The complexity of the topological conjugacy problem for Toeplitz subshifts

In this paper, we analyze the Borel complexity of the topological conjugacy relation on Toeplitz subshifts. More specifically, we prove that topological conjugacy of Toeplitz subshifts with separated holes is hyperfinite. Indeed, we show that the topological conjugacy relation is hyperfinite on a larger class of Toeplitz subshifts which we call Toeplitz subshifts with growing blocks. This result provides a partial answer to a question asked by Sabok and Tsankov

On the closed Ramsey numbers Rcl(ω+n,3)R^{cl}(\omega+n,3)

In this paper, we contribute to the study of topological partition relations for pairs of countable ordinals and prove that, for all integers $n \geq 3$, \begin{align*} R^{cl}(\omega+n,3) &\geq \omega^2 \cdot n + \omega \cdot (R(n,3)-n)+n\\ R^{cl}(\omega+n,3) &\leq \omega^2 \cdot n + \omega \cdot (R(2n-3,3)+1)+1 \end{align*} where $R^{cl}(\cdot,\cdot)$ and $R(\cdot,\cdot)$ denote the closed Ramsey numbers and the classical Ramsey numbers respectively. We also establish the following asymptotically weaker upper bound $$R^{cl}(\omega+n,3) \leq \omega^2 \cdot n + \omega \cdot (n^2-4)+1$$ eliminating the use of Ramsey numbers. These results improve the previously known upper and lower bounds

Antioxidant defense system parameters in isolated fish hepatocytes exposed to bisphenol A — Effect of vitamin C

In this study, isolated hepatocytes of pearl mullet (Alburnus tarichi) were exposed to bisphenol A (BPA) at concentrations of 25, 50, 100, and 200 μM for 24 h. Moreover, an in vitro antioxidant concentration of vitamin C (50 μM) was administrated to the culture medium along with the BPA exposures. Next, the antioxidant defense system parameters were analyzed. According to the results, the highest concentration of BPA (200 μM) proved to be severely toxic for the cells. The increased activities of superoxide dismutase (SOD) and glutathione-S-transferase (GST), the fluctuated activities of glutathione peroxidase (GPx), and the decreased content of reduced glutathione (GSH) were compared to the control group after the BPA exposures. Vitamin C co-administration was found to cause further increases in the SOD, GPx, and GST activities in some of the experimental groups and vitamin C could not restore the GSH content. Malondialdehyde (MDA) levels were observed to be unaffected in all exposure groups. These results show that BPA causes alterations in the antioxidant defenses of the isolated fish hepatocytes. In addition, vitamin C co-administration along with BPA was found to be non-protective against BPA-induced oxidative stress, consequently, aggravated a negative BPA impact

Tacit Knowledge Capacity: A Comparison of University Lecturers in Germany and North Cyprus

The importance of universities as knowledge hubs is increasing due to knowledge production via research and teaching. An emerging aspect of knowledge management literature is the study of the knowledge requirements of universities. In particular, the transformation from knowledge creation to knowledge sharing has proved to be important in the university context and is subject to cultural differences. For example, previous research has indicated that a physician’s Tacit Knowledge Capacity (TKC) is affected by social software and social media. This creates opportunities to carry out new research on different occupations that have an intense TKC. As part of this research, a survey was conducted in order to assess the TKC of lecturers in both Germany and North Cyprus. These are two countries that have universities providing knowledge management programmes. The research determined the TKC in both countries and compared the two in order to determine if cultural factors affect the TKC of the profession. Through this research, the authors aimed to contribute to the ongoing research on the knowledge requirements of universities that will enable them to be knowledge intensive institutions. The Faculty of Economics and Administrative Sciences at Near East University, which has 2200 students and 20 chairs, was compared with the Faculty of Business and Economics at the Technische Universität Dresden, which has 2800 students and 23 chairs. The study was carried out to provide an intercultural comparison, which is currently lacking in the Knowledge Management field. The research findings have highlighted the factors influencing the transfer and the accumulation of tacit knowledge

Procjena odnosa srednjeg volumena trombocita, širine distribucije eritrocita i indeksa volumena trombocita s težinom bolesti kod bolesnika s COVID-19

Coronavirus was first detected in three severe pneumonia cases in Wuhan, China, in December 2019. Studies on red cell distribution width (RDW-CV) and mean platelet volume (MPV) laboratory parameters, which can be examined in complete blood count in COVID-19 patients, are still very limited. However, to the best of our knowledge, there are no studies examining the relationship between platelet volume index (PVI) and disease severity in COVID-19 patients, which was evaluated in this study. The aim of this study was to evaluate the relationship of disease severity in COVID-19 patients with their MPV, RDW, and PVI parameters. The study included 92 COVID-19 patients as a study group and 84 healthy individuals as control group. All laboratory data and radiological images were scanned retrospectively from patient files and hospital information system. Evaluation of the RDW-CV and MPV blood parameters, and PVI measured in COVID-19 patients yielded statistically significant differences according to the disease severity. We suggest that RDW-CV and PVI, evaluated within the scope of the study, may be the parameters that should be considered in the early diagnosis of the disease, from the initial stages of COVID-19. In addition, we think that the RDW-CV and MPV laboratory parameters, as well as PVI, which all are simple, inexpensive and widely used hematologic tests, can be used as important biomarkers in determining COVID-19 severity and mortality.Koronavirus je prvi put otkriven kod tri slučaja teške upale pluća u Wuhanu, Kina u prosincu 2019. godine. Istraživanja laboratorijskih parametara širine distribucije eritrocita (RDW-CV) i srednjeg volumena trombocita (MPV) koji se mogu testirati unutar kompletne krvne slike kod bolesnika s COVID-19 još uvijek su vrlo ograničena. Međutim, prema našim saznanjima, nema istraživanja koja bi se bavila odnosom indeksa volumena trombocita (PVI) i težine bolesti kod ovih bolesnika, a upravo to smo ispitivali u našem istraživanju. Cilj studije bio je procijeniti odnos težine bolesti u bolesnika s COVID- 19 s parametrima MPV, RDW i PVI. Istraživanje je obuhvatilo 92 bolesnika s COVID-19 i 84 zdrave osobe kao kontrolna skupina. Svi laboratorijski podaci i radiološke snimke preslikane su retrospektivno iz bolesničkih kartona i bolničkog informacijskog sustava. Procjena krvnih parametara RDW-CV i MPV, kao i PVI izmjerenih u bolesnika s COVID-19 pokazala je statistički značajne razlike prema težini bolesti. Predlažemo da bi RDW-CV i PVI koji su istraživani u ovoj studiji mogli poslužiti kao parametri u ranoj dijagnostici bolesti već u početnom stadiju COVID-19. Uz to, smatramo da bi se laboratorijski parametri RDW-CV i MPV te PVI kao jednostavne, jeftine i široko primjenjivane hematološke pretrage mogli primijeniti kao važni biološki biljezi u utvrđivanju težine i smrtnosti COVID-19

An Accurate EEGNet-based Motor-Imagery Brain-Computer Interface for Low-Power Edge Computing

This paper presents an accurate and robust embedded motor-imagery brain-computer interface (MI-BCI). The proposed novel model, based on EEGNet, matches the requirements of memory footprint and computational resources of low-power microcontroller units (MCUs), such as the ARM Cortex-M family. Furthermore, the paper presents a set of methods, including temporal downsampling, channel selection, and narrowing of the classification window, to further scale down the model to relax memory requirements with negligible accuracy degradation. Experimental results on the Physionet EEG Motor Movement/Imagery Dataset show that standard EEGNet achieves 82.43%, 75.07%, and 65.07% classification accuracy on 2-, 3-, and 4-class MI tasks in global validation, outperforming the state-of-the-art (SoA) convolutional neural network (CNN) by 2.05%, 5.25%, and 5.48%. Our novel method further scales down the standard EEGNet at a negligible accuracy loss of 0.31% with 7.6x memory footprint reduction and a small accuracy loss of 2.51% with 15x reduction. The scaled models are deployed on a commercial Cortex-M4F MCU taking 101ms and consuming 4.28mJ per inference for operating the smallest model, and on a Cortex-M7 with 44ms and 18.1mJ per inference for the medium-sized model, enabling a fully autonomous, wearable, and accurate low-power BCI