# Brno University of Technology

• Brno, Czechia
Recent publications
Microfluidic paper-based analytical devices modified with molecularly imprinted polymers (μPADs@MIPs) were developed for fluorescent detection of targeted thiols via in situ UV-induced formation of quantum dots (μPADs@MIPs@QDs). The selectivity enhancement by the MIP layer formed on the filter paper surface was demonstrated for the isolation of L-homocysteine from wine. Followed by the addition of metal precursors solution (Zn/Cd/Cu) and UV irradiation, fluorescent quantum dots were formed thus enabling quantitative detection of the thiol (serving as a QD capping agent). The effect of different semiconductors was investigated to achieve a lower band gap and higher fluorescence intensity. Increasing fluorescence intensity in the presence of thiol groups was obtained for the following precursors mixture composition: ZnCdCu/S > ZnCd/S > ZnCu/S > ZnS. The proposed method has a good relationship between the fluorescence intensity of ZnCdCu/S QDs and L-homocysteine in a linear range from 0.74 to 7.40 μM with a limit of detection (LOD) and quantification (LOQ) of 0.51 and 1.71 μM respectively. This method was applied for the determination of L-homocysteine in white wine with RSD under 6.37%.
This paper theoretically and experimentally investigates the effects of textures produced by a mechanical indentation on the stability of journal bearings. The research primarily aims at lightly loaded journal bearings used, e.g. in vertical rotors and microturbines. The results show that textures located close to the minimum oil film thickness can noticeably improve the stability at low specific loads but have only a negligible effect at a specific load of 0.15 MPa. The texturing also impacts the bearing temperature, which is closely related to the bearing friction. Since the textured journal bearings are prone to the formation of cavities in the oil film, the paper also deals with computational methods. It is demonstrated that an accurate estimate of stability threshold requires very dense computational meshes, which are impractical for mass-conserving treatment of cavitation due to CPU requirements. Interestingly, errors due to non-conservation of mass are up to the same magnitude as uncertainties due to employed numerical algorithms. The results demonstrate that numerical results describing lightly-loaded textured journal bearings are very sensitive to the density of the computational mesh. Hence, the simplified cavitation treatment can be legitimate in applications where the CPU time is a concern, such as the optimization, iterative algorithms and time-integration of equations of motion.
Hydrogen applications range from an energy carrier to a feedstock producing bulk and other chemicals and as an essential reactant in various industrial applications. However, the sustainability of hydrogen production, storage and transport are neither unquestionable nor equal. Hydrogen is produced from natural gas, biogas, aluminium, acid gas, biomass, electrolytic water splitting and others; a total of eleven sources were investigated in this work. The environmental impact of hydrogen production, storage and transport is evaluated in terms of greenhouse gas and energy footprints, acidification, eutrophication, human toxicity potential, and eco-cost. Different electricity mixes and energy footprint accounting approaches, supported by sensitivity analysis, are conducted for a comprehensive overview. H2 produced from acid gas is identified as the production route with the highest eco-benefit (−41,188 €/t H2), while the biomass gasification method incurred the highest eco-cost (11,259 €/t H2). The water electrolysis method shows a net positive energy footprint (60.32 GJ/t H2), suggesting that more energy is used than produced. Considering the operating footprint of storage, and transportation, gaseous hydrogen transported via a pipeline is a better alternative from an environmental point of view, and with a lower energy footprint (38 %–85%) than the other options. Storage and transport (without construction) could have accounted for around 35.5% of the total GHG footprint of a hydrogen value chain (production, storage, transportation and losses) if liquefied and transported via road transport instead of a pipeline. The identified results propose which technologies are less burdensome to the environment.
In this paper, the elastic lateral–torsional behavior of simple beams is discussed by presenting a novel analytical solution and performing numerical studies. The motivation of the presented research is the observation that classic analytical prediction and finite element prediction are, typically, significantly different when the second-order nonlinear behavior of beams with initial imperfections is analyzed. To understand and explain the observed differences, a novel analytical model is worked out for the geometrically nonlinear analysis of beams with initial geometric imperfections. The advancement in the presented analytical solution is the explicit consideration of the changing geometry as the load increases. The most important steps of the derivations are summarized, and the resulting formulae are briefly discussed. The derivations are done for general cross-sections, however, the bending is assumed to act in one of the principal planes. Numerical studies are also presented, focusing on mono-symmetric cross-sections. As part of the numerical studies, first, the results of the new analytical formulae are compared to those from shell finite element analysis. The results suggest that the new formulae can capture the most essential elements of the behavior observed in the shell finite element calculations, justifying that the cross-section shape might have a significant effect on the nonlinear lateral–torsional behavior of beams. Then the effect of the lateral–torsional buckling is predicted by calculating buckling reduction factors, using the results of the geometrically nonlinear finite element calculations. The capacity prediction results, again, justify that the cross-section shape, as well as the sign of the assumed geometric imperfection, might have a non-negligible effect on the buckling reduction factors, and on the capacity of the member.
Although the general concept of nanotechnology relies on exploitation of size-dependent properties of nanoscaled materials, the relation between the size/morphology of nanoparticles with their biological activity remains not well understood. Therefore, we aimed at investigating the biological activity of Se nanoparticles, one of the most promising candidates of nanomaterials for biomedicine, possessing the same crystal structure, but differing in morphology (nanorods vs. spherical particles) and aspect ratios (AR, 11.5 vs. 22.3 vs. 1.0) in human cells and BALB/c mice. Herein, we report that in case of nanorod-shaped Se nanomaterials, AR is a critical factor describing their cytotoxicity and biocompatibility. However, spherical nanoparticles (AR 1.0) do not fit this statement and exhibit markedly higher cytotoxicity than lower-AR Se nanorods. Beside of cytotoxicity, we also show that morphology and size substantially affect the uptake and intracellular fate of Se nanomaterials. In line with in vitro data, in vivo i.v. administration of Se nanomaterials revealed the highest toxicity for higher-AR nanorods followed by spherical nanoparticles and lower-AR nanorods. Moreover, we revealed that Se nanomaterials are able to alter intracellular redox homeostasis, and affect the acidic intracellular vesicles and cytoskeletal architecture in a size- and morphology-dependent manner. Although the tested nanoparticles were produced from the similar sources, their behavior differs markedly, since each type is promising for several various application scenarios, and the presented testing protocol could serve as a concept standardizing the biological relevance of the size and morphology of the various types of nanomaterials and nanoparticles.
Exploring the influence of various heteroatoms on MNxC and developing novel synthetic MNC of strategies are great significance to improve the efficiency of continuable energy transformation and storage technologies. In this work, an economic and environmental in-situ doping synthesis scheme for extensible synthesis Co, N and S doped multiple porous-structure carbon (Co-NSEC) using egg gel as carbon precursor was reported. The Co-NSEC were certified to possess multiple porous structure, large surface area and uniform Co distribution. Moreover, systematic characterization results and electrochemical study revealed that thiophene sulfur could enhance Co-Nx oxygen reduction reaction (ORR) catalytic ability. The Co-NSEC catalysts exhibit excellent ORR performance akin to Pt/C (onset potential 0.947 V vs RHE, half-wave potential 0.842 V vs RHE, limiting current density 5.70 mA cm⁻²) and better alcohol resistance and durability in alkaline solutions. The Co-NSEC electrocatalysts are promising as Pt replacement and are desired to be applied in the aspect of fuel cells.
Sustainable biodiesel synthesis from waste, toxic and non-edible oil seeds give a sustainable opportunity to combat energy crises and environmental depreciation. A new non-edible oil of Diospyros malabarica (Malabar Ebony) was analyzed for the synthesis of eco-friendly biodiesel using newly synthesized green nanoparticles (NPs) of Cadmium oxide (CdO 2) prepared from leaf extract of Buxus papillosa via biological method followed by in situ wet impregnation approach. The highest fatty acid methyl ester (FAME) yield of 94 wt% was attained through the process of transesterification at ideal experimental conditions i.e., 1:9 M ratio of oil to methanol, catalyst loading 0.5 wt%, experiment duration 180 min and reaction temperature of 90 • C. Optimize biodiesel yield from Diospyros malabarica using response surface methodology was also applied. Scanning electron mi-croscopy (SEM), energy dispersive X-ray (EDX), thermogravimetric analysis and X-ray diffraction (XRD) were utilized for the characterization of newly synthesized CdO 2 NPs. The findings obtained from SEM revealed that CdO 2 NPs were cubic in shape. The size of CdO 2 NPs was 45 nm, which obtained from XRD analysis. EDX analysis showed 83.72 % cadmium composition. In thermogravimetric analysis, 5.2 % thermal degradation was observed which revealed that CdO 2 NPs have strong thermal stability. The production of FAME was confirmed by using gas chromatography-mass spectroscopy (GC-MS), nuclear magnetic resonanceand Fourier transform infrared spec-troscopy techniques. 9-Octadecenoic acid is the key fatty acid with the highest abundance in the GC-MS spectrum. This study revealed that inedible oil seed of Diospyros malabarica and newly synthesized green NPs of CdO 2 has the highest potential to be used as highly reliable cost-effective and sustainable entrants for synthesizing eco-friendly diesel which is ultimately open up the avenue for further research in the exploration and application of economical feedstock for biodiesel industry at a larger scale.
The accurate power generation forecast of multiple renewable energy sources is significant for the power scheduling of renewable energy systems. However, previous studies focused more on the prediction of a single energy source, ignoring the relationship among different energy sources, and failing to predict accurate power generation for all energy sources simultaneously. This paper proposes a hybrid framework for the power generation forecast of multiple renewable energy sources to overcome deficiencies. A Convolutional Neural Network (CNN) is developed to extract the local correlations among multiple energy sources, the Attention-based Long Short-Term Memory (A-LSTM) network is developed to capture the nonlinear time-series characteristics of weather conditions and individual energy, and the Auto-Regression model is applied to extract the linear time-series characteristics of each energy source. The accuracy and practicality of the proposed method are verified by taking a renewable energy system as an example. The results show that the hybrid framework is more accurate than other advanced models, such as artificial neural networks and decision trees. Mean absolute errors of the proposed method are reduced by 13.4%, 22.9%, and 27.1% for solar PV, solar thermal, and wind power compared with A-LSTM. The sensitivity analysis has been conducted to test the effectiveness of each component of the proposed hybrid framework to prove the significance of energy correlation patterns with higher accuracy and stability compared with the other two patterns.
The presented paper deals with the testing of a possibility to reduce emissions of undesirable greenhouse gases (CH 4 , CO 2; NO x) and their mixture (biogas) during the storage of digestate using applications of secondary plant metabolites (tannins). The experiment was conducted in laboratory conditions in which the digestate was placed in fermentation chambers. Prior to the fermentation process, preparations were applied to the digestate, which contained tannins: Tanenol Antibotrytis (TA), Tanenol Clar (TC) and Tanenol Rouge (TR) in three concentrations (0.5, 1.0 and 2.0% w/w). The application of these preparations demonstrably affected the production of biogas and the contents of CH 4 , CO 2 and N therein. The application of TR preparation in the concentration of 1.0% and 2.0% significantly reduced the production of biogas as compared with all variants. The preparation further inhibited the process of CH 4 development. In contrast, the other preparations with the content of different kinds of TA and TC increased the production of biogas (on average by 15%), CH 4 (on average by 7%) and CO 2 (on average by 12%) as compared with the control variant and TR variant. These two variants reduced the concentration of N in biogas on average by 38%. Thus, the tested Tanenol tannin preparations can be used in different concentrations either to control emissions of greenhouse gases during the storage of digestate or, in case of increased production of CO 2 for its reuse in order to increase methane yields in the process of anaerobic fermentation.
Low efficiency of nutrient use, especially nitrogen, from mineral fertilizers under the drought conditions is a worldwide problem in agriculture. Therefore, low-cost, and environmentally friendly technologies that improve the utilization of nutrients from applied fertilizers while increasing water availability to plants are urgently needed. The aim of our research was to prepare bio-based carriers composed from different ratios of natural hydroabsorbent (NHA), synthetic superabsorbent polymer (SAP), and zeolite. The commercial fertilizers (NP and NPK) were enriched with these carriers with subsequent determination of their ability to release nutrients and affect the growth of maize plants grown under drought conditions. The first (i) part of our experiment focused on the lab preparation of bio-based carriers followed by a testing of their abilities to release nitrogen into water in the lab conditions. The effect of selected carriers in the mixture with commercial fertilizers to the growth of maize were subsequently tested under the optimal and limited watering regime in the greenhouse pot experiment (ii). The control treatment (no fertilizer) and fertilization treatments were established, namely, single bio-based carrier (C2) and compound fertilizers (NP, NPK) and their mixture (C2-NP, C2-NPK). The effect of these fertilizers applied in two doses (at the level of 30 and 60 kg/ha N) on the yield and grain quality of maize (iii) was finally evaluated in a two-year field experiment (2020 – 2021). Based on the existing kinetic models, it was possible to the link nitrogen release to the structural variables of the composite carriers. A small volume of zeolite microparticles incorporated into the biopolymer network of the NHA and SAP carrier accelerated the nitrogen release in the lab experiment (i) and increased the maximum amount of released nitrogen in proportion to the zeolite content without significantly affecting the water-holding capacity. The results of the greenhouse pot experiment (ii) demonstrated that application of a bio-based carrier composed of 7 wt% SAP, 7 wt% zeolite and 86 wt% NHA in combination with NP and NPK fertilizers significantly increased chlorophyll content, the ability of maize plants to absorb radiation in photosystem II, and the weight of above-ground maize biomass under limited and optimal irrigation conditions. The C2-NPK increased grain weight, grain yield and protein content in the grain of maize under the field conditions (iii). Fertilizers enriched with bio-based carrier are a promising alternative to improve soil moisture and increase nutrient availability to plants grown not only in drought conditions.
Polymeric foams tailor-made of polyvinylpyrrolidone (PVP) and carboxymethylcellulose/oxidized 6-carboxycellulose (CMC07/OC) composite were proposed as suitable sorbents for the collection and analysis of dried blood spots (DBSs). The PVP and CMC07/OC foams were easy to prepare, enabled collection of minute volumes of capillary blood, and blood drying at ambient temperature. The resulting foams were prepared as small porous discs with uniform dimensions (approx. 6 × 3 mm) and were fully soluble in aqueous solutions. The DBSs were formed in standard capillary electrophoresis (CE) vials fitted with the soluble foam discs and enabled the direct in-vial DBS processing and at-line analysis by CE. The DBSs were pretreated with a simple process, which involved a complete dissolution of the foam disc in an acidic solution and a simultaneous hollow fiber liquid-phase microextraction (HF-LPME) in one step. The complete solubility of the foam disc with the DBS served for a quantitative transfer of all blood components into the eluate and a nearly exhaustive HF-LPME of target analytes, whereas the blood matrix and the polymeric foam components were efficiently retained by the organic solvent impregnated in the walls of the HF. The suitability of the PVP and CMC07/OC foams for the collection and the direct analysis of DBSs was demonstrated by the HF-LPME/CE determination of model acidic drugs (warfarin, ibuprofen, naproxen, ketoprofen, and diclofenac) at therapeutically relevant concentrations. Repeatability of the analytical method was better than 8.1% (RSD), extraction recoveries ranged from 70 to 99% (for PVP foam), calibration curves were linear over two orders of magnitude (R2 higher than 0.9991), and limits of detection were less than 44 μg/L (for concentrations in undiluted capillary blood). The soluble polymeric foams exhibited non-significant variations in analyte concentrations for DBSs prepared from blood samples with different hematocrit levels and for aged DBSs (less than 9.2%), moreover, they outperformed standard DBS sampling devices in terms of sample pretreatment time and extraction recovery.
Prostate cancer is the most commonly diagnosed tumor disease in men, and its treatment is still a big challenge in standard oncology therapy. Magnetically actuated microrobots represent the most promising technology in modern nanomedicine, offering the advantage of wireless guidance, effective cell penetration, and non‐invasive actuation. Here, new biodegradable magnetically actuated zinc/cystine‐based microrobots for in situ treatment of prostate cancer cells are reported. The microrobots are fabricated via metal‐ion‐mediated self‐assembly of the amino acid cystine encapsulating superparamagnetic Fe3O4 nanoparticles (NPs) during the synthesis, which allows their precise manipulation by a rotating magnetic field. Inside the cells, the typical enzymatic reducing environment favors the disassembly of the aminoacidic chemical structure due to the cleavage of cystine disulfide bonds and disruption of non‐covalent interactions with the metal ions, as demonstrated by in vitro experiments with reduced nicotinamide adenine dinucleotide (NADH). In this way, the cystine microrobots served for site‐specific delivery of Zn2+ ions responsible for tumor cell killing via a “Trojan horse effect”. This work presents a new concept of cell internalization exploiting robotic systems’ self‐degradation, proposing a step forward in non‐invasive cancer therapy. A metal‐ion‐mediated self‐assembly approach is used to synthesize magnetically driven cystine microrobots, whose motion can be precisely manipulated by a transversal rotating magnetic field. After their internalization in prostate cancer cells, the typical enzymatic reducing environment favors the microrobots disassembly for site‐specific delivery of Zn2+ ions responsible for tumor cell killing via a “Trojan horse” effect.
The unconventional wire electric discharge machining (WEDM) technology represents a vital manufacturing technology in different industrial branches. This technology is essential because of the possibility to machine difficult-to-machine materials such as sintered carbides. For this reason, this study analyses the machinability of sintered carbides WKP23S, WSM33S and WK1 with WEDM in both water and oil baths. We investigated the influence of the machining parameters, namely, pulse off time, gap voltage, discharge current, pulse on time and wire feed, on the cutting speed, surface roughness and defect occurrence. We investigated 9 different roughness parameters, analysed surface morphology with an electron microscope and also analysed cross-sectioned samples. We found out that machining sintered carbides in oil bath yields better results than machining in deionized water. The oil tank prevents the removal of the cobalt binder, but it does not reduce fissure occurrence in any significant way. The lowest Ra value, that is 0.7 µm, was recorded for the WKP23S sample when machined in oil and Ra 0.9 µm when the same material was machined in water.
In this paper, we consider the Schrödinger equation involving the fractional (p,p1,⋯,pm)\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$(p,p_1,\dots ,p_m)$$\end{document}-Laplacian as follows (-Δ)psu+∑i=1m(-Δ)pisu+V(εx)(|u|(N-2s)/2su+∑i=1m|u|pi-2u)=f(u)inRN,\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}\begin{aligned} (-\Delta )_{p}^{s}u+\sum _{i=1}^{m}(-\Delta )_{p_i}^{s}u+V(\varepsilon x)(|u|^{(N-2s)/2s}u+\sum _{i=1}^{m}|u|^{p_i-2}u)=f(u)\;\text{ in }\; {\mathbb {R}}^{N}, \end{aligned}\end{document}where ε\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\varepsilon$$\end{document} is a positive parameter, N=ps,s∈(0,1),2≤p<p1<⋯<pm<+∞,m≥1\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$N=ps, s\in (0,1), 2\le p<p_1< \dots< p_m<+\infty , m\ge 1$$\end{document}. The nonlinear function f has the exponential growth and potential function V is continuous function satisfying some suitable conditions. Using the penalization method and Ljusternik–Schnirelmann theory, we study the existence, multiplicity and concentration of nontrivial nonnegative solutions for small values of the parameter. In our best knowledge, it is the first time that the above problem is studied.
Retinal images are a key element for ophthalmologists in diagnosing a variety of eye illnesses. The retina is vulnerable to microvascular changes as a result of many retinal diseases and a variety of research have been done on early diagnosis of medical images to take proper treatment on time. This paper designs an automated deep learning-based non-invasive framework to diagnose multiple eye diseases using colour fundus images. A multi-class eye disease RFMiD dataset was used to develop an efficient diagnostic framework. Multi-class fundus images were extracted from a multi-label dataset and then various augmentation techniques were applied to make the framework robust in real-time. Images were processed according to the network for low computational demand. A multi-layer neural network EyeDeep-Net has been developed to train and test images for diagnosis of various eye problems in which the keystone convolutional neural network extracts relevant features from the input colour fundus image dataset and then processed features were used to make predictive diagnostic decisions. The strength of the EyeDeep-Net is evaluated using multiple statistical parameters and the performance of the proposed model is found to be significantly superior to multiple baseline state-of-the-art models. A comprehensive comparison of the proposed methodology to the most recent methods proves its efficacy in terms of classification and disease identification through digital fundus images.
Handwriting is a complex perceptual–motor skill that is mastered around the age of 8. Although its computerized analysis has been utilized in many biometric and digital health applications, the possible effect of gender is frequently neglected. The aim of this paper is to analyze different online handwritten tasks performed by intact subjects and explore gender differences in commonly used temporal, kinematic, and dynamic features. The differences were explored in the BIOSECUR-ID database. We have identified a significant gender difference in on-surface/in-air time of genuine and skilled forgery signatures, on-surface time in cursive letters and numbers, and pressure, speed, and acceleration in text written in capital letters. Our findings accent the need to consider gender as an important confounding factor in studies dealing with online handwriting signal processing.
A universal approach to calculating diffusion coefficients in lead halide perovskite single crystals, which have ionic and mixed ionic–electronic conductivity, is proposed. Using impedance spectroscopy, it is demonstrated how to model a non-ideal Warburg element and transmission line equivalent circuit to identify ionic diffusion in the material. The proposed method is applicable to samples of any thickness and electrical properties. Additionally, it is shown how to overcome the challenges of low-frequency impedance measurement and the non-ideal behavior of the elements through extrapolative modeling and approximation.
Investment, the entry of foreign firms depends of a large extent on the country’s goodwill, which is reflected in various ratings. This representation of the situation is approximate, as it does not estimate the differences between the values of the indicators with adjacent grades. This can be avoided by dividing countries into homogeneous groups. It is appropriate to do so on the basis of non-linear grouping rather than linear grouping. It is based on the transformation of data into a dimensionless scale and linear grouping. In the case, its homogeneity increases thanks to the levelling of the most distinctive values and the alignment of the statistical characteristics of the groups. The aim of the article is to propose in principle, a new approach to the ranking of countries on the basis of their level of economic development. It was found that the nonlinear decision of countries into homogenous groups and compared to the linear grouping more accurately reflect the current situation.
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7,011 members
• Central European Institute of Technology "CEITEC"
• Department of Bio-medical Engineering
• Department of Radio Electronics
• Institute of Chemistry and Technology of Environmental Protection "ICTEP"
Information
Antonínská 548/1, 601 90, Brno, Czechia
prof. RNDr. Ing. Petr Štěpánek, CSc.
Website
http://www.vutbr.cz/en/
Phone
+420 541 141 111