• MeSH
• systémy člověk-stroj MeSH
• uživatelské rozhraní počítače MeSH

• Konspekt
• Lékařské vědy. Lékařství
• NLK Obory
• lékařská informatika
• NLK Publikační typ
• elektronické časopisy

• MeSH
• informační věda MeSH
• počítače MeSH
• počítačem řízená výuka MeSH

• Konspekt
• Technika všeobecně
• NLK Obory
• psychologie, klinická psychologie
• technika
• NLK Publikační typ
• elektronické časopisy

This paper describes an ongoing project that has the aim to develop a low cost application to replace a computer mouse for people with physical impairment. The application is based on an eye tracking algorithm and assumes that the camera and the head position are fixed. Color tracking and template matching methods are used for pupil detection. Calibration is provided by neural networks as well as by parametric interpolation methods. Neural networks use back-propagation for learning and bipolar sigmoid function is chosen as the activation function. The user’s eye is scanned with a simple web camera with backlight compensation which is attached to a head fixation device. Neural networks significantly outperform parametric interpolation techniques: 1) the calibration procedure is faster as they require less calibration marks and 2) cursor control is more precise. The system in its current stage of development is able to distinguish regions at least on the level of desktop icons. The main limitation of the proposed method is the lack of head-pose invariance and its relative sensitivity to illumination (especially to incidental pupil reflections).

• MeSH
• fotografování metody   MeSH
• interpretace obrazu počítačem metody   MeSH
• lidé MeSH
• mladý dospělý MeSH
• neuronové sítě MeSH
• pohyby očí fyziologie   MeSH
• retina anatomie a histologie   fyziologie   MeSH
• retinoskopie metody   MeSH
• rozpoznávání automatizované metody   MeSH
• senzitivita a specificita MeSH
• uživatelské rozhraní počítače MeSH
• Check Tag
• lidé MeSH
• mladý dospělý MeSH
• mužské pohlaví MeSH
• ženské pohlaví MeSH
• Publikační typ
• práce podpořená grantem MeSH

• Publikační typ
• abstrakty MeSH

• Publikační typ
• úvodníky MeSH

• MeSH
• benzen MeSH
• hemoglobiny MeSH
• kyslík MeSH
• počítače využití   MeSH
• techniky in vitro MeSH
• vazebná místa MeSH

MOTIVATION: Proteins often recognize their interaction partners on the basis of short linear motifs located in disordered regions on proteins' surface. Experimental techniques that study such motifs use short peptides to mimic the structural properties of interacting proteins. Continued development of these methods allows for large-scale screening, resulting in vast amounts of peptide sequences, potentially containing information on multiple protein-protein interactions. Processing of such datasets is a complex but essential task for large-scale studies investigating protein-protein interactions. RESULTS: The software tool presented in this article is able to rapidly identify multiple clusters of sequences carrying shared specificity motifs in massive datasets from various sources and generate multiple sequence alignments of identified clusters. The method was applied on a previously published smaller dataset containing distinct classes of ligands for SH3 domains, as well as on a new, an order of magnitude larger dataset containing epitopes for several monoclonal antibodies. The software successfully identified clusters of sequences mimicking epitopes of antibody targets, as well as secondary clusters revealing that the antibodies accept some deviations from original epitope sequences. Another test indicates that processing of even much larger datasets is computationally feasible. AVAILABILITY AND IMPLEMENTATION: Hammock is published under GNU GPL v. 3 license and is freely available as a standalone program (from http://www.recamo.cz/en/software/hammock-cluster-peptides/) or as a tool for the Galaxy toolbox (from https://toolshed.g2.bx.psu.edu/view/hammock/hammock). The source code can be downloaded from https://github.com/hammock-dev/hammock/releases. CONTACT: muller@mou.cz SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

• MeSH
• algoritmy * MeSH
• databáze proteinů * MeSH
• epitopy chemie   MeSH
• interakční proteinové domény a motivy * MeSH
• lidé MeSH
• Markovovy řetězce MeSH
• molekulární sekvence - údaje MeSH
• monoklonální protilátky chemie   MeSH
• peptidy chemie   MeSH
• sekvence aminokyselin MeSH
• sekvenční seřazení MeSH
• shluková analýza MeSH
• software MeSH
• src homologní domény MeSH
• Check Tag
• lidé MeSH
• Publikační typ
• časopisecké články MeSH
• práce podpořená grantem MeSH

Verbal communication relies heavily upon mutual understanding, or common ground. Inferring the intentional states of our interaction partners is crucial in achieving this, and social neuroscience has begun elucidating the intra- and inter-personal neural processes supporting such inferences. Typically, however, neuroscientific paradigms lack the reciprocal to-and-fro characteristic of social communication, offering little insight into the way these processes operate online during real-world interaction. In the present study, we overcame this by developing a "hyperscanning" paradigm in which pairs of interactants could communicate verbally with one another in a joint-action task whilst both undergoing functional magnetic resonance imaging simultaneously. Successful performance on this task required both interlocutors to predict their partner's upcoming utterance in order to converge on the same word as each other over recursive exchanges, based only on one another's prior verbal expressions. By applying various levels of analysis to behavioural and neuroimaging data acquired from 20 dyads, three principal findings emerged: First, interlocutors converged frequently within the same semantic space, suggesting that mutual understanding had been established. Second, assessing the brain responses of each interlocutor as they planned their upcoming utterances on the basis of their co-player's previous word revealed the engagement of the temporo-parietal junctional (TPJ), precuneus and dorso-lateral pre-frontal cortex. Moreover, responses in the precuneus were modulated positively by the degree of semantic convergence achieved on each round. Second, effective connectivity among these regions indicates the crucial role of the right TPJ in this process, consistent with the Nexus model. Third, neural signals within certain nodes of this network became aligned between interacting interlocutors. We suggest this reflects an interpersonal neural process through which interactants infer and align to one another's intentional states whilst they establish a common ground.

• MeSH
• dospělí MeSH
• lidé MeSH
• magnetická rezonanční tomografie MeSH
• mladý dospělý MeSH
• mozek fyziologie   MeSH
• neurozobrazování metody   MeSH
• počítačové zpracování obrazu metody   MeSH
• sociální chování * MeSH
• sociální interakce * MeSH
• verbální chování fyziologie   MeSH
• Check Tag
• dospělí MeSH
• lidé MeSH
• mladý dospělý MeSH
• mužské pohlaví MeSH
• ženské pohlaví MeSH
• Publikační typ
• časopisecké články MeSH
• práce podpořená grantem MeSH

• MeSH
• biomechanika fyziologie   MeSH
• dítě MeSH
• experimenty na lidech MeSH
• financování organizované MeSH
• lidé MeSH
• ortopedické fixační pomůcky využití   MeSH
• počítačové zpracování obrazu MeSH
• protetické prostředky využití   MeSH
• skolióza patofyziologie   patologie   MeSH
• software MeSH
• statistika jako téma MeSH
• tlak MeSH
• výzkumné techniky MeSH
• zobrazování trojrozměrné MeSH
• Check Tag
• dítě MeSH
• lidé MeSH

Fractals are models of natural processes with many applications in medicine. The recent studies in medicine show that fractals can be applied for cancer detection and the description of pathological architecture of tumors. This fact is not surprising, as due to the irregular structure, cancerous cells can be interpreted as fractals. Inspired by Sierpinski carpet, we introduce a flexible parametric model of random carpets. Randomization is introduced by usage of binomial random variables. We provide an algorithm for estimation of parameters of the model and illustrate theoretical and practical issues in generation of Sierpinski gaskets and Hausdorff measure calculations. Stochastic geometry models can also serve as models for binary cancer images. Recently, a Boolean model was applied on the 200 images of mammary cancer tissue and 200 images of mastopathic tissue. Here, we describe the Quermass-interaction process, which can handle much more variations in the cancer data, and we apply it to the images. It was found out that mastopathic tissue deviates significantly stronger from Quermass-interaction process, which describes interactions among particles, than mammary cancer tissue does. The Quermass-interaction process serves as a model describing the tissue, which structure is broken to a certain level. However, random fractal model fits well for mastopathic tissue. We provide a novel discrimination method between mastopathic and mammary cancer tissue on the basis of complex wavelet-based self-similarity measure with classification rates more than 80%. Such similarity measure relates to Hurst exponent and fractional Brownian motions. The R package FractalParameterEstimation is developed and introduced in the paper.

• MeSH
• algoritmy MeSH
• diagnóza počítačová metody   MeSH
• duktální karcinom prsu MeSH
• fraktály MeSH
• hodnocení rizik metody   MeSH
• lidé MeSH
• nádory prsu diagnóza   patologie   MeSH
• patologie metody   MeSH
• počítačová simulace MeSH
• stochastické procesy MeSH
• Check Tag
• lidé MeSH
• ženské pohlaví MeSH
• Publikační typ
• časopisecké články MeSH
• práce podpořená grantem MeSH
• srovnávací studie MeSH