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243 result(s) for "Pal, Ajay"
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Cu-chitosan nano-net improves keeping quality of tomato by modulating physio-biochemical responses
Minimizing the post-harvest losses in fruits and vegetables is one of the challenging tasks in agriculture. To address this issue, we report nano-net of Cu-chitosan nanoparticles (Cu-chitosan NPs) which has the ability to extend the shelf-life of stored tomato. The application of Cu-chitosan NPs (0.01–0.04%) significantly curtailed microbial decay (< 5 versus > 50% in control), physiological loss in weight (14.36 versus 28.13% in control), respiration rate (0.01173 versus 0.01879 g CO 2 kg −1  h −1 ) and maintained fruit firmness (34.0 versus 17.33 N in control) during storage. Further, these NPs significantly retarded loss of titratable acidity, retained total soluble solids, total and reducing sugars, lycopene, ascorbic acid and inhibited polyphenol oxidase. Likewise, NPs effectively preserved L * (lightness), a* (red/green) and b* (blue/yellow) values and maintained organoleptic score. Scanning electron microscopy study confirmed that Cu-chitosan NPs orchestrate into an invisible-intangible nano-net over tomato surface which may plausibly act as a potential barrier at all possible openings (stem scar, cuticle wax, lenticels, and aquaporins) to control microbial infection, moisture loss, gas exchanges and respiration rate. Overall, nano-net extended keeping quality of tomatoes up to 21 days at room temperature (27 ± 2 °C, 55 ± 2% relative humidity).
Closed-loop supply chain network design and modelling under risks and demand uncertainty: an integrated robust optimization approach
Closed loop supply chain network design (CL-SCND) is a critical economic and environmental activity. The closing of the loop to handle return, uncertainty in business environment, various supply chain risks, impact network design processes and performance of the firm in the long term. Thus, it is important to design robust and reliable supply chain structures and obtain network configurations which can always outperform the other configurations under the worst cases of risks and uncertainty. A generic closed-loop supply chain network based on mixed integer programming formulation is proposed with direct shipping to the customer from manufacturing plants as well as shipping through distribution centers under supply risks, transportation risk and uncertain demand using a robust optimization (RO) approach. A large number of numerical tests are carried out to test the performance of the model by considering a total of four levels of uncertainty for four different network structures types. The results of the tests confirm that the risk and uncertainty based integrated supply chain network models are more efficient (cost effective) than the other set of network configurations which treats the supply chain risks and uncertainty post-ante. To demonstrate the applicability of the proposed model, the case of an Indian e-commerce firm which wants to redesign its supply chain structure is presented. The results of case study show that the topology obtained from integrated treatment of risk and uncertainty called as RORU model, outperform other supply chain networks on various network performance indicators such as supply chain costs, the number of facilities open or close and the amount of products flowing through supply chain echelon. Thus, RO based mathematical modeling to address risks and its applicability for SCND for close loop supply chain is proposed, demonstrated and applied in practical cases.
Sourcing, Refining and Recycling of Rare-Earth Magnets
Permanent magnets today are used in a wide range of transportation, industrial, residential/commercial, consumer electronics, defense, domestic, data storage, wind energy, and medical markets and applications. There are five classes of commercial permanent magnet materials; however, magnets based on Nd-Fe-B account for over 60% of the global magnet production by value. They typically contain around 31 wt.% of rare earth elements (REEs), principally, Nd and Pr, plus Dy for higher-temperature performance. Nd-Fe-B magnets are forecast to grow throughout this decade, largely driven by the growth in electric vehicles of all types. However, several studies forecast a shortfall of the primary REEs from mined resources. In this paper, the sourcing, processing, and recycling of REEs are discussed. Additionally, presented are the advantages and disadvantages of the major recovery and recycling technologies for REEs.
On the nature of supply chain reliability: models, solution approaches and agenda for future research
Purpose This research aims to update the literature about the importance of reliability in supply chain (SC) and to find out the SC determinants.Design/methodology/approach This research surveys while contributing to the academic grasp of supply chain reliability (SCR) concepts. The study found 45 peer-reviewed publications using a structured survey technique with a four-step filtering process. The filtering process includes data reduction processes such as an evaluation of abstract and conclusion. The filtered study focuses on SCR and its determinants.Findings One of the major findings is that most of the study has focused on mathematical and conceptual studies. Also, this study provides the answer to a question like how can reliability be better accepted and evolved within the SC after finding the determinants of SCR.Originality/value The observed methodological gap in understanding and development of SCR was identified and classified into three categories: mathematical, conceptual and empirical studies (case studies and survey’s mainly). This research will aid academics in developing and understanding the determinants of SCR.
Risk analysis and mitigation for perishable food supply chain: a case of dairy industry
Purpose The purpose of this paper is to present a methodology to analyze the risks present in perishable food supply chain and to determine the most effective risk mitigation strategies. It is achieved by understanding the dynamics between various risks in perishable food supply chain and modeling them using interpretive structural modeling (ISM). Design/methodology/approach Four categories and 17 types of risk are established from literature and conducting brainstorming sessions with managers/engineers in Indian dairy firms. A methodology is proposed using ISM, risk priority number and risk mitigation number to prioritize risk mitigation strategy decisions for the dairy industry. Findings For a perishable food supply chain, risk positioned at lower levels (levels 1 or 2) in the hierarchy should be targeted first, while formulating mitigation strategies. To investigate further, risk- enabling factors which are identified for an Indian dairy firm for these levels 1 and 2 risks and mitigation strategy prioritization show that supplier side risks are more dominant followed by market risks and process risks. Research limitations/implications This proposed methodology has not been statistically validated or empirically tested, and factors taken are in the Indian context, but the authors believe that the study is highly relevant to other markets as well because the ISM-based analysis is for generic perishable food supply chain environment. Practical implications This study provides a useful approach to managers/decision makers to identify, analyze and prioritize risk in the supply chain. It also provides insights into the mutual relationships of supply chain risks which would help them to focus on the effective risk mitigation strategies formulation. The study provides the insights to benchmark and risk management in the dairy industry environment with priority considerations. Originality/value This paper provides an integrated approach to identifying, quantify, analyze, evaluate and mitigate the risks of perishable food (in the dairy environment) in the Indian context.
Unlocking financial inclusion: Indian banks' efficiency in Pradhan Mantri Jan-Dhan Yojana explored through DEA
Purpose - Financial inclusion is a prerequisite for inclusive development. In 2014, the Indian Government introduced the Pradhan Mantri Jan-Dhan Yojana (PMJDY) with a similar objective. The study aims to analyse the effectiveness of banks in the implementation of financial inclusion policy, i.e. PMJDY. Design/methodology/approach - To evaluate the effectiveness of Indian banks, the study used the data over a seven-year period, from 2014-2015 to 2020-2021. Data are analysed by using the data envelopment analysis technique. Findings - The study discovered that public sector banks performed better than private sector banks (PVBs) in terms of boosting financial inclusion under the PMJDY scheme. In terms of implementing the PMJDY programme, the State Bank of India rated first. Practical implications - Results recommended that policymakers set goals for banks. In order to encourage consumers to utilise their accounts, banks ought to introduce supplementary financial products and implement incentive programs. Originality/value - The study is the first of its kind to measure the performance of Indian banks in the implementation of the PMJDY scheme.
Screening for Peptides to Bind and Functionally Inhibit SARS-CoV-2 Fusion Peptide Using Mirrored Combinatorial Phage Display and Human Proteomic Phage Display
To identify pancoronaviral inhibitors, we sought to identify peptides that bound the evolutionarily conserved SARS-CoV-2 spike fusion peptide (FP). We screened the NEB PhD-7-mer random combinatorial phage display library against FP, synthesised as a D-peptide, to identify peptides from the L-library to be synthesised as proteolytically resistant D peptides. We selected the top ten peptides that were not seen in another published screen with this library, as these were more likely to be specific. All ten D-peptides had no impact on the infection of Vero-E6/TMPRSS2 cells by SARS-CoV-2. Screening of a proteomic-derived phage display library from the disordered regions of human proteins identified two overlapping 14mer peptides from a region of OTUD1. While a synthetic peptide based on their sequences failed to markedly inhibit viral entry, molecular dynamics structural modelling highlighted a stable binding mode where positive residues on one side of the OTUD1 helix interacted with hydrophobic residues of the FP triple-helical wedge. Thus, while the two phage display strategies failed to yield peptide sequences that are themselves strong inhibitors of viral infection, they led to the development of a computational model that can underpin future designs of potential pancoronaviral FP disruptors.
Investigating the effects of corporate social responsibility on sustainable consumer purchase behavior
PurposeSustainable manufacturing practices are excessively being practised in the industry today. The impact on sustainability is ever more visible to the stakeholders because of faster and more efficient communication due to social media and the internet. This paper aims to study the impact of greenwashing by corporations and the stakeholders’ environmental concerns on consumers’ sustainable purchase behaviour.Design/methodology/approachThe relationships between the impression of “greenwash”, sustainable purchasing behaviour, green word-of-mouth and green brand loyalty were investigated in this quantitative study. Participants who made up a representative sample filled out written surveys. The variables of interest were evaluated using scales that have undergone validation. Structural equation modelling was used in mediation analysis to investigate the mediating impacts of green word-of-mouth and green brand loyalty. The goal of the study was to offer empirical proof of how these factors affected consumers’ choices for sustainable products.FindingsAnalysis of the mediating relationship of perceived customer effectiveness in the relationship between environmental concern and sustainable purchase behaviour has been studied.Research limitations/implicationsThis study implicates that a company that primarily markets basic green and sustainable products or services must invest in informing people about environmental concerns and that by proper practices, a lot of the harm to the environment can be reduced.Originality/valueCorporate greenwashing, also called false greening, has received much public attention recently. The unethical practices by the corporations, which previously majorly went unnoticed, have also recently gained a lot of visibility. This paper is one of the early attempts towards establishing the effect of corporate greenwashing on sustainable consumer behaviour.
Prioritization of dimensions of visual merchandising for apparel retailers using FAHP
PurposeVisual merchandising has a direct impact on shopping experience, making it pertinent for the retailers to ensure that their store environment has an effective design. This study blends fuzzy numbers and Analytical Hierarchy Process to create a fuzzy evaluation model prioritizing the relative weights of visual merchandising dimensions of online fashion apparel store. This study will help the fashion retailers in creating more engaging and informative online stores leading to subsequent increase in online retail sales.Design/methodology/approachVisual merchandising dimensions and sub dimensions used by retailers for online stores were identified through review of literature and discussion with experts. Twenty experts were interviewed and their responses captured. The responses were analyzed using Fuzzy AHP technique resulting in prioritizing the dimensions according to the weight. For testing the stability of the results, sensitivity analysis was conducted.FindingsFour key dimensions and sixteen sub dimensions were extracted. Weights were calculated using FAHP. “Pictorial Presentation” has the highest weight followed closely by “Product Information” dimension. Amongst the sub-dimensions “Number of Product Images” scored highest followed by “Product Presentation mode”. “Alterable Background” scored the least weight.Originality/valuePrevious studies have identified Online Visual Merchandising dimensions and have also studied the impact of some of these dimensions on consumer buying behavior, but the relative significance has not been determined yet. This study fills the gap.
Autism Spectrum Disorders: A Recent Update on Targeting Inflammatory Pathways with Natural Anti-Inflammatory Agents
Autism spectrum disorder (ASD) is a heterogeneous category of developmental psychiatric disorders which is characterized by inadequate social interaction, less communication, and repetitive phenotype behavior. ASD is comorbid with various types of disorders. The reported prevalence is 1% in the United Kingdom, 1.5% in the United States, and ~0.2% in India at present. The natural anti-inflammatory agents on brain development are linked to interaction with many types of inflammatory pathways affected by genetic, epigenetic, and environmental variables. Inflammatory targeting pathways have already been linked to ASD. However, these routes are diluted, and new strategies are being developed in natural anti-inflammatory medicines to treat ASD. This review summarizes the numerous preclinical and clinical studies having potential protective effects and natural anti-inflammatory agents on the developing brain during pregnancy. Inflammation during pregnancy activates the maternal infection that likely leads to the development of neuropsychiatric disorders in the offspring. The inflammatory pathways have been an effective target for the subject of translational research studies on ASD.