1,686 research outputs found

    Quantum mechanical study of molecules - Eigenvalues and eigenvectors of real symmetric matrices

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    Computer methods for calculating eigenvalue and eigenvectors of real symmetric matrices arising in problems of molecular quantum mechanic

    Scaling of the Hysteresis Loop in Two-dimensional Solidification

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    The first order phase transitions between a two-dimensional (2d) gas and the 2d solid of the first monolayer have been studied for the noble gases Ar, Kr and Xe on a NaCl(100) surface in quasi-equilibrium with the three-dimensional gas phase. Using linear temperature ramps, we show that the widths of the hysteresis loops of these transitions as a function of the heating rate, r, scales with a power law r^alpha with alpha between 0.4 and 0.5 depending on the system. The hysteresis loops for different heating rates are similar. The island area of the condensed layer was found to grow initially with a t^4 time dependence. These results are in agreement with theory, which predicts alpha = 0.5 and hysteresis loop similarity.Comment: 4 pages, 5 figures, Revte

    A case report of an interrupted inferior vena cava and azygos continuation:Implications for preoperative screening in minimally invasive cardiac surgery

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    Background: Femoral cannulation is commonly used in minimally invasive cardiac surgery to establish extracorporeal circulation. We present a case with a finding that should be evaluated when screening candidates for minimally invasive cardiac surgery. Case summary: A 57-year-old male patient was scheduled for minimally invasive repair of the mitral and tricuspid valve and a MAZE procedure. During surgery there was difficulty advancing the venous cannula inserted in the right femoral vein. On transoesophageal echocardiography a guidewire advanced from the femoral vein was observed entering the right atrium from the superior vena cava. Despite inserting a second venous cannula in the jugular vein, venous drainage was insufficient for minimal invasive surgery. The approach was converted to a median sternotomy with bicaval cannulation. Re-examination of the preoperative computed tomography (CT) scan showed an interrupted inferior vena cava (IVC) with azygos continuation. Discussion: In patients with major venous malformations such as the interrupted IVC with azygos continuation a full sternotomy is the preferred approach. The venous system should be evaluated when screening candidates for minimally invasive mitral valve surgery with preoperative CT. Additional cues to suspect interruption of the IVC are polysplenia and a broad superior mediastinal projection on the chest radiograph, mimicking a right paratracheal mass.</p

    Multiplicative noise: A mechanism leading to nonextensive statistical mechanics

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    A large variety of microscopic or mesoscopic models lead to generic results that accommodate naturally within Boltzmann-Gibbs statistical mechanics (based on S1kdup(u)lnp(u)S_1\equiv -k \int du p(u) \ln p(u)). Similarly, other classes of models point toward nonextensive statistical mechanics (based on Sqk[1du[p(u)]q]/[q1]S_q \equiv k [1-\int du [p(u)]^q]/[q-1], where the value of the entropic index qq\in\Re depends on the specific model). We show here a family of models, with multiplicative noise, which belongs to the nonextensive class. More specifically, we consider Langevin equations of the type u˙=f(u)+g(u)ξ(t)+η(t)\dot{u}=f(u)+g(u)\xi(t)+\eta(t), where ξ(t)\xi(t) and η(t)\eta(t) are independent zero-mean Gaussian white noises with respective amplitudes MM and AA. This leads to the Fokker-Planck equation tP(u,t)=u[f(u)P(u,t)]+Mu{g(u)u[g(u)P(u,t)]}+AuuP(u,t)\partial_t P(u,t) = -\partial_u[f(u) P(u,t)] + M\partial_u\{g(u)\partial_u[g(u)P(u,t)]\} + A\partial_{uu}P(u,t). Whenever the deterministic drift is proportional to the noise induced one, i.e., f(u)=τg(u)g(u)f(u) =-\tau g(u) g'(u), the stationary solution is shown to be P(u,){1(1q)β[g(u)]2}11qP(u, \infty) \propto \bigl\{1-(1-q) \beta [g(u)]^2 \bigr\}^{\frac{1}{1-q}} (with qτ+3Mτ+Mq \equiv \frac{\tau + 3M}{\tau+M} and β=τ+M2A\beta=\frac{\tau+M}{2A}). This distribution is precisely the one optimizing SqS_q with the constraint q{du[g(u)]2[P(u)]q}/{du[P(u)]q}=_q \equiv \{\int du [g(u)]^2[P(u)]^q \}/ \{\int du [P(u)]^q \}= constant. We also introduce and discuss various characterizations of the width of the distributions.Comment: 3 PS figure

    Do the prelingual deaf code verbal material visually in short-term memory?

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    Human-Robot Team Interaction Through Wearable Haptics for Cooperative Manipulation

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    The interaction of robot teams and single human in teleoperation scenarios is beneficial in cooperative tasks, for example the manipulation of heavy and large objects in remote or dangerous environments. The main control challenge of the interaction is its asymmetry, arising because robot teams have a relatively high number of controllable degrees of freedom compared to the human operator. Therefore, we propose a control scheme that establishes the interaction on spaces of reduced dimensionality taking into account the low number of human command and feedback signals imposed by haptic devices. We evaluate the suitability of wearable haptic fingertip devices for multi-contact teleoperation in a user study. The results show that the proposed control approach is appropriate for human-robot team interaction and that the wearable haptic fingertip devices provide suitable assistance in cooperative manipulation tasks

    Circadian Intraocular Pressure Profiles in Chronic Open Angle Glaucomas

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    Purpose: To evaluate circadian intraocular pressure (IOP) profiles in eyes with different types of chronic open-angle glaucoma (COAG) and normal eyes. Methods: This study included 3,561 circadian IOP profiles obtained from 1,408 eyes of 720 Caucasian individuals including glaucoma patients under topical treatment (1,072 eyes) and normal subjects (336 eyes). IOP profiles were obtained by Goldmann applanation tonometry and included measurements at 7 am, noon, 5 pm, 9 pm, and midnight. Results: Fluctuations of circadian IOP in the secondary open-angle glaucoma (SOAG) group (6.96±3.69 mmHg) was significantly (P<0.001) higher than that of the normal pressure glaucoma group (4.89±1.99 mmHg) and normal eyes (4.69±1.95 mmHg); but the difference between the two latter groups was not significant (P=0.47). Expressed as percentages, IOP fluctuations did not vary significantly among any of the study groups. Inter-ocular IOP difference for any measurement was significantly (P<0.001) smaller than the profile fluctuations. In all study groups except the SOAG group, IOP was highest at 7 am, followed by noon, 5 pm, and finally 9 pm or midnight. In the SOAG group, mean IOP measurements did not vary significantly during day and night. Conclusions: In contrast to normal eyes and eyes with primary open-angle glaucoma under topical antiglaucoma treatment, eyes with SOAG under topical treatment do not show the usual circadian IOP profile in which the highest IOP values occur in the morning, and the lowest in the evening or at midnight. These findings may have implications for timing of tonometry. Fluctuation of circadian IOP was highest in SOAG compared to other types of open angle glaucomas

    Towards a New Science of a Clinical Data Intelligence

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    In this paper we define Clinical Data Intelligence as the analysis of data generated in the clinical routine with the goal of improving patient care. We define a science of a Clinical Data Intelligence as a data analysis that permits the derivation of scientific, i.e., generalizable and reliable results. We argue that a science of a Clinical Data Intelligence is sensible in the context of a Big Data analysis, i.e., with data from many patients and with complete patient information. We discuss that Clinical Data Intelligence requires the joint efforts of knowledge engineering, information extraction (from textual and other unstructured data), and statistics and statistical machine learning. We describe some of our main results as conjectures and relate them to a recently funded research project involving two major German university hospitals.Comment: NIPS 2013 Workshop: Machine Learning for Clinical Data Analysis and Healthcare, 201
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