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This article proposes a novel approach to managing inventory by incorporating machine learning techniques to handle imperfect deteriorating products under green investment technology. The shortages are permitted and partially backlogged. Due to uncertainty, deterioration rate and defective percentage in quantity in the received lot are considered fuzzy variables. This study aims to determine optimal ordering quantity and replenishment period to minimise the total average cost with carbon emission cost. Decision Tree Classifier algorithm is used to demand forecast seasonally. The total fuzzy cost functions defuzzify by applying sign distance approach method. A numerical example is taken to illustrate the proposed model. A comparative analysis has been studied between fixed demand and month-wise forecasted demand. The study highlights the importance of forecasted demand in the inventory system and establishes methodology to get direct month-wise forecasted demand. Finally, the sensitivity analysis performs to determine more sensitive parameters and provides managerial insights. [ABSTRACT FROM AUTHOR]

In today's environment, organizations utilise Machine Learning based-models to keep stocks depending on the demand for a particular type of product. This article develops an inventory model considering the imperfect deteriorating product in a fuzzy environment. The shortages are allowed and partially backlogged. Since the deterioration rate and defective percentage in quantity in the received lot may not be predicted precisely because it depends on many uncertain situations, therefore both are considered fuzzy variables. This study aims to determine the optimal ordering quantity and replenishment period to optimize (minimize) the average overall cost with carbon emission cost. The defuzzification process is done using the sign distance approach method. A methodology based on Machine Learning is used to demand forecast seasonally. Some numerical examples are taken to validate the proposed mathematical model. The findings demonstrate the generation of direct month-wise predicted demand for deteriorating products based on the input of the month value, enabling organizations to optimize their inventory management according to forecasted demand. A comparative analysis is conducted between fixed and month-wise forecasted demand by highlighting the advantages of machine learning-based forecasting approaches. Sensitivity analysis performs to examine the behaviour of several parameters on an optimal solution and provides some managerial insights. [ABSTRACT FROM AUTHOR]

The Covid-19 epidemic has caused substantial obstacles to the supply network globally. Hence there is urgency and necessity to build a model for cash flow in the chain of demand and supply system. This research suggests an inventory model to assist retailers in determining the optimal ordering quantity and replenishment cycle to reduce the total cost in different payment cases. The current study looks toward a partial advance and delays in the payment system considering time-sensitive demand, shortage, and partial backlogging for instantaneous deteriorating items. During the financial crisis, the partial advance and delay-in-payment strategy is planned to keep orders flowing from retailers to suppliers and customers to retailers. The impact of advanced and delayed payments on the total cost of a retailer is examined. To exemplify the model's application, numerical examples are used. A sensitivity study of critical parameters has been done to identify more sensitive parameters which reveal the clear depiction of present problems. [ABSTRACT FROM AUTHOR]

Sustainable integrated inventory management policy focuses on reducing the environmental impact of the manufacturing and transport sector. This study develops an integrated single-manufacturer single-buyer inventory model for substitutable deteriorating items considering transport and industry carbon emissions. This article categorizes carbon emissions into two parts: direct and indirect emissions. We also assume two mutually substitutable items, and substitution is considered on the buyer's side. If one of the items is out of stock, the demand for that item can be partially satisfied by the stock of the other item; else, demand will be lost. The purpose of this study is to minimize the integrated cost of the supply chain with total carbon emissions produced by industry and transport sectors and to determine the optimal number of deliveries, order level and carbon emission quantity. A solution procedure is developed to find the optimal values of the policy. Numerical experiments and sensitivity analyses are presented to demonstrate the proposed model. [ABSTRACT FROM AUTHOR]

India has a long history of policies that aim to improve rural drinking water services, through various combinations of state support and decentralization that face deeply rooted institutional challenges. These include debates about: the duty of the state to provide rural drinking water supply; tension over the role of central, state, and local governments; and frequent changes in policy and senior public officials that disrupt long-term implementation. Some water governance theorists have described policy-making in this context as a pragmatic process of bricolage, that is, of piecing together practical opportunities for improvement where possible. This paper takes a macrohistorical geographic approach to these institutional problems, with an emphasis on northern India. It shows that ancient sources dating back to the Arthashastra have underscored the role of the state in developing water supplies for the people. Subsequent regimes have advocated various combinations of centralized and local responsibility to fulfill drinking water needs. We show that frequent rotation of senior public officials was actually systematized in the sixteenth century Mughal empire. Changing roles of India's five levels of center, state, district, block, and village government have a half-millennium-long history, evolving through the dramatically different Mughal, Maratha, colonial, and post-colonial contexts. Devolution policies were frequently changed in the colonial period. Independence in 1947 and a constitutional amendment in 1993 increased emphasis on devolution to Panchayati Raj Institutions at district, block, and village levels, but without resolving the functional and structural relations among them. This macrohistorical geographic perspective on water institutions offers insights into current issues and prospects for drinking water reform in India. [ABSTRACT FROM AUTHOR]

Salmonella is a well-known food-borne pathogen causing disease in humans and animals worldwide. Peptidyl-prolyl isomerases (PPIases) catalyse the cis–trans isomerisation of prolyl bound, which is a slow and rate-limiting step of protein folding. Here, we present the biochemical and molecular characterisation of a novel multi-domain parvulin-type, PPIases-C from the pathogenic bacteria Salmonella Typhimurium, annotated as rPpiC. The recombinant plasmid PpiC_pET28c was used for protein induction using 1.5 mM concentration of isopropyl-β-D-thiogalactopyranoside at 30 °C. Subsequently, the protein was identified by using the LC–MS technique showing high match score and sequence coverage with available PPIases-C proteins database. Using the succinyl-ala-phe-pro-phe-p nitroanilide as a substrate, Vmax of the enzyme was found to be 0.8187 ± 0.1352 µmoles/min and Km = 1.6014 ± 0.8449 µM, respectively. With this, we conclude that rPpiC protein is an active form of protein from Salmonella Typhimurium and plays an important role in protein folding. [ABSTRACT FROM AUTHOR]