Search results for "Random"
showing 10 items of 3931 documents
Randomized controlled trial of postoperative exercise rehabilitation program after lumbar spine fusion: study protocol
2012
Abstract Background Lumbar spine fusion (LSF) effectively decreases pain and disability in specific spinal disorders; however, the disability rate following surgery remains high. This, combined with the fact that in Western countries the number of LSF surgeries is increasing rapidly it is important to develop rehabilitation interventions that improve outcomes. Methods/design In the present RCT-study we aim to assess the effectiveness of a combined back-specific and aerobic exercise intervention for patients after LSF surgery. One hundred patients will be randomly allocated to a 12-month exercise intervention arm or a usual care arm. The exercise intervention will start three months after su…
Simulation of Phase Transitions of Single Polymer Chains: Recent Advances
2006
The behaviour of a flexible polymer chain in solvents of variable quality in dilute solution is discussed both in the bulk and in the presence of an adsorbing wall. Monte Carlo simulations of coarse-grained bead-spring models and of the bond fluctuation model are presented and interpreted in terms of phenomenological theories and scaling concepts. Particular attention is paid to the behaviour of the polymer chain when the temperature of the polymer solution gets lower than the Theta temperature. It is argued that the adsorption transition line at the Theta temperature splits into lines of wetting and drying transitions of polymer globules attached to the wall. In addition, it is shown that …
The phase diagram of a single polymer chain: New insights from a new simulation method
2006
We present simulation results for the phase behavior of a single chain for a flexible lattice polymer model using the Wang-Landau sampling idea. Applying this new algorithm to the problem of the homopolymer collapse allows us to investigate not only the high temperature coil–globule transition but also an ensuing crystallization at lower temperature. Performing a finite size scaling analysis on the two transitions, we show that they coincide for our model in the thermodynamic limit corresponding to a direct collapse of the random coil into the crystal without intermediate coil–globule transition. As a consequence, also the many chain phase diagram of this model can be predicted to consist o…
Feature selection on a dataset of protein families: from exploratory data analysis to statistical variable importance
2016
Proteins are characterized by several typologies of features (structural, geometrical, energy). Most of these features are expected to be similar within a protein family. We are interested to detect which features can identify proteins that belong to a family, as well as to define the boundaries among families. Some features are redundant: they could generate noise in identifying which variables are essential as a fingerprint and, consequently, if they are related or not to a function of a protein family. We defined an original approach to analyze protein features for defining their relationships and peculiarities within protein families. A multistep approach has been mainly performed in R …
<strong>Machine Learning and Atom-Based Quadratic Indices for Proteasome Inhibition Prediction </strong>
2015
The atom-based quadratic indices are used in this work together with some machine learning techniques that includes: support vector machine, artificial neural network, random forest and k-nearest neighbor. This methodology is used for the development of two quantitative structure-activity relationship (QSAR) studies for the prediction of proteasome inhibition. A first set consisting of active and non-active classes was predicted with model performances above 85% and 80% in training and validation series, respectively. These results provided new approaches on proteasome inhibitor identification encouraged by virtual screenings procedures. .
Calculation of chromatographic properties of barbiturates by molecular topology
1995
A study has been made of the relationship between the RF values obtained by thin layer chromatography for a group of barbiturates and the connectivity indices proposed by Kier and Hall. By using multivariable regression we obtained the corresponding connectivity functions, which were selected on the basis of their respective statistics parameters. The regression analysis of the connectivity functions shows a correct prediction of the experimental elution sequence for this group of molecules on silicagel with two mobile phases of different polarity. The corresponding random and stability studies of the different prediction models selected were carried out, demonstrating good stability and nu…
Prediction of chromatographic parameters for some anilines by molecular connectivity
1995
The possible relation existing between RF values obtained by thin-layer chromatography for a group of anilines with connectivity indices proposed by Kier and Hall has been studied. Using multivariable regression the corresponding connectivity functions, selected for their respective correlation coefficients, standard deviations, Snedecor's F and Student's t were obtained. Regression analysis of the connectivity functions gives a correct prediction of the experimental elution sequence for this group of substances on silica gel stationary phases and various mobile phases of different polarity. The corresponding random and stability studies of the different prediction models selected were carr…
<strong>Predicting Proteasome Inhibition using Atomic Weighted Vector and Machine Learning</strong>
2018
Ubiquitin/Proteasome System (UPS) is a highly regulated mechanism of intracellular protein degradation and turnover. Through the concerted actions of a series of enzymes, proteins are marked for proteasomal degradation by being linked to the polypeptide co-factor, ubiquitin. The UPS participates in a wide array of biological functions such as antigen presentation, regulation of gene transcription and the cell cycle, and activation of NF-κB. Some researchers have applied QSAR method and machine learning in the study of proteasome inhibition (EC50(µmol/L)), such as: the analysis of proteasome inhibition prediction, in the prediction of multi-target inhibitors of UPP and in the prediction of p…
Contextuality is About Identity of Random Variables
2014
Contextual situations are those in which seemingly "the same" random variable changes its identity depending on the conditions under which it is recorded. Such a change of identity is observed whenever the assumption that the variable is one and the same under different conditions leads to contradictions when one considers its joint distribution with other random variables (this is the essence of all Bell-type theorems). In our Contextuality-by-Default approach, instead of asking why or how the conditions force "one and the same" random variable to change "its" identity, any two random variables recorded under different conditions are considered different "automatically". They are never the…
Extracting work from random collisions: A model of a quantum heat engine
2022
We study the statistical distribution of the ergotropy and of the efficiency of a single-qubit battery ad of a single-qubit Otto engine, respectively fuelled by random collisions. The single qubit, our working fluid, is assumed to exchange energy with two reservoirs, a non-equilibrium "hot" reservoir and a zero temperature cold reservoir. The interactions between the qubit and the reservoirs is described in terms of a collision model of open system dynamics. The qubit interacts with the non-equilibrium reservoir (a large ensemble of qudits all prepared in the same pure state) via random unitary collisions and with the cold reservoir (a large ensemble of qubits in their ground state) via a p…