This paper presents the results of an investigation of the possibility of the reliable determination of the residual stress–strain state in polymers and composites using a combination of bridge curvature, optical scanning, and finite element methods. A three-factor experiment was conducted to determine the strength of printed PLA plastic products. The effect of the residual stresses on the strength of the printed products was evaluated. By comparing the values of the same strength stresses, a relationship between the nature of the stresses and the strength of the samples was found. A tendency of the negative influence of tensile stresses and the opposite strengthening effect of compressive stresses was obvious, so at the same values of tensile strength, the value of residual stress of 42.9 MPa is lower than that of the fibre compression at the value of 88.9 MPa. The proposed new methods of the residual stress determination allow obtaining a complete picture of the stressed state of the material in the investigated areas of the products. This may be necessary in confirming the calculated models of the residual stress–strain state, clarifying the strength criteria and assessing the quality of the selected technological modes of manufacturing the products. © 2024 by the authors.

Background: This review summarizes data on heterocyclic systems with thiadiazole and thiazole fragments in molecules as promising antimicrobial agents. Introduction: Thiadiazole and thiazole backbones are the most favored and well-known heterocy-cles, a common and essential feature of various drugs. These scaffolds occupy a central position and are the main structural components of numerous drugs with a wide spectrum of action. These in-clude antimicrobial, antituberculous, anti-inflammatory, analgesic, antiepileptic, antiviral, and anti-cancer agents. Method: The research is based on bibliosemantic and analytical methods using bibliographic and abstract databases, as well as databases of chemical compounds. Result: This review reports on thiadiazole and thiazole derivatives, which have important pharmacological properties. We are reviewing the structural modifications of various thiadiazole and thia-zole derivatives, more specifically, the antimicrobial activity reported over the last years, as we have taken this as our main research area. 80 compounds were illustrated, and various derivatives containing hydrazone bridged thiazole and pyrrole rings, 2-pyridine and 4-pyridine substituted thiazole derivatives, compounds containing di-, tri-and tetrathiazole moieties, spiro-substituted 4-thiazolidinone-imidazoline-pyridines were analyzed. Derivatives of 5-heteroarylidene-2,4-thiazolidinediones, fluoroquinolone-thiadiazole hybrids, and others. Conclusion: 1,3,4-thiadiazoles and thiazoles are valuable resource for researchers engaged in rational drug design and development in this area. © 2024 Bentham Science Publishers.

Central Asia is highly exposed to a broad range of hazardous phenomena including earthquakes, floods and landslides, which have cause substantial damage in the past. However, disaster risk reduction strategies are still under development in the area. We provide a regional-scale exposure database for population and residential buildings based on existing information from previous exposure development efforts at the regional and national scale. Such datasets are complemented with country-based data (e.g., building census, national statistics) collected by national representatives in each Central Asian country (Kazakhstan, the Kyrgyz Republic, Tajikistan, Turkmenistan, Uzbekistan). We also develop population and residential-building exposure layers for the year 2080, which support the definition of disaster risk reduction strategies in the region. © 2024 Chiara Scaini et al.

Hydrological droughts occur as a result of various hydrometeorological conditions, such as precipitation deficits, reduced snow cover, and high evapotranspiration. Droughts caused by precipitation deficits and occurring during warm seasons are usually longer in duration. This important observation raises the question that climate change associated with global warming may increase drought conditions. Consequently, it is important to understand changes in the processes leading to dry periods in order to predict potential changes in the future. This study is a scientific analysis of the impact of climate change on drought conditions in the Zhaiyk–Caspian, Tobyl–Torgai, Yesil, and Nura–Sarysu water management basins using the standardized precipitation index (SPI) and streamflow drought index (SDI). The analysis methods include the collection of hydrometeorological data for the entire observation period up to and including 2021 and the calculation of drought indices to assess their intensity and duration. The results of this study indicate an increase in the intensity and frequency of drought periods in the areas under consideration, which is associated with changes in climatic conditions. The identified trends have serious implications for agriculture, ecological balance, and water resources. The conclusions of this scientific study can be useful for the development of climate change adaptation strategies and the sustainable management of natural resources in the regions under consideration. © 2024 by the authors.

Development of advanced structures using modern manufacturing methods has become attractive since they allow to improve system efficiency and performance, fuel consumption reduction, lightweighting to decrease weight and durability of structures, and many more. Designing tools such as topology optimization (TO) has contributed to such developments and facilitated in adapting new manufacturing methods such as 3D printing and computer numerical control machining in many areas of engineering and industry. TO requires computational resources, which can be significantly complex and time consuming when complicated designs and multiphysics problems are considered. To overcome these difficulties, computational acceleration techniques have been applied together with high performance computing. In the current work, various up-to-date research studies in computational acceleration of TO methods are analysed, classified and research trends are evaluated. Thus, the results of the work clearly shows that earlier works relied on central processing unit (CPU)-based computational acceleration techniques, while latest research studies mostly consider graphics processing unit (GPU) and machine learning (ML)-based approaches. The latter got significant attention within last few years and becoming one of the research areas in computational TO. From the reviewed works, it can be concluded that in all of the acceleration techniques, solid mechanics problems were mostly studied, while a few number of research studies are dedicated to heat transfer, fluid flow and electro thermomechanical applications. © 2022

The fight against cancer, a relentless global health crisis, emphasizes the urgency for efficient and automated early detection methods. To address this critical need, this review assesses recent advances in non-invasive cancer prediction techniques, comparing conventional machine learning (CML) and deep neural networks (DNNs). Focusing on these seven major cancers, we analyze 310 publications spanning the years 2018 to 2024, focusing on detection accuracy as the key metric to identify the most effective predictive models, highlighting critical gaps in current methodologies, and suggesting directions for future research. We further delved into factors like datasets, features, and modalities to gain a comprehensive understanding of each approach’s performance. Separate review tables for each cancer type and approach facilitated comparisons between top performers (accuracy exceeding 99%) and low performers (65.83 to 85.8%). Our exploration of public databases and commonly used classifiers revealed that optimal combinations of features, datasets, and models can achieve up to 100% accuracy for both CML and DNN. However, significant variations in accuracy (up to 35%) were observed, particularly when optimization was lacking. Notably, colorectal cancer exhibited the lowest accuracy (DNN 69%, CML 65.83%). A five-point comparative analysis (best/worst models, performance gap, average accuracy, and research trends) revealed that while DNN research is gaining momentum, CML approaches remain competitive, even outperforming DNN in some cases. This study presents an in-depth comparative analysis of CML and DNN techniques for cancer detection. This knowledge can inform future research directions and contribute to the development of increasingly accurate and reliable cancer detection tools. Graphical abstract: (Figure presented.). © International Federation for Medical and Biological Engineering 2024.

This review discusses the current situation of Kazakhstan's mining and metallurgical industry, emphasizing the potential and challenges confronting the sector. It offers a detailed analysis of the industry's current situation, considering issues related to the economy, society, regulations, infrastructure, and the environment. Additionally, the evaluation explores the industry's future direction, particularly considering the National Development Plan in place until 2029. Key aspects include the importance of environmentally responsible practices, foreign investments' role, and technical improvements' impact on production and efficiency. The analysis also highlights Kazakhstan's abundant mineral resources, such as copper, gold, iron, lead, and uranium, and examines mining operations associated environmental and social impacts. Government policies and regulations are significant factors shaping the sector's development. The National Development Plan outlines several strategic objectives, including increasing production, attracting foreign investment, and promoting environmentally responsible practices. The review concludes with recommendations for overcoming obstacles and maximizing opportunities to achieve sustainable growth in Kazakhstan's mining and metallurgical sector. This systematic review, a valuable resource, will greatly benefit stakeholders, researchers, policymakers, and potential investors interested in the future of this crucial industry. © Engineered Science Publisher LLC 2024.

This article introduces an ontological model of digital twins and explores their classification specifically in the context of ensuring human life safety. The paper delves into how digital twins - virtual replicas of physical systems or processes - can be used to improve safety standards, especially in high-risk industries like oil and gas. By simulating real-world scenarios and potential hazards, digital twins provide valuable insights that can help predict and mitigate risks before they impact human life. The article also highlights various examples of digital twins successfully applied to enhance safety measures, such as monitoring dangerous environments, predicting equipment failures, and providing real-time data to improve decision-making during emergencies. Moreover, the prospects for developing digital twins are discussed, particularly in integrating advanced technologies like artificial intelligence, machine learning, and IoT. These advancements could significantly enhance the capabilities of digital twins in safeguarding human life, making them an indispensable tool in industrial safety and risk management practices. © 2024 Copyright for this paper by its authors.

Comprehensive studies of plant communities are essential for preserving rare and valuable species that are diminishing in number. Currently, there is an increasing demand for robust methodologies to conduct population-level research in geobotany, ecological monitoring, and forestry. This article focuses on the rare plant species Hepatica falconeri, Ranunculus polyanthemus L., Ranunculus oxyspermus, and Ranunculus dilatatus, which belong to the Ranunculaceae family and are found in the Tien Shan Mountains of Kazakhstan, based on geobotanical research findings. We present a manual that integrates both traditional and modern techniques for studying environmental factors, biotopes, ectopes, phytocenoses, floral composition, and the condition of natural populations of endemic and medicinal plants. This includes methodologies for assessing the biomass reserves of rare, endemic, and medicinal species, as well as evaluating the state of juvenile plants, population density, and the anatomical, morphological, phytochemical, and molecular genetic characteristics of the studied taxa. These parameters are influenced by geographical variations, microclimatic conditions, and soil properties. This article serves as a comprehensive guide for researchers in the fields of geobotany, biodiversity, botany, biology, agriculture, and medicinal plant studies. Additionally, it provides actionable recommendations for developing effective strategies for the conservation, protection, and sustainable utilization of biodiversity. © The Author(s) 2024.

This paper presents the development, modeling, and analysis of an autonomous active ankle prosthesis with two degrees of freedom (2-DoF), designed to reproduce movements in the sagittal (dorsiflexion/plantarflexion) and frontal (inversion/eversion) planes in order to enhance the stability and naturalness of the user’s gait. Unlike most commercial prostheses, which typically feature only one active degree of freedom, the proposed device combines a lightweight mechanical design, a screw drive with a stepper motor, and a microcontroller-based control system. The prototype was developed using CAD modeling in SolidWorks 2024, followed by dynamic modeling and finite element analysis (FEA). The simulation results confirmed the achievement of physiological angular ranges of ±20–22 deg. in both planes, with stable kinematic behavior and minimal vertical displacements. According to the FEA data, the maximum von Mises stress (1.49 × 108 N/m2) and deformation values remained within elastic limits under typical loading conditions, though cyclic fatigue and impact energy absorption were not experimentally validated and are planned for future work. The safety factor was estimated at ~3.3, indicating structural robustness. While sensor feedback and motor dynamics were idealized in the simulation, future work will address real-time uncertainties such as sensor noise and ground contact variability. The developed design enables precise, energy-efficient, and adaptive motion control, with an estimated average power consumption in the range of 7–9 W and an operational runtime exceeding 3 h per charge using a standard 18,650 cell pack. These results highlight the system’s potential for real-world locomotion on uneven surfaces. This research contributes to the advancement of affordable and functionally autonomous prostheses for individuals with transtibial amputation. © 2025 by the authors.