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[Editorial] Information technology governance in Internet of Things supply chain networks
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A Comprehensive Review: COVID-19 And Post-Covid Versus Thromboembolism
In spite of the fact that COVID-19 was previously predominantly believed to be a respiratory ailment, rapidly increasing data point to a significant prevalence of venous thromboembolic consequences in the disease. This review article's main goal was to determine if there was a requirement to raise knowledge of PE (Pulmonary Embolism) in the aftermath of the COVID-19 outbreak given the still-weak epidemiologic data. The gathered studies were subjected to a critical evaluation and literature search. A digital search of Science Direct, Google Scholar, PubMed, and Scopus until June 2022. COVID-19’s lasting effects on health are yet mostly unknown. The pathophysiology of pulmonary embolism is highlighted in this review, along with the significance of being aware of the possible ways that enhanced the risk of VTE (Venous Thromboembolism) in patients suffering from post- COVID-19, including those who have a moderate or asymptomatic illness. To define suitable clinical care recommendations for the avoidance of thromboembolic consequences in the critically sick and post-COVID-19 phase, further study is necessary.
 
Determining Vitamin D Status: A Comparison Between Diabetic And Non-diabetic Women With Breast Cancer By RP-HPLC
Background:
Suboptimal levels of Vitamin D, remains a common problem worldwide and its prevalence is high in India, ranging from 70-100%. Several molecular mechanisms have been found about the effects of Vitamin D in modulating glycemic levels and its protective nature in the development of breast cancer. Breast cancer in India is a common problem and studies regarding its association with Vitamin D levels among diabetics remain inconclusive. This study aims to find the association between Vitamin D status and breast cancer in diabetic and non-diabetic women.
Materials and methods:
25 hydroxy vitamin D levels were estimated by RP-HPLC. A total of 25 serum samples were analysed (20 Breast cancer patients+5 normal).
Results:
Serum sample analysis report of breast cancer patients (irrespective of diabetic status) showed 50% low Vitamin D compared to normal individuals.
Conclusions:
Vitamin D deficiency is very common among women suffering from breast cancer. Although diabetic breast cancer women have lower Vitamin D levels when compared to non-diabetic women, the results in this study are not statistically significant
Significance of the vehicle front design and gait postures on traumatic brain injuries sustained by different pedestrian populations during car-to-pedestrian collisions (CPCs) - A computational approach
With the increasing prevalence of traumatic brain injuries (TBIs) in road traffic accidents (RTAs), it was identified that the shape of the vehicle\u27s front end and pedestrian postures prior to impact significantly influence pedestrian head injuries. However, the effect of vehicle front shape parameters and gait postures on TBIs sustained in car-to-pedestrian collisions (CPCs) has yet to be quantified. This study used a computational approach to analyze the effect of vehicle shape parameters and pedestrian gait postures on pedestrian TBI risks across a diverse pedestrian population with varying body sizes. Our findings indicate that vehicle shape parameter such as BLEH (Bonnet leading edge height), BA (Bonnet angle), and WA (Windshield angle) were statistically significant predictors of pedestrians\u27 TBI risk. Increasing BLEH in sedans and decreasing BLEH in high-leading-edged vehicles reduce the risk of TBIs. Vehicles with high BLEH and low BA were susceptible to AIS (Abbreviated injury scale) 4+ head injuries. In vehicles with a low BLEH, pedestrian height and mass were statistically significant factors affecting pedestrian head rotation. Our results demonstrate that TBI risks were found to be different for gait percentage in the same and different gait types. Walking and emergency gaits dominate linear head kinematics, whereas running gaits dominate head rotation in pedestrians, resulting in substantial brain strain. Linear head kinematics varies significantly between the stance and swing phases of walking and running gait postures, whereas rotational head kinematics and brain strains vary cyclically but to a less extent
Pharmacokinetic interaction between alcohol and two of the commonly prescribed anti-hypertensive drugs-amlodipine and nebivolol
Background: Alcoholism is one of the leading causes of secondary hypertension. Many a times in clinical setting, many hypertensive patients also happen to be alcoholics, either social/moderate drinkers or suffer from alcohol dependence. For these patients, cessation of alcohol consumption is advocated and counselled as part of diet and lifestyle modifications. However, compliance rates have been found to be variable. Therefore, these patients consume alcohol and also take anti-hypertensive medications on a day-to-day basis. This study was initiated to explore influence of alcohol on the pharmacokinetics of anti-hypertensive drugs – Amlodipine and Nebivolol.Methods: 24 human volunteers were recruited for the study after obtaining informed consent. 12 volunteers each for Amlodipine, Nebivolol and alcohol’s effect on the drugs respectively were evaluated. Two standard drinks of alcohol were administered in respective period as per randomization. Clinical confinement and blood sampling was carried out as per ethics committee approved protocol in accordance with good clinical practice principles.Plasma samples were analyzed using validated LC-MS/MS bio-analytical method, for quantification of Nebivolol and Amlodipine in lines with good laboratory practice principles. Pharmacokinetic and statistical analysis of results was evaluated using WinNonlin Version 5.3.Results: The pharmacokinetic parameters were evaluated statistically and ANOVA results suggest that despite changes in individual parameters, the bioavailability was comparable, as both Cmax and AUC0-inf were well within the range of 80-125%.Conclusions: It is clearly observed that there are variations in all pharmacokinetic parameters when the drug is administered with alcohol. However, the same are well within acceptable limits and bioavailability of the drugs is comparable when administered with alcohol. Hence, two standard drinks of alcohol have limited effect on the pharmacokinetics of Amlodipine and Nebivolol. Further studies are required to evaluate influence of higher and frequent doses of alcohol on pharmacokinetics of Amlodipine and Nebivolol
Composite particle algorithm for sustainable integrated dynamic ship routing and scheduling optimization
Ship routing and scheduling problem is considered to meet the demand for various products in multiple ports within the planning horizon. The ports have restricted operating time, so multiple time windows are taken into account. The problem addresses the operational measures such as speed optimisation and slow steaming for reducing carbon emission. A Mixed Integer Non-Linear Programming (MINLP) model is presented and it includes the issues pertaining to multiple time horizons, sustainability aspects and varying demand and supply at various ports. The formulation incorporates several real time constraints addressing the multiple time window, varying supply and demand, carbon emission, etc. that conceive a way to represent several complicating scenarios experienced in maritime transportation. Owing to the inherent complexity, such a problem is considered to be NP-Hard in nature and for solutions an effective meta-heuristics named Particle Swarm Optimization-Composite Particle (PSO-CP) is employed. Results obtained from PSO-CP are compared using PSO (Particle Swarm Optimization) and GA (Genetic Algorithm) to prove its superiority. Addition of sustainability constraints leads to a 4–10% variation in the total cost. Results suggest that the carbon emission, fuel cost and fuel consumption constraints can be comfortably added to the mathematical model for encapsulating the sustainability dimensions
A concerted enzymatic de-structuring of lignocellulosic materials using a compost-derived microbial consortia favoring the consolidated pretreatment and bio-saccharification
The robustness of microbial consortia isolated from compost habitat encompasses the complementary metabolism that aids in consolidated bioprocessing (CBP) of lignocellulosic biomass (LCB) by division of labor across the symbionts. Composting of organic waste is deemed to be an efficient way of carbon recycling, where the syntrophic microbial population exerts a concerted action of lignin and polysaccharide (hemicellulose and cellulose) component of plant biomass. The potential of this interrelated microorganism could be enhanced through adaptive laboratory evolution (ALE) with LCB for its desired functional capabilities. Therefore, in this study, microbial symbionts derived from organic compost was enriched on saw dust (SD) (woody biomass), aloe vera leaf rind (AVLR) (agro-industrial waste) and commercial filter paper (FP) (pure cellulose) through ALE under different conditions. Later, the efficacy of enriched consortium (EC) on consolidated pretreatment and bio-saccharification was determined based on substrate degradation, endo-enzymes profiling and fermentable sugar yield. Among the treatment sets, AVLR biomass treated with EC-5 has resulted in the higher degradation rate of lignin (47.01 ± 0.66%, w/w) and polysaccharides (45.87 ± 1.82%, w/w) with a total sugar yield of about 60.01 ± 4.24 mg/g. In addition, the extent of structural disintegration of substrate after EC-treatment was clearly deciphered by FTIR and XRD analysis. And the factors of Pearson correlation matrix reinforces the potency of EC-5 by exhibiting a strong positive correlation between AVLR degradation and the sugar release. Thus, a consortium based CBP could promote the feasibility of establishing a sustainable second generation biorefinery framework
Unlocking the potential of insect and ruminant host symbionts for recycling of lignocellulosic carbon with a biorefinery approach: a review
Uprising fossil fuel depletion and deterioration of ecological reserves supply have led to the search for alternative renewable and sustainable energy sources and chemicals. Although first generation biorefinery is quite successful commercially in generating bulk of biofuels globally, the food versus fuel debate has necessitated the use of non-edible feedstocks, majorly waste biomass, for second generation production of biofuels and chemicals. A diverse class of microbes and enzymes are being exploited for biofuels production for a series of treatment process, however, the conversion efficiency of wide range of lignocellulosic biomass (LCB) and consolidated way of processing remains challenging. There were lot of research efforts in the past decade to scour for potential microbial candidate. In this context, evolution has developed the gut microbiota of several insects and ruminants that are potential LCB degraders host eco-system to overcome its host nutritional constraints, where LCB processed by microbiomes pretends to be a promising candidate. Synergistic microbial symbionts could make a significant contribution towards recycling the renewable carbon from distinctly abundant recalcitrant LCB. Several studies have assessed the bioprospection of innumerable gut symbionts and their lignocellulolytic enzymes for LCB degradation. Though, some reviews exist on molecular characterization of gut microbes, but none of them has enlightened the microbial community design coupled with various LCB valorization which intensifies the microbial diversity in biofuels application. This review provides a deep insight into the significant breakthroughs attained in enrichment strategy of gut microbial community and its molecular characterization techniques which aids in understanding the holistic microbial community dynamics. Special emphasis is placed on gut microbial role in LCB depolymerization strategies to lignocellulolytic enzymes production and its functional metagenomic data mining eventually generating the sugar platform for biofuels and renewable chemicals production
A systematic literature review on machine learning applications for sustainable agriculture supply chain performance
Agriculture plays an important role in sustaining all human activities. Major challenges such as overpopulation, competition for resources poses a threat to the food security of the planet. In order to tackle the ever-increasing complex problems in agricultural production systems, advancements in smart farming and precision agriculture offers important tools to address agricultural sustainability challenges. Data analytics hold the key to ensure future food security, food safety, and ecological sustainability. Disruptive information and communication technologies such as machine learning, big data analytics, cloud computing, and blockchain can address several problems such as productivity and yield improvement, water conservation, ensuring soil and plant health, and enhance environmental stewardship. The current study presents a systematic review of machine learning (ML) applications in agricultural supply chains (ASCs). Ninety three research papers were reviewed based on the applications of different ML algorithms in different phases of the ASCs. The study highlights how ASCs can benefit from ML techniques and lead to ASC sustainability. Based on the study findings an ML applications framework for sustainable ASC is proposed. The framework identifies the role of ML algorithms in providing real-time analytic insights for pro-active data-driven decision-making in the ASCs and provides the researchers, practitioners, and policymakers with guidelines on the successful management of ASCs for improved agricultural productivity and sustainability
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