Data driven flexible supplier network of selfcare essentials during disruptions in supply chain.

During disruptive events, supply chains struggle to meet the demand due to limitations posed by logistics, transportation and supply side failures. In the present study, a flexible supplier network of personal protective equipment (PPEs), such as face masks, hand sanitizers, gloves, and face shields, has been modelled using an extensive risk enabled data driven decision making for addressing disruptions in the supply chain. This paper studies various risks which exists in PPE supply chain and evaluates the total supplier risk based on them. Furthermore, the paper proposes a Multi-objective Mixed Integer Linear Program (MOMILP) to optimally select suppliers and the sustainable allocation of orders under various risks, namely disruption, delay, receivables, inventory, and capacity. The proposed MOMILP model is also extended to promptly revise the orders to other suppliers under a disruption scenario enabling an effective response resulting in minimization of stockouts. The criteria-risk matrix is developed with the help of supply chain experts from industry and academia. Conclusively, the numerical case study and its computational analysis is conducted on the PPE data received from distributors to demonstrate the applicability of the proposed model. The findings suggest that the proposed flexible MOMILP can optimally revise allocations during disruptions to drastically reduce the stockouts and minimize overall cost of procurement in the PPE supply network.

Emergency order allocation of e-medical supplies due to the disruptive events of the healthcare crisis.

The availability of electronic (e-medical) homecare essentials, such as thermometers, oximeters, and oxygen concentrators during the peaks of the pandemic coronavirus disease (COVID-19), has been witnessed as critical in saving the lives of people across the world. This paper presents a supply order allocation strategy of e-medical homecare essentials (HCEs) in a multi-supplier environment by a distributor while ensuring sufficient and timely availability for emergency consumption during pandemic peaks. The results, based on the actual demand data of HCEs obtained from a regional HCE distributor during the pandemic peak of the second wave in India, i.e. April-May 2021, suggest that a minimum (maximum) average of 94% (98%) availability of e-medical HCEs respectively at pharmacies could be achieved during the peak demand period using the proposed emergency order allocation algorithm in this study. Conclusively, the analysis of this study could generate insightful implications for emergency operations decisions in the HCEs supply-distribution channel.

Implications for sustainable healthcare operations in embracing telemedicine services during a pandemic.

Technological interventions in the healthcare sector, namely, telemedicine services, have helped the government and people in these extraordinarily challenging times of ongoing COVID-19 pandemic. We identify and group key success factors relevant to telemedicine services under 7 contextual criteria. Furthermore, we explore the causal relations among them using the decision-making trial and evaluation laboratory (DEMATEL) method. Then, by applying the Bayesian best-worst method (BWM), we compute the relative importance of these criteria. Thereafter, we rank six hospitals that have provided telemedicine services through a comparative evaluation using the VIsekriterijumsko KOmpromisno Rangiranjie (VIKOR) method. The threefold findings of our study reveal that (i) the technological criteria provide the highest causal impact, while the environmental criteria provide the least causal impact. (ii) The hierarchical model of criteria, achieved through the Bayesian BWM score, shows that the criteria weights for both technological and organizational criteria are maximum (0.205) and minimum (0.087), respectively. (iii) The evaluation of six hospitals with VIKOR based on seven criteria ranks the Himalayan hospital as first, showing that it is best in providing telemedicine services to patients. Public health policymakers could use the results of our study to devise an effective plan for patient care in crisis, like COVID-19.

Scanning Electron Microscopic and Dye Penetration Evaluation of Hand Instrumentation Techniques on Formation of Smear Layer in Root Canal Preparation: An In vitro Study.

AIMS AND OBJECTIVES: The present study was undertaken for evaluating various hand instrumentation techniques with different instruments in the formation of smear layer. MATERIALS AND METHODS: One hundred and seventy-five extracted mandibular molars were collected and were cut at cementoenamel junction. Afterward, the distal roots were separated. Working length was determined, and roots were divided into five equal groups with 35 roots in each group as follows: Group A: K-type files with conventional step-back technique, Group B: Canal Master U instrument with clockwise-counterclockwise rotation, Group C: Flex-R® files with clockwise-counterclockwise rotation, Group D: FlexoFiles® with conventional step-back technique, and Group E: Nickel titanium files with conventional step-back technique. Biomechanical preparation was done according to their respective groups. The teeth in various groups were scanned under scanning electron microscope and scoring was done. All the results were analyzed by SPSS software version 17.0. RESULTS: Scanning electron microscopic results indicated that apparently there seems to be a significant difference in the scoring of the smear layer between each group at all the three levels, but the difference was statistically nonsignificant. Microleakage was present in all the samples. Nonsignificant results were obtained while comparing the microleakage in between different the groups. However, microleakage was highest in Group D. CONCLUSION: The amount of smear layer is maximum at the apical third and lesser in the middle third followed by the coronal third in all the groups. All the samples showed microleakage to a varying extent.

Selection of healthcare waste disposal firms using a multi-method approach.

The aim of this study is to propose a hybrid multi criteria decision making model with a linear programming (LP) model to tackle the issue of safe disposal of hazardous and infectious healthcare waste. For this, ten criteria in this study have been identified from literature and field surveys which are modelled using Decision making trial and evaluation (DEMATEL) and Analytic network process (ANP) methods to select the best disposal firm i.e. single sourcing for a hospital. We found that Experience of the firm, Technology for disposal, and Waste collection infrastructure acts as the most vital criteria in selecting a healthcare waste disposal firm for single sourcing. Furthermore, to optimize the total value of disposal and mitigating the risk involved in disposing waste through single sourcing; the LP model considering constraints such as waste lose constraint and waste processing constraint etc. Is solved for multiple sourcing using Lingo 18.0. The solution to LP results into allocation of 500, 500, and 1000 (kg/day) disposables to healthcare waste disposal firms D1, D2 and D3, respectively. The multi-method approach proposed in this study helps the hospital management in selecting economically, socially, and environmentally sustainable healthcare waste disposal firm.

The interplay of circular economy with industry 4.0 enabled smart city drivers of healthcare waste disposal.

Generation of healthcare waste from different patient care activities in hospitals, pathology labs and research centres has been a matter of great concern for environmental and social bodies across the world. This concern comes from its infectious and hazardous nature which brings life taking disease such as human immunodeficiency virus and Hepatitis-B. Moreover, with the outbreak of corona virus disease 2019 (COVID-19) pandemic across the world, healthcare waste has become even more infectious like never before and showing its potential for claiming lives if not disposed properly. Additionally, the COVID-19 has put up another challenge in terms of exponentially increasing demand for personal protective equipments for healthcare workers such as doctors, nurses, ward boys, and sanitation workers. In this paper, seven criteria related to smart healthcare waste disposal system infused by circular economy aspects to recover value from disposables are identified and analysed using a decision making trial and evaluation laboratory (DEMATEL) method. The criteria have been prioritized by its importance and net cause and effect relationship through a causal diagram. Two criteria, (i) digitally connected healthcare centres, waste disposal firms and pollution control board, and (ii) providing a pollution control board's feedback app to public and other stakeholders, feature as strong reasons for a smart healthcare waste disposal system. Conclusively, this study provides a causal relationship model among the intertwined drivers of industry 4.0 and circular economy for developing a smart healthcare waste disposal system enriched with the benefits of circular economy.

Predictors of COVID-19 Vaccine Confidence: Findings from Slums of Four Major Metro Cities of India.

There are limited studies on COVID vaccine confidence at the household level in urban slums, which are at high risk of COVID-19 transmission due to overcrowding and poor living conditions. The objective was to understand the reasons influencing COVID-19 vaccine confidence, in terms of barriers and enablers faced by communities in urban slums and informal settlements in four major metro cities in India. A mixed method approach was adopted, where in field studies were conducted during April-May 2021. First, a survey of at least 50 subjects was conducted among residents of informal urban settlements who had not taken any dose of the COVID-19 vaccine in Mumbai, Bengaluru, Kolkata and Delhi; second, a short interview with five subjects who had taken at least one dose of the vaccine in each of the four cities to understand the factors that contributed to positive behaviour and, finally, an in-depth interview of at least 3 key informants in each city to ascertain the vaccination pattern in the communities. The reasons were grouped under contextual, individual/group and vaccine/vaccination specific issues. The most frequent reason (27.7%) was the uncertainty of getting the vaccine. The findings show the need for increasing effectiveness of awareness campaigns, accessibility and the convenience of vaccination, especially among vulnerable groups, to increase the uptake.

An interpretive structural modeling (ISM) and decision-making trail and evaluation laboratory (DEMATEL) method approach for the analysis of barriers of waste recycling in India.

Increasing amount of wastes is posing great difficulties for all countries across the world. The problem of waste management is more severe in developing countries such as India where the rates of economic growth and urbanization are increasing at a fast pace. The governments in these countries are often constrained by limited technical and financial capabilities, which prevent them from effectively addressing these problems. There is a limited participation from the private players too in terms of setting up of waste recycling units. The present study aims at identifying various barriers that challenge the establishment of these units, specific to India. Further, it attempts to identify the most influential barriers by utilizing multicriterion decision-making tools of interpretive structural modeling (ISM) and decision-making trail and evaluation laboratory (DEMATEL). The findings of the study suggest that the lack of funds, input material, and subsidy are the most influential barriers that are needed to be addressed for the development of waste recycling infrastructure in India. IMPLICATIONS: This work has been carried out to address the problem of proper waste management in India. To deal with this problem, the method of waste recycling has been felt appropriate by the government of various countries, including India. Therefore, the barriers that play vital role in waste recycling for private players have been identified and their importance has been established with the help of ISM and DEMATEL methods. Doing so will assist the government to take appropriate steps for the betterment of waste recycling infrastructure in India and enhance waste management.

Saccade Velocity Driven Oscillatory Network Model of Grid Cells.

Grid cells and place cells are believed to be cellular substrates for the spatial navigation functions of hippocampus as experimental animals physically navigated in 2D and 3D spaces. However, a recent saccade study on head fixated monkey has also reported grid-like representations on saccadic trajectory while the animal scanned the images on a computer screen. We present two computational models that explain the formation of grid patterns on saccadic trajectory formed on the novel Images. The first model named Saccade Velocity Driven Oscillatory Network -Direct PCA (SVDON-DPCA) explains how grid patterns can be generated on saccadic space using Principal Component Analysis (PCA) like learning rule. The model adopts a hierarchical architecture. We extend this to a network model viz. Saccade Velocity Driven Oscillatory Network-Network PCA (SVDON-NPCA) where the direct PCA stage is replaced by a neural network that can implement PCA using a neurally plausible algorithm. This gives the leverage to study the formation of grid cells at a network level. Saccade trajectory for both models is generated based on an attention model which attends to the salient location by computing the saliency maps of the images. Both models capture the spatial characteristics of grid cells such as grid scale variation on the dorso-ventral axis of Medial Entorhinal cortex. Adding one more layer of LAHN over the SVDON-NPCA model predicts the Place cells in saccadic space, which are yet to be discovered experimentally. To the best of our knowledge, this is the first attempt to model grid cells and place cells from saccade trajectory.

Evaluation on the responses of succinate dehydrogenase, isocitrate dehydrogenase, malate dehydrogenase and glucose-6-phosphate dehydrogenase to acid shock generated acid tolerance in Escherichia coli.

BACKGROUND: Escherichia coli have an optimum pH range of 6-7 for growth and survival that's why, called neutrophiles. The ΔpH across the cytoplasmic membrane is linked to cellular bioenergetics and metabolism of the body which is the major supplier of the proton motive force, so homeostasis of cellular pH is essential. When challenged by low pH, protons enter the cytoplasm; as a result, mechanisms are required to alleviate the effects of lowered cytoplasmic pH. MATERIALS AND METHODS: The activities of Succinate dehydrogenase, isocitrate dehydrogenase, malate dehydrogenase and glucose-6-phosphate dehydrogenase in acid shocked cells of E. coli DH5 α and E. coli W3110 subjected to pH 3, 4, and 5 by two types of acidification, like external (using 0.1 N HCl), external along with the monensin (1 µM) and cytoplasmic acidification using the sodium benzoate as an acid permeant (20 mM) which is coupled to the electron transport chain by the reducing power, as yet another system possessed by E. coli as an armor against harsh acidic environments. RESULT: Results showed that an exposure to acidic environment (pH 3, 4 and 5) for a short period of time increased the activities of these dehydrogenases in all types of acidification except cytoplasmic acidification, which shows that higher recycling of reducing power results in pumping out of protons from the cytoplasm through the electron transport chain complexes, thereby restoring the cytoplasmic pH of the bacteria in the range of 7.4-7.8. CONCLUSION: Study indicates that acid shocked E. coli for a period of 2 h can survive for a sustained period.