The mechanism of ϕC31 integrase directionality : experimental analysis and computational modelling

Acknowledgments We thank Sally Rowland for helpful comments on the manuscript. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.

A Comparative Review of Computational Methods as Applied to Gold(I) Complexes and Mechanisms

In the last two decades, the field of homogeneous gold catalysis has been

extremely active, growing at a rapid pace. Another rapidly-growing field—that of

computational chemistry—has often been applied to the investigation of various gold-

catalyzed reaction mechanisms. Unfortunately, a number of recent mechanistic studies

have utilized computational methods that have been shown to be inappropriate and

inaccurate in their description of gold chemistry. This work presents an overview of

available computational methods with a focus on the approximations and limitations

inherent in each, and offers a review of experimentally-characterized gold(I) complexes

and proposed mechanisms as compared with their computationally-modeled

counterparts. No aim is made to identify a “recommended” computational method for

investigations of gold catalysis; rather, discrepancies between experimentally and

computationally obtained values are highlighted, and the systematic errors between

different computational methods are discussed.

Computational Methods for Identifying Hypertrophic Cardiomyopathy using 12-lead ECG

Hypertrophic cardiomyopathy (HCM) is a cardiovascular disease where the heart muscle is partially thickened and blood flow is - potentially fatally - obstructed. It is one of the leading causes of sudden cardiac death in young people. Electrocardiography (ECG) and Echocardiography (Echo) are the standard tests for identifying HCM and other cardiac abnormalities. The American Heart Association has recommended using a pre-participation questionnaire for young athletes instead of ECG or Echo tests due to considerations of cost and time involved in interpreting the results of these tests by an expert cardiologist. Initially we set out to develop a classifier for automated prediction of young athletes’ heart conditions based on the answers to the questionnaire. Classification results and further in-depth analysis using computational and statistical methods indicated significant shortcomings of the questionnaire in predicting cardiac abnormalities. Automated methods for analyzing ECG signals can help reduce cost and save time in the pre-participation screening process by detecting HCM and other cardiac abnormalities. Therefore, the main goal of this dissertation work is to identify HCM through computational analysis of 12-lead ECG. ECG signals recorded on one or two leads have been analyzed in the past for classifying individual heartbeats into different types of arrhythmia as annotated primarily in the MIT-BIH database. In contrast, we classify complete sequences of 12-lead ECGs to assign patients into two groups: HCM vs. non-HCM. The challenges and issues we address include missing ECG waves in one or more leads and the dimensionality of a large feature-set. We address these by proposing imputation and feature-selection methods. We develop heartbeat-classifiers by employing Random Forests and Support Vector Machines, and propose a method to classify full 12-lead ECGs based on the proportion of heartbeats classified as HCM. The results from our experiments show that the classifiers developed using our methods perform well in identifying HCM. Thus the two contributions of this thesis are the utilization of computational and statistical methods for discovering shortcomings in a current screening procedure and the development of methods to identify HCM through computational analysis of 12-lead ECG signals.

Computational models for improved diagnosis and prognosis of stroke using robot-based biomarkers

Stroke is a leading cause of death and permanent disability worldwide, affecting millions of individuals. Traditional clinical scores for assessment of stroke-related impairments are inherently subjective and limited by inter-rater and intra-rater reliability, as well as floor and ceiling effects. In contrast, robotic technologies provide objective, highly repeatable tools for quantification of neurological impairments following stroke. KINARM is an exoskeleton robotic device that provides objective, reliable tools for assessment of sensorimotor, proprioceptive and cognitive brain function by means of a battery of behavioral tasks. As such, KINARM is particularly useful for assessment of neurological impairments following stroke. This thesis introduces a computational framework for assessment of neurological impairments using the data provided by KINARM. This is done by achieving two main objectives. First, to investigate how robotic measurements can be used to estimate current and future abilities to perform daily activities for subjects with stroke. We are able to predict clinical scores related to activities of daily living at present and future time points using a set of robotic biomarkers. The findings of this analysis provide a proof of principle that robotic evaluation can be an effective tool for clinical decision support and target-based rehabilitation therapy. The second main objective of this thesis is to address the emerging problem of long assessment time, which can potentially lead to fatigue when assessing subjects with stroke. To address this issue, we examine two time reduction strategies. The first strategy focuses on task selection, whereby KINARM tasks are arranged in a hierarchical structure so that an earlier task in the assessment procedure can be used to decide whether or not subsequent tasks should be performed. The second strategy focuses on time reduction on the longest two individual KINARM tasks. Both reduction strategies are shown to provide significant time savings, ranging from 30% to 90% using task selection and 50% using individual task reductions, thereby establishing a framework for reduction of assessment time on a broader set of KINARM tasks. All in all, findings of this thesis establish an improved platform for diagnosis and prognosis of stroke using robot-based biomarkers.

Grammar in dictionaries revisited: the case of verbs with se

This paper is a study about the way in which se structures are represented in 20 verb entries of nine dictionaries of Spanish language. There is a large number of these structures and they are problematic for native and non native speakers. Verbs of the analysis are middle-high frequency and, in the most part of the cases, very polysemous, and this allows to observe interconnections between the different se structures and the different meanings of each verb. Data of the lexicographic analysis are cross-checked with corpus analysis of the same units. As a result, it is observed that there is a large variety in the data which are offered in each dictionary and in the way they are offered, inter and intradictionary. The reasons range from the theoretical overall of each Project to practical performance. This leads to the conclusion that it is necessary to further progress in the dictionary model it is being handled, in order to offer lexico-grammatical phenomenon such as se verbs in an accurate, clear and exhaustive way.

Receptive Vocabulary of CLIL and Non-CLIL Primary and Secondary School Learners

CLIL instruction has been reported to be beneficial for foreign language vocabulary learning since CLIL students show higher vocabulary profiles than students of their same age in traditional EFL contexts. However, to our knowledge, the receptive vocabulary knowledge of CLIL and non-CLIL learners at the end of primary and secondary education has not been examined yet. Hence, this study aims at comparing the receptive vocabulary size 79 CLIL primary learners with the receptive vocabulary knowledge of 331 non-CLIL learners at the end of primary and secondary school. Sex-based differences were also analysed. The 2k Vocabulary Levels Test (VLT) was used for the purposes of the study. Results revealed that learners’ receptive vocabulary sizes lie within the most frequent 1000 words, non-CLIL secondary school students throw better results than primary students but the differences between the secondary group and the CLIL group are not statistically significant. As for sex-based differences, we found no significant differences among the groups. These findings led us to believe that the CLIL approach offers a benefit for vocabulary acquisition since CLIL learners have been exposed to the foreign language for a shorter period of time and the results are quite similar to their non-CLIL secondary school partners.

Using Computational Significance and Resilience in System Software Stacks.:Keynote Talk

This talk explores how the runtime system and operating system can leverage metrics that express the significance and resilience of application components in order to reduce the energy footprint of parallel applications. We will explore in particular how software can tolerate and indeed exploit higher error rates in future processors and memory technologies that may operate outside their safe margins.

Particle Trajectory Tracing and Computational Electromagnetics for Accelerator and Related Technologies

The main objective of this R&D work is to simulate particle beam optics in CV-28 Cyclotron of Instituto de Engenharia Nuclear – IEN/CNEN, as a support for improvements or optimization of this particle accelerator. Besides 2D magnetostatic field computation results, the authors present an alternative method for charged particle trajectories computation in electrostatic or magnetostatic fields. This task is approached by analytical computation of trajectories, by parts, considering constant fields within each finite element. This method has some advantages over numerical integration ones: numerical miscomputation of trajectories is avoided; stability problem is also avoided, for the magnetostatic field case. Some examples are presented, including positive ion extraction from cyclotrons with strip-foil. This latter technique is an interesting alternative for upgrading positive ion cyclotrons, such as CV-28 Cyclotron. The particle trajectory computation method presented in this work is of interest not only for cyclotrons, but for accelerator and related technology, in general.

Computational approaches and tools for modeling biomass pyrolysis

Thesis (Ph.D.)--University of Washington, 2016-08

PHYSICA: A multiphysics computational framework and its application to casting simulations

Metal casting is a process governed by the interaction of a range of physical phenomena. Most computational models of this process address only what are conventionally regarded as the primary phenomena – heat conduction and solidification. However, to predict other phenomena, such as porosity formation, requires modelling the interaction of the fluid flow, heat transfer, solidification and the development of stressdeformation in the solidified part of the casting. This paper will describe a modelling framework called PHYSICA[1] which has the capability to stimulate such multiphysical phenomena.

Computational statistics, electronic publishing, and access to research data

Abstract not available