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Apricots are not only nutritionally-rich but also possess pharmacological significance owing to their high antioxidant activity, and they are rich in vitamins, fibers, bioactive phytochemicals and minerals. Because of its immense organoleptic characteristics, apricot juice (AJ) is well accepted; however, it has a limited shelf-life, thereby demanding it to be converted into other shelf-stable form. One of the approaches is converting this juice into dehydrated powder. Amongst the various dehydration techniques available, spray drying is usually preferred; however, it involves the use of several independent variables, which need to be optimized, thus prompting to optimize the process to obtain spray dried apricot powder (SDAP) with improved quality.

The spray-drying process of apricot juice was done using the response surface approach. The process variables included the inlet air temperature of 135–220°C, gum arabic concentration of 4–25%, feed flow rate of 124–730 mL/h, feed total soluble solids (TSS) of 10-30°Brix and atomization speed of 11,400–28,000 rpm. The dependent responses were powder yield, hygroscopicity, solubility, moisture content, carotenoids (CT), ascorbic acid (AA), radical scavenging activity (RSA), lightness, wettability, bulk density, particle density and porosity.

Amongst all independent variables, inlet air temperature had most predominant impact on all the investigated responses. The optimum processing conditions for development of apricot powder with optimum quality were 190°C inlet air temperature, 18.99% gum arabic, 300.05 mL/h feed flow rate, 24°Brix feed TSS and 17433.41 rpm atomization speed. The experimental values were found to be in agreement with the predicted values, indicating the suitability of models in predicting optimizing responses of apricot powder. Flowability as Carr's index (CI) (22.36 ± 1.01%) suggests fair flow of powder. Glass transition temperature of powder was 57.85 ± 2.03°C, which is much higher than that of ambient, suggesting its better shelf stability.

To the best of author's knowledge, very limited or very few studies have been carried out on the spray-drying process for the manufacture of SDAP. The results of this investigation will open up new horizons in the field of food industry in the Union Territory of Jammu and Kashmir, India or elsewhere in the apricot-growing areas of India.

The purpose of this study are to identify the factors influencing the adoption of big data in libraries, determine the challenges causing the hindrance of big data implementation and reveal the best practices for the efficient adoption of big data in libraries.

A systematic literature review was applied to address the objectives of the study. Twenty-two studies published in peer-reviewed journals were selected to conduct the study.

The findings of the study revealed that decision-making, service enhancement, professional development and preservation factors influenced the adoption of big data technologies in libraries. The study also displayed that challenges of infrastructure, technical skills, data management and legal considerations caused barriers to the adoption of big data in libraries. Results also revealed that training and professional development, guidelines and policies establishment, leadership and strategic planning and resource allocation proved fruitful in the efficient adoption of big data applications in libraries.

The study offers theoretical implications for future investigators through the provision of innovative literature on the factors, challenges and best practices associated with big data in the context of librarianship. The study has also provided practical implications for management bodies by offering guidelines for the successful adoption of big data in libraries.

Snack industry is one of the fastest growing food sectors globally, and people are nowadays conscious about intake of healthy snacks on regular basis. There is enormous variety of ready-to-snacks available in the market. Brown rice though highly nutritious in comparison to polished rice is consumed meagerly by masses. Each raw material/ingredient used in extrusion cooking requires specific control of processing variables to meet acceptable product characteristics and consumer demands, which in turn necessitates the need to optimize the conditions for development of brown-rice-based snacks. The aim of this study was to optimize the extrusion cooking conditions for development of brown-rice-based extrudates.

Extrusion conditions were optimized through design expert using central composite rotatable design (CCRD) experimental design. The effect of feed moisture (10–22%), screw speed (215–385 rpm) and barrel temperature (95–160 °C) on specific mechanical energy (SME), bulk density (BD), water absorption index (WAI), water solubility index (WSI), expansion ratio (ER), breaking strength (BS) and instrumental color (L*, a*, b*) was evaluated.

All the system and product responses were significantly (p < 0.01) affected by independent variables. Regression models obtained were highly significant with high coefficient of determination (R² = 0.992). The optimum extrusion conditions obtained by numerical optimization for development of snacks were moisture content of 12%, screw speed of 350 rpm and temperature of 133 °C. The vitamin B₁ content of brown-rice-based snacks was 0.45 mg/100 (50% of RDA) whereas no vitamin B₁ was detected in white-rice-based snacks used as control.

The developed snacks contain 0.45 mg/100 g of vitamin B₁. If a person on an average consumes 150 g of snacks in a day, 50% of RDA (1.2 mg/day) for vitamin B₁ can be sufficed. Therefore, developed snacks can prove to be a viable vehicle to reduce the vitamin B₁ deficiency burden among the target population. Large-scale production and consumption of such type of snacks could improve the nutritional status of vitamin B1 deficient people. Furthermore, it can also provide a good opportunity for snack industry to develop nutritious snacks through utilization of brown rice.

Brown rice flour contains nutrients such as iron, calcium, zinc, sodium and vitamin B₁ in appreciable portions and was thus explored for development of nutritious snacks. Moreover, developed snacks recorded an overall acceptability of 4.70 out of 5, which depicts it is acceptable for mass production and consumption.

The coronavirus (COVID-19) pandemic has led to a surge in demand for health-care facilities, medicines, vaccines and other health-care items. The purpose of this study is to investigate different facets of integrated Green Lean Six Sigma and Industry 4.0 approach in the context of COVID-19 for better healthcare management. Integrating Green Lean Six Sigma (GLSS) and Industry 4.0 (I4.0) has the potential to meet the modern demand of health-care units and also leads to improving the quality of inpatient care with better safety, hygiene and real-time diagnoses. A systematic review has been conducted to determine the tools/techniques, challenges, application areas and potential benefits for the adoption of an integrated GLSS-I4.0 approach within health-care facilities from the perspective of COVID management. Further, a conceptual framework of integrated GLSS-I4.0 has been proposed for better COVID management.

To conduct the literature review, the authors used the preferred reporting items for systematic reviews and meta-analysis and covers relevant papers from the arrival of COVID-19. Based on the systematic understanding of the different facets of the integrated GLSS-I4.0 approach and through insights of experts (academicians and health-care personnel), a conceptual framework is proposed to combat COVID-19 for better detection, prevention and cure.

The systematic review presented here provides different avenues to comprehend the different facets of the integrated GLSS-I4.0 approach in different areas of COVID health-care management. In this study, the proposed framework reveals that the Internet of Things, big data and artificial intelligence are the major constituents of I4.0 technologies that lead to better COVID management. Moreover, integration of I4.0 with GLSS aids during different stages of the COVID management, right from diagnosis, manufacture of items and inpatient and outpatient care of the affected person.

This study provides a significant knowledge database to the practitioners by understanding different tools and techniques of an integrated approach for better COVID management. Moreover, the proposed framework aids to grab day-to-day information from the affected people and ensures reduced hospital stay with better space utilization and the creation of a healthy environment around the patient. This inclusive implementation of the proposed framework will enhance knowledge base in medical areas and provides different novel prospects to combat other medical urgencies.

To the best of the authors’ knowledge, this study is the first of its kind to review different facets of the integrated GLSS-I4.0 approach with a view of the COVID health-care perspective and provides a conceptual framework.

This paper aims to explore the factors influencing customers' attitudes and behaviours, specifically in terms of affective satisfaction, participation behaviour, and word-of-mouth, within the restaurant industry, with a focus on both tangible and intangible elements. Additionally, the study seeks to identify the dual mediating role of customer affective satisfaction in this relationship.

In this exploratory study, SEM-VB was utilized to examine data from 312 valid respondents who completed a face-to-face questionnaire using a quantitative methodology. The respondents were targeted at restaurants that serve comparable food and beverages for a similar socioeconomic class.

The findings reveal that perceived value, physical appearance, and standardization significantly contribute to customer affective satisfaction, which, in turn, positively influences their participation behaviour and word-of-mouth.

Practically, restaurant managers can enhance customer experiences and boost positive word-of-mouth by fostering affective satisfaction and encouraging interactive customer participation.

The novel concept of “affective satisfaction” contributes to restaurant management literature by identifying its tangible and intangible drivers and uncovering its outcomes in participation behaviour and word of mouth. By combining numerous factors and investigating the mediating function of affective satisfaction and based on the theory of Expectancy-Disconfirmation, this study adds to the theoretical understanding of what drives the affective satisfaction and word-of-mouth of casual dining restaurants’ customers.

The increased health-care costs, improved service quality and sustainability-oriented customer demand have forced the health-care sector to relook their current process. The present work deals with the identification, analysis and prioritization of just in time (JIT) enablers in the health-care sector.

JIT leads to waste reduction, improves productivity and provides high-quality patient care. The practical implementation of JIT depends on vital factors known as enablers. The enablers have been found through the comprehensive literature review and prioritized using responses from different health-care facilities of the national capital region of India. Grey relational analysis (GRA) has been used in the present study to rank enablers and ranks were further validated using the fuzzy technique for order of preference by similarity to ideal solution (TOPSIS) and sensitivity analysis.

It has been found that top management support, teamwork and real-time information sharing are the most significant enablers of JIT in health care with grey relational grades 0.956, 0.832 and 0.718, respectively. The corresponding closeness coefficients of the fuzzy TOPSIS for the enablers were found as 0.875, 0.802 and 0.688, respectively. The findings of the present research work will facilitate the health-care organizations to implement a comprehensive JIT approach that further leads to improved patient care at a low cost.

The present study is unique in terms of the exploration of the readiness measures or enablers of JIT using GRA and fuzzy TOPSIS. The findings of the present research work will facilitate the health-care organizations to optimize their resources for better patient care.