Application of Artificial Intelligence in Automation of Supply Chain Management

A well-functioning supply chain is a key to success for every business entity. Having an accurate projection on inventory offers a substantial competitive advantage. There are many internal factors like product introductions, distribution network expansion; and external factors such as weather, extreme seasonality, and changes in customer perception or media coverage that affects the performance of the supply chain. In recent years Artificial Intelligence (AI) has been proved to become an extension of our brain, expanding our cognitive abilities to levels that we never thought would be possible. Though many believe AI will replace humans, it is not true, rather it will help us to unleash our true strategic and creative potential. AI consists of a set of computational technologies developed to sense, learn, reason, and act appropriately. With the technological advancement in mobile computing, the capacity to store huge data on the internet, cloud-based machine learning and information processing algorithms etc. AI has been integrated into many sectors of business and been proved to reduce costs, increase revenue, and enhance asset utilization. AI is helping businesses to get almost 100% accurate projection and forecast the customer demand, optimizing their R&D and increase manufacturing with lower cost and higher quality, helping them in the promotion (identifying target customers, demography, defining the price, and designing the right message, etc.) and providing their customers a better experience. These four areas of value creation are extremely important for gaining competitive advantage. Supply-chain leaders use AI-powered technologies to a) make efficient designs to eliminate waste b) real-time monitoring and error-free production and c) facilitate lower process cycle times. These processes are crucial in bringing Innovation faster to the market

Synthesis and characterization of water-soluble carbon nanotubes from mustard soot

Carbon nanotubes (CNT) has been synthesized by pyrolysing mustard oil using an oil lamp. It was made water-soluble (wsCNT) through oxidative treatment by dilute nitric acid and was characterized by SEM, AFM, XRD, Raman and FTIR spectroscopy. The synthesized wsCNT showed the presence of several junctions and defects in it. The presence of curved graphene structure (sp2) with frequent sp3 hybridized carbon is found to be responsible for the observed defects. These defects along with the presence of di- and tri-podal junctions showed interesting magnetic properties of carbon radicals formed by spin frustration. This trapped carbon radical showed ESR signal in aqueous solution and was very stable even under drastic treatment by strong oxidizing or reducing agents. Oxidative acid treatment of CNT introduced several carboxylic acid group functionalities in wsCNT along with the nicking of the CNT at different lengths with varied molecular weight. To evaluate molecular weights of these wsCNTs, an innovative method like gel electrophoresis using high molecular weight DNA as marker was introduced

Effect of reduction of antiepileptic drugs in patients with drug-refractory epilepsy

AbstractPurposeThe present study was conducted with the aim of evaluating the effects of reducing the number of antiepileptic drugs (AEDs) administered to patients with drug-refractory epilepsy (DRE) during their admission and document any change in seizure frequency in subsequent follow up.MethodsA total of 962 patients with DRE who were admitted to the neurology wards waiting for connection to video EEG were recruited for this prospective study. After their admission to the neurology ward, modifications in the number and dosage of AEDs were done with a target of a maximum of three AEDs in every patient. Drug tapering was done using a standardized protocol. The primary outcome was the change in seizure frequency in the follow-up period of 6 months. Secondary outcome measures were the adverse event profile (AEP) and the quality of life (QOL).ResultsOf the 1134 patients screened, 962 patients gave consent to participate in the study. The mean number of AEDs received by each patient was 4.24. After the tapering following a standardized protocol each patient received a mean of 2.65 AEDs per patient. In 82.70% patients with DRE, there was either a reduction or no change in seizure frequency in the subsequent 6 months follow up. There was a significant reduction in the AEP score after the reduction in the number of AEDs (P=0. 001).ConclusionOur study proves that optimization of reduction of the number of AED's in patients with DRE leads to reduction or no change in seizure frequency with a significant decrease in adverse effects

Disrupting the ArcA Regulatory Network Amplifies the Fitness Cost of Tetracycline Resistance in Escherichia coli.

There is an urgent need for strategies to discover secondary drugs to prevent or disrupt antimicrobial resistance (AMR), which is causing \u3e700,000 deaths annually. Here, we demonstrate that tetracycline-resistant (TetR) Escherichia coli undergoes global transcriptional and metabolic remodeling, including downregulation of tricarboxylic acid cycle and disruption of redox homeostasis, to support consumption of the proton motive force for tetracycline efflux. Using a pooled genome-wide library of single-gene deletion strains, at least 308 genes, including four transcriptional regulators identified by our network analysis, were confirmed as essential for restoring the fitness of TetR E. coli during treatment with tetracycline. Targeted knockout of ArcA, identified by network analysis as a master regulator of this new compensatory physiological state, significantly compromised fitness of TetR E. coli during tetracycline treatment. A drug, sertraline, which generated a similar metabolome profile as the arcA knockout strain, also resensitized TetR E. coli to tetracycline. We discovered that the potentiating effect of sertraline was eliminated upon knocking out arcA, demonstrating that the mechanism of potential synergy was through action of sertraline on the tetracycline-induced ArcA network in the TetR strain. Our findings demonstrate that therapies that target mechanistic drivers of compensatory physiological states could resensitize AMR pathogens to lost antibiotics. IMPORTANCE Antimicrobial resistance (AMR) is projected to be the cause of \u3e10 million deaths annually by 2050. While efforts to find new potent antibiotics are effective, they are expensive and outpaced by the rate at which new resistant strains emerge. There is desperate need for a rational approach to accelerate the discovery of drugs and drug combinations that effectively clear AMR pathogens and even prevent the emergence of new resistant strains. Using tetracycline-resistant (TetR) Escherichia coli, we demonstrate that gaining resistance is accompanied by loss of fitness, which is restored by compensatory physiological changes. We demonstrate that transcriptional regulators of the compensatory physiologic state are promising drug targets because their disruption increases the susceptibility of TetR E. coli to tetracycline. Thus, we describe a generalizable systems biology approach to identify new vulnerabilities within AMR strains to rationally accelerate the discovery of therapeutics that extend the life span of existing antibiotics

Characterization of bond coat in a thermal barrier coated superalloy used in combustor liners of aero engines

This paper deals with characterization of a thermal barrier coated (TBC) Supeni 263 super alloy, mostly employed for manufacturing combustion chamber of aero turbines, with respect to microstructure, residual stress, hardness and with special emphasis in establishing the ductile to brittle transition temperature (DBTT) of the bond coat by using acoustic emission technique during room temperature and high temperature tensile tests. Results reveal that the residual stress was tensile in nature in the TBC layer and compressive in the bond coat as well as in the substrate. The DBTT of this bond coat is around 650°C, which is in close proximity to the value reported in literature for CoCrAlY type of bond coat. Finite element technique used for analyzing the equivalent stresses in the bond coat, at a particular load within the elastic limit of the composite specimens, revealed highest order of equivalent stress at 800°C as the bond coat is ductile above 650°C. Delamination of the bond coat and spallation of the TBC were evident at high stresses during high temperature (800°C) fatigue