Equilibrium glassy phase in a polydisperse hard sphere system

The phase diagram of a polydisperse hard sphere system is examined by numerical minimization of a discretized form of the Ramakrishnan-Yussouff free energy functional. Crystalline and glassy local minima of the free energy are located and the phase diagram in the density-polydispersity plane is mapped out by comparing the free energies of different local minima. The crystalline phase disappears and the glass becomes the equilibrium phase beyond a "terminal" value of the polydispersity. A crystal to glass transition is also observed as the density is increased at high polydispersity. The phase diagram obtained in our study is qualitatively similar to that of hard spheres in a quenched random potential.Comment: 4 pages, 4 figure

Sensitivity of temporal heart rate variability in Poincaré plot to changes in parasympathetic nervous system activity

<p>Abstract</p> <p>Background</p> <p>A novel descriptor (Complex Correlation Measure (CCM)) for measuring the variability in the temporal structure of Poincaré plot has been developed to characterize or distinguish between Poincaré plots with similar shapes.</p> <p>Methods</p> <p>This study was designed to assess the changes in temporal structure of the Poincaré plot using <it>CCM </it>during atropine infusion, 70° head-up tilt and scopolamine administration in healthy human subjects. <it>CCM </it>quantifies the point-to-point variation of the signal rather than gross description of the Poincaré plot. The physiological relevance of <it>CCM </it>was demonstrated by comparing the changes in <it>CCM </it>values with autonomic perturbation during all phases of the experiment. The sensitivities of short term variability (<it>SD</it>1), long term variability (<it>SD</it>2) and variability in temporal structure (<it>CCM</it>) were analyzed by changing the temporal structure by shuffling the sequences of points of the Poincaré plot. Surrogate analysis was used to show <it>CCM </it>as a measure of changes in temporal structure rather than random noise and sensitivity of <it>CCM </it>with changes in parasympathetic activity.</p> <p>Results</p> <p><it>CCM </it>was found to be most sensitive to changes in temporal structure of the Poincaré plot as compared to <it>SD</it>1 and <it>SD</it>2. The values of all descriptors decreased with decrease in parasympathetic activity during atropine infusion and 70° head-up tilt phase. In contrast, values of all descriptors increased with increase in parasympathetic activity during scopolamine administration.</p> <p>Conclusions</p> <p>The concordant reduction and enhancement in <it>CCM </it>values with parasympathetic activity indicates that the temporal variability of Poincaré plot is modulated by the parasympathetic activity which correlates with changes in <it>CCM </it>values. <it>CCM </it>is more sensitive than <it>SD</it>1 and <it>SD</it>2 to changes of parasympathetic activity.</p

Complex Correlation Measure: a novel descriptor for Poincaré plot

<p>Abstract</p> <p>Background</p> <p>Poincaré plot is one of the important techniques used for visually representing the heart rate variability. It is valuable due to its ability to display nonlinear aspects of the data sequence. However, the problem lies in capturing temporal information of the plot quantitatively. The standard descriptors used in quantifying the Poincaré plot (<it>SD</it>1, <it>SD</it>2) measure the gross variability of the time series data. Determination of advanced methods for capturing temporal properties pose a significant challenge. In this paper, we propose a novel descriptor "Complex Correlation Measure (<it>CCM</it>)" to quantify the temporal aspect of the Poincaré plot. In contrast to <it>SD</it>1 and <it>SD</it>2, the <it>CCM </it>incorporates point-to-point variation of the signal.</p> <p>Methods</p> <p>First, we have derived expressions for <it>CCM</it>. Then the sensitivity of descriptors has been shown by measuring all descriptors before and after surrogation of the signal. For each case study, <it>lag-1 </it>Poincaré plots were constructed for three groups of subjects (Arrhythmia, Congestive Heart Failure (CHF) and those with Normal Sinus Rhythm (NSR)), and the new measure <it>CCM </it>was computed along with <it>SD</it>1 and <it>SD</it>2. ANOVA analysis distribution was used to define the level of significance of mean and variance of <it>SD</it>1, <it>SD</it>2 and <it>CCM </it>for different groups of subjects.</p> <p>Results</p> <p><it>CCM </it>is defined based on the autocorrelation at different lags of the time series, hence giving an in depth measurement of the correlation structure of the Poincaré plot. A surrogate analysis was performed, and the sensitivity of the proposed descriptor was found to be higher as compared to the standard descriptors. Two case studies were conducted for recognizing arrhythmia and congestive heart failure (CHF) subjects from those with NSR, using the Physionet database and demonstrated the usefulness of the proposed descriptors in biomedical applications. <it>CCM </it>was found to be a more significant (<it>p </it>= 6.28E-18) parameter than <it>SD</it>1 and <it>SD</it>2 in discriminating arrhythmia from NSR subjects. In case of assessing CHF subjects also against NSR, <it>CCM </it>was again found to be the most significant (<it>p </it>= 9.07E-14).</p> <p>Conclusion</p> <p>Hence, <it>CCM </it>can be used as an additional Poincaré plot descriptor to detect pathology.</p

Toe clearance and velocity profiles of young and elderly during walking on sloped surfaces

Background Most falls in older adults are reported during locomotion and tripping has been identified as a major cause of falls. Challenging environments (e.g., walking on slopes) are potential interventions for maintaining balance and gait skills. The aims of this study were: 1) to investigate whether or not distributions of two important gait variables [minimum toe clearance (MTC) and foot velocity at MTC (VelMTC)] and locomotor control strategies are altered during walking on sloped surfaces, and 2) if altered, are they maintained at two groups (young and elderly female groups). Methods MTC and VelMTC data during walking on a treadmill at sloped surfaces (+3°, 0° and -3°) were analysed for 9 young (Y) and 8 elderly (E) female subjects. Results MTC distributions were found to be positively skewed whereas VelMTC distributions were negatively skewed for both groups on all slopes. Median MTC values increased (Y = 33%, E = 7%) at negative slope but decreased (Y = 25%, E = 15%) while walking on the positive slope surface compared to their MTC values at the flat surface (0°). Analysis of VelMTC distributions also indicated significantly (p < 0.05) lower minimum and 25th percentile (Q1) values in the elderly at all slopes. Conclusion The young displayed a strong positive correlation between MTC median changes and IQR (interquartile range) changes due to walking on both slopes; however, such correlation was weak in the older adults suggesting differences in control strategies being employed to minimize the risk of tripping

Large expert-curated database for benchmarking document similarity detection in biomedical literature search

Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research.Peer reviewe

Distribution Entropy (DistEn) : a complexity measure to detect arrhythmia from short length RR interval time series

Heart rate complexity analysis is a powerful non-invasive means to diagnose several cardiac ailments. Non-linear tools of complexity measurement are indispensable in order to bring out the complete non-linear behavior of Physiological signals. The most popularly used non-linear tools to measure signal complexity are the entropy measures like Approximate entropy (ApEn) and Sample entropy (SampEn). But, these methods become unreliable and inaccurate at times, in particular, for short length data. Recently, a novel method of complexity measurement called Distribution Entropy (DistEn) was introduced, which showed reliable performance to capture complexity of both short term synthetic and short term physiologic data. This study aims to i) examine the competence of DistEn in discriminating Arrhythmia from Normal sinus rhythm (NSR) subjects, using RR interval time series data; ii) explore the level of consistency of DistEn with data length N; and iii) compare the performance of DistEn with ApEn and SampEn. Sixty six RR interval time series data belonging to two groups of cardiac conditions namely `Arrhythmia\u27 and `NSR\u27 have been used for the analysis. The data length N was varied from 50 to 1000 beats with embedding dimension m = 2 for all entropy measurements. Maximum ROC area obtained using ApEn, SampEn and DistEn were 0.83, 0.86 and 0.94 for data length 1000, 1000 and 500 beats respectively. The results show that DistEn undoubtedly exhibits a consistently high performance as a classification feature in comparison with ApEn and SampEn. Therefore, DistEn shows a promising behavior as bio marker for detecting Arrhythmia from short length RR interval data