AIMS OF THE STUDY: Commonly used approach to illness assessment focuses on the patient's actual state supplemented by binary records of past events and conditions. This research project was designed to explain subjective experience in idiopathic hypersomnia (IH) patients influenced by their clinical symptoms and comorbidities. MATERIAL AND METHODS: Forty-three IH patients of both sexes (female 60.5%, male 39.5%) were assessed using a detailed structured examination. The interview covered neurologic, psychiatric, and internal medicine anamnesis, medication past and current, substance abuse, work impairment, detailed sleep-related data, specific sleep medication, and a full-length set of questionnaires including depression, quality of life, sleepiness, anxiety, fatigue, insomnia, and sleep inertia. The data were digitized and imported into statistical software (SPSS by IBM), and dynamic simulation software (Vensim by Ventana Systems Inc.) was used to build a causal loop diagram and stocks and flows diagram as a simulation structure. RESULTS: The overall raw data and simulation-based patterns fit at 76.1%. The simulation results also identified the parameters that contribute the most to patients' subjective experience. These included sleep inertia, the refreshing potential of naps, the quality of nocturnal sleep, and the social aspects of the patient's life. Psychiatric disorders influence the overall pattern at a surprisingly low level. The influence of medication has been studied in detail. Although its contribution to the dynamics looks marginal at first sight, it significantly influences the contribution of other variables to the overall patient experience of the disease. CONCLUSION: Even the simplified dynamic structure designed by the research team reflects the real-life events in patients with IH at the acceptable level of 76.1% and suggests that a similar structure plays an important role in the course of the disease. Therapeutic focus on the parameters identified by the model should enhance the patients' subjective experience throughout illness duration and might even turn the progress from negative into positive. Further research is needed to understand the dynamics of idiopathic hypersomnia in greater detail to better understand the causes and design therapeutic approaches to improve patients' quality of life.

• Klíčová slova
• dynamic modeling, idiopathic hypersomnia, sleep disorders, treatment strategy, work impairment,
• Publikační typ
• časopisecké články MeSH

This paper presents a new approach to inverting (fitting) models of coupled dynamical systems based on state-of-the-art (cubature) Kalman filtering. Crucially, this inversion furnishes posterior estimates of both the hidden states and parameters of a system, including any unknown exogenous input. Because the underlying generative model is formulated in continuous time (with a discrete observation process) it can be applied to a wide variety of models specified with either ordinary or stochastic differential equations. These are an important class of models that are particularly appropriate for biological time-series, where the underlying system is specified in terms of kinetics or dynamics (i.e., dynamic causal models). We provide comparative evaluations with generalized Bayesian filtering (dynamic expectation maximization) and demonstrate marked improvements in accuracy and computational efficiency. We compare the schemes using a series of difficult (nonlinear) toy examples and conclude with a special focus on hemodynamic models of evoked brain responses in fMRI. Our scheme promises to provide a significant advance in characterizing the functional architectures of distributed neuronal systems, even in the absence of known exogenous (experimental) input; e.g., resting state fMRI studies and spontaneous fluctuations in electrophysiological studies. Importantly, unlike current Bayesian filters (e.g. DEM), our scheme provides estimates of time-varying parameters, which we will exploit in future work on the adaptation and enabling of connections in the brain.

• MeSH
• algoritmy * MeSH
• hemodynamika fyziologie   MeSH
• interpretace obrazu počítačem metody   MeSH
• lidé MeSH
• magnetická rezonanční tomografie MeSH
• metoda Monte Carlo MeSH
• modely neurologické * MeSH
• mozek krevní zásobení   fyziologie   MeSH
• nervové dráhy fyziologie   MeSH
• neurony fyziologie   MeSH
• Check Tag
• lidé MeSH
• Publikační typ
• časopisecké články MeSH
• práce podpořená grantem MeSH
• Research Support, N.I.H., Extramural MeSH

Simul 6 is a 1D dynamic simulator of electromigration based on the mathematical model of electromigration in free solutions. The model consists of continuity equations for the movement of electrolytes in a separation channel, acid-base equilibria of weak electrolytes, and the electroneutrality condition. It accounts for any number of multivalent electrolytes or ampholytes and provides a complete picture about dynamics of electromigration and diffusion in the separation channel. The equations are solved numerically using software means which allow for parallelization and multithreaded computation. Simul 6 has a user-friendly graphical interface. It is typically used for inspection of system peaks (zones) in electrophoresis, stacking and preconcentrating analytes, optimization of separation conditions, method development in either capillary zone electrophoresis, isotachophoresis, and isoelectric focusing. Simul 6 is the successor of Simul 5, and has been launched as a free software available for download at https://simul6.app/.

• Klíčová slova
• Continuity equation, Dynamic simulator, Electromigration, Electrophoresis, Numerical solution,
• MeSH
• elektroforéza kapilární MeSH
• elektrolyty MeSH
• počítačová simulace MeSH
• software * MeSH
• teoretické modely MeSH
• Publikační typ
• časopisecké články MeSH
• práce podpořená grantem MeSH
• Názvy látek
• elektrolyty MeSH

This paper presents one of the soft computing methods, specifically the artificial neural network technique, that has been used to model the temperature dependence of dynamic mechanical properties and visco-elastic behavior of widely exploited thermoplastic polyurethane over the wide range of temperatures. It is very complex and commonly a highly non-linear problem with no easy analytical methods to predict them directly and accurately in practice. Variations of the storage modulus, loss modulus, and the damping factor with temperature were obtained from the dynamic mechanical analysis tests across transition temperatures at constant single frequency of dynamic mechanical loading. Based on dynamic mechanical analysis experiments, temperature dependent values of both dynamic moduli and damping factor were calculated by three models of well-trained multi-layer feed-forward back-propagation artificial neural network. The excellent agreement between the modeled and experimental data has been found over the entire investigated temperature interval, including all of the observed relaxation transitions. The multi-layer feed-forward back-propagation artificial neural network has been confirmed to be a very effective artificial intelligence tool for the modeling of dynamic mechanical properties and for the prediction of visco-elastic behavior of tested thermoplastic polyurethane in the whole temperature range of its service life.

• Klíčová slova
• artificial neural networks, dynamic mechanical analysis, stiffness-temperature model, thermoplastic polyurethanes, visco-elastic properties,
• Publikační typ
• časopisecké články MeSH

BACKGROUND: Alzheimer's disease is one of the most common mental illnesses. It is posited that more than 25% of the population is affected by some mental disease during their lifetime. Treatment of each patient draws resources from the economy concerned. Therefore, it is important to quantify the potential economic impact. METHODS: Agent-based, system dynamics and numerical approaches to dynamic modeling of the population of the European Union and its patients with Alzheimer's disease are presented in this article. Simulations, their characteristics, and the results from different modeling tools are compared. RESULTS: The results of these approaches are compared with EU population growth predictions from the statistical office of the EU by Eurostat. The methodology of a creation of the models is described and all three modeling approaches are compared. The suitability of each modeling approach for the population modeling is discussed. CONCLUSION: In this case study, all three approaches gave us the results corresponding with the EU population prediction. Moreover, we were able to predict the number of patients with AD and, based on the modeling method, we were also able to monitor different characteristics of the population.

• Klíčová slova
• Alzheimer’s disease, agent-based model, numerical model, population modeling, population prediction, system dynamics.,
• MeSH
• Alzheimerova nemoc diagnóza   epidemiologie   MeSH
• biologické modely MeSH
• lidé MeSH
• systémová analýza * MeSH
• teoretické modely * MeSH
• Check Tag
• lidé MeSH
• Publikační typ
• časopisecké články MeSH
• práce podpořená grantem MeSH

The presented work deals with the creation of a new radial basis function artificial neural network-based model of dynamic thermo-mechanical response and damping behavior of thermoplastic elastomers in the whole temperature interval of their entire lifetime and a wide frequency range of dynamic mechanical loading. The created model is based on experimental results of dynamic mechanical analysis of the widely used thermoplastic polyurethane, which is one of the typical representatives of thermoplastic elastomers. Verification and testing of the well-trained radial basis function neural network for temperature and frequency dependence of dynamic storage modulus, loss modulus, as well as loss tangent prediction showed excellent correspondence between experimental and modeled data, including all relaxation events observed in the polymeric material under study throughout the monitored temperature and frequency interval. The radial basis function artificial neural network has been confirmed to be an exceptionally high-performance artificial intelligence tool of soft computing for the effective predicting of short-term viscoelastic behavior of thermoplastic elastomer systems based on experimental results of dynamic mechanical analysis.

• Klíčová slova
• artificial neural networks, dynamic mechanical analysis, radial basis functions, thermoplastic polyurethanes, visco-elastic properties,
• Publikační typ
• časopisecké články MeSH

Computational models of biological materials enable researchers to gain insight and make testable predictions of quantitative dynamic responses to stimuli. These models are particularly challenging to develop because biological materials are (1) highly heterogeneous containing both biological cells and complex substances such as extra-cellular medium, (2) undergo structural rearrangement (3) couple biological cells with their environment via chemical and mechanical processes. Existing numerical approaches excel at either describing biological cells or solids and fluids, but have difficulty integrating them into a single simulation approach. We present a novel dynamic non-manifold mesh data structure that naturally represents biological materials with coupled chemical and mechanical processes and structural rearrangement in a unified way.

• Klíčová slova
• Biological Simulation, Dynamic Meshing, Finite Element Simulation, Physically Based Modeling,
• Publikační typ
• časopisecké články MeSH

Capillary electrophoresis hyphenated with electrospray mass spectrometry (CE-ESI-MS) has emerged in the past decade as one of the most powerful bioanalytical techniques. As the sensitivity and efficiency of new CE-ESI-MS interface designs are continuously improving, numerical modeling can play important role during their development. In this review, different aspects of computer modeling and simulation of CE-ESI-MS interfaces are comprehensively discussed. Relevant essentials of hydrodynamics as well as state-of-the-art modeling techniques are critically evaluated. Sheath liquid-, sheathless-, and liquid-junction interfaces are reviewed from the viewpoint of multidisciplinary numerical modeling along with details of single and multiphase models together with electric field mediated flows, electrohydrodynamics, and free fluid-surface methods. Practical examples are given to help non-specialists to understand the basic principles and applications. Finally, alternative approaches like air amplifiers are also included. © 2014 Wiley Periodicals, Inc. Mass Spec Rev 34: 558-569, 2015.

• Klíčová slova
• CE-ESI-MS, CFD, interface design, modeling, simulation,
• MeSH
• algoritmy MeSH
• chemické modely MeSH
• elektroforéza kapilární přístrojové vybavení   metody   MeSH
• elektromagnetická pole MeSH
• hmotnostní spektrometrie s elektrosprejovou ionizací přístrojové vybavení   metody   MeSH
• hydrodynamika MeSH
• lidé MeSH
• počítačová simulace MeSH
• zvířata MeSH
• Check Tag
• lidé MeSH
• zvířata MeSH
• Publikační typ
• časopisecké články MeSH
• práce podpořená grantem MeSH
• přehledy MeSH

The need for an environmental risk assessment for engineered nanomaterials (ENM) necessitates the knowledge about their environmental emissions. Material flow models (MFA) have been used to provide predicted environmental emissions but most current nano-MFA models consider neither the rapid development of ENM production nor the fact that a large proportion of ENM are entering an in-use stock and are released from products over time (i.e., have a lag phase). Here we use dynamic probabilistic material flow modeling to predict scenarios of the future flows of four ENM (nano-TiO2, nano-ZnO, nano-Ag and CNT) to environmental compartments and to quantify their amounts in (temporary) sinks such as the in-use stock and ("final") environmental sinks such as soil and sediment. In these scenarios, we estimate likely future amounts if the use and distribution of ENM in products continues along current trends (i.e., a business-as-usual approach) and predict the effect of hypothetical trends in the market development of nanomaterials, such as the emergence of a new widely used product or the ban on certain substances, on the flows of nanomaterials to the environment in years to come. We show that depending on the scenario and the product type affected, significant changes of the flows occur over time, driven by the growth of stocks and delayed release dynamics.

• MeSH
• látky znečišťující životní prostředí * MeSH
• nanostruktury * MeSH
• půda MeSH
• teoretické modely MeSH
• životní prostředí MeSH
• Publikační typ
• časopisecké články MeSH
• práce podpořená grantem MeSH
• Názvy látek
• látky znečišťující životní prostředí * MeSH
• půda MeSH

Calculating the spectroscopic properties of complex conjugated organic molecules in their relaxed state is far from simple. An additional complexity arises for flexible molecules in solution, where the rotational energy barriers are low enough so that nonminimum conformations may become dynamically populated. These metastable conformations quickly relax during the minimization procedures preliminary to density functional theory calculations, and so accounting for their contribution to the experimentally observed properties is problematic. We describe a strategy for stabilizing these nonminimum conformations in silico, allowing their properties to be calculated. Diadinoxanthin and alloxanthin present atypical vibrational properties in solution, indicating the presence of several conformations. Performing energy calculations in vacuo and polarizable continuum model calculations in different solvents, we found three different conformations with values for the δ dihedral angle of the end ring ca. 0, 180, and 90° with respect to the plane of the conjugated chain. The latter conformation, a nonglobal minimum, is not stable during the minimization necessary for modeling its spectroscopic properties. To circumvent this classical problem, we used a Car-Parinello MD supermolecular approach, in which diadinoxanthin was solvated by water molecules so that metastable conformations were stabilized by hydrogen-bonding interactions. We progressively removed the number of solvating waters to find the minimum required for this stabilization. This strategy represents the first modeling of a carotenoid in a distorted conformation and provides an accurate interpretation of the experimental data.

• Publikační typ
• časopisecké články MeSH