Dynamic fluctuations in ascending heart-to-brain communication under mental stress

Dynamical information exchange between central and autonomic nervous systems, as referred to functional brain-heart interplay, occurs during emotional and physical arousal. It is well documented that physical and mental stress lead to sympathetic activation. Nevertheless, the role of autonomic inputs in nervous system-wise communication under mental stress is yet unknown. In this study, we estimated the causal and bidirectional neural modulations between electroencephalogram (EEG) oscillations and peripheral sympathetic and parasympathetic activities using a recently proposed computational framework for a functional brain-heart interplay assessment, namely the sympathovagal synthetic data generation model. Mental stress was elicited in 37 healthy volunteers by increasing their cognitive demands throughout three tasks associated with increased stress levels. Stress elicitation induced an increased variability in sympathovagal markers, as well as increased variability in the directional brain-heart interplay. The observed heart-to-brain interplay was primarily from sympathetic activity targeting a wide range of EEG oscillations, whereas variability in the efferent direction seemed mainly related to EEG oscillations in the c band. These findings extend current knowledge on stress physiology, which mainly referred to top-down neural dynamics. Our results suggest that mental stress may not cause an increase in sympathetic activity exclusively as it initiates a dynamic fluctuation within brain-body networks including bidirectional interactions at a brain-heart level. We conclude that directional brain-heart interplay measurements may provide suitable biomarkers for a quantitative stress assessment and bodily feedback may modulate the perceived stress caused by increased cognitive demand

Effect of Bending Anisotropy on the 3D Conformation of Short DNA Loops

The equilibrium three dimensional shape of relatively short loops of DNA is studied using an elastic model that takes into account anisotropy in bending rigidities. Using a reasonable estimate for the anisotropy, it is found that cyclized DNA with lengths that are not integer multiples of the pitch take on nontrivial shapes that involve bending out of planes and formation of kinks. The effect of sequence inhomogeneity on the shape of DNA is addressed, and shown to enhance the geometrical features. These findings could shed some light on the role of DNA conformation in protein--DNA interactions

Comparing Probabilistic Models for Melodic Sequences

Modelling the real world complexity of music is a challenge for machine learning. We address the task of modeling melodic sequences from the same music genre. We perform a comparative analysis of two probabilistic models; a Dirichlet Variable Length Markov Model (Dirichlet-VMM) and a Time Convolutional Restricted Boltzmann Machine (TC-RBM). We show that the TC-RBM learns descriptive music features, such as underlying chords and typical melody transitions and dynamics. We assess the models for future prediction and compare their performance to a VMM, which is the current state of the art in melody generation. We show that both models perform significantly better than the VMM, with the Dirichlet-VMM marginally outperforming the TC-RBM. Finally, we evaluate the short order statistics of the models, using the Kullback-Leibler divergence between test sequences and model samples, and show that our proposed methods match the statistics of the music genre significantly better than the VMM.Comment: in Proceedings of the ECML-PKDD 2011. Lecture Notes in Computer Science, vol. 6913, pp. 289-304. Springer (2011

A preliminary assessment of GPM-based multi-satellite precipitation estimates over a monsoon dominated region

Following the launch of the Global Precipitation Measurement (GPM) Core Observatory, two advanced high resolution multi-satellite precipitation products namely, Integrated Multi-satellitE Retrievals for GPM (IMERG) and Global Satellite Mapping of Precipitation (GSMaP) version 6 are released. A critical evaluation of these newly released precipitation data sets is very important for both the end users and data developers. This study provides a comprehensive assessment of IMERG research product and GSMaP estimates over India at a daily scale for the southwest monsoon season (June to September 2014). The GPM-based precipitation products are inter-compared with widely used TRMM Multi-satellite Precipitation Analysis (TMPA), and gauge-based observations over India. Results show that the IMERG estimates represent the mean monsoon rainfall and its variability more realistically than the gauge-adjusted TMPA and GSMaP data. However, GSMaP has relatively smaller root-mean-square error than IMERG and TMPA, especially over the low mean rainfall regimes and along the west coast of India. An entropy-based approach is employed to evaluate the distributions of the selected precipitation products. The results indicate that the distribution of precipitation in IMERG and GSMaP has been improved markedly, especially for low precipitation rates. IMERG shows a clear improvement in missed and false precipitation bias over India. However, all the three satellite-based rainfall estimates show exceptionally smaller correlation coefficient, larger RMSE, larger negative total bias and hit bias over the northeast India where precipitation is dominated by orographic effects. Similarly, the three satellite-based estimates show larger false precipitation over the southeast peninsular India which is a rain-shadow region. The categorical verification confirms that these satellite-based rainfall estimates have difficulties in detection of rain over the southeast peninsula and northeast India. These preliminary results need to be confirmed in other monsoon seasons in future studies when the fully GPM-based IMERG retrospectively processed data prior to 2014 are available

How to determine local elastic properties of lipid bilayer membranes from atomic-force-microscope measurements: A theoretical analysis

Measurements with an atomic force microscope (AFM) offer a direct way to probe elastic properties of lipid bilayer membranes locally: provided the underlying stress-strain relation is known, material parameters such as surface tension or bending rigidity may be deduced. In a recent experiment a pore-spanning membrane was poked with an AFM tip, yielding a linear behavior of the force-indentation curves. A theoretical model for this case is presented here which describes these curves in the framework of Helfrich theory. The linear behavior of the measurements is reproduced if one neglects the influence of adhesion between tip and membrane. Including it via an adhesion balance changes the situation significantly: force-distance curves cease to be linear, hysteresis and nonzero detachment forces can show up. The characteristics of this rich scenario are discussed in detail in this article.Comment: 14 pages, 9 figures, REVTeX4 style. New version corresponds to the one accepted by PRE. The result section is restructured: a comparison to experimental findings is included; the discussion on the influence of adhesion between AFM tip and membrane is extende

Zero-Shot Hashing via Transferring Supervised Knowledge

Hashing has shown its efficiency and effectiveness in facilitating large-scale multimedia applications. Supervised knowledge e.g. semantic labels or pair-wise relationship) associated to data is capable of significantly improving the quality of hash codes and hash functions. However, confronted with the rapid growth of newly-emerging concepts and multimedia data on the Web, existing supervised hashing approaches may easily suffer from the scarcity and validity of supervised information due to the expensive cost of manual labelling. In this paper, we propose a novel hashing scheme, termed \emph{zero-shot hashing} (ZSH), which compresses images of "unseen" categories to binary codes with hash functions learned from limited training data of "seen" categories. Specifically, we project independent data labels i.e. 0/1-form label vectors) into semantic embedding space, where semantic relationships among all the labels can be precisely characterized and thus seen supervised knowledge can be transferred to unseen classes. Moreover, in order to cope with the semantic shift problem, we rotate the embedded space to more suitably align the embedded semantics with the low-level visual feature space, thereby alleviating the influence of semantic gap. In the meantime, to exert positive effects on learning high-quality hash functions, we further propose to preserve local structural property and discrete nature in binary codes. Besides, we develop an efficient alternating algorithm to solve the ZSH model. Extensive experiments conducted on various real-life datasets show the superior zero-shot image retrieval performance of ZSH as compared to several state-of-the-art hashing methods.Comment: 11 page

Construction and validation of the questionnaire of technology learning competencies of student-teachers

Background and Objectives:Given the impact that new technologies have had on individual and social activities, it is the task of education to respond to the growing needs of the society. To emphasize this task, UNESCO, in 2008, in collaboration with major companies such as Microsoft, Intel, Cisco, the International Association of Education Technology, the Polytechnic Institute and the University of Virginia, designed a document for teacher information and communication technology knowledge. Due to the importance of the issue and the welcome of member countries, this document was further revised. In the introduction to this document, students and teachers must be able to use technology effectively to live, learn and function successfully in highly complex, knowledge-based and information-rich environments. Education should strive to design students with specific characteristics that meet the needs of today's societies by designing an appropriate environment. Some of these characteristics are: capable of using information technology, searcher, analyst and information evaluator, decision maker and problem solver, capable of effective and creative use of productivity tools, informed, responsible and participatory citizens. By increasing the daily and effective use of technology in the educational process, student-teachers gain the opportunity to learn through technology. The growth and development of various information and communication technologies has made it possible to build a variety of software, hardware and Internet networks that can help the educational system of any country in a variety of formal, informal and free learning. Accordingly, given the important role that the teacher has in organizing learning experiences, it is necessary for them to be trained in a way that finds the necessary attitude, knowledge and skills. Accordingly, in-service and pre-service professional programs for teachers should include objective experiences of information and communication technology in the professional dimension. The present paper aims to construct, validate and estimate the reliability of the questionnaire of technology competencies of student-teachers at Shahid Rajaee Teacher Training University (SRTTU) in Tehran. Methods: To do so a questionnaire was developed after a systematic review of literature on theories of technology competencies. Through a random cluster sampling a sample of 60 student teachers of SRTTU was selected and the questionnaire was administered among them. The instrument included 49 items. Item analysis such as item discrimination and loop, construct validation (factor analysis) and reliability analysis (Cronbach Alpha) were utilized. Findings: In factor analysis, three factors were identified as: technology knowledge, knowledge consolidation and knowledge production. The reliability of the questionnaire turned out to be .98. The results indicate that the instrument is both reliable and valid and can be readily used to assess student-teachers’ technology competencies. Conclusion: The results indicate that the instrument is both reliable and valid and can be readily used to assess student-teachers’ technology competencies

Changes of Leptin concentration in plasma in patients with spinal cord injury: A Meta-analysis

Objective:The aim of this study was to investigate changes of leptin concentration in plasma in patients with spinal cord injury to come to a single concept by using a Meta-analysis.Setting:Systematic Review.Methods:Searching relevant articles was performed in Ovid data base, Medline (PubMed) EMBASE, Google Scholar, Cochrane and Scopus up to February 2013. Five articles were selected using two independent reviewers. Analysis were performed using SPSS version 18 and Comparative Meta-analysis software version 2.0.Results:The combined analysis with confidence interval of 95 using comprehensive meta-analysis showed significant higher leptin levels in patients with spinal cord injury in comparison with able bodies (P<0.0001). The effect of spinal lesion level on plasma leptin concentration was also statistically significant (P<0.0001). Body mass index was positively related to plasma leptin concentration in both groups (P<0.0001).Conclusion:This Meta analysis approves increased level of leptin in spinal cord injured patients which can be due to fat distribution changes and sympathetic dysfunction in these patients. Our results also showed that patients with higher spinal lesion level have higher plasma leptin concentration. © 2013 International Spinal Cord Society All rights reserved