A-Brain: a general system for solving data analysis problems

An intelligent system should be able to solve a wide range of problems from different domains. In this paper we propose a complex and adaptive system capable of solving various data analysis problems without needing human help for parameter settings. The system, called A-Brain, consists of several interconnected components (a decision-maker, a trainer, and several problem solvers) which provide a base for building complex problem solvers. The parameters of the trainer's algorithm are problem independent. This fact is a requirement for intelligent systems which cannot rely on human intervention while operating. The A-Brain system is used to solve some well-known problems in the field of symbolic regression and classification. Numerical experiments show that the A-Brain system is able to perform very well on the considered test problems.     

A linearly implicit trapezoidal method for integrating stiff multibody dynamics with contact,joints, and friction

We present a hard constraint, linear complementarity based, method for the simulation of stiff multibody dynamics with contact, joints and friction. The approach uses a linearization of the modified trapezoidal method, incorporates a Poisson restitution model at collision, and solves only one linear complementarity problem per time step when no collisions are encountered. We prove that, under certain assumptions, the method has order two, a fact that is also demonstrated by our numerical simulations. For the unconstrained (ODE) case, the method achieves second‐order convergence and absolute stability while solving only one linear system per step. When we use a special approximation of the Jacobian matrix for the case where the stiff forces originate in springs and dampers attached to two points in the system, the linear complementarity problem can be solved for any value of the time step and numerical simulation demonstrate that the method is stiffly stable. The method was implemented in UMBRA, an industrial‐grade virtual prototyping software. Copyright © 2005 John Wiley & Sons, Ltd.     

Quantitative Thermal Microscopy Measurement with Thermal Probe Driven by dc+ac Current

Quantitative thermal measurements with spatial resolution allowing the examination of objects of submicron dimensions are still a challenging task. The quantity of methods providing spatial resolution better than 100 nm is very limited. One of them is scanning thermal microscopy (SThM). This method is a variant of atomic force microscopy which uses a probe equipped with a temperature sensor near the apex. Depending on the sensor current, either the temperature or the thermal conductivity distribution at the sample surface can be measured. However, like all microscopy methods, the SThM gives only qualitative information. Quantitative measuring methods using SThM equipment are still under development. In this paper, a method based on simultaneous registration of the static and the dynamic electrical resistances of the probe driven by the sum of dc and ac currents, and examples of its applications are described. Special attention is paid to the investigation of thin films deposited on thick substrates. The influence of substrate thermal properties on the measured signal and its dependence on thin film thermal conductivity and film thickness are analyzed. It is shown that in the case where layer thicknesses are comparable or smaller than the probe–sample contact diameter, a correction procedure is required to obtain actual thermal conductivity of the layer. Experimental results obtained for thin SiO\(_{\mathrm {2}}\) and BaTiO\(_{\mathrm {3 }}\)layers with thicknesses in the range from 11 nm to 100 nm are correctly confirmed with this approach.     

Microstructural characterization and amorphous phase formation in Co40Fe22Ta8B30 powders produced by mechanical alloying

In this work, microstructural evolution and amorphous phase formation in Co₄₀Fe₂₂Ta₈B₃₀ alloy produced by mechanical alloying (MA) of the elemental powder mixture under argon gas atmosphere was investigated. Milling time had a profound effect on the phase transformation, microstructure, morphological evolution and thermal behavior of the powders. These effects were studied by the X-ray powder diffraction (XRD) in reflection mode using Cu Kα and in transmission configuration using synchrotron radiation, transmission electron microscopy (TEM), scanning electron microscopy (SEM) and differential scanning calorimetry (DSC). The results showed that at the early stage of the milling, microstructure consisted of nanocrystalline bcc-(Fe, Co) phases and unreacted tantalum.Further milling, produced an amorphous phase, which became a dominant phase with a fraction of 96 wt% after 200 h milling. The DSC profile of 200 h milled powders demonstrated a huge and broad exothermic hump due to the structural relaxation, followed by a single exothermic peak, indicating the crystallization of the amorphous phase. Further XRD studies in transmission mode by synchrotron radiation revealed that the crystalline products were (Co, Fe)_20.82Ta_2.18B₆, (Co, Fe)₂₁ Ta₂ B₆, and (Co, Fe)₃B₂. The amorphization mechanisms were discussed in terms of severe grain refinement, atomic size effect, the concept of local topological instability and the heat of mixing of the reactants.     

In vitro evaluation of anti-pathogenic surface coating nanofluid,obtained by combining Fe3O4/C12 nanostructures and 2-((4-ethylphenoxy)methyl)-N-(substituted-phenylcarbamothioyl)-benzamides

In this paper, we report the design of a new nanofluid for anti-pathogenic surface coating. For this purpose, new 2-((4-ethylphenoxy)methyl)-N-(substituted-phenylcarbamothioyl)-benzamides were synthesized and used as an adsorption shell for Fe₃O₄/C₁₂ core/shell nanosized material. The functionalized specimens were tested by in vitro assays for their anti-biofilm properties and biocompatibility. The optimized catheter sections showed an improved resistance to Staphylococcus aureus ATCC 25923 and Pseudomonas aeruginosa ATCC 27853 in vitro biofilm development, as demonstrated by the viable cell counts of biofilm-embedded bacterial cells and by scanning electron microscopy examination of the colonized surfaces. The nanofluid proved to be not cytotoxic and did not influence the eukaryotic cell cycle. These results could be of a great interest for the biomedical field, opening new directions for the design of film-coated surfaces with improved anti-biofilm properties.     

Algebraic structures for fuzzy numbers from categorial point of view

Using a classic algebraic construction additive and multiplicative structures (as commutative monoids) for fuzzy numbers are obtained. Moreover, we realize here an isomorphism between these structures.     

A method for rough estimation of the catalyst surface area in a fuel cell

A method for a rough estimation of the catalyst surface area in a fuel cell is developed. It is based on the deconvolution of experimental CO oxidation data by use of a mathematical model. The kinetic parameters of the model are determined by fitting the experimental curves. The experimental data are collected at different sweep rates (2–100 mV s⁻¹) and at different temperatures (room −60.0 °C). The model can predict the sweep rate dependence of the CO oxidation onset potential, the peak current, the peak potential and the peak broadness. The model is further used for the prediction of the baseline in the presence of CO and for calculation of the CO charge consumed up to half peak potential. It is obtained that the latter value is constant at different sweep rates and that the baseline deviates from linearity already at low sweep rates (2 mV s⁻¹), but not very significantly (2.0% in comparison to 8.8% at 100 mV s⁻¹, based on calculated CO charge). It is suggested that lower sweep rates should be used for experimental surface area determination.     

Criteria for Identifying the Major Risks Associated with Tailings Ponds in Romania

Damage caused by accidents at hydraulic structures, due to natural hazards or human causes (e.g. terrorist sabotage) can be comparable to those caused by natural disasters. The paper identifies the major advantages of a common methodology for risk identification and quantification regarding the potential impact of accidents at tailings dams on the environment. Relevant Romanian and EU legislation and regulations enacted following the “Baia Mare” accident in 2000 are reviewed, along with a common risk evaluation methodology that can be applied by the mining sector to tailings dams.     

Spatio-temporal reconstruction of bilateral auditory steady-state responses using MEG beamformers

A rapidly growing number of neuromagnetic studies focus on the analysis of auditory steady-state responses (ASSR) in relation to a diverse array of factors including age, selective attention, and presence of psychopathology. The objectives of these studies require accurate spatio-temporal estimation of the underlying neural generators, a challenging task due to the relatively low signal strength and high correlation between bilateral auditory cortical sources. This paper evaluates the performance of two beamforming schemes that can potentially overcome such difficulties: 1) the linearly constrained minimum variance beamformer with partial sensor coverage (LCMV-PSC), and 2) the multiple constrained minimum-variance beamformer with coherent source region suppression (MCMV-CSRS). Simulation experiments are conducted to assess the impact of source parameters on the reconstruction accuracy. The results indicate that the LCMV-PSC method is prone to localization errors that essentially occur along medio-lateral directions, increase with source depth, and are associated to amplitude and phase distortions of the estimated time courses of activity. Comparatively, the MCMV-CSRS method exhibits precise localization and minimal amplitude and phase distortion for a broad range of relative interferer's positions within the suppression region. The results from the numerical experiments are validated on real magnetoencephalographic (MEG) data collected from a 40-Hz ASSR paradigm.     

Prostate Cancer Radiogenomics—From Imaging to Molecular Characterization

Radiomics and genomics represent two of the most promising fields of cancer research, designed to improve the risk stratification and disease management of patients with prostate cancer (PCa). Radiomics involves a conversion of imaging derivate quantitative features using manual or automated algorithms, enhancing existing data through mathematical analysis. This could increase the clinical value in PCa management. To extract features from imaging methods such as magnetic resonance imaging (MRI), the empiric nature of the analysis using machine learning and artificial intelligence could help make the best clinical decisions. Genomics information can be explained or decoded by radiomics. The development of methodologies can create more-efficient predictive models and can better characterize the molecular features of PCa. Additionally, the identification of new imaging biomarkers can overcome the known heterogeneity of PCa, by non-invasive radiological assessment of the whole specific organ. In the future, the validation of recent findings, in large, randomized cohorts of PCa patients, can establish the role of radiogenomics. Briefly, we aimed to review the current literature of highly quantitative and qualitative results from well-designed studies for the diagnoses, treatment, and follow-up of prostate cancer, based on radiomics, genomics and radiogenomics research.