Search Results (4,933)

This study evaluated the potential of chicken by-products (hearts, gizzards, and skin) as functional raw materials for protein–fat emulsions to partially replace animal fat in pâtés. Five variants of pâté (PV1–PV5) were prepared, including a control without emulsion and four samples with increasing emulsion levels. Emulsions were formulated from chicken by-product mixtures and vegetable oil with potato starch, sodium bicarbonate, and salt to improve solubility and viscosity. The chemical composition of by-product mixtures varied with organ ratio: heart-rich mixtures supplied higher protein, supporting emulsion stability, whereas skin-rich mixtures contributed more fat for texture. Emulsion composition ranged from 6.6–8.1% protein, 19.1–28.4% fat, and 56.7–66.9% moisture. Functional properties depended on formulation balance: water-holding (58–67%), fat retention (70–83%), emulsifying capacity (50–62%), and stability (47–55%). Variant 5 achieved the most favorable combination of composition, stability, and viscosity. In pâtés, emulsion addition reduced protein and fat but increased ash and carbohydrate contents (p < 0.05), improving hydration and stability. Fat retention rose up to 83% and emulsion stability up to 62%. Drip loss declined markedly from 9.2% in the control to 3.6% in Variant 5, while yield stress decreased by 25%, producing softer, more spreadable products. Sensory evaluation favored emulsion-containing samples, with PV-5 scoring highest in texture and appearance. TBARS values rose with the amount of emulsion due to higher PUFA, but acid numbers increased more slowly, indicating reduced hydrolytic rancidity. Overall, pâté with 25% of emulsion offered the best balance of technological performance, sensory quality, and lipid stability, highlighting chicken by-products as sustainable emulsifiers in pâté production. Full article

This paper examines the relationship between weak orthogonality and almost orthogonality for complete non-algebraic 1-types in weakly ordered minimal theories. A central element of our approach is the concept of neighborhoods, which encapsulate local properties of type realizations. This work contributes to a deeper understanding of the geometry of types in weakly ordered minimal theories and provides tools that may be applied in related model-theoretic contexts. Full article

The article presents experimental data on the electrochemical oxidation of vanadium-bearing ore with the aim of increasing the efficiency of vanadium extraction during subsequent hydrometallurgical processing. Three different charge compositions were studied during the preliminary oxidative roasting stage, differing in the type of oxidizers used: calcined soda, sodium chloride, and their mixture in a mass ratio of 9:1. Electrochemical oxidation was carried out in a sulfuric acid medium using a membrane electrolysis cell equipped with an MK-40 type diaphragm. Experimental studies were conducted by varying key technological parameters: H₂SO₄ concentration (5–15%), solid-to-liquid phase ratio (1:2–1:5), temperature (25–85 °C), process duration (0.5–3 h), and current density (100–1000 A/m²). It was found that preliminary roasting promotes the conversion of vanadium into higher oxidation states, predominantly V⁵⁺, which significantly increases its solubility during subsequent electrochemical treatment. For the first time, the kinetic patterns of electrochemical vanadium leaching were identified, as well as the limiting mechanism of the process, associated with the formation of poorly soluble oxide films on the ore surface. Optimization of the electrochemical oxidation parameters allowed us to achieve vanadium extraction into solution up to 92%. Full article

Modern tissue regeneration strategies rely on soft biocompatible materials with adequate mechanical properties to support the growing tissues. Polymer hydrogels have been shown to be available for this purpose, as their mechanical properties can be controllably tuned. In this work, we introduce interpenetrating polymer networks (IPN) hydrogels with improved elasticity due to a dual cross-linking mechanism in one of the networks. The proposed hydrogels contain entangled polymer networks of covalently cross-linked poly(ethylene glycol) methacrylate/diacrylate (PEGMA/PEGDA) and poly(vinyl alcohol) (PVA) with two types of physical cross-links—microcrystallites and tannic acid (TA). Rheological measurements demonstrate the synergistic enhancement of the elastic modulus of the single PEGMA/PEGDA network just upon the addition of PVA, since the entanglements between the two components are formed. Moreover, the mechanical properties of IPNs can be independently tuned by varying the PEGMA/PEGDA ratio and the concentration of PVA. Subsequent freezing–thawing and immersion in the TA solution of IPN hydrogels further increase the elasticity because of the formation of the microcrystallites and OH-bonds with TA in the PVA network, as evidenced by X-ray diffraction and ATR FTIR-spectroscopy, respectively. Structural analysis by cryogenic scanning electron microscopy and light microscopy reveals a microphase-separated morphology of the hydrogels. It promotes extensive contact between PVA macromolecules, but nevertheless enables the formation of a 3D network. Such structural arrangement results in the enhanced mechanical performance of the proposed hydrogels, highlighting their potential use for tissue engineering. Full article

Tourist reviews provide essential insights into travellers experiences and public perceptions of destinations. In Kazakhstan, however, sentiment analysis, particularly using ensemble learning, remains underexplored for evaluating such reviews. This study proposes a hybrid stacking ensemble for sentiment analysis of English-language tourist reviews about Kazakhstan, integrating four complementary approaches: VADER, TextBlob, Stanza, and Local Context Focus Mechanism with Bidirectional Encoder Representations from Transformers (LCF-BERT). Each model contributes distinct analytical capabilities, including lexicon-based polarity detection, rule-based subjectivity evaluation, generalised star-rating estimation, and contextual aspect-oriented sentiment classification. The evaluation utilised a cleaned dataset of 11,454 TripAdvisor reviews collected between February 2022 and June 2025. The ensemble aggregates model outputs through majority and weighted voting strategies to enhance robustness. Experimental results (accuracy 0.891, precision 0.838, recall 0.891, and F1-score 0.852) demonstrate that the proposed method KazSATR outperforms individual models in overall classification accuracy and exhibits superior capacity for aspect-level sentiment detection. These findings underscore the potential of the hybrid ensemble as a practical and scalable tool for the tourism sector in Kazakhstan. By leveraging multiple analytical paradigms, the model enables tourism professionals and policymakers to better understand traveller preferences, identify service strengths and weaknesses, and inform strategic decision-making. The proposed approach contributes to advancing sentiment analysis applications in tourism research, particularly in underrepresented geographic contexts. Full article

Objectives: To evaluate the diagnostic and prognostic value of histophenotyping of the extracellular matrix of the cervical stroma at cervical intraepithelial neoplasia (CIN). Methods: Retrospective analysis of 160 biopsies and surgical preparations of the cervix in women of reproductive age included cases of CIN 1–3 and the group with confirmed persistence or lesion progression (CIN P) at repeated biopsy. The control group (n = 40) consisted of morphologically intact cervical tissue. Histophenotypes were evaluated by staining with hematoxylin, eosin, and Masson trichrome, and classified as follows: normal (dense parallel bundles of type I collagen), intermediate (disorganized and fragmented type I collagen fibers), and myxoid (amorphous weakly fibrillar matrix). The clinical, viral, and inflammatory characteristics between histophenotypes were statistically compared. Results: The distribution of histophenotypes of the extracellular matrix of the cervix varied significantly depending on the CIN degree (p < 0.001). In the control group, the normal pattern was detected in 97.5% of cases; its frequency decreased from CIN 1 (27.5%) to CIN 2 (12.5%) and was absent at CIN 3. The frequency of the myxoid pattern increased significantly in severe and persistent forms: 55% at CIN 3 and 62.5% at CIN P. Human papillomavirus 16/18 was most frequently detected in groups with intermediate (69.1%) and myxoid (27.2%) patterns. Inflammatory changes were more often accompanied by disorganized extracellular matrix; however, intermediate and myxoid types also occurred in the absence of inflammation. Conclusions: The myxoid histophenotype of the extracellular matrix is significantly associated with the high degree of dysplasia and CIN persistence. It can reflect the morphological equivalent of tumor-associated stroma remodeling. Histophenotyping of the extracellular matrix of the cervix appears to be a promising method of risk stratification and may complement existing diagnostic algorithms for CIN. Full article

The development of bio-derived composites represents a sustainable and cost-effective strategy for advanced energy storage applications. In this work, a porous carbon/nickel oxide (NiO) composite was synthesized from orange peel via carbonization at 500 °C followed by KOH activation at 700 °C and subsequent hydrothermal NiO modification. The resulting material exhibited a hierarchical porous structure with a high specific surface area (2120 m² g⁻¹ for OP_500_700 and 1968 m² g⁻¹ for NiO-modified OP_500_700_0.1M), with both values being significantly higher than that of the non-activated OP_500 (3.40–18.12 m² g⁻¹). Electrochemical evaluation revealed that the NiO-functionalized composite achieved a specific capacitance of 306.0 F g⁻¹ at 5 mV s⁻¹ and 281.5 F g⁻¹ at 2 A g⁻¹, surpassing the pristine activated carbon (281.9 F g⁻¹ and 259.6 F g⁻¹, respectively). In addition, both electrodes demonstrated excellent cycling stability, retaining more than 80% capacitance after 5000 charge–discharge cycles at a high current density of 20 A g⁻¹, while the NiO-modified electrode further benefited from a self-activation effect leading to >100% retention. These findings emphasize the synergistic effects of hierarchical porosity and NiO pseudocapacitance, establishing orange peel-derived carbon/NiO composites as scalable and sustainable electrode materials for next-generation supercapacitors. Full article

Timely identification and accurate delineation of ultra-early ischemic stroke lesions in non-contrast computed tomography (CT) scans of the human brain are of paramount importance for prompt medical intervention and improved patient outcomes. In this study, we propose a deep learning-driven methodology specifically designed for segmenting ultra-early ischemic regions, with a particular emphasis on both the ischemic core and the surrounding penumbra during the initial stages of stroke progression. We introduce a lightweight preprocessing model based on convolutional filtering techniques, which enhances image clarity while preserving the structural integrity of medical scans, a critical factor when detecting subtle signs of ultra-early ischemic strokes. Unlike conventional preprocessing methods that directly modify the image and may introduce artifacts or distortions, our approach ensures the absence of neural network-induced artifacts, which is especially crucial for accurate diagnosis and segmentation of ultra-early ischemic lesions. The model employs predefined differentiable filters with trainable parameters, allowing for artifact-free and precision-enhanced image refinement tailored to the challenges of ultra-early stroke detection. In addition, we incorporated into the combined preprocessing pipeline a newly proposed trainable linear combination of pretrained image filters, a concept first introduced in this study. For model training and evaluation, we utilize a publicly available dataset of acute ischemic stroke cases, focusing on the subset relevant to ultra-early stroke manifestations, which contains annotated non-contrast CT brain scans from 112 patients. The proposed model demonstrates high segmentation accuracy for ultra-early ischemic regions, surpassing existing methodologies across key performance metrics. The results have been rigorously validated on test subsets from the dataset, confirming the effectiveness of our approach in supporting the early-stage diagnosis and treatment planning for ultra-early ischemic strokes. Full article

Under the Belt and Road Initiative, China and Kazakhstan have developed a strategic partnership in the automotive industry that has progressed through three distinct phases. This study provides a comprehensive analysis of the evolution and future of this cooperation, structured into the Export and Assembly phase (2014 to 2017), the Technology Partnership phase (2018 to 2021), and the Localization and Joint Ventures phase (2022 to 2024). Based on qualitative content analysis of policy documents, industry reports, and media coverage, the paper examines how China’s drive for industrial upgrading aligns with Kazakhstan’s goals of economic diversification and industrial growth. The findings indicate that Chinese automotive companies, such as JAC Motors, have transitioned from exporting vehicles to assembling them locally, transferring technology, and investing in joint ventures, thereby strengthening Kazakhstan’s automotive production and market potential. However, challenges remain, including overcapacity, market saturation, and the need for skilled local labor. The study concludes with recommendations to enhance cooperation through joint research and development, the creation of localized parts manufacturing clusters, and the harmonization of technical standards, offering a replicable model for bilateral partnerships within the Belt and Road framework. Full article

Background: Cardiovascular diseases (CVDs) remain the primary cause of global mortality, with arterial hypertension, ischemic heart disease (IHD), and cerebrovascular accident (CVA) forming a progressive continuum from early risk factors to severe outcomes. While numerous studies focus on isolated biomarkers, few integrate multidimensional visualization with artificial intelligence to reveal hidden, clinically relevant patterns. Methods: We conducted a comprehensive analysis of 106 patients using an integrated framework that combined clinical, biochemical, and lifestyle data. Parameters included renal function (glomerular filtration rate, cystatin C), inflammatory markers, lipid profile, enzymatic activity, and behavioral factors. After normalization and imputation, we applied correlation analysis, parallel coordinates visualization, t-distributed stochastic neighbor embedding (t-SNE) with k-means clustering, principal component analysis (PCA), and Random Forest modeling with SHAP (SHapley Additive exPlanations) interpretation. Bootstrap resampling was used to estimate 95% confidence intervals for mean absolute SHAP values, assessing feature stability. Results: Consistent patterns across outcomes revealed impaired renal function, reduced physical activity, and high hypertension prevalence in IHD and CVA. t-SNE clustering achieved complete separation of a high-risk group (100% CVD-positive) from a predominantly low-risk group (7.8% CVD rate), demonstrating unsupervised validation of biomarker discriminative power. PCA confirmed multidimensional structure, while Random Forest identified renal function, hypertension status, and physical activity as dominant predictors, achieving robust performance (Accuracy 0.818; AUC-ROC 0.854). SHAP analysis identified arterial hypertension, BMI, and physical inactivity as dominant predictors, complemented by renal biomarkers (GFR, cystatin) and NT-proBNP. Conclusions: This study pioneers the integration of multidimensional visualization and AI-driven analysis for CVD risk profiling, enabling interpretable, data-driven identification of high- and low-risk clusters. Despite the limited single-center cohort (n = 106) and cross-sectional design, the findings highlight the potential of interpretable models for precision prevention and transparent decision support in cardiovascular aging research. Full article

The growing global demand for lithium, driven by its pivotal role in battery production, highlights the need for alternative technologies to recover this metal from low-grade and anthropogenic raw materials. This study investigates lithium extraction from aluminosilicate tailings of rare-metal production by sulfate roasting with concentrated sulfuric acid, followed by aqueous and hydrochloric acid leaching. Mineralogical analysis confirmed lithium mainly in muscovite and biotite (isomorphic substitutions) and partly as spodumene within the aluminosilicate matrix. The optimal parameters of thermochemical treatment were determined as 300 °C for 1 h at a liquid-to-solid ratio of 1:6. Subsequent aqueous leaching (90 °C, 1 h, L/S = 6:1) achieved a lithium recovery of 82.3%, while HCl proved less effective. Using response surface methodology (RSM) and a central composite design (CCD), a regression model was developed predicting up to 93.4% lithium extraction at 90 °C, a liquid-to-solid ratio of 10:1, and a leaching duration of 75 min. The calculated values showed good agreement with experimental data obtained at 90 °C, L/S = 10:1, and 30 min leaching, yielding 91.92% lithium recovery. These results confirm the efficiency of the proposed thermochemical approach and provide a scientific foundation for its further development and industrial scale-up. Full article

The integration of solar generation into national energy balances is associated with a wide range of technical, economic, and organizational challenges, the solution of which requires the adoption of innovative strategies for energy system management. The inherent variability of electricity production, driven by fluctuating climatic conditions, complicates system balancing processes and necessitates the reservation of capacities from conventional energy sources to ensure reliability. Under modern market conditions, the pricing of generated electricity is commonly based on day-ahead forecasts of day energy yield, which significantly affects the economic performance of solar power plants. Consequently, achieving high accuracy in day-ahead electricity production forecasting is a critical and highly relevant task. To address this challenge, a physico-statistical model has been developed, in which the analytical approximation of daily electricity generation is represented as a function of a random variable—cloud cover—modeled by a β-distribution. Analytical expressions were derived for calculating the mathematical expectation and variance of daily electricity generation as functions of the β-distribution parameters of cloudiness. The analytical approximation of daily generation deviates from the exact value, obtained through hourly integration, by an average of 3.9%. The relative forecasting error of electricity production, when using the mathematical expectation of cloudiness compared to the analytical approximation of daily generation, reaches 15.2%. The proposed forecasting method, based on a β-parametric cloudiness model, enhances the accuracy of day-ahead production forecasts, improves the economic efficiency of solar power plants, and contributes to strengthening the stability and reliability of power systems with a substantial share of solar generation. Full article

In situ leaching represents an efficient and safe method for uranium mining, where a suboptimal well flow rate distribution leads to solution imbalances between wells, forming stagnant zones that increase operational costs. This study examines a real technological block from the Budenovskoye deposit, applying reactive transport modeling to optimize well flow rates and reduce operational time and reagent consumption. A reactive transport model was developed based on mass conservation and Darcy’s laws coupled with chemical kinetics describing sulfuric acid interactions with uranium minerals ($U{O}_2$ and $U{O}_3$). The model simulated a technological block with 4 production and 18 injection wells arranged in hexagonal cells over 511–542 days to achieve 90% uranium recovery. Six approaches for well flow rate redistribution were compared, based on different weighting factor calculation methods: advanced traditional, linear distance, squared distance, quadrilateral area, and two streamline-based approaches utilizing the minimum and average time of flight. The squared distance method achieved the highest efficiency, reducing operational costs by 5.7% through improved flow redistribution. The streamline-based methods performed comparably and offer potential advantages for heterogeneous conditions by automatically identifying hydraulic connections. The reactive transport modeling approach successfully demonstrated that multi-criteria optimization methods can improve ISL efficiency by 3.9%–5.7% while reducing operational costs. Full article

Background/Objectives: We aimed to investigate the association between VDR gene variants and vitamin D levels in elite male power athletes of Kazakhstan. Methods: We recruited 92 elite male power athletes of Kazakhstan. Concentrations of serum 25(OH)D were measured with the Access 25(OH) Vitamin D Total Assay on the Unicel Dxl 800 Access Immunoassay System. Gene polymorphisms were determined by a real-time polymerase chain reaction (RT-PCR) allelic discrimination assay using TaqMan™ probes. Results: Vitamin D insufficiency was registered in 63% of athletes. Age (χ² = 6.83, p < 0.01), BMI (χ² = 6.83, p < 0.01), and sport experience (χ² = 4.44, p < 0.04) showed a statistically significant association with vitamin D insufficiency and deficiency (age, χ² = 7.93, p < 0.01; BMI, χ² = 5.11, p < 0.03; sport experience, χ² = 6.19, p = 0.01). The A/A genotype of the VDR FokI polymorphism (rs2228570) showed a strong correlation with vitamin D insufficiency (G/G-G/A vs. A/A, OR = 9.25, 95% CI = 2.01–42.51, p < 0.01) but not deficiency. Conclusions: Our study reveals a significant prevalence of vitamin D insufficiency and deficiency among elite male power athletes of Kazakhstan. Age, BMI, and sport experience are essential factors in developing personalized strategies to address vitamin D insufficiency. The A/A genotype of the VDR FokI polymorphism can be used as a potential biomarker for vitamin D inadequacy in elite male power athletes of Kazakhstan. Full article

A novel inclusion complex of a fluorinated pyrazolopiperidine derivative (5-benzyl-7-(2-fluorobenzylidene)-2,3-bis(2-fluorophenyl)-3,3a,4,5,6,7-hexahydro-2H-pyrazolo [4,3-c]pyridine hydrochloride, PP·HCl) with β-cyclodextrin (PPβCD) was designed, synthesized, and characterized as a potential therapeutic agent for chemotherapy-induced myelosuppression and lymphopenia. Encapsulation of PP within β-cyclodextrin increased aqueous solubility by approximately 3.4-fold and improved dissolution rate by 2.8-fold compared with the free compound. Structural analysis using IR, ^1H/^13C NMR, and TLC confirmed the formation of a stable 1:1 host–guest complex, and the disappearance of free PP signals further supported complete encapsulation. In vivo evaluation in a cyclophosphamide-induced myelosuppression model demonstrated that PPβCD accelerated hematopoietic recovery, restoring leukocyte and erythrocyte counts 35–40% faster than methyluracil, without any signs of systemic toxicity. These findings indicate that β-cyclodextrin complexation significantly enhances solubility, dissolution, and biological efficacy of the pyrazolopiperidine scaffold, supporting further preclinical development of PPβCD as a supportive therapy for chemotherapy-related hematological complications. Full article