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This paper aims to consider approximation-estimation tests for decision-making by machine-learning methods, and integral-estimation tests are defined, which is a generalization for the continuous case. Approximation-estimation tests are measurable sampling functions (statistics) that estimate the approximation error of monotonically increasing number sequences in different classes of functions. These tests make it possible to determine the Markov moments of a qualitative change in the increase in such sequences, from linear to nonlinear type. If these sequences are trajectories of discrete quasi-deterministic random processes, then moments of change in the nature of their growth and qualitative change in the process match up. For example, in cluster analysis, approximation-estimation tests are a formal generalization of the “elbow method” heuristic. In solid mechanics, they can be used to determine the proportionality limit for the stress strain curve (boundaries of application of Hooke’s law). In molecular biology methods, approximation-estimation tests make it possible to determine the beginning of the exponential phase and the transition to the plateau phase for the curves of fluorescence accumulation of the real-time polymerase chain reaction, etc.

The precipitation mechanism of the Q phase in Al–Mg–Si–Cu alloys has long been the subject of ambiguity and debate since its metastable phase (Q′) has the same crystal structure and similar lattice parameters as its equilibrium counterparts. In the present work, the evolution of the Q′ (Q) phase during aging is studied by combination of quantitative atomic-resolution scanning transmission electron microscopy and atom probe tomography. It was found that the transformation from the Q′ to the Q phase involves changes of the occupancy of Al atoms in atomic columns of the Q′ (Q) phase. The Al atoms incorporated in the Cu, Si and Mg columns are gradually released into the Al matrix, while mixing between Cu and Si atoms occurs in the Si columns. This transformation process is mainly attributed to the low lattice misfit of the equilibrium Q phase. Besides, the formation of various compositions of the Q phase is due to the different occupancy in the atomic columns of the Q phase. The occupancy changes in the columns of the Q phase are kinetically controlled and are strongly influenced by the alloy composition and aging temperature.

Amorphous alumina is hard but brittle like all ceramic type materials which affects durability under impact or scratch. Here we show that alumina layers below 100 nm thickness when stacked with aluminum interlayers exhibit exceptional performances including toughness equal to 300 J.m −2 determined by on chip nanomechanics. This is almost two orders of magnitude higher than bulk alumina and higher than any other thin hard coatings. In addition, a hardness above 8 GPa combines with a fracture strain above 5%. The origin of this superior set of properties is unravelled via in-situ TEM and mechanical models. The combination of constrained alumina layers with ductile behavior, strong “accommodating” interfaces, giant shear deformability of Al layers, and plasticity-controlled crack shielding cooperate to stabilize deformation, dissipate energy and arrest cracks. These performances unlock several options of applications of Al 2 O 3 in which brittleness under contacts prevents benefiting from remarkable functional properties and chemical stability. Alumina layers below 100 nm thickness stacked with aluminum interlayers combine exceptional properties including high toughness, strength and ductility. The origin of this optimal tryptic is unraveled by advanced nanomechanics and in-situ TEM.

The paper is dedicated to solving the problem of optimal text classification in the area of automated detection of typology of texts. In conventional approaches to topicality-based text classification (including topic modeling), the number of clusters is to be set up by the scholar, and the optimal number of clusters, as well as the quality of the model that designates proximity of texts to each other, remain unresolved questions. We propose a novel approach to the automated definition of the optimal number of clusters that also incorporates an assessment of word proximity of texts, combined with text encoding model that is based on the system of sentence embeddings. Our approach combines Universal Sentence Encoder (USE) data pre-processing, agglomerative hierarchical clustering by Ward’s method, and the Markov stopping moment for optimal clustering. The preferred number of clusters is determined based on the “e-2” hypothesis. We set up an experiment on two datasets of real-world labeled data: News20 and BBC. The proposed model is tested against more traditional text representation methods, like bag-of-words and word2vec, to show that it provides a much better-resulting quality than the baseline DBSCAN and OPTICS models with different encoding methods. We use three quality metrics to demonstrate that clustering quality does not drop when the number of clusters grows. Thus, we get close to the convergence of text clustering and text classification.

Background: Severe and difficult-to-control asthma occurs in 3–10% of patients in developed countries. The aim of our study was to investigate the association of the prognostic role of leptin and adiponectin, as well as the leptin receptor gene polymorphism Gln223Arg, in patients with difficult-to-control and severe asthma. Methods: The present study included 200 patients with asthma hospitalized in the Department of Pulmonology between January 2018 and December 2021. In all patients, in addition to routine clinical investigations, adiponectin, leptin and their ratio were analyzed, as well as levels of pro-inflammatory cytokines (IL-6, IL-8 and TNF-alpha). External respiratory function was also assessed. LEPR Gln223Arg single-nucleotide polymorphisms were genotyped by real-time PCR method. Results: Patients were randomized into two groups, depending on the severity of asthma: an uncontrolled asthma group and a controlled asthma group, according to the GINA criteria. Among patients with uncontrolled asthma, 101 subjects (74.3%) had metabolic syndrome (p < 0.001). There was an inverse association of the adiponectin/leptin ratio with the eosinophil count (B = −0.305, p < 0.001), IL-6 (B = −0.026, p < 0.001), IL-8 (B = −0.062, p < 0.001) and TNF-alpha (B = −0.047, p < 0.001) and a direct correlation with the level of FEV1 (B = 0.121, p < 0.001) and FVC (B = 0.104, p < 0.001). A probable association of homozygous A/A allele with increased risk of uncontrolled asthma was shown (p = 0.007). Conclusions: Leptin receptor polymorphism with A/A genotype may be associated with a higher probability of developing severe and difficult-to-control asthma.

Background: Environmental problems can significantly influence population health. Cardiovascular diseases (CVDs) are the most common cause of death in developed countries including in Kazakhstan. The aim of our study was to assess the relationship between exposure to ionizing radiation and mortality risks from major CVDs for the population of Kazakhstan living in areas adjacent to the Semipalatinsk nuclear test site (SNTS). Materials and Methods: The study of the structure and dynamics of cardiovascular mortality was based on the State Scientific Automated Medical Registry (SSAMR) database. Among members of the exposed group, the median equivalent radiation dose was 864.0 mSv, compared to 64.4 mSv in the control group. It should be noted that almost the entire population of the Semipalatinsk region was exposed to some degree of radiation; however, the Kokpekti district received the lowest radiation doses. Results: Mortality rates from CVD were statistically significantly higher in the radiation-exposed population from 1960 to 1994, with RR fluctuating from 1.118 to 8.7. The predominant mortality events were chronic coronary heart disease, chronic cerebrovascular disease, and hemorrhagic stroke throughout the study period, and acute myocardial infarction within 20 years of the start of nuclear testing. In the exposed group, RR = 10.35 for chronic cerebrovascular disease, RR = 3.56 for hemorrhagic stroke, and RR = 5.77 for peripheral arterial atherosclerosis. A dose of 100–500 mSv increased the risk of mortality from CVD by 3.14 times, and a dose of >600 mSv increased it by 7.05 times. Conclusions: A link has been established between long-term exposure to ionizing radiation and increased risks of mortality from CVD in the population of areas contaminated with radiation as a result of nuclear testing.

Background: In-stent restenosis of coronary arteries is a significant problem in interventional cardiology. Inflammatory processes in the arterial intima play a key role among the well-known risk factors for restenosis. The COVID-19 pandemic has contributed to the development of inflammation and the activation of the coagulation system. The aim of this study was to assess the risk factors for coronary artery restenosis and patient survival during the COVID-19 pandemic. Materials and Methods: We performed a cross-sectional study on a targeted sample of patients with coronary artery disease who underwent repeat myocardial revascularization (931 patients). The main study group, consisting of patients with coronary artery stent restenosis, included 420 patients (38.5% had previous COVID-19). The control group included 511 patients without stent restenosis (20.9% had COVID-19). Results: The results of multiple logistic regression analysis showed that the odds ratio (OR) for COVID-19 was 2.29 (95% CI 2.78–3.19) (p < 0.001), and the OR for C-reactive protein (CRP) was 1.08 (95% CI 1.002–1.013). The average hospital survival time for subjects with prior COVID-19 (N = 269) was 9.53 ± 0.106 days (95% CI 9.32–9.74), while for those without COVID-19 (N = 662), it was 9.89 ± 0.032 days (95% CI 9.83–9.96) (p < 0.001). The one-year survival time was 316.7 ± 6.982 days (95% CI 303.0–330.4) for the COVID-19 group and 340.14 ± 3.243 days (95% CI 333.8–346.5) for the non-COVID-19 group (p < 0.001). Conclusions: The main risk factors for in-stent restenosis were COVID-19 and elevated CRP levels. The average survival time in the group with prior COVID-19 was statistically significantly lower than in patients without COVID-19, both during the hospital stay and within one year after repeated revascularization.

Background: The neutrophil-to-lymphocyte ratio (NLR) is an independent predictor of the severity of coronary heart disease and COVID-19. This study aims to assess the predictive ability of the NLR in patients with in-stent restenosis after COVID-19. Materials and Methods: a cross-sectional study included 931 patients who underwent repeated myocardial revascularization between May 2020 and May 2023. The 420 patients of the main group had in-stent restenosis, of which 162 patients had COVID-19 previously. The control group included 511 patients without stent restenosis (107 patients had COVID-19 previously). All reported events were verified by hospital electronic records from the Complex Medical Information System. Results: The mean values of the NLR were 2.51 and 2.68 in the study groups, respectively. A statistically significant positive relationship in both groups was found between the NLR and troponin, D-dimer, C-reactive protein, creatinine, ALT, and AST. A statistically significant positive relationship was found between NLR and myocardial infarction (MI) in patients of both groups (p = 0.004; p < 0.001, respectively) and a negative relationship with the ejection fraction (p = 0.001; p < 0.036, respectively). An evaluation of the predictive ability of the clinical and laboratory predictors of recurrent myocardial infarction shows a high degree of utility of this model. The area under the ROC curve for AUC for NLR was 0.664 with 95% CI from 0.627 to 0.700 (p < 0.001). Conclusions: NLR is one of the significant factors for predicting the development of adverse outcomes in patients with revascularized myocardium after COVID-19.

Lead based bulk piezoelectric materials, e.g., PbZrxTi1‐xO3 (PZT), are widely used in electromechanical applications, sensors, and transducers, for which optimally performing thin films are needed. The results of a multi‐domain Landau–Ginzberg‐Devonshire model applicable to clamped ferroelectric thin films are used to predict the lattice symmetry and properties of clamped PZT thin films on different substrates. Guided by the thermal strain phase diagrams that are produced by this model, experimentally structural transitions are observed. These can be related to changes of the piezoelectric properties in PZT(x = 0.6) thin films that are grown on CaF2, SrTiO3 (STO) and 70% PbMg1/3Nb2/3O3‐30% PbTiO3 (PMN‐PT) substrates by pulsed laser deposition. Through temperature en field dependent in situ X‐ray reciprocal space mapping (RSMs) and piezoelectric force microscopy (PFM), the low symmetry monoclinic phase and polarization rotation are observed in the film on STO and can be linked to the measured enhanced properties. The study identifies a monoclinic ‐rhombohedral MC‐MA‐R crystal symmetry path as the polarization rotation mechanism. The films on CaF2 and PMN‐PT remain in the same symmetry phase up to the ferroelectric‐paraelectric phase transition, as predicted. These results support the validity of the multi‐domain model which provides the possibility to predict the behavior of clamped, piezoelectric PZT thin films, and design films with enhanced properties. Different symmetry phases are identified in PbZr0.6Ti0.4O3 ferroelectric thin films as function of the strain introduced by CaF2, SrTiO3 and PMN‐PT substrates. Measured strain‐temperature paths are successfully described by a multi‐domain LGD‐model that predicts the symmetry phases and phase transitions, and the observed enhanced piezoelectricity in one of the phases.