Search results for "software"

2020

Human movements are characterized by highly non-linear and multi-dimensional interactions within the motor system. Recently, an increasing emphasis on machine-learning applications has led to a significant contribution to the field of gait analysis, e.g., in increasing the classification performance. In order to ensure the generalizability of the machine-learning models, different data preprocessing steps are usually carried out to process the measured raw data before the classifications. In the past, various methods have been used for each of these preprocessing steps. However, there are hardly any standard procedures or rather systematic comparisons of these different methods and their im…

Alterations in White Matter Network and Microstructural Integrity Differentiate Parkinson’s Disease Patients and Healthy Subjects

2019

Parkinson’s disease (PD) is a neurodegenerative disease, neuropathologically characterized by progressive loss of neurons in distinct brain areas. We hypothesize that quantifiable network alterations are caused by neurodegeneration. The primary motivation of this study was to assess the specific network alterations in PD patients that are distinct but appear in conjunction with physiological aging. 178 subjects (130 females) stratified into PD patients, young, middle-aged and elderly healthy controls (age- and sex-matched with PD patients), were analyzed using 3D-T1 magnetization-prepared rapid gradient-echo (MPRAGE) and diffusion weighted images acquired in 3T MRI scanner. Diffusion modeli…

Generalized Molecular Descriptors Derived From Event-Based Discrete Derivative.

2016

In the present study, a generalized approach for molecular structure characterization is introduced, based on the relation frequency matrix (F) representation of the molecular graph and the subsequent calculation of the corresponding discrete derivative (finite difference) over a pair of elements (atoms). In earlier publications (22- 24), an unique event, named connected subgraphs, (based on the Kier-Hall's subgraphs) was systematically employed for the computation of the matrix F. The present report is a generalization of this notion, in which eleven additional events are introduced, classified in three categories, namely, topological (terminal paths, vertex path incidence, quantum subgrap…

Stochastic sampling effects favor manual over digital contact tracing.

2020

Isolation of symptomatic individuals, tracing and testing of their nonsymptomatic contacts are fundamental strategies for mitigating the current COVID-19 pandemic. The breaking of contagion chains relies on two complementary strategies: manual reconstruction of contacts based on interviews and a digital (app-based) privacy-preserving contact tracing. We compare their effectiveness using model parameters tailored to describe SARS-CoV-2 diffusion within the activity-driven model, a general empirically validated framework for network dynamics. We show that, even for equal probability of tracing a contact, manual tracing robustly performs better than the digital protocol, also taking into accou…

Spike-wave discharges in absence epilepsy: segregation of electrographic components reveals distinct pathways of seizure activity.

2020

Key points The major electrophysiological hallmarks of absence seizures are spike and wave discharges (SWDs), consisting of a sharp spike component and a slow wave component. In a widely accepted scheme, these components are functionally coupled and reflect an iterative progression of neuronal excitation during the spike and post-excitatory silence during the wave. In a genetic rat model of absence epilepsy, local pharmacological inhibition of the centromedian thalamus (CM) selectively suppressed the spike component, leaving self-contained waves in epidural recordings. Thalamic inputs induced activity in cortical microcircuits underlying the spike component, while intracortical oscillations…

Response to I. Batinic-Haberle et al.

2016

Letter to the editor.-- et al.

The habitual nature of food purchases at the supermarket: Implications for policy making

2020

Abstract Supermarkets have become the most important provider of food products worldwide. However, empirical evidence about how consumers make their food purchase decisions in this environment is still scarce. The present field study aimed to: i) explore how people make their in-store food purchases, and ii) identify the information they search for when making those purchases. Consumers (n = 144) were intercepted when entering the facilities of three supermarkets in two Uruguayan cities. They were asked to wear a mobile eye-tracker while they made their purchases as they normally do. The great majority of the consumers bought at least one food product or beverage (92%) and, on average, exam…

KnotGenome: a server to analyze entanglements of chromosomes.

2018

Abstract The KnotGenome server enables the topological analysis of chromosome model data using three-dimensional coordinate files of chromosomes as input. In particular, it detects prime and composite knots in single chromosomes, and links between chromosomes. The knotting complexity of the chromosome is presented in the form of a matrix diagram that reveals the knot type of the entire polynucleotide chain and of each of its subchains. Links are determined by means of the Gaussian linking integral and the HOMFLY-PT polynomial. Entangled chromosomes are presented graphically in an intuitive way. It is also possible to relax structure with short molecular dynamics runs before the analysis. Kn…

Computational modeling of bicuspid aortopathy: Towards personalized risk strategies.

2019

This paper describes current advances on the application of in-silico for the understanding of bicuspid aortopathy and future perspectives of this technology on routine clinical care. This includes the impact that artificial intelligence can provide to develop computer-based clinical decision support system and that wearable sensors can offer to remotely monitor high-risk bicuspid aortic valve (BAV) patients. First, we discussed the benefit of computational modeling by providing tangible examples of in-silico software products based on computational fluid-dynamic (CFD) and finite-element method (FEM) that are currently transforming the way we diagnose and treat cardiovascular diseases. Then…

Automatic sleep scoring: A deep learning architecture for multi-modality time series

2020

Background: Sleep scoring is an essential but time-consuming process, and therefore automatic sleep scoring is crucial and urgent to help address the growing unmet needs for sleep research. This paper aims to develop a versatile deep-learning architecture to automate sleep scoring using raw polysomnography recordings. Method: The model adopts a linear function to address different numbers of inputs, thereby extending model applications. Two-dimensional convolution neural networks are used to learn features from multi-modality polysomnographic signals, a “squeeze and excitation” block to recalibrate channel-wise features, together with a long short-term memory module to exploit long-range co…