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The purpose of this paper is to eliminate the medicine stock-out problem by building an optimum medicine stock in rural healthcare centers in India.

Data associated with inflow and outflow of a specific medicine (folic acid tablets) arer collected from all consecutive supply chain stages during the survey. While conducting the survey, it is found that several medicines are out of stock owing to uncertain lead time and demand. Integrating with quantity discount and min–max (s, S) inventory policy, two models are developed using system dynamics: one is Model 1 with constant lead time and uncertain demand, and the other is Model 2 with both uncertain lead time and demand.

Both models are simulated for a period of one year on Stella 9.1 platform. The results are compared with actual data, and the comparison shows significant improvement of the medicine stock at all downstream stages, while maintaining a certain safety stock. Further, Model 2 suggests a larger stock than Model 1 at each point of time.

Despite numerous issues, the stocks of medicine in rural healthcare systems can be improved as suggested by the models. The models depict the behavior of inventory stock at each stage of the supply chain and act as a function of time that could be used in the form of a prediction tool for the policymakers.

This paper is one of the first papers that had developed the model of the medicine supply chain in rural parts of a developing country. It provides a generic framework for the stock assessment and improvement throughout the supply chain.

The already-strained vaccine supply chain (VSC) of the expanded program for immunization (EPI) require a more robust and structured distribution network for pandemic/outbreak vaccination due to huge volume demand and time constraint. In this paper, a lean-agile-green (LAG) practices approach is proposed to improve the operational, economic and environmental efficiency of the VSC.

A fuzzy decision framework of importance performance analysis (IPA)–analytical hierarchy process (AHP)–technique for order for preference by similarity in ideal solution (TOPSIS) has been presented in this paper to prioritize the LAG practices on the basis of the influence on performance indicators. Sensitivity analysis is carried out to check the robustness of the presented model.

The derived result indicates that sustainable packaging, coordination among supply chain stakeholders and cold chain technology improvement are among the top practices affecting most of the performance parameters of VSC. The sensitivity analysis reveals that the priority of practices is highly dependent on the weightage of performance indicators.

This study's finding will help policymakers reframe strategies for sustainable VSC (SVSC) by including new management practices that can handle regular immunization programs as well as emergency mass vaccination.

To the best of the authors' knowledge, this is the first study that proposes the LAG framework for SVSC. The IPA–Fuzzy AHP (FAHP)–Fuzyy TOPSIS (FTOPSIS) is also a novel combination in decision-making.

The purpose of this paper is to provide an extensive examination and analysis of the current literature on the use of blockchain technology in courts. The paper aims to explore the potential benefits of implementing blockchain technology in courts, such as increasing transparency and accountability, improving the efficiency of court procedures and enhancing the security of court records. Additionally, the paper intends to identify the challenges and limitations of using blockchain technology in courts and propose potential solutions to overcome these obstacles. The ultimate goal is to provide a comprehensive understanding of the potential applications and implications of blockchain technology in the context of the court system.

The research design of this study is qualitative, involving a thorough examination and analysis of existing literature on the use of blockchain technology in courts. The data collection procedure involves gathering information from various sources, such as academic publications, official reports and other relevant records. Data analysis is conducted using a thematic analysis approach, which identifies and categorizes recurring themes that emerge from the data. This approach ensures that the results are credible, dependable and accurate representations of the experiences of the participants. By using these methodologies, the study is able to draw meaningful conclusions and insights into the use of blockchain technology in courts.

The major findings of this paper suggest that the implementation of blockchain technology in courts has the potential to bring significant benefits such as increased transparency, efficiency and security. The use of blockchain technology in courts can enable the creation of tamper-proof records that are immutable, secure and transparent, which can help prevent fraud, reduce costs and enhance trust in the judicial system. However, adopting this technology also poses challenges and limitations, such as interoperability, governance and scalability. Overall, the paper concludes that while there are challenges to be addressed, the benefits of blockchain technology in courts are significant and should be explored further.

The study has several limitations that need to be taken into account. Firstly, the availability of data on blockchain implementation in the court system is limited, making it challenging to provide a comprehensive analysis of the topic. Thus, the study’s findings may not be generalizable to other contexts. Secondly, the study takes a technology-centric approach and does not consider blockchain technology’s social and legal implications in court operations. Thirdly, the case studies presented in this paper are limited to a few countries. Moreover, the implementation of blockchain technology in the court system is still in its early stages and lacks standardization, technical expertise and regulatory frameworks. Lastly, uncertainty around the legal framework may hinder its widespread adoption and use.

The practical implications of this study suggest that the use of blockchain technology in courts has the potential to improve efficiency, security, transparency and accountability in the court system. It can reduce the risk of data tampering, expedite case resolution and lower the cost of legal proceedings. Therefore, this study provides a framework for courts to consider blockchain technology’s potential benefits and explore its future adoption.

The social implications of this study are significant, as the adoption of blockchain technology in the court system can have a profound impact on society. Firstly, by increasing transparency and accountability, blockchain technology can promote public trust in the court system and improve access to justice, particularly for disadvantaged communities (Liu et al., 2020). Secondly, blockchain technology can reduce the reliance on intermediaries, such as lawyers, and streamline the case management process, making legal services more accessible and affordable for the general public (Khurana, 2020). Finally, the use of blockchain technology can create a more secure and efficient court system, enhancing the overall effectiveness of the judicial system and promoting public confidence.

This study provides an original contribution to the literature by exploring the use of blockchain technology in courts from a qualitative research design perspective. While there are a growing number of studies on the potential applications of blockchain technology in various fields, this study provides a comprehensive examination of the current literature on the use of blockchain in courts, identifying the benefits and limitations of its implementation. The study’s focus on the strengths and limitations of blockchain technology and its implications in court adds to the originality of this research.

The purpose of the research is to concentrate on the most important smart metropolitan applications which are smart living, smart security and smart maintainable. In that, Power management and security is a most important problem in the current metropolitan situation.

A smart metropolitan area utilizes recent innovative technologies to improve its living, security and maintainable. The aim of this study is to recognize and resolve the difficulties in metropolitan area applications.

The main aim of this study is to reduce the metropolitan foremost energy consumption, to recharge the electric vehicles and to increase the lifetime of smart street lights.

The hybrid renewable energy street light applies smart resolutions to substructure and facilities in rural and metropolitan areas to create them well. This study will be applying smart metropolitan solar and wind turbine street light using renewable energy for existing areas. In future, the smart street light work will be implemented everywhere else.

The purpose of this paper is to identify the factors that influence hospitals’ selection by health-care insurers in India and to establish a hierarchical model representing the relationship among different factors and their influence on the entire scenario.

A survey with a set of questionnaires was conducted with different health-care insurer executives of reputed health insurance companies. The data has been gathered by using a five-point Likert scale. Their opinions were converted into a reachability matrix and an interpretive structural modeling was constructed. The final results obtained were verified by using fuzzy Matriced Impacts Croises-Multiplication Applique and Classement analysis.

The results suggested three key driving factors, National Accreditation Board for Hospitals & Healthcare Providers accreditation of the hospital, purchasing power of people in the region and national and international recognition of the hospital among the eleven factors selected for the study.

The research mainly focuses on the health insurance benefits provided by privately owned insurance companies and do not comment on any government’s mass health insurance scheme.

With a small proportion of people under the umbrella of health insurance in India, these factors will assist and expedite insurer’s effort to penetrate deep into rural and urban areas enhancing availability and escalating affordability.

This paper presents key factors responsible for better coordination between health-care systems and insurance companies.

Each individual needs to be vaccinated to control the spread of the COVID-19 pandemic in the shortest possible time. However, the vaccine distribution with an already strained supply chain in low- and middle-income countries (LMICs) will not be effective enough to vaccinate all the population in stipulated time. The purpose of this paper is to show that there is a need to revolutionize the vaccine supply chain (VSC) by overcoming the challenges of sustainable vaccine distribution.

An integrated lean, agile and green (LAG) framework is proposed to overcome the challenges of the sustainable vaccine supply chain (SVSC). A hybrid best worst method (BWM)–Measurement of Alternatives and Ranking According to COmpromise Solution (MARCOS) methodology is designed to analyze the challenges and solutions.

The analysis shows that vaccine wastage is the most critical challenge for SVSC, and the coordination among stakeholders is the most significant solution followed by effective management support.

The result of the analysis can help the health care organizations (HCOs) to manage the VSC. The effective vaccination in stipulated time will help control the further spread of the virus, which will result in the normalcy of business and availability of livelihood for millions of people.

To the best of the author's knowledge, this is the first study to explore sustainability in VSC by considering the environmental and social impact of vaccination. The LAG-based framework is also a new approach in VSC to find the solution for existing challenges.

In today's competitive market subject to various uncertainties, supply chain flexibility (SCF) arose as a potential weapon to enhance the firm's performance. This paper model the effect of SCF on automobile industry performance during sales promotional schemes (SPS), which has turned out to be one of the most important marketing tools.

In view of the literature and the expert opinion taken from an automobile OEM, the SCFs and performance measures pertaining to the SPS environment have been identified. For the purpose of ranking the SCFs with respect to the performance measures, the Interpretive Ranking Process (IRP) has been applied using the direct contact method as a means for establishing the contextual relationships between SCFs and performance measures and to draw the interpreting reasons behind them.

The findings of this study along with the validity and stability of the results assessed through the system graphs and sensitivity analysis demonstrate that flexibility at the procurement end followed by the organizational end has the highest impact on the performance of the company during SPS.

Analysis of SCFs in regard to performance measures during SPS helps improve supply chain performance and offer valuable insights to the practicing managers in decision-making. This study augments the flexibility literature, by clubbing the two independent research streams, SCF and SPS.

This study aims to investigate the corrosion behavior of stir-cast hybrid aluminum composite reinforced with CeO₂ and graphene nanoplatelets (GNPs) nanoparticulates used as cylinder liner material in the engines (automotive, aerospace and aircraft industries).

The composites were prepared using the stir-casting technique, and their microstructure and corrosion behavior was evaluated using scanning electron microscopy (SEM) and potentiodynamic polarization test, respectively.

The results showed that the addition of CeO₂ and GNPs improved the corrosion resistance of the composites, and the optimal combination of these two nanoparticles was found to be 3 wt.% CeO₂ and 3 wt.% GNPs. The enhanced corrosion resistance was attributed to the formation of a protective layer on the surface of the composite, as well as the effective dispersion and uniform distribution of nanoparticles in the matrix. The 0.031362 was noted as the lowest corrosion rate (mmpy) and was noticed in 94% Al-6061 alloy + (3 Wt.% CeO₂ + 3 Wt.% GNPs) sample at room temperature and at elevated temperatures; the corrosion rate (mmpy) was observed as 0.0601 and 0.0636 at 45 °C and 75 °C, respectively.

In the vast majority of the published research publications, either cerium oxide or graphene nanoplatelets were utilized as a single reinforcement or in conjunction with other types of reinforcement such as alumina, silicon carbide, carbon nano-tubes, tungsten carbide, etc., but on the combination of the CeO₂ and GNPs as reinforcements have very less literatures with 2 wt.% each only. The prepared hybrid aluminum composite (reinforcing 1 wt.% to 3 wt.% in Al-6061 alloy) was considered for replacing the cylinder liner material in the piston-cylinder arrangement of engines.

This research outlines the development and characterization of advanced composite materials and their potential applications in the aerospace industry for interior applications. Advanced composites, such as carbon-fiber-reinforced polymers and ceramic matrix composites, offer significant advantages over traditional metallic materials in terms of weight reduction, stiffness and strength. These materials have been used in various aerospace applications, including aircraft, engines and thermal protection systems.

The development of design of experiment–based hybrid aluminum composites using the stir-casting technique has further enhanced the performance and cost-effectiveness of these materials. The design of the experiment was followed to fabricate hybrid composites with nano cerium oxide (nCeO₂) and graphene nanoplatelets (GNPs) as reinforcements in the Al-6061 matrix.

The Al6061 + 3% nCeO2 + 3% GNPs exhibited a high hardness of 119.6 VHN. The ultimate tensile strength and yield strength are 113.666 MPa and 73.08 MPa, respectively. A uniform distribution of reinforcement particulates was achieved with 3 Wt.% of each reinforcement in the matrix material, which is analyzed using scanning electron microscopy. Fractography revealed that brittle and ductile fractures caused the failure of the fractured specimens in the tensile test.

The manufactured aluminum composite can be applied in a range of exterior and interior structural parts like wings, wing boxes, motors, gears, engines, antennas, floor beams, etc. The fan case material of the GEnx engine (currently using carbon-fiber reinforcement plastic) for the Boeing 7E7 can be another replacement with manufactured hybrid aluminum composite, which predicts weight savings per engine of close to 120 kg.

The development of hybrid reinforcements, where two or more types of reinforcements are used in combination, is also a novel approach to improving the properties of these composites. Advanced composite materials are known for their high strength-to-weight ratio. If the newly developed composite material demonstrates superior properties, it can potentially be used to replace traditional materials in aircraft manufacturing. By reducing the weight of aircraft structures, fuel efficiency can be improved, leading to reduced operating costs and environmental impact. This allows for a more customized solution for specific application requirements and can lead to further advancements in materials science and technology.

The purpose of this paper is to incorporate a multimodal biometric system, which plays a major role in improving the accuracy and reducing FAR and FRR performance metrics. Biometrics plays a major role in several areas including military applications because of robustness of the system. Speech and face data are considered as key elements that are commonly used for multimodal biometric applications, as they are simultaneously acquired from camera and microphone.

In this proposed work, Viola‒Jones algorithm is used for face detection, and Local Binary Pattern consists of texture operators that perform thresholding operation to extract the features of face. Mel-frequency cepstral coefficients exploit the performances of voice data, and median filter is used for removing noise. KNN classifier is used for fusion of both face and voice. The proposed method produces better results in noisy environment with better accuracy. In this proposed method, from the database, 120 face and voice samples are trained and tested with simulation results using MATLAB tool that improves performance in better recognition and accuracy.

The algorithms perform better for both face and voice recognition. The outcome of this work provides better accuracy up to 98 per cent with reduced FAR of 0.5 per cent and FRR of 0.75 per cent.

The algorithms perform better for both face and voice recognition. The outcome of this work provides better accuracy up to 98 per cent with reduced FAR of 0.5 per cent and FRR of 0.75 per cent.