Brno University of Technology

About: Brno University of Technology is a education organization based out in Brno, Czechia. It is known for research contribution in the topics: Computer science & Fracture mechanics. The organization has 6339 authors who have published 15226 publications receiving 194088 citations. The organization is also known as: Vysoké učení technické v Brně & BUT.

Lead and cadmium removal from wastewater using eco-friendly biochar adsorbent derived from rice husk, wheat straw, and corncob

Abstract: Cleaner and sustainable water production lead to the development of environmentally friendly adsorbent materials for energy-efficient, cost-effective, and cleaner water production. In this study, the biochar derived from the rice husk, wheat straw, and corncob has been used for the adsorptive removal of heavy metals, including the lead (Pb+2) and cadmium (Cd+2). The synthesised biochar was characterised by a different structural and analytical approach. The characterisation of biochar revealed the existence of the combined redox, i.e. reductive and oxidative surface functional groups along with some inert functional groups which play a significant role in donating or accepting an electron to degrade the pollutants in the wastewater. The biochar synthesised in this study was found to be amorphous, and some negligible disorders and defects have been observed in the structure of biochar. The biochar has been highly stable under harsh thermal conditions by sustaining significant weight over a temperature of 700 ​°C and also be hygroscopic. The biochar rice husk, wheat straw, and corncob demonstrated the lead (Pb+2) adsorption capacity of 96.41%, 95.38%, and 96.92%, while for cadmium (Cd+2), the uptake capacity was found to be 94.73%, 93.68%, and 95.78%. The reported biochar is a cleaner, environmentally friendly, economical, and sustainable alternative to conventional adsorbent materials.

Printing inks of electroactive polymer PEDOT:PSS: The study of biocompatibility, stability, and electrical properties.

Abstract: Biocompatibility tests and a study of the electrical properties of thin films prepared from six electroactive polymer ink formulations based on poly(3,4-ethylenedioxythiophene):poly(styrene sulfonate) (PEDOT:PSS) were performed The aim was to find a suitable formulation of PEDOT:PSS and conditions for preparing thin films in order to construct printed bioelectronic devices for biomedical applications The stability and electrical properties of such films were tested on organic electrochemical transistor (OECT)-based sensor platforms and their biocompatibility was evaluated in assays with 3T3 fibroblasts and murine cardiomyocytes It was found that the thin films prepared from inks without an additive or any thin film post-treatment provide limited conductivity and stability for use in biomedical applications These properties were greatly improved by using ethylene glycol and thermal annealing Addition or post-treatment by ethylene glycol in combination with thermal annealing provided thin films with electrical resistance and a stability sufficient to be used in sensing of animal cell physiology These films coated with collagen IV showed good biocompatibility in the assay with 3T3 fibroblasts when compared to standard cell culture plastics Selected films were then used in assays with murine cardiomyocytes We observed that these cells were able to attach to the PEDOT:PSS films and form an active sensor element Spontaneously beating clusters were formed, indicating a good physiological status for the cardiomyocyte cells These results open the door to construction of cheap printed electronic devices for biointerfacing in biomedical applications © 2018 Wiley Periodicals, Inc J Biomed Mater Res Part A: 106A: 1121-1128, 2018

Time series forecasting of new cases and new deaths rate for COVID-19 using deep learning methods.

Abstract: The first known case of Coronavirus disease 2019 (COVID-19) was identified in December 2019. It has spread worldwide, leading to an ongoing pandemic, imposed restrictions and costs to many countries. Predicting the number of new cases and deaths during this period can be a useful step in predicting the costs and facilities required in the future. The purpose of this study is to predict new cases and deaths rate one, three and seven-day ahead during the next 100 days. The motivation for predicting every n days (instead of just every day) is the investigation of the possibility of computational cost reduction and still achieving reasonable performance. Such a scenario may be encountered in real-time forecasting of time series. Six different deep learning methods are examined on the data adopted from the WHO website. Three methods are LSTM, Convolutional LSTM, and GRU. The bidirectional extension is then considered for each method to forecast the rate of new cases and new deaths in Australia and Iran countries. This study is novel as it carries out a comprehensive evaluation of the aforementioned three deep learning methods and their bidirectional extensions to perform prediction on COVID-19 new cases and new death rate time series. To the best of our knowledge, this is the first time that Bi-GRU and Bi-Conv-LSTM models are used for prediction on COVID-19 new cases and new deaths time series. The evaluation of the methods is presented in the form of graphs and Friedman statistical test. The results show that the bidirectional models have lower errors than other models. A several error evaluation metrics are presented to compare all models, and finally, the superiority of bidirectional methods is determined. This research could be useful for organisations working against COVID-19 and determining their long-term plans.

Computation of the Area of Memristor Pinched Hysteresis Loop

Abstract: It is well known that the memristor driven by a periodical voltage or current exhibits pinched v - i hysteresis loop. A novel finding is published in this brief, namely, that the area within the loop is directly related to the value of action potential, which was introduced by Leon Chua in his original work from 1971.

The Presence and Localization of G-Quadruplex Forming Sequences in the Domain of Bacteria

Abstract: The role of local DNA structures in the regulation of basic cellular processes is an emerging field of research. Amongst local non-B DNA structures, the significance of G-quadruplexes was demonstrated in the last decade, and their presence and functional relevance has been demonstrated in many genomes, including humans. In this study, we analyzed the presence and locations of G-quadruplex-forming sequences by G4Hunter in all complete bacterial genomes available in the NCBI database. G-quadruplex-forming sequences were identified in all species, however the frequency differed significantly across evolutionary groups. The highest frequency of G-quadruplex forming sequences was detected in the subgroup Deinococcus-Thermus, and the lowest frequency in Thermotogae. G-quadruplex forming sequences are non-randomly distributed and are favored in various evolutionary groups. G-quadruplex-forming sequences are enriched in ncRNA segments followed by mRNAs. Analyses of surrounding sequences showed G-quadruplex-forming sequences around tRNA and regulatory sequences. These data point to the unique and non-random localization of G-quadruplex-forming sequences in bacterial genomes.