The current stage of the country development is characterized by increasing the role of universities not only in the educational and public space of the country, but also in the socio-economic advancement of cities and regions. Universities forming the educational potential of the cities are flagships of their technological transformation, form the city brand, increase their sustainability, lifeabitity and competitiveness. The aim of the study is the typologization of cities – university centers of Russia, carried out with the help of a comprehensive index of educational potential developed by the authors. The statistical base for assessing the educational potential of cities was the data of the Monitoring of the effectiveness of the educational institutions of higher education in 2022, university rankings of the British company Quacquarelli Symonds (integral QS ranking and 5 integrated areas of study), RA-Expert (integrated and individual in 29 areas of study), the Three Missions of the University rating, and the University Reputation Ranking.The study was carried in 3 stages, each of them involved special methodological approaches. At the first stage, there was a review of existing theoretical and practical research on the subject, the integrated index of the educational potential of university centers was developed. At the second stage of the study on the bases of this index a typology of university centers of the Russian Federation was carried out. At the third stage, there was a comparation of the previous results with their positions in the Sustainable Urban Development Index and realization of creative potential. The implementation of educational potential of the most sustainable competitive university centers was separately analyzed in the context of the strategy of internationalization and export of education.National project “Science and Universities” aimed at formation of 100 universities as centers of scientific, technological and socio-economic development by 2030, as well as the program for the construction of 25 world-level modern campuses increase attention to cities as centers of localization of higher education, their educational potential, and, ultimately, their competitiveness.The scientific importance of the research is the development of methodological approaches to assessing the educational potential of cities – university centers and its testing on the example of 1208 universities located in 306 cities of 84 regions of Russia. As a result, a typology of Russian university centers was carried out according to the level of educational potential: 6 types of cities were identified, differing in the city-forming role of higher educational institutions, their role in brand formation and the competitiveness of the city.The typology makes it possible to assess the educational potential of university centers in Russia to form effective strategies for their development in the context of the realizing the national development goals of Russia.

Abstract Background The European Society of Plastic, Reconstructive and Aesthetic Surgery (ESPRAS) comprises 40 national societies across Europe. In addition to ESPRAS, there are 8 different European Plastic Surgery societies representing Plastic Surgeons in Europe. The 4 th European Leadership Forum (ELF) of ESPRAS, held under the motto “Stronger together in Europe” in Munich in 2023, aimed to collect and disseminate information regarding the national member societies of ESPRAS and European societies for Plastic Surgeons. The purpose was to identify synergies and redundancies and promote improved cooperation and exchange to enhance coordinated decision-making at the European level. Material and methods An online survey was conducted regarding the organisational structures, objectives and challenges of national and European societies for Plastic Surgeons in Europe. This survey was distributed to official representatives (Presidents, Vice Presidents and General Secretaries) and delegates of national and European societies at the ELF meeting. Missing information was completed using data obtained from the official websites of the respective European societies. Preliminary results were discussed during the 4 th ELF meeting in Munich in March 2023. Results The ESPRAS survey included 22 national and 9 European Plastic Surgery societies representing more than 7000 Plastic Surgeons in Europe. Most national societies consist of less than 500 full members (median 182 members (interquartile range (IQR) 54–400); n=22). European societies, which covered the full spectrum or subspecialities, differed in membership types and congress cycles, with some requiring applications by individuals and others including national societies. The main purposes of the societies include research, representation against other disciplines, specialisation and education as well as more individual goals like patient care and policy regulation. Conclusion This ESPRAS survey offers key insights into the structures, requirements and challenges of national and European societies for Plastic Surgeons, highlighting the relevance of ongoing close exchange between the societies to foster professional advancement and reduce redundancies. Future efforts of the ELF will continue to further explore strategies for enhancing collaboration and harmonisation within the European Plastic Surgery landscape.

The influence of process parameters in the three-stage purification of aluminate solution from the Bayer process and aluminum hydroxide was considered in this paper. One of the ways of purification is treating the aluminate solution in order to reduce the concentrations in the starting raw material (solution) and then treating the aluminum hydroxide at a certain temperature and time in order to obtain an alumina precursor of adequate quality. The purification process itself is divided into three phases. The first phase involves the treatment of sodium aluminate with lime in order to primarily remove Ca2+ and (SiO3)2− impurities. Phase II aims to remove impurities of Zn2+, Fe2+, and Cu2+ by treatment with controlled precipitation using specially prepared crystallization centers. In Phase III, Na+ is removed by the process of hydrothermal washing of Al2O3 ∙ 3H2O. In this work, parameters such as temperature (T), reaction time (t), and concentration of lime (c) were studied in order to remove the mentioned impurities and obtain the purest possible product that would be an adequate precursor for special types of alumina.

Mycotoxins present a significant health concern within the animal-feed industry, with profound implications for the pig-farming sector. The objective of this study was to evaluate the efficacy of two commercial adsorbents, an organically modified clinoptilolite (OMC) and a multicomponent mycotoxin detoxifying agent (MMDA), to ameliorate the combined adverse effects of dietary aflatoxins (AFs: sum of AFB1, AFB2, AFG1, and AFG2), fumonisins (FBs), and zearalenone (ZEN) at levels of nearly 0.5, 1.0, and 1.0 mg/kg, on a cohort of cross-bred female pigs (N = 24). Pigs were randomly allocated into six experimental groups (control, mycotoxins (MTX) alone, MTX + OMC 1.5 kg/ton, MTX + OMC 3.0 kg/ton, MTX + MMDA 1.5 kg/ton, and MTX + MMDA 3.0 kg/ton), each consisting of four individuals, and subjected to a dietary regimen spanning 42 days. The administration of combined AFs, FBs, and ZEN reduced the body-weight gain and increased the relative weight of the liver, while there was no negative influence observed on the serum biochemistry of animals. The supplementation of OMC and MMDA ameliorated the toxic effects, as observed in organ histology, and provided a notable reduction in residual AFs, FBs, and ZEN levels in the liver and kidneys. Moreover, the OMC supplementation was able to reduce the initiation of liver carcinogenesis without any hepatotoxic side effects. These findings demonstrate that the use of OMC and MMDA effectively mitigated the adverse effects of dietary AFs, FBs, and ZEN in piglets. Further studies should explore the long-term protective effects of the studied adsorbent supplementation to optimize mycotoxin management strategies in pig-farming operations.

This research delves into the intricate dynamics of travelers’ decision-making processes, particularly their response to the media’s portrayal of environmental risks and the subsequent redirection of their travel choices toward medical destinations (MD). Employing a sophisticated research approach combining path analysis with moderation and multilinear logistic regression models, this study investigates the nuanced factors underlying travelers’ resilience to environmental risks and their propensity to opt for medical destinations. The results of the path analysis reveal a complex network of direct influences of factors from the PPM model (push, pull, and mooring) on choosing a medical destination in the sense that, before moderation, the only significant direct effect on the intention to choose medical destination (MD) was the pull factors. Through moderation, a significant effect of all three factors was achieved, while the direction of influence was changed in the case of push and pull factors. Furthermore, the multinomial logistic regression showed that the respondents prefer to go to a medical destination rather than a rural or urban one after the media emphasis on environmental risks. By integrating these analytical approaches and models, this research advances our understanding of how travelers navigate their choices amid environmental uncertainty. Furthermore, this research sheds light on the pivotal role that these traveler choices play in shaping the sustainability of medical destinations, offering essential insights for stakeholders, policymakers, and researchers navigating the evolving landscape of these destinations.

A common way of exposing functionality in contemporary systems is by providing a Web-API based on the REST API architectural guidelines. To describe REST APIs, the industry standard is currently OpenAPI-specifications. Test generation and fuzzing methods targeting OpenAPI-described REST APIs have been a very active research area in recent years. An open research challenge is to aid users in better understanding their API, in addition to finding faults and to cover all the code. In this paper, we address this challenge by proposing a set of behavioural properties, common to REST APIs, which are used to generate examples of behaviours that these APIs exhibit. These examples can be used both (i) to further the understanding of the API and (ii) as a source of automatic test cases. Our evaluation shows that our approach can generate examples deemed relevant for understanding the system and for a source of test generation by practitioners. In addition, we show that basing test generation on behavioural properties provides tests that are less dependent on the state of the system, while at the same time yielding a similar code coverage as state-of-the-art methods in REST API fuzzing in a given time limit.

Background Mammogram risk scores based on texture and density defined by different brightness thresholds are associated with breast cancer risk differently and could reveal distinct information about breast cancer risk. We aimed to investigate causal relationships between these intercorrelated mammogram risk scores to determine their relevance to breast cancer aetiology. Methods We used digitised mammograms for 371 monozygotic twin pairs, aged 40–70 years without a prior diagnosis of breast cancer at the time of mammography, from the Australian Mammographic Density Twins and Sisters Study. We generated normalised, age-adjusted, and standardised risk scores based on textures using the Cirrus algorithm and on three spatially independent dense areas defined by increasing brightness threshold: light areas, bright areas, and brightest areas. Causal inference was made using the Inference about Causation from Examination of FAmilial CONfounding (ICE FALCON) method. Results The mammogram risk scores were correlated within twin pairs and with each other ( r  = 0.22–0.81; all P  < 0.005). We estimated that 28–92% of the associations between the risk scores could be attributed to causal relationships between the scores, with the rest attributed to familial confounders shared by the scores. There was consistent evidence for positive causal effects: of Cirrus, light areas, and bright areas on the brightest areas (accounting for 34%, 55%, and 85% of the associations, respectively); and of light areas and bright areas on Cirrus (accounting for 37% and 28%, respectively). Conclusions In a mammogram, the lighter (less dense) areas have a causal effect on the brightest (highly dense) areas, including through a causal pathway via textural features. These causal relationships help us gain insight into the relative aetiological importance of different mammographic features in breast cancer. For example our findings are consistent with the brightest areas being more aetiologically important than lighter areas for screen-detected breast cancer; conversely, light areas being more aetiologically important for interval breast cancer. Additionally, specific textural features capture aetiologically independent breast cancer risk information from dense areas. These findings highlight the utility of ICE FALCON and family data in decomposing the associations between intercorrelated disease biomarkers into distinct biological pathways.

The Brief Psychiatric Rating Scale (BPRS) is a useful tool for measuring the severity of psychopathological symptoms among patients with psychosis. Many studies, predominantly in Western countries, have investigated its factor structure. This study has the following aims: (a) to further explore the factor structure of the BPRS-Expanded version (BPRS-E, 24 items) among outpatients with psychotic disorders in Southeast European countries; (b) to confirm the identified model; and (c) to investigate the goodness-of-fit of the three competing BPRS-E factor models derived from previous studies. The exploratory factor analysis (EFA) produced a solution with 21 items grouped into five factors, thus supporting the existence of a fifth factor, i.e., Disorganization. A follow-up confirmatory factor analysis (CFA) revealed a 19-item model (with two items removed) that fit the data well. In addition, the stability of two out of three competing factor models was confirmed. Finally, the BPRS-E model with 5 factors developed in this cross-national study was found to include a greater number of items compared to competing models.

In memristors and resistance switching devices, there is a region prior to switching which exhibits current transients with potentially useful dynamics. We refer to this region as the subthreshold region owing to it occurring prior to any switching threshold. These transients exhibit a characteristic peaked response with a fast rise in current followed by a slower decay. This behaviour has previously been used to quantify the mobilities of defects drifting within the active layer of the devices, but it has also been used in neuromorphic circuits to carry out edge detection, to implement homeostasis within artificial synapses and could have uses in replicating eligibility traces. We present an empirical SPICE model to reproduce these transients within circuit simulators. The model is compared with experimental datasets for a range of applied voltages and we present experimentally verified parameters for readers to use within their own simulations.

Introduction: Hypertension is a major and modifiable risk factor for cardiovascular diseases. Essential, primary, or idiopathic hypertension accounts for 90–95% of all cases. Identifying novel biomarkers specific to essential hypertension may help in understanding pathophysiological pathways and developing personalized treatments. We tested whether the integration of circulating microRNAs (miRNAs) and clinical risk factors via machine learning modeling may provide useful information and novel tools for essential hypertension diagnosis and management. Materials and methods: In total, 174 participants were enrolled in the present observational case–control study, among which, there were 89 patients with essential hypertension and 85 controls. A discovery phase was conducted using small RNA sequencing in whole blood samples obtained from age- and sex-matched hypertension patients (n = 30) and controls (n = 30). A validation phase using RT-qPCR involved the remaining 114 participants. For machine learning, 170 participants with complete data were used to generate and evaluate the classification model. Results: Small RNA sequencing identified seven miRNAs downregulated in hypertensive patients as compared with controls in the discovery group, of which six were confirmed with RT-qPCR. In the validation group, miR-210-3p/361-3p/362-5p/378a-5p/501-5p were also downregulated in hypertensive patients. A machine learning support vector machine (SVM) model including clinical risk factors (sex, BMI, alcohol use, current smoker, and hypertension family history), miR-361-3p, and miR-501-5p was able to classify hypertension patients in a test dataset with an AUC of 0.90, a balanced accuracy of 0.87, a sensitivity of 0.83, and a specificity of 0.91. While five miRNAs exhibited substantial downregulation in hypertension patients, only miR-361-3p and miR-501-5p, alongside clinical risk factors, were consistently chosen in at least eight out of ten sub-training sets within the SVM model. Conclusions: This study highlights the potential significance of miRNA-based biomarkers in deepening our understanding of hypertension’s pathophysiology and in personalizing treatment strategies. The strong performance of the SVM model highlights its potential as a valuable asset for diagnosing and managing essential hypertension. The model remains to be extensively validated in independent patient cohorts before evaluating its added value in a clinical setting.

As the future electric power grid will be driven by distributed renewable energy sources, the deployment of grid-connected power converters will also grow to enable seamless grid and energy source interaction. To provide the reliable operation of these converters, the estimation of fundamental grid parameters is important. The most common estimation techniques are a phase-locked loops (PLL) and a frequency-locked loops (FLL). However, those techniques encounter challenges in conducting parameter estimation when the input signal is unbalanced due to DC-offset, harmonics, signal sags, and frequency and phase variations. This paper presents an enhanced FLL loop enriched with an additional loop for estimation and rejection of the DC-offset. Active and reactive power calculations in grid-connected microgrids by using the modified FLL loops with DC-offset rejection is a novel application introduced in this paper. Experimental verification has demonstrated that the enhanced FLL loop provides fast and reliable parameter estimation as well as stable and robust power calculations, even in the presence of a DC-offset.

Background: Compared to conventional 2D mammography, digital breast tomosynthesis (DBT) offers greater breast lesion detection rates. Ring-like hypodense artifacts surrounding dense lesions are a common byproduct of DBT. This study’s purpose was to assess whether minuscule changes spanning this halo—termed the “broken halo sign”—could improve lesion classification. Methods: This retrospective study was approved by the local ethics review board. After screening 288 consecutive patients, DBT studies of 191 female participants referred for routine mammography with a subsequent histologically verified finding of the breast were assessed. Examined variables included patient age, histological diagnosis, architectural distortion, maximum size, maximum halo depth, conspicuous margins, irregular shape and broken halo sign. Results: While a higher halo strength was indicative of malignancy in general (p = 0.031), the broken halo sign was strongly associated with malignancy (p < 0.0001, odds ratio (OR) 6.33), alongside architectural distortion (p = 0.012, OR 3.49) and a diffuse margin (p = 0.006, OR 5.49). This was especially true for denser breasts (ACR C/D), where the broken halo sign was the only factor predicting malignancy (p = 0.03, 5.22 OR). Conclusion: DBT-associated halo artifacts warrant thorough investigation in newly found breast lesions as they are associated with malignant tumors. The “broken halo sign”—the presence of small lines of variable diameter spanning the peritumoral areas of hypodensity—is a strong indicator of malignancy, especially in dense breasts, where architectural distortion may be obfuscated due to the surrounding tissue.