input parameters
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The study of cellular structures and their properties represents big potential for their future applications in real practice. The article aims to study the effect of input parameters on the quality and manufacturability of cellular samples 3D-printed from Nylon 12 CF in synergy with testing their bending behavior. Three types of structures (Schwarz Diamond, Shoen Gyroid, and Schwarz Primitive) were selected for investigation that were made via the fused deposition modeling technique. As part of the research focused on the settings of input parameters in terms of the quality and manufacturability of the samples, input parameters such as volume fraction, temperature of the working space, filament feeding method and positioning of the sample on the printing pad were specified for the combination of the used material and 3D printer. During the experimental investigation of the bending properties of the samples, a three-point bending test was performed. The dependences of force on deflection were mathematically described and the amount of absorbed energy and ductility were evaluated. The results show that among the investigated structures, the Schwarz Diamond structure appears to be the most suitable for bending stress applications.
- Klíčová slova
- Nylon 12 CF, additive technology, bending, cellular structures, input parameters,
- Publikační typ
- časopisecké články MeSH
HESP 2.b risk assessment program was studied in detail concerning the effect of changing different input parameters for the output ADI values calculated by the program. We used the standard Netherlands 1.0 scenario offered by the program. With this we fixed a lot of input parameters which define the area, human and animal recipient parameters etc. The remaining 31 unfixed parameters were fixed at first to "BASE" input values and the BASE output values were calculated by HESP. Later we chose only one parameter at a time and changed it to an another value. The calculated ADI values were then compared to BASE output values. Seven parameters (soil type, soil usage, site length, soil pH, groundwater fraction in drinking water, basement floor type and Qev) were studied. We found, that changing soil pH or Qev have not any influence on the output ADI values in case of any contaminant. Soil type change has not any effect on the output ADI value in case of Pb or Cd but it seems to play important role in all cases of the four organic material we investigated. Changing soil usage have influence on the output ADI value almost in every case. It seems to be linear relation between the maximal concentration of contaminant and calculated ADI. Changing the site length and basement floor type gave in some cases different ADI values compared to BASE values. If we alter the groundwater fraction in drinking water we got usually different ADI values. With Risc Human risk assessment program we got similar results: nor the changes in soil type, site diameter or soil pH gave any changes in output ADI values. Our results hint that using HESP and Risc Human requires enhanced caution.
This paper presents new voltage-mode shadow filters employing a low-power multiple-input differential difference transconductance amplifier (MI-DDTA). This device provides multiple-input voltage-mode arithmetic operation capability, electronic tuning ability, high-input and low-output impedances. Therefore, the proposed shadow filters offer circuit simplicity, minimum number of active and passive elements, electronic control of the natural frequency and the quality factor, and high-input and low-output impedances. The proposed MI-DDTA can work with supply voltage of ±0.5 V and consumes 9.94 μW of power. The MI-DDTA and shadow filters have been designed and simulated with the SPICE program using 0.18 μm CMOS process parameters to validate the functionality and workability of the new circuits.
- Klíčová slova
- analog filter, differential difference transconductance amplifier, multiple-input MOS technique, shadow filter,
- Publikační typ
- časopisecké články MeSH
The Ornstein-Uhlenbeck neuronal model is specified by two types of parameters. One type corresponds to the properties of the neuronal membrane, whereas the second type (local average rate of the membrane depolarization and its variability) corresponds to the input of the neuron. In this article, we estimate the parameters of the second type from an intracellular record during neuronal firing caused by stimulation (audio signal). We compare the obtained estimates with those from the spontaneous part of the record. As predicted from the model construction, the values of the input parameters are larger for the periods when neuron is stimulated than for the spontaneous ones. Finally, the firing regimen of the model is checked. It is confirmed that the neuron is in the suprathreshold regimen during the stimulation.
- MeSH
- akční potenciály fyziologie MeSH
- akustická stimulace metody MeSH
- časové faktory MeSH
- elektroencefalografie MeSH
- membránové potenciály fyziologie MeSH
- modely neurologické * MeSH
- morčata MeSH
- nervové dráhy fyziologie MeSH
- neurony klasifikace fyziologie MeSH
- počítačové zpracování signálu MeSH
- reakční čas fyziologie MeSH
- stochastické procesy * MeSH
- zvířata MeSH
- Check Tag
- morčata MeSH
- zvířata MeSH
- Publikační typ
- časopisecké články MeSH
- práce podpořená grantem MeSH
An equation for a stochastic neuronal model describing the initiation of action potentials is studied for the case in which the depolarization of the membrane potential is restricted by the reversal potentials. It is assumed that the values of the membrane potential can be continuously recorded between consecutive spikes. Under this assumption, the estimators of the model parameters are derived and the methods for testing the model are proposed. The objective of the methods presented in this contribution is to provide neuroscientists with quantitative means in order to estimate parameters of stochastic neuronal models.
The process of electrospinning is subject to a variety of input parameters ranging from the characterization of polymers and solvents, the resulting solutions, the geometrical configuration of the device, including its process parameters, and ending with crucial parameters such as temperature and humidity. It is not possible to expect that functional expressions relating all these parameters can be derived in a common description. Nevertheless, it is possible to fix the majority of these parameters to derive explicit relations for a restricted number of entry parameters such that it contributes to the partial elimination of the classical trial-and-error method saving time and financial costs. However, several contributions providing such results are rather moderate. Special attention is provided to fibre diameter approximation as this parameter strongly influences the application of nanofibrous mats in various instances such as air filtration, tissue engineering, and drug delivery systems. Various difficulties connected with the derivation of these explicit relations are presented and discussed in detail.
- Klíčová slova
- electrospinning, explicit relations, nanofibre diameter,
- Publikační typ
- časopisecké články MeSH
Detached off-grids, subject to the generated renewable energy (RE), need to balance and compensate the unstable power supply dependent on local source potential. Power quality (PQ) is a set of EU standards that state acceptable deviations in the parameters of electrical power systems to guarantee their operability without dropout. Optimization of the estimated PQ parameters in a day-horizon is essential in the operational planning of autonomous smart grids, which accommodate the norms for the specific equipment and user demands to avoid malfunctions. PQ data for all system states are not available for dozens of connected / switched on household appliances, defined by their binary load series only, as the number of combinations grows exponentially. The load characteristics and eventual RE contingent supply can result in system instability and unacceptable PQ events. Models, evolved by Artificial Intelligence (AI) methods using self-optimization algorithms, can estimate unknown cases and states in autonomous systems contingent on self-supply of RE power related to chaotic and intermitted local weather sources. A new multilevel extension procedure designed to incrementally improve the applicability and adaptability to training data. The initial AI model starts with binary load series only, which are insufficient to represent complex data patterns. The input vector is progressively extended with correlated PQ parameters at the next estimation level to better represent the active demand of the power consumer. Historical data sets comprise training samples for all PQ parameters, but only the load sequences of the switch-on appliances are available in the next estimation states. The most valuable PQ parameters are selected and estimated in the previous algorithm stages to be used as supplementary series in the next more precise computing. More complex models, using the previous PQ-data approximates, are formed at the secondary processing levels to estimate the target PQ-output in better quality. The new added input parameters allow us to evolve a more convenient model form. The proposed multilevel refinement algorithm can be generally applied in modelling of unknown sequence states of dynamical systems, initially described by binary series or other insufficient limited-data variables, which are inadequate in a problem representation. Most AI computing techniques can adapt this strategy to improve their adaptive learning and model performance.
PURPOSE: One of the main obstacles for reliable quantitative dynamic contrast-enhanced (DCE) MRI is the need for accurate knowledge of the arterial input function (AIF). This is a special challenge for preclinical small animal applications where it is very difficult to measure the AIF without partial volume and flow artifacts. Furthermore, using advanced pharmacokinetic models (allowing estimation of blood flow and permeability-surface area product in addition to the classical perfusion parameters) poses stricter requirements on the accuracy and precision of AIF estimation. This paper addresses small animal DCE-MRI with advanced pharmacokinetic models and presents a method for estimation of the AIF based on blind deconvolution. METHODS: A parametric AIF model designed for small animal physiology and use of advanced pharmacokinetic models is proposed. The parameters of the AIF are estimated using multichannel blind deconvolution. RESULTS: Evaluation on simulated data show that for realistic signal to noise ratios blind deconvolution AIF estimation leads to comparable results as the use of the true AIF. Evaluation on real data based on DCE-MRI with two contrast agents of different molecular weights showed a consistence with the known effects of the molecular weight. CONCLUSION: Multi-channel blind deconvolution using the proposed AIF model specific for small animal DCE-MRI provides reliable perfusion parameter estimates under realistic signal to noise conditions.
- Klíčová slova
- Arterial input function, Blind deconvolution, DCE-MRI,
- MeSH
- algoritmy MeSH
- arterie diagnostické zobrazování MeSH
- farmakokinetika MeSH
- kontrastní látky farmakokinetika MeSH
- lidé MeSH
- magnetická rezonanční tomografie * MeSH
- myši inbrední BALB C MeSH
- myši MeSH
- nekróza patologie MeSH
- perfuze MeSH
- počítačová simulace MeSH
- počítačové zpracování obrazu metody MeSH
- poměr signál - šum MeSH
- regresní analýza MeSH
- reprodukovatelnost výsledků MeSH
- zvířata MeSH
- Check Tag
- lidé MeSH
- myši MeSH
- zvířata MeSH
- Publikační typ
- časopisecké články MeSH
- práce podpořená grantem MeSH
- Názvy látek
- kontrastní látky MeSH
This paper is primarily concerned with determining and assessing the properties of a cement-based composite material containing large particles of aggregate in digital manufacturing. The motivation is that mixtures with larger aggregate sizes offer benefits such as increased resistance to cracking, savings in other material components (such as Portland cement), and ultimately cost savings. Consequently, in the context of 3D Construction/Concrete Print technology (3DCP), these materials are environmentally friendly, unlike the fine-grained mixtures previously utilized. Prior to printing, these limits must be established within the virtual environment's process parameters in order to reduce the amount of waste produced. This study extends the existing research in the field of large-scale 3DCP by employing coarse aggregate (crushed coarse river stone) with a maximum particle size of 8 mm. The research focuses on inverse material characterization, with the primary goal of determining the optimal combination of three monitored process parameters-print speed, extrusion height, and extrusion width-that will maximize buildability. Design Of Experiment was used to cover all possible variations and reduce the number of required simulations. In particular, the Box-Behnken method was used for three factors and a central point. As a result, thirteen combinations of process parameters covering the area of interest were determined. Thirteen numerical simulations were conducted using the Abaqus software, and the outcomes were discussed.
Stimulus response latency is the time period between the presentation of a stimulus and the occurrence of a change in the neural firing evoked by the stimulation. The response latency has been explored and estimation methods proposed mostly for excitatory stimuli, which means that the neuron reacts to the stimulus by an increase in the firing rate. We focus on the estimation of the response latency in the case of inhibitory stimuli. Models used in this paper represent two different descriptions of response latency. We consider either the latency to be constant across trials or to be a random variable. In the case of random latency, special attention is given to models with selective interaction. The aim is to propose methods for estimation of the latency or the parameters of its distribution. Parameters are estimated by four different methods: method of moments, maximum-likelihood method, a method comparing an empirical and a theoretical cumulative distribution function and a method based on the Laplace transform of a probability density function. All four methods are applied on simulated data and compared.
- MeSH
- aferentní nervové dráhy fyziologie MeSH
- akční potenciály fyziologie MeSH
- časové faktory MeSH
- fyzikální stimulace MeSH
- lidé MeSH
- modely neurologické * MeSH
- nervový útlum fyziologie MeSH
- neurony fyziologie MeSH
- počítačová simulace MeSH
- reakční čas fyziologie MeSH
- statistické modely MeSH
- Check Tag
- lidé MeSH
- Publikační typ
- časopisecké články MeSH
- práce podpořená grantem MeSH
