Search

In this research article, we proposed an inventory model for the replenishment policy. The focus of our research article is on the companies that frequently deal with backorders. An advanced inventory model considering back order has been proposed the results highlight the dynamic nature of the system, with optimal values achieved in different cycles. In this model, replenishment policy is given and to lower the economic ordering cost, we used new parameters such as price-sensitive demand, complete back ordering, and backorder is taken as a quadratic function as well as linear backorder with shortages in a finite planning horizon. The result is discussed for both backorders (linear and quadratic), to minimize the total cost obtained using the Hessian matrix to be positive definite. Software 'MATHEMATICA VERSION 12' has been used for the solution of the proposed model by using numerical iterative method. For different parameters, different tables are provided. The outcomes of the sensitivity analysis with the help of tables and graphs are depicted. Finally, we have discussed the conclusion and practical implications. [ABSTRACT FROM AUTHOR]

Cardiovascular diseases continue to challenge global health, demanding innovative therapeutic solutions. This review delves into the transformative role of mesenchymal stem cells (MSCs) in advancing cardiovascular therapeutics. Beginning with a historical perspective, we trace the development of stem cell research related to cardiovascular diseases, highlighting foundational therapeutic approaches and the evolution of cell-based treatments. Recognizing the inherent challenges of MSC-based cardiovascular therapeutics, which range from understanding the pro-reparative activity of MSCs to tailoring patient-specific treatments, we emphasize the need to refine the pro-regenerative capacity of these cells. Crucially, our focus then shifts to the strategies of the fourth generation of cell-based therapies: leveraging the secretomic prowess of MSCs, particularly the role of extracellular vesicles; integrating biocompatible scaffolds and artificial sheets to amplify MSCs' potential; adopting three-dimensional ex vivo propagation tailored to specific tissue niches; harnessing the promise of genetic modifications for targeted tissue repair; and institutionalizing good manufacturing practice protocols to ensure therapeutic safety and efficacy. We conclude with reflections on these advancements, envisaging a future landscape redefined by MSCs in cardiovascular regeneration. This review offers both a consolidation of our current understanding and a view toward imminent therapeutic horizons. [ABSTRACT FROM AUTHOR]

Due to tougher carbon restrictions and regulations, businesses have been researching approaches to decrease the amount of carbon emissions throughout the inventory supply process and achieve sustainable development. The two most common approaches are (i) decentralized, which involves implementing a carbon tax or cost for emitting carbon, and (ii) centralized, which includes introducing an emissions trading (cap-and-trade) mechanism. Within this research, we optimize a two-stage supply management system under FPH(finite planning horizon) while taking into consideration these two policies. Using a linear time and inventory-dependent demand model, we investigated various techniques within a specific time frame. We created and solved two distinct MINLP (Mixed Integer Non-Linear Programming) approaches for each carbon strategy. These models can assist businesses/firms in determining the minimum overall cost, optimal order quantity, optimal replenishment time, and replenishment cycles. Using mathematical tools, our sensitivity evaluations indicate that organizations can reduce overall projected emissions and costs by making parameter variations under both carbon regimes. We additionally showed that while both approaches optimize the overall supply chain cost, the order quantity and total emissions remain constant. [ABSTRACT FROM AUTHOR]

This research introduces a decentralized supply chain optimization model that incorporates blockchain technology. The model, implemented through an optimized iterative method, integrates ordering, holding, and purchasing costs to offer a comprehensive view of total costs for both retailers and suppliers. The model's uniqueness and optimality are demonstrated through theoretical analysis, highlighting the optimal ordering interval as the sole solution to the derived equation. Employing an algorithmic methodology, optimal replenishment schedules are efficiently calculated using Wolfram Mathematica 13.0. A numerical example and sensitivity analysis illustrate the impact of key parameters on replenishment cycles, order quantity, and costs, encompassing wholesale prices, demand uncertainty, and holding/ordering costs. Managerial insights derived from sensitivity analysis guide decision-makers in optimizing supply chain management, emphasizing strategies such as wholesaler price balance and strategic blockchain information management. In essence, this research contributes to an enhanced understanding of decentralized supply chain models with blockchain, providing a systematic decision-making optimization approach for increased efficiency and resilience. [ABSTRACT FROM AUTHOR]

Achieving sustainability within today's competitive environment is highly challenging. Therefore, we proposed a supply chain inventory replenishment model incorporating a finite planning horizon. So, to enhance their profit and lessen the total cost and carbon, this research study examines the investment in green (carbon offset) and preservation technologies. Additionally, we analyzed the trade credit duration granted by suppliers to the retailers. Carbon offsets/green technology represent a prevalent and significant measure to reduce carbon emissions. Time becomes a critical factor influencing demand rates in this context, while the degradation of materials affects a vast number of business sectors. Therefore, the cost of investing in preservation or green technology to control the deterioration of the materials, and reduce environmental emissions, the cost for ordering, the holding cost, and the replenishment cycle duration are all calculated. Consequently, a numerical iterative algorithm is prepared to identify the optimized solution for the supply chain approach for inventory control and management challenges. The optimality and uniqueness of the parameters of the proposed research study are furnished with a theoretical, mathematical, tabular, and pictorial analysis. Also, proposed research studies are provided with managerial implications that provide practical insights for industry practitioners. In conclusion, this research not only contributes valuable theoretical insights but also offers a tangible framework applicable to real-world scenarios. [ABSTRACT FROM AUTHOR]

Extrapulmonary involvement of coronavirus-19 disease (COVID-19) is being documented and studied at an increasing frequency. Specifically, gastrointestinal involvement is hypothesized to occur due to cellular entry via the ACE2 receptor found in gastrointestinal epithelial cells, causing inflammation and symptoms such as abdominal pain, nausea/vomiting, and diarrhea. We present the case of a 45-year-old female with recent severe COVID-19 infection and early gastrointestinal symptoms who later presented with worsening abdominal pain, nausea, vomiting, and constipation after initial discharge. She was diagnosed with a large bowel obstruction and underwent urgent exploratory laparotomy, which revealed a stricture of the distal transverse colon. Following segmental resection, the patient experienced resolution of symptoms. We hypothesize that this patient's colonic stricture arose secondary to severe COVID-19-induced bowel inflammation. [ABSTRACT FROM AUTHOR]