The KNIME Based Classification Models for Yellow Fever Virus Inhibition

The Naïve Bayes method as implemented in KNIME platform for classification of YFV inhibition. The best classification model is able to correctly discriminate &gt;90% of inhibitors and non-inhibitors.</p

Best Communication Node Election for well-organized Path in Flat Topology

There has been an increasing attentiveness in the uses of sensor networks. Because sensors are normally controlled in on-board power supply, proficient supervision of the network is essential in improving the life of the sensor. The majority research protocols objective at offering link breakage reducing and mitigating from the same. Yet, selecting the well-organized communication do all the beneficial to the transmission process thus demonstrating better improvement in the network performance. In this article, we propose Best Communication Node Election for well-organized Path in Flat Topology The main goal of this work is to choose the best data transmission node in flat topology for improve the multi hop routing. This scheme, the best communication node selection based on Path Metric and this Path Metric is measured by the packet obtained rate, dropped rate, latency rate and node energy. This scheme provide guarantees quality of Service in the network

Simultaneous Engineering and Knowledge Management in a Semiconductor Manufacturing Firm Using TQM

For a long time, add up to quality administration, simultaneous designing and learning administration have won extensive consideration from modern specialists and the scholarly community. Be that as it may, few examinations have been directed on the impact of these three practices among Malaysian assembling firms. Subsequently, the target of this examination is to break down the impact of TQM, CE and KM on designing execution in a Malaysian semiconductor producing firm. For this investigation, overviews were utilized to get observational information on these three practices. The information was investigated utilizing different straight relapse examination. The discoveries demonstrated that TQM, CE and KM essentially impacts the company's building execution with the three indicators disclosing up to 53.9% of the fluctuation in designing execution. The discoveries of this examination are helpful to administrators, specialists and analysts as it gives bits of knowledge on particular zones that require sufficient thoughtfulness regarding guarantee compelling designing execution

Evaluation of detoxifying activity of ORGCHP against acetaminophen induced hepatotoxicity in Sprague Dawley rats

Background: Accumulation of toxins in the body over a period of time interferes with the normal body functioning. The removal of toxins from the body is called ‘detoxification’. The liver is the main organ involved in detoxification and damage to the liver may impede the removal of toxins. The present study assessed the hepatoprotective activity of an organic Chlorella vulgaris in acetaminophen-induced liver damage model.Methods: A total of 35 animals were randomized to five groups with seven animals in each group. The test drug, organic Chlorella vulgaris (ORGCHP; 350 mg/kg and 700 mg/kg) was compared with a reference standard (200 mg/kg). The positive control group and the vehicle control group were administered 0.5% w/v carboxy methyl cellulose. All groups received dose volume of 10 ml/kg for 10 days. Acetaminophen was given on day 8 and day 9. Blood collections were done at baseline day 1, day 8 and day 10. Outcome measures were the change in body weight, oxidation biomarkers, histopathological evaluation, gross pathological evaluation and relative body weight.Results: Test drug ORGCHP Chlorella vulgaris showed dose dependent reduction in hepatoxicity with high reduction in aspartate transaminase (AST) and modest lowering of alanine transaminase (ALT) (350 mg/kg; p.o.); while at high dose (700 mg/kg; p.o.) there was significant reduction in alkaline phosphatase (p<0.05), ALT (p<0.001) and AST (p<0.001) levels. No pathological or histopathological abnormality was seen in control group. In drug group, one animal showed minimal necrosis, while mild and moderate necrosis was seen in three animals each respectively.Conclusions: The test drug exhibits detoxifying and hepatoprotective activity against acetaminophen induced hepatotoxicity

Time Series Analysis of Clinical Dataset Using ImageNet Classifier

Deep learning is a bunch of calculations in AI that endeavor to learn in numerous levels, comparing to various degrees of deliberation. It regularly utilizes counterfeit brain organizations. The levels in these learned factual models compare to unmistakable degrees of ideas, where more significant level ideas are characterized from lower-level ones, and a similar lower level idea can assist with characterizing numerous more elevated level ideas. As of late, an AI (ML) region called profound learning arose in the PC vision field and turned out to be exceptionally famous in many fields. It began from an occasion in late 2018, when a profound learning approach in light of a convolutional brain organization (CNN) won a mind-boggling triumph in the most popular overall com management rivalry, ImageNet Characterization. From that point forward, scientists in many fields, including clinical picture examination, have begun effectively partaking in the dangerously developing field of profound learning. In this section, profound learning procedures and their applications to clinical picture examination are studied. This study outlined 1) standard ML procedures in the PC vision field, 2) what has changed in ML when the presentation of profound learning, 3) ML models in profound learning, and 4) uses of profound figuring out how-to clinical picture examination. Indeed, even before the term existed, profound learning, in particular picture input ML, was applied to an assortment of clinical picture examination issues, including harm and non-harm characterization, harm type grouping, harm or organ division, and sore locatio

Energy and Exergy Analysis of an Advanced Cookstove-Based Annular Thermoelectric Cogeneration System

This chapter deals with the energy and exergy analysis of the cookstove-based gasifier annular thermoelectric generator (GATEG). The vented waste heat is made available at the outer surface of the combustion chamber of an advanced micro-gasifier cookstove for added energy feed to the GATEG. This combined device has a competence to satisfy both cooking needs and micro-electrification of rural villages by a simultaneous recovery of heat energy and power (CHP) as cogeneration system. The power output (W), electrical energy efficiency (%) and exergy efficiency (%) of the proposed advanced micro-gasifier cookstove-based ATEG are 10 W, 6.78 and 15%, respectively. The maximum hot side wasted temperature without annulus gain is 275°C, which translates equivalent loss values as 7.64 W, 5.45 and 10.49%; this loss is higher than achievable minimum hot side temperature of 150°C on which this analytical chapter is drafted. This detailed study will be extremely useful to the designers of commercial biomass advanced micro-gasifier cookstove integrated ATEG systems

Recent developments in the medicinal chemistry of single boron atom-containing compounds

Various boron-containing drugs have been approved for clinical use over the past two decades, and more are currently in clinical trials. The increasing interest in boron-containing compounds is due to their unique binding properties to biological targets; for example, boron substitution can be used to modulate biological activity, pharmacokinetic properties, and drug resistance. In this perspective, we aim to comprehensively review the current status of boron compounds in drug discovery, focusing especially on progress from 2015 to December 2020. We classify these compounds into groups showing anticancer, antibacterial, antiviral, antiparasitic and other activities, and discuss the biological targets associated with each activity, as well as potential future developments.</p

Binding Free Energy Based Structural Dynamics Analysis of HIV-1 RT RNase H-Inhibitor Complexes

The binding free energy based models have been used to study the structural dynamics of HIV-1 RT RNase H–inhibitor complexes.</p