4 resultados para Semi-supervised clustering

em Brock University, Canada


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The goal of most clustering algorithms is to find the optimal number of clusters (i.e. fewest number of clusters). However, analysis of molecular conformations of biological macromolecules obtained from computer simulations may benefit from a larger array of clusters. The Self-Organizing Map (SOM) clustering method has the advantage of generating large numbers of clusters, but often gives ambiguous results. In this work, SOMs have been shown to be reproducible when the same conformational dataset is independently clustered multiple times (~100), with the help of the Cramérs V-index (C_v). The ability of C_v to determine which SOMs are reproduced is generalizable across different SOM source codes. The conformational ensembles produced from MD (molecular dynamics) and REMD (replica exchange molecular dynamics) simulations of the penta peptide Met-enkephalin (MET) and the 34 amino acid protein human Parathyroid Hormone (hPTH) were used to evaluate SOM reproducibility. The training length for the SOM has a huge impact on the reproducibility. Analysis of MET conformational data definitively determined that toroidal SOMs cluster data better than bordered maps due to the fact that toroidal maps do not have an edge effect. For the source code from MATLAB, it was determined that the learning rate function should be LINEAR with an initial learning rate factor of 0.05 and the SOM should be trained by a sequential algorithm. The trained SOMs can be used as a supervised classification for another dataset. The toroidal 10×10 hexagonal SOMs produced from the MATLAB program for hPTH conformational data produced three sets of reproducible clusters (27%, 15%, and 13% of 100 independent runs) which find similar partitionings to those of smaller 6×6 SOMs. The χ^2 values produced as part of the C_v calculation were used to locate clusters with identical conformational memberships on independently trained SOMs, even those with different dimensions. The χ^2 values could relate the different SOM partitionings to each other.

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We study the phonon dispersion, cohesive and thermal properties of raxe gas solids Ne, Ar, Kr, and Xe, using a variety of potentials obtained from different approaches; such as, fitting to crystal properties, purely ab initio calculations for molecules and dimers or ab initio calculations for solid crystalline phase, a combination of ab initio calculations and fitting to either gas phase data or sohd state properties. We explore whether potentials derived with a certain approaxih have any obvious benefit over the others in reproducing the solid state properties. In particular, we study phonon dispersion, isothermal ajid adiabatic bulk moduli, thermal expansion, and elastic (shear) constants as a function of temperatiue. Anharmonic effects on thermal expansion, specific heat, and bulk moduli have been studied using A^ perturbation theory in the high temperature limit using the neaxest-neighbor central force (nncf) model as developed by Shukla and MacDonald [4]. In our study, we find that potentials based on fitting to the crystal properties have some advantage, particularly for Kr and Xe, in terms of reproducing the thermodynamic properties over an extended range of temperatiures, but agreement with the phonon frequencies with the measured values is not guaranteed. For the lighter element Ne, the LJ potential which is based on fitting to the gas phase data produces best results for the thermodynamic properties; however, the Eggenberger potential for Ne, where the potential is based on combining ab initio quantum chemical calculations and molecular dynamics simulations, produces results that have better agreement with the measured dispersion, and elastic (shear) values. For At, the Morse-type potential, which is based on M0ller-Plesset perturbation theory to fourth order (MP4) ab initio calculations, yields the best results for the thermodynamic properties, elastic (shear) constants, and the phonon dispersion curves.

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The aim of this study was to investigate the neural correlates of operant conditioning in a semi-intact preparation of the pond snail, Lymnaea stagnalis. Lymnaea learns, via operant conditioning, to reduce its aerial respiratory behaviour in response to an aversive tactile stimulus to its open pneumostome. This thesis demonstrates the successful conditioning of na'ive semiintact preparations to show learning in the dish. Furthermore, these conditioned preparations show long-term memory that persists for at least 18 hours. As the neurons that generate this behaviour have been previously identified I can, for the first time, monitor neural activity during both learning and long-term memory consolidation in the same preparation. In particular, I record from the respiratory neuron Right Pedal Dorsal 1 (RPeD 1) which is part of the respiratory central pattern generator. In this study, I demonstrate that preventing RPeDl impulse activity between training sessions reduces the number of sessions needed to produce long-term memory in the present semi-intact preparation.

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SiC and AtB 12 have been prepared and their resistivities and Hall voltages measured. The resistivities and Hall voltages were measured by the Van der Pauw's method, using spring loaded tungsten contacts. In this method, the major requirement is to have samples of plane parallel surfaces of arbitrary shape with four small contacts at the circumference. Similar measurements were made with a number of SiC crystals obtained from the Norton Research Corporation (Canada)-Ltd., Carolina Aluminum Co., Exolon Co. and Carborundum Co. It was found that resistivity, carrier concentration and mobility of ions depend on the type of impurity. AtB 12 was prepared from the melt containing At and B in the ratio of 4:1. They formed amber-colour pseudo tetragonal crystals. As the crystals obtained were small for electrical measurements, hot pressed lumps have been used to measure their resistivity.