Forecast Pupil Performance using SVM & Logistic Regression

The primary reason why machine learning has gained so much prominence nowadays is that it enables accurate and reliable decision making by extracting hidden relationships between various features present in the data. For this purpose the technique such as supervised methodologies and unsupervised methodologies are used. For this reason, machine learning can be used in almost any area of work to help in proper decision making and predictions. In our current project, we are trying to predict this student performance that utilizes supervised machine learning methodologies like support vector machines , logistic regression, random forests etc. We have also tried to publish this model to a web application so that it can be used by the academic community. The information extracted and the knowledge gained by extracting information from the educational data set would be helpful for predicting the student grades and their future performance. The main intention of the project used to predict student performance beforehand and help them get good grades in future. This would help in increasing the motivation levels of the students, improving their grades, decreasing their dropout ratio, and preparing better students for a better world

Metabolite profiling and biological activities of bioactive compounds produced by Chrysosporium lobatum strain BK-3 isolated from Kaziranga National Park, Assam, India

In an ongoing survey for bioactive potential of microorganisms from different biosphere zones of India, a new Chrysosporium lobatum strain BK-3 was isolated from soil sample collected from a biodiversity hotspot, Kaziranga National Park, Assam, India. Bioactivity-guided purification resulted in the isolation of two bioactive compounds whose chemical structures were elucidated by (1)H and (13)C Nuclear Magnetic Resonance (NMR), 2D-NMR, Fourier Transform Infra-red (FT-IR) and mass spectroscopic techniques, and were identified as α, β-dehydrocurvularin and curvularin. Only curvularin exhibited 80% acetylcholinesterase (AChE) inhibitory activity. Detailed ligand receptor binding interactions were studied for curvularin by molecular docking studies. Further, both curvularin and α, β-dehydrocurvularin had similar level of cytotoxicity against different human tumour cell lines like A549, HeLa, MDA-MB-231 and MCF-7, while α, β-dehydrocurvularin was active against COLO 205 with a IC(50) of 7.9 μM, but curvularin was inactive. α, β-Dehydrocurvularin also showed good superoxide anion scavenging activity with an EC(50) value of 16.71 μg ml(-1). Hence, both these compounds exhibited differences in bioactive profiles and this was probably associated with their minor structural differences. This is a first report on bioactive compounds exhibiting AChE inhibitory, cytotoxicity and antioxidant activities from Chrysosporium lobatum strain BK-3. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/2193-1801-2-122) contains supplementary material, which is available to authorized users

Detecting COVID 19 using Deep Learning

Abstract: Corona virus disease 2019 (COVID 19) is defined as illness caused by novel corona virus now called severe acute respiratory syndrome corona virus 2 (SARS-Cov-2; formally called as 2019-nCov), which was first identified in Wuhan City, Hubei Province, China. The spreading of COVID 19 is very fast throughout the world. World economy as well as public health has been facing a devastating effect caused by COVID 19. Hence detecting COVID 19 is challenging task even we have multiple methods like RT-PCR, COVID kits. The RT-PCR may not available in all laboratory, even exists which take some time to process and get reports and COVID 19 test kits may not available in all places. So, the main intention of this paper is to detect COVID 19 with in low budget, less time and accurate results. We have trained deep transferred learning models like ResNet-50, ResNet-101 using COVID positive, Normal, Viral Pneumonia chest x-rays. ResNet-50, ResNet-101 is pre-trained deep learning neural network. ResNet-50 provides 98% of accuracy where ResNet-101 gives us 97% of accuracy. Keywords: COVID 19, Deep Learning, ResNet-50, Transferred Learning, Artificial Intelligence.</jats:p

A Retrospective Study of Chloral Hydrate vs. Midazolam Containing Triple Cocktail Oral Sedation in Pediatric Dentistry

ABSTRACTPurpose: To evaluate, retrospectively, the safety and efficacy of two moderate oral conscious sedation drug regimens used at UCSF Pediatric Dentistry Clinic: chloral hydrate, meperidine, and hydroxyzine (CH/M/H) versus midazolam, meperidine, and hydroxyzine (Mid/M/H).Methods: Data was collected from sedation records from 7/21/2010- 6/3/2015 at UCSF Pediatric Dental Clinic. The records were screened and those meeting inclusion criteria were analyzed for patient behavior, completion of treatment, and adverse events. Appropriate statistically analyses were conducted based on specific collected data set with P-value &lt;0.05 to be significant different.Results: Of the original sample of 1016 sedation charts, 295 met the inclusion criteria for analysis. There were 27 adverse reactions (vomiting, over-sedation, or desaturation) of which 16 were in Mid/M/H cases and 11 were in CH/M/H cases. There was no statistically significant difference between the two regimens in safety. The average behavior scale was closer to sleeping for CH/M/H cases whereas it was closer to crying/moving for Mid/M/H cases. However, there was a significant difference between the two regimens in efficacy. CH/M/H worked significantly better on children younger than 9 years of age. Resident operator experience did not significantly affect sedation outcomes. Moderately uncooperative patients had significantly better sedation results with the CH/M/H regimen than with the Mid/M/H regimen. For fairly cooperative and extremely uncooperative patients, there was no significant difference.Conclusion: There was a significant difference in efficacy between the two triple cocktail regimens, with the CH/M/H regimen showing better behavior outcomes and completion of treatment versus Mid/M/H regimen. There was no significant difference in safety between the two regimens. Per this study, as long as sedation guidelines are followed, the chloral hydrate regimen can be safely and effectively used in pediatric dental oral conscious sedation

Exploration of conformations and quantum chemical investigation of l-tyrosine dimers, anions, cations and zwitterions: a DFT study

Conformational analysis of tyrosine (YN) and its ionized counter parts cations (YC), anions (YA) and biologically relevant zwitterionic form (YZ) has been carried out. An exhaustive and systematic exploration of l-tyrosine dimer (YD) conformations resulted in about 59 distinct minima on the potential energy surface. The hydrogen bonds and a variety of non-covalent interactions such as OH–&#x03C0;, NH–&#x03C0;, CH–&#x03C0;, CH–O and &#x03C0;–&#x03C0; interactions stabilized the different forms of tyrosine and its dimers. Atoms in molecules analysis was performed to evaluate the nature and strength of the non-covalent interactions. Over all the NH–O, hydrogen bonds have showed higher stability than other non-covalent interactions in this study. The most stable dimers predominantly possess hydrogen bonding interactions, while the ones with aromatic side chain interactions are less stable. A delicate balance of non-covalent interactions governed the stability of different forms of tyrosine and its dimers

POLYAMINE SUPPLEMENTS TO THE DIET ENHANCE LARVAL AND SILK GLAND CHARACTERISTICS IN TASAR SILKWORM Antheraea mylitta D

Polyamines (PAs) are polycationic, biosynthetic intermediate metabolites of amino acids and regulate many metabolic processes inside cells i.e., organization of DNA, RNA, transcription and translation etc., which contribute to promoting growth and development in animals. The DABA bivoltine (2 crops/year) ecorace of Tasar silkworm, Antheraea mylitta is reared by tribal populations in Indian forest ecosystems mainly for livelihood.&nbsp; Due to its rearing in natural wild conditions, the abiotic and biotic environmental stress led to 60-70% crop loss in every rearing. Silk yarn is used in textile industries while raw and fabricated products possess export value. Recent investigations revealed that silk proteins viz., fibroin and Sericin tend to have high potential biomaterial for tissue engineering. Hence, there is a need to select high-yielding and disease-resistant varieties for sustainable crop improvement. As silk production relies on the fifth instar larval and silk gland development, which in turn is determined by quality food intake and molecular mechanism contributed by nutritive supplements, the present work is taken up which was not explored to date. The fifth instar larvae of A. mylitta D (Daba TV) were allowed to feed on the Terminalia arjuna leaves treated with polyamines (Spermidine, Spermine and Putrescine) in 50 µM, 100 µM and 150 µMconcentrations. The larval behaviour was studied; larval characteristics, silk gland development, silkworm Body Mass Index (BMI), mortality and Effective Rearing Rate (ERR) were estimated statistically and interpreted. The study revealed significant enhancement in larval, silk gland weight and disease resistance in certain specified concentrations of PAs

A comprehensive conformational analysis of tryptophan, its ionic and dimeric forms

Tryptophan is an essential amino acid, and understanding the conformational preferences of monomer and dimer is a subject of outstanding relevance in biological systems. An exhaustive first principles investigation of tryptophan (W) and its ionized counterparts cations (WC), anions (WA), and zwitterions (WZ) has been carried out. A comprehensive and systematic study of tryptophan dimer (WD) conformations resulted in about 62 distinct minima on the potential energy surface. The hydrogen bonds and a variety of noncovalent interactions such as OH-π, NH-π, CH-π, CH-O, and π-π interactions stabilized different forms of tryptophan and its dimers. Over all in monomeric conformers which have NH-O, hydrogen bonds showed higher stability than other conformers. A cursory analysis reveal that the most stable dimers stabilized by hydrogen bonding interactions while the less stable dimers showed aromatic side chain interactions. Protein Data Bank analysis of tryptophan dimers reveals that at a larger distance greater than 5 Å, T-shaped orientations (CH-π interactions) are more prevalent, while stacked orientations (π-π interactions) are predominant at a smaller distance