Aims/introduction: Coronavirus disease 2019 (COVID-19) vaccinations have been proven to be generally safe in healthy populations. However, the data on vaccine safety in patients with type 1 diabetes are scarce. This study aimed to evaluate the frequency and severity of short-term (<7-day) adverse vaccination events (AEs) and their risk factors among type 1 diabetes patients. Materials and methods: This study analyzed data from the COVID-19 vaccination in Autoimmune Diseases (COVAD) survey database (May to December 2021; 110 collaborators, 94 countries), comparing <7-day COVID-19 vaccine AE among type 1 diabetes patients and healthy controls (HCs). Descriptive statistics; propensity score matching (1:4) using the variables age, sex and ethnicity; and multivariate analyses were carried out. Results: This study analyzed 5,480 completed survey responses. Of all responses, 5,408 were HCs, 72 were type 1 diabetes patients (43 females, 48.0% white European ancestry) and Pfizer was the most administered vaccine (39%). A total of 4,052 (73.9%) respondents had received two vaccine doses. Patients with type 1 diabetes had a comparable risk of injection site pain, minor and major vaccine AEs, as well as associated hospitalizations to HCs. However, type 1 diabetes patients had a higher risk of severe rashes (3% vs 0.4%, OR 8.0, 95% confidence interval 1.7-36), P = 0.007), although reassuringly, these were rare (n = 2 among type 1 diabetes patients). Conclusions: COVID-19 vaccination was safe and well tolerated in patients with type 1 diabetes with similar AE profiles compared with HCs, although severe rashes were more common in type 1 diabetes patients.
Professional development can be achieved independently by reading books, scientific journals and other literature. But professional development with participation in international trainings, courses and seminars, the authors consider as the most valuable. This report reviews the problems and opportunities for professional development of physical education and sports professionals internationally. The aim is to present the opportunities for increasing the qualification of the sports pedagogical and academic staff, through participation in a qualification course with a foreign lecturer. Methods: Theoretical analysis of a course conducted to increase the qualification of the pedagogical staff. Results: The conducted international course was successful for the participating course participants from the Republic of Kazakhstan and for the Bulgarian lecturer. Similarities were found on the methodological side of the sports training of school teams and. Differences related to the management of the organization for participation in the competition process were found. Conclusion: Physical education and sports teachers work in isolation compared to teachers from other faculties. For them, international programs are unavailable or very limited. Legislation and university regulations need to find a way to work together more effectively to support university teachers who train physical education and sport teachers.
The relationship between ICTs and the environment is complex and multifaceted, as ICTs can play positive and negative roles. The article's main idea is how the ICT sector can help tackle climate change, from measurement, monitoring, and automation of processes to self-organizing the sector to refurbish and ecologically scrape ICT hardware. The life cycle of services must be managed to minimize their impact on the environment – management of production, use, and end of life. Based on the analysis, the current article identified some groups of indicators used in the proposed model to estimate the ICT footprint. This information contributes to a more accurate measurement of any company the effect on the environment.
In this paper, we describe an expert system with three tools - Support Vector Machine (SVM), Deep Neural Network (DNN), and feed-forward neural network (NN) in MATLAB and Python to identify potential candidates with diabetes at the initial stages of the disease. To achieve this goal, the importance of the main factors associated with previous health problems and the onset of diabetes in individuals with a medical history is analyzed. By recognizing the common early indications of diabetes, the system can aid in the selection of patients and potentially benefit them by detecting the disease at an early stage and applying appropriate and timely healing.
This study aimed to assess the incidence, predictors, and outcomes of breakthrough infection (BI) following coronavirus disease (COVID-19) vaccination in patients with systemic sclerosis (SSc), a risk group associated with an immune-suppressed state and high cardiopulmonary disease burden. Cross-sectional data from fully vaccinated respondents with SSc, non-SSc autoimmune rheumatic diseases (AIRDs), and healthy controls (HCs) were extracted from the COVAD database, an international self-reported online survey. BI was defined according to the Centre for Disease Control definition. Infection-free survival was compared between the groups using Kaplan-Meier curves with log-rank tests. Cox proportional regression was used to assess the association between BI and age, sex, ethnicity, and immunosuppressive drugs at the time of vaccination. The severity of BI in terms of hospitalization and requirement for oxygen supplementation was compared between groups. Of 10,900 respondents, 6836 fulfilled the following inclusion criteria: 427 SSc, 2934 other AIRDs, and 3475 HCs. BI were reported in 6.3% of SSc, 6.9% of non-SSc AIRD, and 16.1% of HCs during a median follow-up of 100 (IQR: 60-137) days. SSc had a lower risk for BI than HC [hazard ratio (HR): 0.56 (95% CI 0.46-0.74)]. BIs were associated with age [HR: 0.98 (0.97-0.98)] but not ethnicity or immunosuppressive drugs at the time of vaccination. Patients with SSc were more likely to have asymptomatic COVID-19, but symptomatic patients reported more breathlessness. Hospitalization [SSc: 4 (14.8%), HCs: 37 (6.6%), non-SSc AIRDs: 32(15.8%)] and the need for oxygenation [SSc: 1 (25%); HC: 17 (45.9%); non-SSc AIRD: 13 (40.6%)] were similar between the groups. The incidence of BI in SSc was lower than that in HCs but comparable to that in non-SSc AIRDs. The severity of BI did not differ between the groups. Advancing age, but not ethnicity or immunosuppressive medication use, was associated with BIs.
Background: Geopolitical and economic crises force a growing number of people to leave their countries and search better employment opportunities abroad. Meanwhile, the highly competitive labor market provides opportunities for employees to change workplaces and job positions. Health assessment data collected during the occupational history is an essential resource for developing efficient occupational disease prevention strategies as well as for ensuring the physical and psychological well-being of newly appointed workers. The diversity in data representation is source for interoperability problems that are insufficiently explored in the existing literature. Objectives: This research aims to design a worker's occupational health assessment summary (OHAS) dataset that satisfies the requirements of an international standard for semantic interoperability in the use case for exchanging extracts of such data. The focus is on the need for a common OHAS standard at EU level allowing seamless exchange of OHAS at both cross-border and at the worker's country of origin level. Results: This paper proposes a novelty systematic approach ensuring semantic interoperability in the exchange of OHAS. Two use cases are explored in terms of UML sequence diagram. The OHAS dataset reflects common data requirements established in the national legislation of EU countries. Finally, an EN 13606 archetype of OHAS is designed by satisfying the requirements for semantic interoperability in the exchange of clinical data. Semantic interoperability of OHAS is demonstrated with realistic use case data. Conclusions: The designed static, non-volatile and reusable information model of OHAS developed in this paper allows to create EN 13606 archetype instances that are valid with respect to the Reference model and the datatypes of this standard. Thus, basic activities in the OHAS use case can be implemented in software, for example, by means of a native XML database as well as integrated into existing information systems.
Despite widespread radon-in-water measurements, no primary radon-in-water standards currently exist. This work aims to bridge this gap by developing a system to produce radon-in-water reference materials. The system relies on cryogenic, loss-free transfer of radon, which is standardized through defined solid angle measurements, to a radon standard in water. It allows for preparation of liquid scintillation and gamma-ray spectrometry samples with traceable radon-in-water concentrations. The system's design, functionality, and the results of pilot performance tests are described.
The majority (about 70%) of the world's population suffers from lactose intolerance. Lactose intolerance leads to long-term discomfort when consuming milk and dairy products, and hence, to their avoidance. Consequently, the intake of important nutrients is reduced, which potentially has a negative impact on the overall health. Knowing the condition - lactose intolerance - will prevent people from unnecessarily restricting dairy products in their diets. In this study, lactose synthesis and catabolism in the human body are presented, also the types of lactose intolerance, as well as the methods of diagnosing this condition, are discussed. Special attention is paid to the genetic causes of this discomfort and to the tests that can be performed. Solutions for the treatment of lactose intolerance have also been proposed, both up-to-date and easily applicable, as well as future developments.
There are a significant number of scientific publications that use epidemic models to propagate malicious objects in a computer network. These models are based on Markovian models with a constant intensity of transitions, which does not correspond to real conditions, since the intensity of transitions changes due to the fact that after some time antivirus systems start to recognize malware. This paper proposes an original approach based on an epidemic model with variable infection intensity of hosts in a computer network. In the beginning, when the threat is not recognized, the malware spreads rapidly. After a certain period of time, the antivirus system recognizes the malicious code, which leads to a decrease in the infection intensity. Simulations have been done for different infection intensity and threat recognition. Demonstrated models account for the infection time of hosts in the computer network, latency phase, malware detection, and clearance from the system.
Adherence to antihypertensive medications is the cornerstone for achieving metabolic syndrome control. The aim of this study was to explore how the pandemic has affected the adherence of patients with high BP to prescribed antihypertensive drugs. This multicentre observational study utilized self-completed questionnaires among patients between June and November 2020. Overall, 842 patients were included in the study. The likelihood of adherence was assessed using the 5‐item version of the Medication Adherence Report Scale (MARS-5Professor Rob Horne). The average MARS score of the sample was 16.81, the median was 4.162, and the most common value was 3 (24.5% of respondents) for the patients treated during the pandemic. The study suggests that several sociodemographic factors but not the COVID pandemic play a role in treatment adherence.
A novel, one-pot sol-gel preparation scheme leading to reproducible incorporation of 20-40 nm sized gold nanoparticles (AuNPs) in SiO 2 gels is developed based on in situ reduction during gelation using chloroauric acid and ascorbic acid. Variation in the preparation conditions affects the chemical composition, optical properties and size distribution of the AuNPs incorporated in the silica gels. Different organic dopants, i.e., oleic acid, acetic acid or dodecanethiol, are applied to modify the final composite material and to control the rate of reduction and growth of the AuNPs in the gels. The synthesized samples are characterized by UV/Vis/NIR spectroscopy, X-ray diffraction, transmission electron microscopy, thermal conductivity measurements and DTA/TG measurements. The optical properties of the obtained composites are explained using Mie theory. The incorporation of AuNPs leads to an increase in the thermal conductivity of the silica gels. The best process method in this contribution is the use of NaOH as a gelation catalyst and oleic acid as an organic modifier, leading to 20 nm AuNPs dispersed in the silica matrix.
People tend to spend the majority of their time indoors. Indoor air properties can significantly affect humans’ comfort, health, and productivity. This study utilizes measurement data of indoor conditions in a kindergarten in Sofia, Bulgaria. Autoregressive integrated moving average (ARIMA) and long short-term memory (LSTM) recurrent neural network (RNN) models were developed to predict CO2 levels in the educational facility over the next hour based on 2.5 h of past data and allow for near real-time decision-making. The better-performing model, LSTM, is also used for temperature and relative humidity forecasting. Global comfort is then estimated based on threshold values for temperature, humidity, and CO2. The predicted R2 values ranged between 0.938 and 0.981 for the three parameters, while the prediction of global comfort conditions achieved a 91/100 accuracy.
The present research investigates the possibilities of the available online resources and GIS analytic tools to facilitate integrating the spatial context in urban and regional planning by testing a GIS-based location analysis that uses widely available data for identifying an appropriate site for National Children’s hospital in Bulgaria. The elaborated methodology is easy to use, employs accessible online resources, and could be applied in different scales. The aim is to produce a comprehensible instrument that could be adopted by public authorities and used for informed political decision-making. A series of geospatial analyses are used to evaluate the potential location and its alternatives based on transport accessibility, population density in the service area, and public transport connectivity. The analyses are based on the online resources of Google Maps that are used to evaluate the transport accessibility to all the possible locations using different perspectives. The pedestrian access to public transport is also calculated to assess the different modes of transport available. To assess the locations according to the transport accessibility of the population, tools from ArcGIS Pro Network analyst are used. Accessibility is considered from the patient's perspective. The results are analyzed to make a supposition of the alternatives and to come up with a conclusion about whether the already chosen location is a sensible choice from a transport accessibility perspective. The outcomes of the research could help policymakers understand some of the spatial complexities associated with the demand and the accessibility dimensions of healthcare access. The article emphasizes the significance of integrating the spatial context in urban and regional planning and the possibilities of the new technologies to facilitate that task. This methodology for location analysis could be also used for other public services and urban-related matters.
The goal of the present study is to assess the soil quality in Bulgaria using (i) an appropriate set of soil quality indicators, namely primary nutrients (C, N, P), acidity (pH), physical clay content and potentially toxic elements (PTEs: Cu, Zn, Cd, Pb, Ni, Cr, As, Hg) and (ii) respective data mining and modeling using chemometrical and geostatistical methods. It has been shown that five latent factors are responsible for the explanation of nearly 70% of the total variance of the data set available (principal components analysis) and each factor is identified in terms of its contribution to the formation of the overall soil quality—the mountain soil factor, the geogenic factor, the ore deposit factor, the low nutrition factor, and the mercury-specific factor. The obtained soil quality patterns were additionally confirmed via hierarchical cluster analysis. The spatial distribution of the patterns throughout the whole Bulgarian territory was visualized via the mapping of the factor scores for all identified latent factors. The mapping of identified soil quality patterns was used to outline regions where additional measures for the monitoring of the phytoavailability of PTEs were required. The suggested regions are located near to thermoelectric power plants and mining and metal production facilities and are characterized by intensive agricultural activity.
The chirality of the polyether ionophore monensic acid A can be successfully used to study its coordination ability in solution. A complementary approach to gain new insights into the complexation chemistry of the antibiotic (studied previously by circular dichroism (CD) spectroscopy in the ultraviolet range (UV-CD)) is presented. (1) Methods: The CD spectroscopy in the visible (VIS-CD) and near-infrared (NIR-CD) range is applied to evaluate the affinity of deprotonated monensic acid A (monensinate A) towards Ni(II) or Co(II) cations in methanolic solution. Competition experiments between a variety of colorless divalent metal ions for binding the ligand anion were also performed. (2) Results: The stability constants of the species observed in binary Ni(II)/Co(II)-monensinate systems and their distribution were reevaluated with the VIS- and NIR-CD techniques. The data confirmed the formation of mono and bis complexes depending on the metal-to-ligand molar ratio. The studies on the systems containing two competing divalent metal cations exclude the formation of ternary complex species but provide an opportunity to also calculate the stability constants of Zn(II), Mg(II), and Ca(II) monensinates. (3) Conclusions: The advantages of CD spectroscopy in the VIS-NIR range (“invisible” ligand and metal salts, “visible” chiral complex species) simplify the experimental dataset evaluation and increase the reliability of computed results.
The article presents the results of an experimental study of the sound pressure level (SPL) caused by a hydraulic power unit with an external gear pump. The study was carried out with a specially developed laboratory experimental setup based on a common architecture used in hydraulic power units. Both the hydraulic system and the measuring equipment used are described in detail. The design of the experimental studies performed, including two main configurations with specific parameters regarding the operating modes of the system, is presented. The experimental results obtained are presented in the form of magnitude frequency responses which are compared in accordance with the experiment design. An analysis of the results obtained is performed using various quantitative indicators. For specific operating modes, parametric models were derived by approximation of the experimental data. The resulting models can serve in future work to reduce the SPL by passive or active means (e.g., frequency control of the electric motor). The quantitative analysis can serve as a basis of comparison with results obtained after adding passive (damping ring, etc.) or active means to reduce the SPL.
This paper proposes two novel methods for computing the robustly controlled invariant set of linear discrete-time systems with additive bounded disturbances. In the proposed methods, the robustly controlled invariant set of discrete-time systems is obtained by solving the linear matrix inequality given by logarithmic norm and difference inequality. Illustrative examples are presented to demonstrate the obtained methods.
We propose a critical dissipaive quantum metrology schemes for single parameter estimation which are based on a quantum probe consisting of coherently driven ensemble of N spin-1/2 particles under the effect of squeezed, collective spin decay. The collective spin system exhibits a dissipative phase transition between thermal and ferromagnetic phases, which is characterized with nonanalytical behavior of the spin observables. We show that thanks to the dissipative phase transition the sensitivity of the parameter estimation can be significantly enhanced. Furthermore, we show that our steady state is an entangled spin squeezed state which allow to perform parameter estimation with sub shot-noise limited measurement uncertainty.
Vascular smooth muscle voltage-gated potassium (Kv) channels have been proposed to contribute to myogenic autoregulation. Surprisingly, in initial experiments, we observed that the Kv2 channel inhibitor stromatoxin induced vasomotion without affecting myogenic tone. Thus, we tested the hypothesis that Kv2 channels contribute to myogenic autoregulation by fine-tuning the myogenic response. Expression of Kv2 channel mRNA was determined using real-time PCR and ‘multiplex’ single-cell RT-PCR. Potassium currents were measured using the patch-clamp technique. Contractile responses of intact arteries were studied using isobaric myography. Expression of Kv2.1 but not Kv2.2 channels was detected in intact rat superior cerebellar arteries and in single smooth muscle cells. Stromatoxin, a high-affinity inhibitor of Kv2 channels, reduced smooth muscle Kv currents by 61% at saturating concentrations (EC50 36 nmol/L). Further, stromatoxin (10–100 nmol/L) induced pronounced vasomotion in 48% of the vessels studied. In vessels not exhibiting vasomotion, stromatoxin did not affect myogenic reactivity. Notably, in vessels exhibiting stromatoxin-induced vasomotion, pressure increases evoked two effects: First, they facilitated the occurrence of random vasodilations and/or vasoconstrictions, disturbing the myogenic response (24% of the vessels). Second, they modified the vasomotion by decreasing its amplitude and increasing its frequency, thereby destabilizing myogenic tone (76% of the vessels). Our study demonstrates that (i) Kv2.1 channels are the predominantly expressed Kv channels in smooth muscle cells of rat superior cerebellar arteries, and (ii) Kv2.1 channels provide a novel type of negative feedback mechanism in myogenic autoregulation by preventing vasomotion and thereby safeguarding the myogenic response.
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