protein digestibility. Iron bioavailability in all samples enhanced significantly; however, only 50 per cent cultivars (K 850, PUSA 362 and PUSA 1108) showed improvement in Zn bioavailability.

The present research therefore brought the outcome as an enhanced in vitro protein digestibility and bioavailability of micro mineral and protein in certain pulses having minimized antinutrients. Therefore, it is concluded that extrusion cooking is an effective tool in enhancing protein and micro mineral bioavailability.

This study aims to determine the effect of online social networks on university students’ environmentally responsible behavior (ERB). This research aimed to develop and test a behavioral model in the context of online social networks, where students’ attitudes, knowledge and behavior influence their ERB.

This study used a quasi-experiment with a pretest-posttest design and a random parallelization control group. The research used a questionnaire to assess ERB, environmental attitudes and environmental knowledge. The researcher randomly assigned 120 students to an experimental and a control group of equal size. Both groups initially completed a pretest. The experimental group was trained in environmental issues over four months (an academic semester) via an online social network.

The findings indicated that the social network had a significant effect on motivating ERB. Additionally, it improved environmental attitudes. According to the results, online social networks such as Facebook can significantly aid in teaching and learning environmental issues in formal academic settings.

Online social networks facilitated significant cognitive progress in environmental education. The primary objective is to educate students about ERB.

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.

Given the relative importance of the Shari’ah supervisory boards (SSBs) in Islamic banks’ (IBs’) performance, this study aims to examine the impact of SSB diversity on IBs’ performance from the stakeholders’ perspective in the context of Pakistan.

Random-effects model and generalized method of moment are used to investigate the impact of SSB diversity on IBs’ performance across a panel data of 22 Islamic banks in Pakistan from 2005 to 2020 inclusive.

The findings of this study show that SSB size, SSB relevant educational background diversity, bank’s size and bank’s stability have a positive impact on IBs’ performance. In contrast, SSB age, nationality and cross-membership diversities have a negative impact on IBs’ performance. Moreover, SSB gender, tenure and general educational diversities have no significant impact on IBs’ performance.

SSB diversity and IBs practices are different across different jurisdictions. This study is conducted on IBs in Pakistan because of data constraints; thus, the results of this study may not be generalizable to other countries' IBs.

In structuring the SSBs’ framework, the regulatory authorities and policymakers should consider mandating an ideal SSB size and hiring relevant qualified members with low cross-membership to improve IBs' performance. Thus, the structure potentially attracts Muslim stakeholders, enhances their satisfaction and improves IBs' performance.

Having diversified members in the SSB, IBs equally benefit both individual and group stakeholders in society. Diversity in SSB members enhances IBs' performance and the social welfare of various stakeholders in society.

To the best of the authors' knowledge, this is the first empirical research that examines comprehensively the impact of SSB structural and demographic diversities on IBs' performance in the context of Pakistan. This paper contributes to the unique Shari’ah governance structure in the context of Pakistan. Additionally, this study may serve to assist IBs’ stakeholders in better comprehending the SSB practices of IBs in Pakistan.

The accelerating business transformation through Industry 4.0 (I4.0) is expected to create significant value in the manufacturing industry by delivering considerably high productivity, superior quality, better efficiency and effectiveness. However, its evolutionary processes have far-reaching challenging for humanity. This has triggered a need to analyze the impact of I4.0 on various people-centric variables (PCVs).

This paper attempts to analyze the interrelationship dynamics between the PCVs in the current digital-industry ecosystem using a focus-group approach and causal loop diagrams. Application of the SWARA (stepwise weight assessment ratio analysis) methodology has provided its prioritized ranking in terms of importance.

The study has highlighted that I4.0 has a significant influence on five of the 13 PCVs – human quality of life, digital dexterity, high-skilled talent, low-skilled employment and creativity which contribute to 80% of the total impact.

The prioritized weights of the human factors from the SWARA approach have facilitated the assessment of the Human Resource Development Index (HRDI). The study is also contributing in enriching the literature on the human impact of the growing I4.0 and triggered the researchers to study further its adverse impact on critical human factors.

1. The paper pertains to debates on a very critical issue of impact of integration of the current intelligent digital technologies in manufacturing and services to transform businesses to be more flexible and agile.

2. This paper features I4.0 as a technology that allows integration of new products in the existing production lines, one-off manufacturing runs and high mix manufacturing.

3. The paper also highlights major adjustments in operational activities, processes, supply chain, and organizational redesign due to I4.0 adoption.

4. The current research study has significantly enriched the literature on the I4.0 impact on people-centric variables (PCVs) using the SWARA method. The use of the Causal Loop Diagram has very aptly brought out the type of causality (polarity) between the different PCVs in the growth of I4.0.

The paper pertains to debates on a very critical issue of impact of integration of the current intelligent digital technologies in manufacturing and services to transform businesses to be more flexible and agile.

This paper features I4.0 as a technology that allows integration of new products in the existing production lines, one-off manufacturing runs and high mix manufacturing.

The paper also highlights major adjustments in operational activities, processes, supply chain, and organizational redesign due to I4.0 adoption.

The current research study has significantly enriched the literature on the I4.0 impact on people-centric variables (PCVs) using the SWARA method. The use of the Causal Loop Diagram has very aptly brought out the type of causality (polarity) between the different PCVs in the growth of I4.0.

The purpose of this paper is to develop an efficient brain tumor detection model using the beneficial concept of hybrid classification using magnetic resonance imaging (MRI) images Brain tumors are the most familiar and destructive disease, resulting to a very short life expectancy in their highest grade. The knowledge and the sudden progression in the area of brain imaging technologies have perpetually ready for an essential role in evaluating and concentrating the novel perceptions of brain anatomy and operations. The system of image processing has prevalent usage in the part of medical science for enhancing the early diagnosis and treatment phases.

The proposed detection model involves five main phases, namely, image pre-processing, tumor segmentation, feature extraction, third-level discrete wavelet transform (DWT) extraction and detection. Initially, the input MRI image is subjected to pre-processing using different steps called image scaling, entropy-based trilateral filtering and skull stripping. Image scaling is used to resize the image, entropy-based trilateral filtering extends to eradicate the noise from the digital image. Moreover, skull stripping is done by Otsu thresholding. Next to the pre-processing, tumor segmentation is performed by the fuzzy centroid-based region growing algorithm. Once the tumor is segmented from the input MRI image, feature extraction is done, which focuses on the first-order and higher-order statistical measures. In the detection side, a hybrid classifier with the merging of neural network (NN) and convolutional neural network (CNN) is adopted. Here, NN takes the first-order and higher-order statistical measures as input, whereas CNN takes the third level DWT image as input. As an improvement, the number of hidden neurons of both NN and CNN is optimized by a novel meta-heuristic algorithm called Crossover Operated Rooster-based Chicken Swarm Optimization (COR-CSO). The AND operation of outcomes obtained from both optimized NN and CNN categorizes the input image into two classes such as normal and abnormal. Finally, a valuable performance evaluation will prove that the performance of the proposed model is quite good over the entire existing model.

From the experimental results, the accuracy of the suggested COR-CSO-NN + CNN was seemed to be 18% superior to support vector machine, 11.3% superior to NN, 22.9% superior to deep belief network, 15.6% superior to CNN and 13.4% superior to NN + CNN, 11.3% superior to particle swarm optimization-NN + CNN, 9.2% superior to grey wolf optimization-NN + CNN, 5.3% superior to whale optimization algorithm-NN + CNN and 3.5% superior to CSO-NN + CNN. Finally, it was concluded that the suggested model is superior in detecting brain tumors effectively using MRI images.

This paper adopts the latest optimization algorithm called COR-CSO to detect brain tumors using NN and CNN. This is the first study that uses COR-CSO-based optimization for accurate brain tumor detection.

The purpose of this paper is to provide a systematic literature review on the technological aspects of smart cities and to give insights about current trends, sources of research, contributing authors and countries. It is required to understand technical concepts like information technology, big data analytics, Internet of Things and blockchain needed to implement smart city models successfully.

The data were collected from the Scopus database, and analysis techniques like bibliometric analysis, network analysis and content analysis were used to obtain research trends, publications growth, top contributing authors and nations in the domain of smart cities. Also, these analytical techniques identified various fields within the literature on smart cities and supported to design a conceptual framework for Industry 4.0 adoption in a smart city.

The bibliometric analysis shows that research publications have increased significantly over the last couple of years. It has found that developing countries like China is leading the research on smart cities. The network analytics and article classification identified six domains within the literature on smart cities. A conceptual framework for the smart city has proposed for the successful implementation of Industry 4.0 technologies.

This paper explores the role of Industry 4.0 technologies in smart cities. The bibliometric data on publications from the year 2013 to 2018 were used and investigated by using advanced analytical techniques. The paper reviewS key technical concepts for the successful execution of a smart city model. It also gives an idea about various technical considerations required for the implementation of the smart city model through a conceptual framework.

Significant numbers of business process management (BPM) projects fail. Their failure is attributed toward many factors. Among them, low quality of BPM is one reason. Some of the tasks in BPM have their roots in business process reengineering (BPR). The literature has cited many different critical success and failure factors for quality BPM and BPR. Lack of software tools is one of the technology-oriented factors that results in poor BPM and BPR. This paper aims to build a generic feature set offered by software tools for process modeling their analysis implementation and management. It presents an objective analysis in identifying weaknesses and strengths of these tools, primarily for BPM.

A method is proposed to evaluate the quality of process reengineering and management delivered by software tools. It consists of four phases: feature extraction, tool selection, data extraction and tool evaluation.

The data gathered is quantified to test research hypotheses, the results are statistically significant and highlight multiple areas for future improvements. Moreover, the cluster visualizations created also help to understand the strengths and weaknesses of BPM/BPR tools.

Despite the research approach used, there is a chance of subjectivity when it comes to evaluating different tools.

The paper includes implications for practitioners and researchers for choosing appropriate software tool for process modeling, analysis, implementation and management, matching their requirements with BPM and BPR. It also identifies features that are missing in these tools.

This paper provides a comprehensive analysis of BPM and supporting tools, relates them to key stages of BPM life cycle and BPR methodologies. It also identifies various areas for further development in these tools.

The dyeing of cellulosic and proteinous fibers with natural and synthetic colorants usually needs large amounts of metal salts to promote the dyeing procedure. To get rid of the necessity to use metal salts, plasma treatment and subsequent attachment of chitosan biopolymer were considered as green processes for surface functionalization of wool and cotton. The purpose of this paper is to investigate the effect of oxygen plasma treatment and attachment of chitosan on the dyeability of wool and cotton fabrics using walnut and weld as model natural dyes, as well as C.I. reactive blue 50 and C.I. acid blue 92 as model synthetic dyes.

Wool and cotton fabrics were modified with oxygen plasma and coated with chitosan solution. The un-modified and modified samples were dyed with the above-mentioned dyes under constant conditions. The color strength, color coordinates and fastness properties of the dyed samples were determined and compared.

The results showed that oxygen plasma treatment could improve the dyeability and fastness properties of wool and cotton fibers when dyed with all of the above-mentioned dyes. Attachment of chitosan to the plasma-treated samples significantly improved the dyeability of wool and cotton fibers with walnut, acid and reactive dyes. The fastness properties of the dyed samples were enhanced by plasma treatment and chitosan coating.

This study uses plasma treatment as an environmentally friendly pre-treatment for attachment of chitosan on wool and cotton. This process improved the dyeing properties of both fibers. The use of metal salts in not needed for dyeing of wool and cotton according to the investigated process.

The investigation of fluid flow and heat transfer is incredibly significant in the present era, particularly in the engineering and manufacturing industries. Hence, this study aims to concern with analysing the unsteady stagnation point flow towards a permeable stretching/shrinking Riga plate of Al₂O₃-Cu/H₂O. The effect of thermal radiation on the boundary layer flow is also taken into account.

The multi-variable differential equations with partial derivatives are transformed into third-order and second-order differential equations by applying appropriate transformations. The reduced mathematical model is solved in the MATLAB system by using the bvp4c procedure. This solution approach is capable of producing multiple solutions once the necessary assumptions are provided.

The results of various control parameters were analysed, and it has been observed that raising the solution viscosity from 0% to 0.5% and 1% improves the coefficient of skin friction and thermal conductivity by almost 1.0% and 1.9%. Similar response and observation can be witnessed in the addition of modified Hartmann number where the highest values dominate about 10.7% improvement. There is a substantial enhancement in the heat transfer rate, approximately 1.8% when the unsteadiness parameter leads around 30% in the boundary layer flow. In contrast, the increment in thermal radiation promotes heat transfer deterioration. Further, more than one solution is proven, which invariably leads to a stability analysis, which validates the first solution’s feasibility.

The present results are new and original for the study of flow and heat transfer on unsteady stagnation point flow past a permeable stretching/shrinking Riga plate in Al₂O₃-Cu/H₂O hybrid nanofluid with thermal radiation.