Importance of supervised learning in prediction analysis

Counterfeit medicines are fake medicines which are either contaminated or contain the wrong or no active ingredient. Up to 30% of medicines in developing countries are counterfeit. Using Supervised Machine learning techniques we build a predictive model for predicting sales figures given other information related to counterfeit medicine selling operations. Thus, by predicting the values we can identify these illegal operations and counter them. In this paper we have also mentioned the importance of Data mining and Machine Learning algorithms with some comparison analysis

ANTIMICROBIAL AND ANTIOXIDANT ACTIVITY OF UREA/ THIOUREA DERIVATIVES OF 5-METHYL-3-(UREDIOMETHYL)-HEXANOIC ACID

A series of urea/ thiourea derivatives of 5-methyl-3-(urediomethyl)-hexanoic acid has been successfully synthesized from the reaction of 3-aminomethyl-5-methylhexanoic acid and aryl isocyanate/ aryl isothiocyanates in presence of triethylamine base in tetrahydrofuran solvent at rt-40C by stirring the contents for 3h

Animal model integration to AutDB, a genetic database for autism

<p>Abstract</p> <p>Background</p> <p>In the post-genomic era, multi-faceted research on complex disorders such as autism has generated diverse types of molecular information related to its pathogenesis. The rapid accumulation of putative candidate genes/loci for Autism Spectrum Disorders (ASD) and ASD-related animal models poses a major challenge for systematic analysis of their content. We previously created the Autism Database (AutDB) to provide a publicly available web portal for ongoing collection, manual annotation, and visualization of genes linked to ASD. Here, we describe the design, development, and integration of a new module within AutDB for ongoing collection and comprehensive cataloguing of ASD-related animal models.</p> <p>Description</p> <p>As with the original AutDB, all data is extracted from published, peer-reviewed scientific literature. Animal models are annotated with a new standardized vocabulary of phenotypic terms developed by our researchers which is designed to reflect the diverse clinical manifestations of ASD. The new Animal Model module is seamlessly integrated to AutDB for dissemination of diverse information related to ASD. Animal model entries within the new module are linked to corresponding candidate genes in the original "Human Gene" module of the resource, thereby allowing for cross-modal navigation between gene models and human gene studies. Although the current release of the Animal Model module is restricted to mouse models, it was designed with an expandable framework which can easily incorporate additional species and non-genetic etiological models of autism in the future.</p> <p>Conclusions</p> <p>Importantly, this modular ASD database provides a platform from which data mining, bioinformatics, and/or computational biology strategies may be adopted to develop predictive disease models that may offer further insights into the molecular underpinnings of this disorder. It also serves as a general model for disease-driven databases curating phenotypic characteristics of corresponding animal models.</p

Physical and chemical techniques for a comprehensive characterization of river sediment: A case of study, the Moquegua River, Peru

River sediment is comprised of complex mineral systems composed by different kinds of organic and inorganic matter, and thus, is difficult to characterize. Besides, some standard techniques, such as X-ray diffraction (XRD), energy dispersive X-ray (EDX), optical and scanning electron microscopy, Fourier transmission infrared spectroscopy, inductively couple plasma-mass spectrometry (ICP-MS), and simultaneous Thermogravimetric Analysis – Differential Thermal Analysis (TGA-DTA), Mössbauer spectroscopy and magnetometry can provide substancial information about the compositional, physical, and chemical characteristics. In the current study, the versality of these methods is tested and the information provided by these methods for eight sediment samples, collected from the Moquegua River, Peru is compared. Qualitative analysis indicates that the samples consist of sand grains with different shapes, sizes, and colors coexisting with the presence of some diatoms. The chemical and mineralogical analysis reveal that the samples are composed mainly of silicon (Si), aluminium (Al), sodium (Na), potassium (K), aluminon–silicates, and carbonates, typical for river sediment. More detailed information obtained by these techniques include the discovery of adsorbed oxygen–hydrogen (O–H), carbon–H (C–H) and C, from organic matter, the thermal reactions and decomposition of the components, and the identification of the minor iron–oxides components. Further, other properties such as magnetic interaction are also analyzed in detail

The Spindle Assembly Checkpoint Safeguards Genomic Integrity of Skeletal Muscle Satellite Cells

© 2015 The Authors. To ensure accurate genomic segregation, cells evolved the spindle assembly checkpoint (SAC), whose role in adult stem cells remains unknown. Inducible perturbation of a SAC kinase, Mps1, and its downstream effector, Mad2, in skeletal m

Highly dispersed Cu(II), Co(II) and Ni(II) catalysts covalently immobilized on imine-modified silica for cyclohexane oxidation with hydrogen peroxide

This paper describes the synthesis of Cu(II), Co(II) and Ni(II) catalysts immobilized on imine-functionalized silica gel through a 3-aminopropyltriethoxysilane linker. The synthesized catalysts were characterized by spectroscopic techniques, namely EDS, FTIR, UV-Vis, Si-29 MAS NMR, powder XRD and ESR spectroscopy. These analytical methods evidently confirmed the formation of silica-supported catalysts. Thermal properties of catalysts were studied between 30 and 800 degrees C by thermogravimetric-differential thermal gravimetric (TG-DTG) analysis. The surface roughness of the silica gel was increased upon modification but without losing its lumpy shape, as evidenced by SEM investigation. Magnified SEM and AFM images both suggested the high dispersive nature of the catalysts. Cyclohexane was successfully converted into cyclohexanol and cyclohexanone by the catalysts with the aid of hydrogen peroxide (oxidant). Comparatively, Cu(II) catalyst exhibited better cyclohexane conversion than the other two catalysts. The reusable nature of the catalysts was established by performing five consecutive catalytic runs with Cu(II) catalyst. Comparatively, the present reported catalytic systems were simple, reusable and effective models for higher cyclohexane conversion with better product selectivity

Synthesis of magnetic nanoparticles and their effect on growth of carbon nanotubes

A series of spinel ferrite nanoparticles viz, manganese ferrite (MnFe2O4), zinc ferrite (ZnFe2O4), cobalt ferrite' (CoFe2O4) and nickel ferrite (NiFe2O4) were prepared by solvothermal proCess. X-Ray diffraction patterns show that the synthesized ferrite samples are pure without any impurities. The as-prepared ferrites were further used as a precursor catalyst for the growth of CNTs using thermal chemical vapor deposition. (CVD) technique. Results show that these ferrites acted as effective catalysts for the growth of carbon nanotubes. The as-grown nanotubes were studied by electron microscope (FE-SEM). Further studies like Raman spectroscopy and VSM analysis were also done to evaluate the properties of the as-prepared catalyst and the as-grown carbon nanotubes.

Solvothermal synthesis of MnFe2O4-graphene composite-Investigation of its adsorption and antimicrobial properties

Graphene manganese ferrite (MnFe2O4-G) composite was prepared by a solvothermal process. The as-prepared graphene manganese ferrite composite was tested for the adsorption of lead (Pb(II)) and cadmium (Cd(II)) ions by analytical methods under diverse experimental parameters. With respect to contact time measurements, the adsorption of Pb and Cd ions increased and reached equilibrium within 120 and 180 min at 37 degrees C with a maximum adsorption at pH 5 and 7 respectively. The Langmuir model correlates to the experimental data showing an adsorption capacity of 100 for Pb(II) and 76.90 mg g(-1) for Cd(II) ions. Thermodynamic studies revealed that the adsorption of Pb and Cd ions onto MnFe2O4-G was spontaneous, exothermic and feasible in the range of 27-47 degrees C. Cytotoxicity behavior of graphene against bacterial cell membrane is well known. To better understand its antimicrobial mechanism, the antibacterial activity of graphene and MnFe2O4-G nanocomposite was compared. Under similar concentration and incubation conditions, nanocomposite MnFe2O4-G dispersion showed the highest antibacterial activity of 82%, as compared to graphene showing 37% cell loss. Results showed that the prepared composite possess good adsorption efficiency and thus could be considered as an excellent material for removal of toxic heavy metal ions as explained by adsorption isotherm. Hence MnFe2O4-G can be used as an adsorbent as well as an antimicrobial agent. (C) 2014 Elsevier B.V. All rights reserved

Air-Jet Textured Yarns: The Effects of Process and Supply Yarn Parameters on the Properties of Textured Yarns

Characteristics of air-jet textured yarns are determined by the instability, linear density, and strength, together with structural properties such as loop size, loop frequency, and degree of entanglement. Such characteristics are affected by various process parameters and supply yarn properties. The effects of these parameters on the final yarn properties have been investigated using instability, linear density, and strength tests, together with SEM photographs for visual assessment of the yarn structure. Optimizing any given yarn property almost always affects other yarn characteristics, and therefore this must be remembered when selecting suitable process parameters and supply yarns for specific end uses. For a given texturing nozzle and conditions, there is an optimum filament fineness and number of filaments that can be textured effectively