A study of hierarchical and flat classification of proteins

Automatic classification of proteins using machine learning is an important problem that has received significant attention in the literature. One feature of this problem is that expert-defined hierarchies of protein classes exist and can potentially be exploited to improve classification performance. In this article we investigate empirically whether this is the case for two such hierarchies. We compare multi-class classification techniques that exploit the information in those class hierarchies and those that do not, using logistic regression, decision trees, bagged decision trees, and support vector machines as the underlying base learners. In particular, we compare hierarchical and flat variants of ensembles of nested dichotomies. The latter have been shown to deliver strong classification performance in multi-class settings. We present experimental results for synthetic, fold recognition, enzyme classification, and remote homology detection data. Our results show that exploiting the class hierarchy improves performance on the synthetic data, but not in the case of the protein classification problems. Based on this we recommend that strong flat multi-class methods be used as a baseline to establish the benefit of exploiting class hierarchies in this area

Real-time measurement of mental workload: A feasibility study

The primary goal of the study was to explore the utility of event-related brain potentials (ERP) as real-time measures of workload. To this end, subjects performed two different tasks both separately and together. One task required that subjects monitor a bank of constantly changing gauges and detect critical deviations. Difficulty was varied by changing the predictability of the gauges. The second task was mental arithmetic. Difficulty was varied by requiring subjects to perform operations on either two or three columns of numbers. Two conditions that could easily be distinguished on the basis of performance measures were selected for the real-time evaluation of ERPs. A bootstrapping approach was adopted in which one thousand samples of n trials (n = 1, 3, 5 ...65) were classified using several measures of P300 and Slow Wave amplitude. Classification accuracies of 85 percent were achieved with 25 trials. Results are discussed in terms of potential enhancements for real-time recording

Eye movements of young and older adults while reading with distraction

This article may not exactly replicate the final version published in the APA journal. It is not the copy of record.The authors used eye-tracking technology to examine young and older adults' online performance in the reading in distraction paradigm. Participants read target sentences and answered comprehension questions following each sentence. In some sentences, single-word distracters were presented in either italic or red font. Distracters could be related or unrelated to the target text. Online measures, including probability of fixation, fixation duration, and number of fixations to distracting text, revealed no age differences in text processing. However, young adults did have an advantage over older adults in overall reading time and text comprehension. These results provide no support for an inhibition deficit account of age differences in the reading in distraction paradigm, but are consistent with J. Dywan and W. E. Murphy's (1996) suggestion that older adults are less able than the young to distinguish target and distracter information held in working memory. (PsycINFO Database Record (c) 2010 APA, all rights reserved

Successful implementation of discrete event simulation: the case of an Italian emergency department

This paper focuses on the study of a practical management problem faced by a healthcare {\it emergency department} (ED) located in the north of Italy. The objective of our study was to propose organisational changes in the selected ED, which admits approximately 7000 patients per month, aiming at improving key performance indicators related to patient satisfaction, such as the waiting time. Our study is based on a design thinking process that adopts a {\it discrete event simulation} (DES) model as the main tool for proposing changes. We used the DES model to propose and evaluate the impact of different improving scenarios. The model is based on historical data, on the observation of the current ED situation, and information obtained from the ED staff. The results obtained by the DES model have been compared with those related to the existing ED setting, and then validated by the ED managers. Based on the results we obtained, one of the tested scenarios was selected by the ED for implementation.Comment: 24 pages, 8 figures and 4 table

Genetic Contributions to Age-Related Decline in Executive Function: A 10-Year Longitudinal Study of COMT and BDNF Polymorphisms

Genetic variability in the dopaminergic and neurotrophic systems could contribute to age-related impairments in executive control and memory function. In this study we examined whether genetic polymorphisms for catechol-O-methyltransferase (COMT) and brain-derived neurotrophic factor (BDNF) were related to the trajectory of cognitive decline occurring over a 10-year period in older adults. A single nucleotide polymorphism in the COMT (Val158/108Met) gene affects the concentration of dopamine in the prefrontal cortex. In addition, a Val/Met substitution in the pro-domain for BDNF (Val66Met) affects the regulated secretion and trafficking of BDNF with Met carriers showing reduced secretion and poorer cognitive function. We found that impairments over the 10-year span on a task-switching paradigm did not vary as a function of the COMT polymorphism. However, for the BDNF polymorphism the Met carriers performed worse than Val homozygotes at the first testing session but only the Val homozygotes demonstrated a significant reduction in performance over the 10-year span. Our results argue that the COMT polymorphism does not affect the trajectory of age-related executive control decline, whereas the Val/Val polymorphism for BDNF may promote faster rates of cognitive decay in old age. These results are discussed in relation to the role of BDNF in senescence and the transforming impact of the Met allele on cognitive function in old age