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This article presents the results of the study of the morphological composition of municipal solid waste (MSW) from the landfill of Atyrau city, and the waste's energy characteristics and presence of microorganisms, including bacteria, fungi and viruses. This study was carried out under a government order to determine the feasibility of recycling accumulated and incoming waste into electricity and its hazard to the environment and the workers involved in handling it. At the moment, there is no MSW recycling in Kazakhstan, which has led to the accumulation of more than 125 million tons of waste with an annual increase of 5 million tons. The research included four major cities (Almaty, Shymkent, Atyrau and Astana), which were selected not only on the basis of population, but also because the cities were located in different climatic zones. Samples were collected at the city landfills: 10 samples with an average distance of 100 m from each other were collected to provide a maximum coverage of both recently received waste and long-time stored waste. The research showed that neither climatic conditions nor the population size had a significant impact on MSW density, the values of which ranged from 120.1 kg/m3 to 145.4 kg/m3, as this indicator directly depends on the quality of life. The mass of the combustible fraction ranged from 39.41% to 54.62% and was mainly represented by plastic, textile and paper waste. The average value for the four cities was 50.30%. The higher calorific value fell in the range of 24.22–30.49 MJ/kg, with an average value of 26.71 MJ/kg. Microbiological studies showed little difference in average composition regardless of climatic conditions. Thus, no sharp differences in MSW composition, its energy characteristics and microbiological composition were found. The results of this study may be useful for optimising MSW recycling and disposal processes, as well as for developing measures to reduce their negative impact on the environment and human health. [ABSTRACT FROM AUTHOR]

This paper investigates the advantages of enhancing construction and demolition waste (CDW) recycling facilities to conform to circular economy (CE) models in Kazakhstan's construction sector. The industry is experiencing significant growth due to urbanization, but it faces difficulties managing CDW, frequently resulting in landfill disposal. In response, this paper provides a cost–benefit analysis of upgrading the CDW recycling centres aligned with CE needs. Reflecting legislative changes in Kazakhstan's Environmental Code, which prohibited CDW in landfills starting December 2020, the initiative to establish modern CDW recycling centres is gaining momentum in major cities. The primary objective is to maximize material recovery and eliminate contaminants that curtail the utilization of recycled sand and aggregate products. The analysis yields compelling results, indicating that the project has the potential to recycle up to 84 million tons of CDW over eight years, with an annual 25% capacity increase and a maximum possible 95% recycling efficiency. Despite an estimated cost of USD 48 million, the project demonstrates a payback period of 9.9 years, signalling eventual cost recovery. These findings underscore the project's capacity to mitigate CDW issues while generating economic benefits and contributing to a sustainable environment. In conclusion, implementing modern CDW recycling centres in Kazakhstan represents a potent solution for the construction industry as it transitions toward a CE model. This transition addresses both pressing environmental challenges and promising economic prospects. [ABSTRACT FROM AUTHOR]

Morphologically derivative languages form words by fusing stems and suffixes, stems are important to be extracted in order to make cross lingual alignment and knowledge transfer. As there are phonetic harmony and disharmony when linguistic particles are combined, both phonetic and morphological changes need to be analyzed. This paper proposes a multilingual stemming method that learns morpho-phonetic changes automatically based on character based embedding and sequential modeling. Firstly, the character feature embedding at the sentence level is used as input, and the BiLSTM model is used to obtain the forward and reverse context sequence, and the attention mechanism is added to this model for weight learning, and the global feature information is extracted to capture the stem and affix boundaries; finally CRF model is used to learn more information from sequence features to describe context information more effectively. In order to verify the effectiveness of the above model, the model in this paper is compared with the traditional model on two different data sets of three derivative languages: Uyghur, Kazakh and Kirghiz. The experimental results show that the model in this paper has the best stemming effect on multilingual sentence-level datasets, which leads to more effective stemming. In addition, the proposed model outperforms other traditional models, and fully consider the data characteristics, and has certain advantages with less human intervention. [ABSTRACT FROM AUTHOR]

This paper provides a detailed description of the findings and methodology related to the monitoring of microplastics in three lakes and one river of the Akmola Region in Kazakhstan. The concentration of microplastic particles and the analysis of water and sediment quality of the Yesil River and Kopa, Zerendinskoye, and Borovoe lakes have been analyzed. A total of 64 water samples were collected across the spring, summer, and autumn seasons, with subsequent analysis revealing a seasonal increase in microplastic concentrations. The average microplastic content ranged from 1.2 × 10−1 particles/dm3 in spring to 4.5 × 10−1 particles/dm3 in autumn. Lakes exhibited higher concentrations compared to the Yesil River. Correlation analysis highlighted a connection between microplastic content and turbidity, particularly notable during the spring season. Analysis of sediments revealed a decrease in microplastic concentrations from the coastal zone toward open waters sediments. Microplastic fibers were predominant in sediments (69.6%), followed by fragments (19.1%), films (7.4%), and granules (3.9%). Larger particles (>500 µm) were found in beach sediments, constituting an average of 40.5% of the total plastics found. This study contributes valuable insights into the spatial and temporal distribution of microplastics, emphasizing the need for ongoing monitoring and management strategies to address this environmental concern. [ABSTRACT FROM AUTHOR]

Efficient waste management, including proper utilization of municipal solid waste (MSW), is imperative for a sustainable future. Among several management options, pyrolysis and combustion of MSW has regained interest because of improved combustion techniques. This work aims to investigate the thermal conversion and combustion characteristics of refuse derived solid fuel (RDF) samples and its individual compounds collected from Nur-Sultan's MSW landfills. The waste-derived solid RDF samples originally consist of textile, mixed paper, and mixed plastic. In particular, the samples, including RDF and its three constituent components, were analyzed in the temperature range of 25 to 900 °C, at three different heating rates, by thermogravimetric method. The gross calorific value for RDF derived from Nur-Sultan's MSW was determined to be 23.4 MJ/kg. The weight loss rates of the samples, differential thermogravimetry (DTG), and kinetic analysis were compared between individual RDF components and for the mixed RDF. Combustion kinetics models were calculated using Flynn–Wall–Ozawa (FWO), Kissinger–Akahira–Sunose (KAS), and Friedman methods. The results revealed that first decomposition of RDF samples was observed at the range of 180–370 °C. Moreover, the activation energy for conversion of RDF was observed to be the highest among the constituent components and gradually decreased from 370 to 140 kJ/kmol. [ABSTRACT FROM AUTHOR]

This paper presents the outcomes derived from an environmental assessment of microplastic pollution resulting from solid waste landfills in the Akmola Region, situated in North Kazakhstan. This research represents a pioneering investigation conducted on microplastics within this specific region. This study encompasses a comprehensive examination of plastic waste disposal sites across the Akmola region, with a particular emphasis on evaluating the status of the municipal solid waste management system. To characterize the plastic content within the waste present at the landfill sites, quantitative techniques were employed. Through experimental means, the composition and fractionation of plastics within the municipal solid waste (MSW) at the landfills were determined. These data were subjected to a comparative analysis, aligning them with official statistics and previously published scientific data from both Kazakhstan and other regions globally. The methodologies employed focused on the "soft" removal of organic substances through the use of oxidants which do not damage plastics, and were tested using a water-bath therapeutic treatment. Furthermore, an analysis of soil samples taken from the landfills unveiled the ultimate retention of microplastic particles, attributed to leachate and rainwater runoff. Extracts were obtained from the subsoil samples using a density-based separation process, involving a three-step extraction followed by subsequent filtration of the resulting supernatants. In addition, the soil samples underwent examination through dry-phase particle fractional separation. The particles were meticulously enumerated and classified, and their dimensions were measured employing microscopic techniques coupled with photographic documentation. The outcomes stemming from these diverse tests will serve as fundamental input for the forthcoming numerical modeling endeavor, which aims to simulate the behavior of microplastics within both soil and water. This endeavor represents a continuation of the research project, the preliminary findings of which are expounded upon in this paper. [ABSTRACT FROM AUTHOR]

Biomass and renewable resources are becoming substitutes for fossil-based resources, providing opportunities for more sustainable environmental management and reductions in environmental damage. This paper studies the prospects for wood pellet production in Kazakhstan through the lens of business model adjustment in a microenterprise in Kazakhstan. This study focuses on answering the following questions: (1) How do microenterprises propose, create, deliver and capture value through business models in the wood industry? (2) What are the opportunities and challenges relating to these business models in the context of wood pellet production in Kazakhstan? Kazakhstan has a high potential for biomass production, providing a particularly interesting case for analysing how microenterprises can tap into this potential to create value. This paper combines an analysis of bioenergy and forestry trends with a qualitative case study. The analysis of the business model is based on Osterwalder's business model canvas. The value proposition of the enterprise studied herein is to provide a local biomass-based alternative to fossil fuels. The overall growth of wood-based industries in Kazakhstan and the national movement towards renewable energy create favourable prospects for microenterprises engaged in the production of wood pellets; however, these industries are also characterised by high institutional and regulatory dependencies. [ABSTRACT FROM AUTHOR]

In this paper, we use preliminary archaeological data spanning the Iron Age through Medieval periods (ca. 800 BCE to 1200 CE) in the Juuku Valley in Kyrgyzstan on the south side of Lake Issyk-Kul to model land use across vertical mountain zones. We have (1) established a radiometric chronology; (2) conducted test excavations of an Iron Age settlement at 2100 m asl and a Turkic period burial at 1934 m asl; (3) undertaken preliminary archaeobotanical research; and (4) performed pedestrian surveys. Archaeobotanical remains of wheat (Triticum aestivum), barley (Hordeum vulgare), broomcorn millet (Panicum milaceum), foxtail millet (Setaria italica), and legumes were recovered in very small quantities from both sites. We compare these preliminary archaeobotanical results with previously published data from Talgar Iron Age settlements on the north side of the Tian Shan Mountain range in Kazakhstan. A small assemblage of faunal remains found at the Turkic period kurgan and from a profile at the upland Iron Age settlement demonstrates the practice of herding sheep/goats, cattle, and horses in the Juuku Valley. The goal of this study was to test the hypothesis that pastoral transhumance and agropastoralism were interchangeable economic strategies used by peoples in the Iron Age through Medieval periods in mountain-river valleys between 600 m to 2100 m asl. These economic strategies combined the pasturing of sheep, goats, cattle, and horses with the cultivation of cereals in a system that was adapted to different vegetational zones along a vertical gradient. This paper is based on preliminary research using survey data and test excavations and initiates a long-term research study of four millennia of settlements that appear to have ranged from pastoral transhumance and combined mountain agriculture. [ABSTRACT FROM AUTHOR]

The article describes the world's experience in developing the solar industry. It discusses the mechanisms of state support for developing renewable energy sources in the cases of five countries that are the most successful in this area—China, the United States, Japan, India, and Germany. Furthermore, it contains a brief review of state policy in producing electricity by renewable energy facilities in Kazakhstan. This paper uses statistical information from the International Renewable Energy Agency (IRENA), the International Energy Agency (IEA), British Petroleum (BP), and the Renewable Energy Network (REN21), and peer-reviewed sources. The research methodology includes analytical research and evaluation methods to examine the current state of solar energy policy, its motivators and incentives, as well as the prospects for its development in Kazakhstan and in the world. Research shows that solar energy has a huge development potential worldwide and is sure to take its place in gross electricity production. This paper focuses on the selected economic policies of the top five countries and Kazakhstan, in what may be considered a specific research limitation. Future research suggestions for the expansion of Renewable Energy (RE) in Kazakhstan could include analysing the impact of introducing dedicated policies and incentives for solar systems and exploring the benefits and challenges of implementing large RE zones with government–business collaboration. [ABSTRACT FROM AUTHOR]

The paper aims to assess the relationship between Azerbaijani and Kazakhstani exchange rates and crude oil prices volatility. The study applies the structural vector autoregressive (SVAR) model. The paper concentrates on Azerbaijan and Kazakhstan, the post-Soviet countries considered as some of the most oil-dependent countries in the Caspian Sea region. The impulse response functions suggest that the rise of crude oil prices is associated with the exchange rates decrease and thus with an Azerbaijani manat and Kazakhstani tenge appreciation against the U.S. dollar. Moreover, the results suggest that an oil price increase leads to the rise of Azerbaijani international reserves. However, the results are insignificant for the Kazakhstani foreign exchange reserves. Additionally, the study reveals a negative and significant relationship between crude oil prices and USD/KZT in both pre-crisis and the COVID-19 crisis periods. We reveal that the correlation has been stronger during the COVID-19 pandemic. However, the relationship is not significant in the case of the Azerbaijani manat. The USD/AZN exchange rate has been stable since 2017, and the first phase of the COVID-19 pandemic has not caused a change in the exchange rate and a weakening of the Azerbaijani currency, despite significant drops in crude oil prices. [ABSTRACT FROM AUTHOR]

In modern times, the risk of food insecurity is a concern for policymakers at the global and national levels, as the issue of hunger and malnutrition still exists. Food security is vulnerable to any crises. The main goal of this paper is to create a neural-network-based predictive model to forecast food consumption trends in Kazakhstan, aiming to reduce the risk of food insecurity. The initial phase of this study involved identifying socioeconomic factors that significantly influence food consumption behaviors in Kazakhstan. Principal component analysis was used to identify key variables, which became the basis for modelling artificial neural networks. It was revealed that the poverty rate, GDP per capita, and food price index are pivotal determinants of food consumption in Kazakhstan. Two models were prepared: to predict food consumption on a national scale per capita per month, and to predict the percentage distribution of various food categories. The prediction of the percentage distribution of various food categories in Kazakhstan demonstrates the positive modelling quality indicators and strengthens the assumption that network modelling can be used. Predictions for total food consumption over the next three years indicate declining metrics, raising concerns about the potential food insecurity risk in Kazakhstan. [ABSTRACT FROM AUTHOR]

Southern Kazakhstan is one of the fastest-growing regions of this country and continued development depends on a sustainable supply of freshwater for multiple purposes. Groundwater in Southern Kazakhstan occurs in a wide variety of hydrogeological conditions with varying levels of quality and vulnerability to contamination. The aim of this paper is to investigate the present groundwater quality through sampling and laboratory analysis of source water from public supply wells, compare results to hydrogeology and known contaminant sources, and indicate where future protections may be needed. Protection from surface-borne contaminants is mainly determined by the thickness of the vadose zone, depth of the groundwater level, presence, thickness and composition of aquifers, and mobility of pollutants. Forty-five wells were sampled, yielding 106 samples of groundwater presently used for drinking water, which were evaluated to investigate the occurrence of potential pollutants and hydrogeology of the region. Of the samples collected, 46 samples were used for analysis of inorganic water chemistry, 30 for individual indicators including metals, and 31 samples for determination of petroleum products. A contaminant inventory database and geospatial database aided the interpretation of the results and allowed the prediction of future water issues. Kazakhstan's maximum permissible concentrations (MPCs) for metals were exceeded in areas associated with industrial enterprises, while fluoride and nitrate were more closely associated with mining and agricultural sources. Groundwater quality is dependent on hydrogeology and environmental contaminants resulting from historical land uses and must be regularly monitored for drinking water safety. Petroleum hydrocarbons were not detected in any of the drinking water sources. [ABSTRACT FROM AUTHOR]

This paper proposes a new approach to predicting the distribution of harmful substances in the atmosphere based on the combined use of the parameter estimation technique and machine learning algorithms. The essence of the proposed approach is based on the assumption that the concentration values predicted by machine learning algorithms at observation points can be used to refine the pollutant concentration field when solving a differential equation of the convection-diffusion-reaction type. This approach reduces to minimizing an objective functional on some admissible set by choosing the atmospheric turbulence coefficient. We consider two atmospheric turbulence models and restore its unknown parameters by using the limited-memory Broyden–Fletcher–Goldfarb–Shanno algorithm. Three ensemble machine learning algorithms are analyzed for the prediction of concentration values at observation points, and comparison of the predicted values with the measurement results is presented. The proposed approach has been tested on an example of two cities in the Republic of Kazakhstan. In addition, due to the lack of data on pollution sources and their intensities, an approach for identifying this information is presented. [ABSTRACT FROM AUTHOR]

Creating an effective and safe vaccine is critical to fighting the coronavirus infection successfully. Several types of COVID-19 vaccines exist, including inactivated, live attenuated, recombinant, synthetic peptide, virus-like particle-based, DNA and mRNA-based, and sub-unit vaccines containing purified immunogenic viral proteins. However, the scale and speed at which COVID-19 is spreading demonstrate a global public demand for an effective prophylaxis that must be supplied more. The developed products promise a bright future for SARS-CoV-2 prevention; however, evidence of safety and immunogenicity is mandatory before any vaccine can be produced. In this paper, we report on the results of our work examining the safety, toxicity, immunizing dose choice, and immunogenicity of QazCoVac-P, a Kazakhstan-made sub-unit vaccine for COVID-19. First, we looked into the product's safety profile by assessing its pyrogenicity in vaccinated rabbit models and using the LAL (limulus amebocyte lysate) test. We examined the vaccine's acute and sub-chronic toxicity on BALB/c mice and rats. The vaccine did not cause clinically significant toxicity-related changes or symptoms in our toxicity experiments. Finally, we performed a double immunization of mice, ferrets, Syrian hamsters, and rhesus macaques (Macaca mulatta). We used ELISA to measure antibody titers with the maximum mean geometric titer of antibodies in the animals' blood sera totaling approximately 8 log2. The results of this and other studies warrant recommending the QazCoVac-P vaccine for clinical trials. [ABSTRACT FROM AUTHOR]

This paper is devoted to the problems of differentiation of stylistic variants in the common phenomenon of the so-called Scythian and Siberian animal styles, which is one of the main distinctive features of Eurasian nomadic art. The animal style is a concept of more scale than an artistic style proper which distinguishes with some formal characteristics and depends directly on generic traditions and ethnic and cultural roots of art. Together with the technical-technological methods these formal features could be evidential indications of the origin of works of art. The Siberian collection of Peter the Great includes some different groups of golden ornaments decorated in animal styles of different origins. The paper focuses on a compact group of items originating from various mostly unknown sites from different territories in Asia including the Oxus treasure, several items from the Siberian collection of Peter the Great from Southern Siberia, a few jewelry pieces from other collections of the world museums as well as items made of leather and felt coming from the First and the Second Pazyryk kurgans. A distinctive feature of this group of zoomorphic images are colored inlays that accentuate a hind-leg or a shoulder of the animal; such inlays have the form of an intricate figure made up of a circle and a curvilinear triangle abutting to it or elongated round brackets. Genetically, such an ornamental motif, which is not generally typical for Persian art, may be linked to a periphery area of the Iranian world and nomadic culture, while the group of sites can be dated back to the 4th–3rd centuries BC. The paper considers a bracelet from the Siberian collection of Peter the Great which is the only item in this category of jewelry type of bracelets. It represents a rare type of ornament with a multi-component structure. It consists of three open-work strips with zoomorphic compositions in an animal style similar to the above-mentioned stylistic group. All three parts of the bracelet are created in a unified style, but obviously in different individual manners. There is no doubt, that the zoomorphic images show three different authors' hands, and were made by different artisans. So, there is evidence of collective work on the object when each artisan makes his own operation to create a unique jewel at a workshop. Some parts of the composition on the bracelet are similar in style to zoomorphic images from kurgan Issyk in Kazakhstan which perhaps were made in the same workshop. This fact confirms the assumption of the origin of some of Siberian jewelry. [ABSTRACT FROM AUTHOR]

The paper provides results of a detailed mineralogical study of some chromitite ores from two deposits in the Southern Urals of Kazakhstan: Almaz-Zhemchuzhina and Geofizicheskoe-VII. It is revealed that the main ore minerals are Cr-spinel with high Cr# (Cr/(Cr + Al) = 0.8–0.83), as well as serpentine and chlorite, replacing primary olivine. Chromium spinel grains contain mineral inclusions, which are distributed rather unevenly. The most common mineral inclusions are olivine (serpentine) and amphibole; phlogopite, pyroxenes, and base metal sulfides are rare. Olivine from inclusions in chromite is the highest in magnesium (Fo97–98), and is anomalously high in nickel (up to 1.8 wt.% NiO). The closure of exchange reactions between olivine and chromite occurred in the temperature range of 700–850 °C and in the oxygen fugacity range of −1.04 ... +2.8 ΔFMQ, which most likely corresponds to the upper mantle settings of the fore-arc basin. A few tens of monomineral grains and polymineral intergrowths of platinum group minerals (PGMs) were found in chromite aggregates. Notably, monomineral grains are mainly represented by Ru, Os, and Ir disulfides, while in polymineral inclusions, iridium prevails (with widespread native phases, sulfides, and sulfoarsenides). PGM grains included in chromite are often associated with hydrous silicates: amphibole, and less often with phlogopite or chlorite. Discussed in the paper is the possible genesis of ores and inclusions. As a preliminary conclusion, we suggest that the solid-phase processes played the most significant role in the crystallization of Cr-spinel in the investigated chromitite ores. [ABSTRACT FROM AUTHOR]

This study provides a critical review and assessment of the problems of enhancing the research activity at a Kazakhstani pedagogical university that prepares future teachers. The aim of this study is to provide a rationale for the relevance of scientific and methodological support for increasing the research activity of teachers at pedagogical universities through the systematic integration of practitioner action research into professional practice. The value of action research is related to the change in and improvement of the professional practice of teachers based on the convergence of practice-oriented science and science-oriented practice. This work is in response to the gap in the professional preparation of future teachers, particularly in terms of developing research competencies and equipping future teachers with knowledge about action research. This is in marked contrast to in-service teachers who have been exposed to action research through the whole country's ongoing reform of teacher education. Using a large survey of academic staff, the paper identifies the key factors influencing the research activity of university teachers. The findings from the survey and the narrative review suggest a willingness and openness to new ways of working among staff, which would make it possible to increase the research activity of university teachers themselves by integrating non-formal forms of research such as action research into their practice. [ABSTRACT FROM AUTHOR]

The uranium required for power plants is mainly extracted by two methods in roughly equal amounts: quarries (underground and open pit) and in situ leaching (ISL). Uranium mining by in situ leaching is extremely attractive because it is economical and has a minimal impact on the region's ecology. The effective use of ISL requires, among other things, the accurate assessment of the host rocks' filtration characteristics. An accurate assessment of the filtration properties of the host rocks allows optimizing the mining process and improving the quality of the ore reserve prediction. At the same time, in Kazakhstan, this calculation is still based on methods that were developed more than 50 years ago and, in some cases, produce inaccurate results. According to our estimates, this method provides a prediction of filtration properties with a determination coefficient R 2 = 0.32. This paper describes a method of calculating the filtration coefficient of ore-bearing rocks using machine learning methods. The proposed approach was based on nonlinear regression models providing a 20–75% increase in the accuracy of the filtration coefficient assessment compared with the current methodology. The work used different types of machine learning algorithms based on the gradient boosting technique, bagging technique, feed-forward neural networks, support vector machines, etc. The results of logging, core sampling, and hydrogeological studies obtained during the exploration stage of the Inkai deposit were used as the initial data. All used machine learning models demonstrated significantly better results than the old method. This resulted in improved results compared with previous studies. The LightGBM regressor demonstrated the best result ( R 2 = 0.710). [ABSTRACT FROM AUTHOR]

The global spread of multi-resistant pathogenic microorganisms has significantly complicated the treatment of chronic wounds. The development of novel drugs requires a substantial time investment. Hybrid materials such as nanoparticles stabilized by plant extracts are considered the best for creating efficient antiseptic substances. This paper is the first to discuss quantitative and qualitative analyses of the phytochemical constituents of the medicinal plant Artemisia terrae-albae, collected in Kazakhstan. The antimicrobial activity of the extracts, as well as of silver nanoparticles (AgNPs) stabilized by Artemisia terrae-albae extract, were evaluated. AgNPs were characterized by an average size of 82 nm or larger with a negative surface charge. TEM analysis of the obtained suspension showed a nonuniform structure of particles synthesized at a low concentration of ethyl acetate solvent in water. The SPR peak of AgNPs@Art aq. extract was detected at 420 nm, while any clear SPR peak was observed for AgNPs@Art ethylacetate extract. Diluted Artemisia terrae-albae extracts did not exhibit pronounced antimicrobial activity due to the poor solubility of compounds in water. Nevertheless, the AgNPs@Art aq. and AgNPs@Art EtAc. extracts possessed antimicrobial activity against the Pseudomonas aeruginosa ATCC 9027, Staphylococcus aureus ATCC 6538, Escherichia coli (ATCC 8739), and Candida albicans ATCC 10231 strains. [ABSTRACT FROM AUTHOR]

Climate change, uneven distribution of water resources and anthropogenic impact have led to salinization and land degradation in the southern regions of Kazakhstan. Identification of saline lands and their mapping is a laborious process associated with a complex of ground measurements. Data from remote sensing are widely used to solve this problem. In this paper, the problem of assessing the salinity of the lands of the South Kazakhstan region using remote sensing data is considered. The aim of the study is to analyze the applicability of machine learning methods to assess the salinity of agricultural lands in southern Kazakhstan based on remote sensing. The authors present a salinity dataset obtained from field studies and containing more than 200 laboratory measurements of soil salinity. Moreover, the authors describe the results of applying several regression reconstruction algorithms (XGBoost, LightGBM, random forest, Support vector machines, Elastic net, etc.), where synthetic aperture radar (SAR) data from the Sentinel-1 satellite and optical data in the form of spectral salinity indices are used as input data. The obtained results show that, in general, these input data can be used to estimate salinity of the wetted arable land. XGBoost regressor ( R 2 = 0.282) showed the best results. Supplementing the radar data with the values of salinity spectral index improves the result significantly ( R 2 = 0.356). For the local datasets, the best result shown by the model is R 2 = 0.473 (SAR) and R 2 = 0.654 (SAR with spectral indexes), respectively. The study also revealed a number of problems that justify the need for a broader range of ground surveys and consideration of multi-year factors affecting soil salinity. Key results of the article: (i) a set of salinity data for different geographical zones of southern Kazakhstan is presented for the first time; (ii) a method is proposed for determining soil salinity on the basis of synthetic aperture radar supplemented with optical data, and this resulted in the improved prediction of the results for the region under consideration; (iii) a comparison of several types of machine learning models was made and it was found that boosted models give, on average, the best prediction result; (iv) a method for optimizing the number of model input parameters using explainable machine learning is proposed; (v) it is shown that the results obtained in this work are in better agreement with ground-based measurements of electrical conductivity than the results of the previously proposed global model. [ABSTRACT FROM AUTHOR]

Nowadays in the world, due to the constant desire for recycling, many countries are considering the use of recycled plastics on roads. Modification of bitumen for roads in Kazakhstan is considered one of the most suitable and popular approaches. This paper presents the results of research on the modification of bitumen by recycled plastics from waste materials. The paper describes the details of the use of plastic waste as bitumen modifiers, with a specific focus on recycled plastics and how they can potentially be used to enhance bitumen performance and the road durability. The main physical and mechanical characteristics of the modified bitumen were determined after routine tests, penetration and plasticity, softening temperature, brittleness temperature on Fraas and microscopic analysis. The morphology of the modified bitumen was studied using scanning electron microscopy. The results confirm that the modified bitumen complies with the requirements for polymer-bitumen binder of Kazakhstani standards and is suitable for the production of modified bitumen by its physical and chemical characteristics. [ABSTRACT FROM AUTHOR]

This paper reports the "Capacity building for innovative engineers through STEAM education" project conducted at Kazakhstan's Saginov Technical University ('STU') and funded by the Science Committee of the Ministry of Education and Science of the Republic of Kazakhstan (Grant No. AR09260338). The problem of intercultural communication and the ability to collaborate, the issues of critical thinking development, and using the creative approach to solving professional tasks remain weak in the system of engineering higher education in Kazakhstan. STEAM Education appears to serve a role in overcoming the problem. Conducting a comprehensive study of the world experience and developing strategies for introducing STEAM into the educational process at Kazakhstani universities based on multifactor SWOT analysis made it possible to form several STEAM approaches for innovative engineering education. In the paper, we present the STEAM (Science-Technology-Engineering-Arts-Mathematics) Education framework for innovative training of engineers developed based on the best practices from around the world. This framework focuses on sustainable engineering education for intercultural communication, creative industry, and creative cooperation. In developing the STEAM Education framework, the researchers applied a methodology that included classification and comparison of international STEAM Education practices, analysis of regulatory documents, and statistical data in the sphere of education and multifactor SWOT analysis. [ABSTRACT FROM AUTHOR]

Solid waste management is one of the main problems in large cities. The determination of the quantitative and qualitative composition of municipal solid waste is necessary for proper planning in the processing of such waste. This article presents the results of studies of the morphological composition, physico-chemical parameters and energetical potential of municipal solid waste (MSW) from the landfill of the city of Shymkent. Waste samples were taken from 10 different points of the landfill. The volume–mass parameters of the samples and their average density were determined. The combined waste samples mainly consisted of food waste, paper and cardboard, polymers and plastic, glass, metal, textiles, wood, leather, bones and rubber. Most of the waste, more than 30%, contains plastic products. The moisture of the combustible fraction of the samples is low and varies from 0.3% to 2.3%. The average ash content of the combustible fraction of the samples was determined and its average value is 18.4%. The yield of the volatile substances was determined and the average value per dry state is 78.7%. To determine the energetical potential of municipal solid waste, the gross calorific value was determined and the net calorific value was calculated, the average value of which is 24.15 MJ/kg. This shows the possibility of using solid waste as an energy source. [ABSTRACT FROM AUTHOR]

This article constructs a multidimensional logistic model for predicting the employment of graduates of higher educational institutions trained under the program of academic mobility, using the example of Kazakh universities. The purpose of the research is to identify the relationship between academic mobility and the employment of university graduates, as well as the necessary skills and competencies that can promote academic mobility in higher education institutions. This paper presents the results of calculating correlation coefficients and conducting a chi-square test, which demonstrated a relationship between the dependent variable and other questions in the graduate questionnaire. After the discovery of pairwise relationships, a multivariate logistic model was built that included statistically significant categories of responses. As a result, it was determined that the usefulness of participation in the academic mobility program is influenced by foreign language proficiency, an increase in academic mobility, the development of educational programs based on the needs of the labor market, as well as an increase in the weight of those methods that form practical skills in information analysis and the creation of public spaces in the labor market. The model demonstrated good predictive properties, which can be used to predict those individuals who were helped by academic mobility in finding employment. [ABSTRACT FROM AUTHOR]

The article provides an overview of the accuracy of various yield forecasting algorithms and offers a detailed explanation of the models and machine learning algorithms that are required for crop yield forecasting. A unified crop yield forecasting methodology is developed, which can be adjusted by adding new indicators and extensions. The proposed methodology is based on remote sensing data taken from free sources. Experiments were carried out on crops of cereals, legumes, oilseeds and forage crops in eastern Kazakhstan. Data on agricultural lands of the experimental farms were obtained using processed images from Sentinel-2 and Landsat-8 satellites (EO Browser) for the period of 2017–2022. In total, a dataset of 1600 indicators was collected with NDVI and MSAVI indices recorded at a frequency of once a week. Based on the results of this work, it is found that yields can be predicted from NDVI vegetation index data and meteorological data on average temperature, surface soil moisture and wind speed. A machine learning programming language can calculate the relationship between these indicators and build a neural network that predicts yield. The neural network produces predictions based on the constructed data weights, which are corrected using activation function algorithms. As a result of the research, the functions with the highest prediction accuracy during vegetative development for all crops presented in this paper are multi-layer perceptron, with a prediction accuracy of 66% to 99% (85% on average), and polynomial regression, with a prediction accuracy of 63% to 98% (82% on average). Thus, it is shown that the use of machine learning and neural networks for crop yield prediction has advantages over other mathematical modelling techniques. The use of machine learning (neural network) technologies makes it possible to predict crop yields on the basis of relevant data. The individual approach of machine learning to each crop allows for the determination of the optimal learning algorithms to obtain accurate predictions. [ABSTRACT FROM AUTHOR]

The paper considers the possibility of reusing previously used railway rails. The analysis is conducted using the standards and operating conditions of the rails of one of the Central Asian states, Kazakhstan, as an example. The operation of these rails causes significant stresses, while the surface layers are strengthened as a result of cold hammering. These phenomena significantly change the physical and mechanical characteristics of rails. As a result, they may not be suitable in terms of parameters for basic use but can be suitable for installation on other tracks. The conducted studies have shown that when the standard service life of the RP65 rail expires, the surface layer is deformed to a depth of up to 300 microns, hardness increases, and internal residual stresses are formed. These changes lead to an increase in the strength properties of the rails. However, at the same time, cracks originate in the surface layer of the rail, thus worsening operational characteristics. The RP65 rails are used under a cyclic load of 700 kN (which is determined by the national standard), withstanding 790,000 cycles. When the load is reduced to 510 kN, these rails can withstand the 2,000,000 cycles required by the standard without failure. Thus, these rails can be reutilized only on non-loaded and non-critical sections. [ABSTRACT FROM AUTHOR]

In this paper, we outline a study conducted on altered rocks in Central Kazakhstan, in particular, focusing on secondary quartzites. The study reveals a connection between copper-porphyry deposits in Central Kazakhstan and secondary quartzites. Recent research has unveiled gold mineralization in various secondary quartzite massifs, which has spurred further investigations in the region. Over the past three decades, extensive studies have been conducted that have demonstrated similarities among the gold deposits in this area and epithermal gold-silver deposits in volcanic-plutonic arcs around the world. By identifying patterns in the distribution of gold mineralization and developing regional exploration criteria, researchers have comprehensively assessed 48 secondary quartzite massifs and have prioritized promising areas for further exploration. Valuable findings have emerged from detailed examinations of the Akgirek and Birlestik massifs, which have involved drilling exploration wells up to a depth of 250 m. These investigations have shed light on the depth distribution of metasomatites and their association with gold mineralization. Consequently, these findings strengthen our belief in the significant potential for gold mineralization in the secondary quartzites of the Jungar-Balkhash folded system. [ABSTRACT FROM AUTHOR]

The skin shows the physiological condition of the body's organs and systems that prevent infections and physical damage. Throughout the ages, in folk medicine, phytotherapy was considered a primary form of treatment in all countries, including Kazakhstan, due to the abundance and availability of plant-based remedies. This paper discusses several medicinal plants that are traditionally used in the treatment of skin diseases in the Republic of Kazakhstan. The chemical composition of these plants was analyzed, with a particular focus on the biologically active basic compounds responsible for their therapeutic efficiency in treating skin ailments. [ABSTRACT FROM AUTHOR]

Ferula ferulaeoides (Steud.) Korov is one of the traditional ethnic medicines in Xinjiang Uygur and Kazakh of China, which mainly contains volatile oils, terpenoids, coumarins and other chemical components. Previous work has shown that F. ferulaeoides exhibited insecticide, antibacterial, antitumor properties, and so on. In this paper, the chemical composition, pharmacological activity, and quality control of F. ferulaeoides were reviewed, and the application of F. ferulaeoides in the food industry was explored, so as to provide some reference for the quality evaluation of F. ferulaeoides and its further development and utilization. [ABSTRACT FROM AUTHOR]

Southern and southeastern Kazakhstan is a region of intraplate seismicity characterized by several destructive earthquakes. Almaty, the largest metropolis in this region, has many structures with different construction materials and seismic-resistant systems. Among them, residential buildings constructed in the Soviet Union era (before the 1990s) may possess low seismic resisting capacities due to limited seismic design and detailing provisions. Therefore, it is essential to assess seismic risks for these buildings. This paper collected information from a government agency (i.e., KazNIISA), including construction materials, lateral force-resisting systems, and structural ductility capacities for residential buildings constructed in this era. These buildings were then categorized in terms of their seismic vulnerabilities following the European Macro-seismic Scale (EMS-98). Vulnerability curves and probability of damages were developed under different earthquake intensities and peak ground accelerations. The likelihood of varying levels of damage was established for the design basis and maximum considered earthquakes in the Almaty region. It was found that unreinforced masonry and wood buildings tend to be very heavily damaged and even collapse under the maximum considered earthquake. The reinforced and precast concrete buildings have a high probability of heavy to very heavy damage, which may require further analytical assessment since the structure at this damage level will undergo a significant nonlinear response and has a high uncertainty in the seismic performance. [ABSTRACT FROM AUTHOR]

In the current paper, we present the results of Kazakh propolis investigations. Due to limited data about propolis from this country, research was focused mainly on phytochemical analysis and evaluation of propolis antimicrobial activity. uHPLC-DAD (ultra-high-pressure-liquid chromatography coupled with diode array detection, UV/VIS) and uHPLC-MS/MS (ultra-high-pressure-liquid chromatography coupled with tandem mass spectrometry) were used to phytochemical characteristics while antimicrobial activity was evaluated in the serial dilution method (MIC, minimal inhibitory concentration, and MBC/MFC, minimal bactericidal/fungicidal concentration measurements). In the study, Kazakh propolis exhibited a strong presence of markers characteristic of poplar-type propolis—flavonoid aglycones (pinocembrin, galangin, pinobanksin and pinobanskin-3-O-acetate) and hydroxycinnamic acid monoesters (mainly caffeic acid phenethyl ester and different isomers of caffeic acid prenyl ester). The second plant precursor of Kazakh propolis was aspen–poplar with 2-acetyl-1,3-di-p-coumaroyl glycerol as the main marker. Regarding antimicrobial activity, Kazakh propolis revealed stronger activity against reference Gram-positive strains (MIC from 31.3 to above 4000 mg/L) and yeasts (MIC from 62.5 to 1000 mg/L) than against reference Gram-negative strains (MIC ≥ 4000 mg/L). Moreover, Kazakh propolis showed good anti-Helicobacter pylori activity (MIC and MBC were from 31.3 to 62.5 mg/L). All propolis samples were also tested for H. pylori urease inhibitory activity (IC50, half-maximal inhibitory concentration, ranged from 440.73 to 11,177.24 µg/mL). In summary Kazakh propolis are potent antimicrobial agents and may be considered as a medicament in the future. [ABSTRACT FROM AUTHOR]

This paper represents the results of a study of the chemical composition of salt lakes within the Burabay rock mass in eastern Kazakhstan. We sampled water and bottom deposits, geochemically analyzed the composition of the salt lakes, and performed aerial photography of the lakes to geometrize them. We studied the linkage between the rare-metal mineralization of granites of the Burabay rock mass and the salt lakes within the territory. Based on the obtained data, we identified the prospects of the survey area for rare metals. The surveys included 15 water samples and 15 bottom-deposit samples. To identify the source of salt in the lake water and deposits, the chemical composition of Burabay rocks was analyzed and seven samples of coarse-grained and porphyritic granites were selected. It was established that the water and bottom deposits accumulated elevated concentrations of valuable components (i.e., Sr, Rb, and U); this fact may be considered as an argument for conducting special surveys of small lakes in the region. The results obtained can be used for conducting further explorations and mining operations in the survey area in order to revive the rare-metal industry in the region, which will allow the development of new high-tech production and the creation of new jobs in this sphere. [ABSTRACT FROM AUTHOR]

This paper presents the development of composite silicate mass compositions based on man-made waste for the production of autoclave hardening products, as well as the results of physicochemical studies of hydration products of silicate materials. The possibility, expediency and efficiency of using multi-tonnage technogenic waste of Kazakhstan in the industry of composite building materials is shown. Based on the results of the conducted research, the composition of a composite silicate mass based on burnt carbonate-barium tailings (8-12%), electrothermophosphoric slags (82-90%) or sand and dust from cement kiln electrofilters (2-5%) for the production of autoclave hardening products was developed. It was found that the cementing substance in composite silicate materials is represented by CSH(B) calcium silicate hydrates, tobermorite and serpentine. The simultaneous presence of fibrous and crystalline calcium and magnesium silicate hydrates in hydration products leads to the creation of composite products with a maximum strength of 41-49 MPa. [ABSTRACT FROM AUTHOR]

National and world news is constantly accompanied by inter-group dramas which are permeated by the dynamics of language use and attitudes. Conflicts can arise between the state insisting on an official language and the family and community who may support the preservation or revitalisation of heritage languages. Kazakhstan is an example of how languages (official Kazakh, the language of communication Russian and international English) coexist peacefully. Language policy and planning depend on the ability and willingness of individual members of the speech community to adopt a language. Language planning is often seen as a top-down, government-controlled activity. This paper shows that language planning can also be carried out from below. Here, we analyze the main initiatives of grassroots movements in promoting the status of the Kazakh language and the emergence of new bottom-up approaches facilitated by the Internet and present sociolinguistic survey results regarding the roles, importance and prestige of languages for the people of Kazakhstan. The focus of the study reported in this article is to monitor the transformative character of bottom-up approaches to language-policy study in Kazakhstan. [ABSTRACT FROM AUTHOR]

Building a good speech recognition system usually requires a lot of pairing data, which poses a big challenge for low-resource languages, such as Kazakh. In recent years, unsupervised pre-training has achieved good performance in low-resource speech recognition, but it is rarely used in Kazakh and other Central and West Asian languages. In this paper, wav2vec2.0 is improved by integrating a Factorized TDNN layer to better preserve the relationship between the voice and the time step before and after the quantization, which is called wav2vec-F. The unsupervised pre-training strategy was used to learn the potential speech representation from a large number of unlabeled audio data and was applied to the cross-language ASR task, which was optimized using the noise contrast binary classification task. At the same time, speech synthesis is used to promote the performance of speech recognition. The experiment shows that wav2vec-F can effectively utilize the unlabeled data from non-target languages, and the multi-language pre-training is obviously better than the single-language pre-training. The data enhancement method using speech synthesis can bring huge benefits. Compared with the baseline model, Librispeech's test-clean dataset has an average reduction of 1.9% in the word error rate. On the Kazakh KSC test set, the pre-training using only Kazakh reduced the word error rate by 3.8%. The pre-training of a small amount of Kazakh speech data synthesized by multi-language combined with TTS achieved a word error rate of 8.6% on the KSC test set when the labeled data were only 10 h, which was comparable to the results of the previous end-to-end model when the labeled data were 30 times less. [ABSTRACT FROM AUTHOR]

Remote work displays the flexibility of labor relations and expands the possibilities of conducting professional activities balanced with fulfilling personal needs. Simultaneously, when implementing the telework mode of labor relations, the problems of ensuring the equality and confidentiality of employees require special attention. Given the current global and internal threats, the effective organization of teleworking is an issue to the fore, even in countries where it was not previously given the attention it deserves. This study aims to explore the labor legislation norms of the Republic of Kazakhstan as far as remote work is concerned from the viewpoint of effectiveness. This paper includes a sociological survey among Kazakhstani organizations to determine the conditions of employees working remotely and to use it for conclusions about the effectiveness of the legislation in preventing violations of workers' rights. The study proposes mechanisms and rules aimed at the effective regulation of remote work to address the problems of confidentiality and the equal treatment of the employee, regardless of the mode of conducting his/her professional activities. This research advances knowledge in the field of legal and ethical aspects of the regulation of remote work, demonstrating the experience of developing countries with the study of the experience of Kazakhstan. [ABSTRACT FROM AUTHOR]

This paper presents the results of an experimental study of freezing and thawing patterns of highways in Kazakhstan. Special sensors measure temperature and moisture change every hour in automatic mode. The purpose of this work is to develop a methodology for determining the depth of freezing of subgrade soils of roads of Kazakhstan, and the task is to establish the pattern of cold temperature change (temperature "0 °C") through certain points (sensors) at any time. In the upper part of the pavement (up to 30–40 cm), the temperature changes in annual and daily cycles. As the depth increases, the daily temperature fluctuations disappear, leaving only the annual fluctuation. At a depth of 180 cm and below, temperature fluctuations occur only in the annual cycle. The freezing rate varied from 14 cm/day to 0.33 cm/day. The maximum freezing depth was 227 cm. The descending branch of thawing occurs almost uniformly, with an average rate of 6.25 cm/day to a depth of 220 cm; the average rate of the ascending branch of thawing is 0.9 cm/day. Asphalt–concrete layers of the pavement and the upper part of the subgrade were in a frozen state for 151 and 166 days, respectively. In the subgrade at the beginning and end of the cold period, there are abrupt changes in moisture, which are explained by phase transitions of the second order: the transition from the liquid state to the solid (ice) at the beginning of the cold period and the transition of moisture from the solid state to liquid at the end of the cold period. [ABSTRACT FROM AUTHOR]

A comprehensive representation of the road pavement state of health is of great interest. In recent years, automated data collection and processing technology has been used for pavement inspection. In this paper, a new signal on graph (SoG) model of road pavement distresses is presented with the aim of improving automatic pavement distress detection systems. A novel nonlinear Bayesian estimator in recovering distress metrics is also derived. The performance of the methodology was evaluated on a large dataset of pavement distress values collected in field tests conducted in Kazakhstan. The application of the proposed methodology is effective in recovering acquisition errors, improving road failure detection. Moreover, the output of the Bayesian estimator can be used to identify sections where the measurement acquired by the 3D laser technology is unreliable. Therefore, the presented model could be used to schedule road section maintenance in a better way. [ABSTRACT FROM AUTHOR]

The ground source heat pump heating system is considered as one of the best solutions for the transition towards green heating under the continental climate conditions like Kazakhstan. In this paper, experimental and theoretical investigations were carried out to develop a ground source heat pump-based heating system under the weather conditions in Kazakhstan and to evaluate its thermodynamic performance. The water-to-water heat pump heating system, integrated with a ground source heat exchanger and used refrigerant R134a, was designed to provide hot water to meet the requirements for space heating. The predicted values of the coefficient of performance and the experimental results were found to be in good agreement within 6.2%. The thermodynamic performance of the system was also assessed using various environment-friendly refrigerants, such as R152a, R450A, R513A, R1234yf and R1234ze, as potential replacements for R134a. Although R152a is found to be a good alternative for R134a in terms of coefficient of performance and total equivalent warming impact, its flammability hinders its application. The heating system using refrigerants R450A, R513A, R1234yf and R1234ze shows 2–3% lower coefficient of performance than that of R134a. The highest exergy destruction is found to be attributed to the compressor, followed by the expansion valve, evaporator, and condenser. Considering their low flammability and low environmental impact, R450A, R513A, R1234yf and R1234ze are identified as valuable replacements for R134a. [ABSTRACT FROM AUTHOR]

The water-flooded zone in a sandstone reservoir with a complex porosity–permeability relationship is difficult to interpret quantitatively. Taking the P Formation of Kalamkas Oilfield in Kazakhstan as an example, this paper proposed a reservoir classification method that introduces the J-function into the crossplot of resistivity and oil column height to realize the classification of sandstone reservoirs with a complex porosity–permeability relationship. Based on the classification results, the initial resistivity calculation models of classified reservoirs were established. The oil–water seepage experiment was performed for classified reservoirs to measure the lithoelectric parameters and establish the relationship between water production rate and resistivity for these reservoirs, and then water production was quantitatively calculated according to the difference between the inverted initial resistivity and the measured resistivity. The results show that the reservoirs with an unclear porosity–permeability relationship can be classified by applying the J-function corresponding to grouped capillary pressure curves to the crossplot of oil column height and resistivity, according to the group average principle of capillary pressure curves. This method can solve the problem that difficult reservoir classification caused by a weak porosity–permeability correlation. Moreover, based on the results of reservoir classification, the water production rate and resistivity model of classified reservoirs is established. In this way, the accuracy of quantitative interpretation of the water-flooded zone in the reservoir can be greatly improved. [ABSTRACT FROM AUTHOR]

This paper is devoted to the creation of an information and analytical system (IAS) which is under development to manage the data obtained in experiments and investigations to justify the safety of atomic energy, which the National Nuclear Center of the Republic of Kazakhstan (RSE NNC RK) has been conducting for over 30 years. The main components of the IAS determining its consumer capabilities is an analytical unit that will allow the creation of programs for planned experiments in view of the technical requirements for them and based on the results of previous experiments, generalized and consolidated by processing and comparison tools provided by the IAS. An important component of the IAS is a set of tools for the predictive calculation of the temperature of materials of test sections depending on a given change in the power of energy release in them, predictive calculation of the required power of energy release in materials depending on a given change in their temperature, formation of arrays of experimental information in digital format and graphical form, comparison of experiments and their data among themselves, and the formation of protocols of experiments with the possibility of choosing specific data and methods for their processing. It should be noted that the created IAS greatly simplifies the preparation for experiments. [ABSTRACT FROM AUTHOR]

The efficiency of the national innovation system (NIS) is widely considered to be the most important factor of innovation-based economic growth. Using the wide spectrum of different metrics for measuring the efficiency of NIS, modern studies focus mainly on high-income or upper-middle-income countries, while the effectiveness of the NIS in post-Soviet countries has not been studied enough. The post-socialist transformation has led to different models of economic development in these countries, which can be divided into three groups: a group with developed European institutions, a group with a focus on the European path of development, and, finally, a group of countries with an economic model of "state capitalism". These models formed the trajectory of innovative development. The main purpose of this study is to compare the performance of NIS in post-Soviet countries and to find out whether differences between development institutions can help explain differences in the performance of NIS. The study applies the DEA methodology and considers NISs as homogeneous economic agents, which transform the same types of inputs (knowledge gained using human and financial resources) into the same types of positive outcomes (innovative products and services). The results of a study conducted on data for the period 2011–2018 show that there is no evidence to support the hypothesis that EU institutions or the type of economic model of the country directly relate to the effectiveness of the NIS. The example of Kazakhstan shows that NIS can be effective, even with strong state intervention in the economy. Taken together, the results of the paper suggest that the structure of R&D expenditures by sources of funding and types of research plays an important role in the formation of effective NIS. [ABSTRACT FROM AUTHOR]

The paper presents the results of a correlation analysis between the information trends in the electronic media of Kazakhstan and indicators of the epidemiological situation of COVID-19 according to the World Health Organization (WHO). The developed method is based on topic modeling and some other methods of processing natural language texts. The method allows for calculating the correlations between media topics, moods, the results of full-text search queries, and objective WHO data. The analysis of the results shows how the attitudes of society towards the problems of COVID-19 changed from 2021–2022. Firstly, the results reflect a steady trend of decreasing interest of electronic media in the topic of the pandemic, although to an unequal extent for different thematic groups. Secondly, there has been a tendency to shift the focus of attention to more pragmatic issues, such as remote learning problems, remote work, the impact of quarantine restrictions on the economy, etc. [ABSTRACT FROM AUTHOR]

Three-dimensional (3D) seismic data and well log data were used to investigate the sandstone architecture of the Middle Jurassic deltaic reservoirs of the Zhetybay Oilfield, Mangeshrak Basin, Kazakhstan. The base-level cycles of different scales were identified and divided using well log and 3D seismic data. Five types of sedimentary boundaries were identified in the mouth bar sandstones. The boundaries divide single mouth bars. Vertically, the spatial distribution of sand bodies can be divided into superposed, spliced, and isolation modes. Laterally, contact modes can be divided into superposition, lateral, and isolation modes. We found that the base-level cycle controls the evolution of the delta front sand body architecture. In the early decline or late rise of the base-level cycle, the superimposed or spliced modes dominate the sand body. By contrast, the lateral or isolation modes dominate the sand body in the late decline or early rise of the base-level cycle. This paper proposes an architecture model of the delta front sand bodies controlled by the base-level cycle. The spatial distribution and morphological variation of deltaic sand bodies could be linked to the base-level cycles. [ABSTRACT FROM AUTHOR]

Using a structural equation model (SEM), this paper investigates the response of soil nitrogen content of five typical grasslands in the middle line countries of China's "Belt and Road" initiative to the changes of climate variables, soil pH value, and normalized vegetation index, and employs the principal component analysis method to determine the spatial variation characteristics and influencing factors of nitrogen reserves in different grasslands. Pontiac grassland (PS), Middle East grassland (MES), Kazakh grassland (KS), Kazakh forest grassland (KFS), and Kazakh semi-desert grassland (KFS) are the five grasslands in the research region (KSD). The results indicated that (1) the nitrogen reserves of the five grassland soils (0–100 cm) in the research area were 7.49 Pg, or approximately 5.7 percent of the total world nitrogen reserves. The sum of the five grasslands' 0–30 cm and 0–50 cm N reserves accounted for 36.3 percent and 63.1 percent, respectively, of the total 0–100 cm N reserves. The density of nitrogen in the soil (0–100 cm) varied significantly between grasslands, ranging from 1.47 to 3.87 kg/m2, with an average of 3.10 kg/m2. (2) PCA analysis revealed a substantial positive correlation between soil N and MAP (p < 0.01), a negative correlation between soil N and Srad (p < 0.01), and a high degree of similarity between the three grassland samples, KFS, KS, and KSD. (3) The decision tree algorithm determined that MAP had the most relative importance for changes in soil nitrogen content in PS, MES, and KFS, whereas Srad had the greatest relative importance for changes in soil nitrogen content in KS and KSD. The pH showed the least proportional impact for variations in soil N concentration in all five grasslands. (4) Different factors influence the change in soil N content across diverse grasslands. The principal positive driving factor of soil N content in KS and KSD is Srad, with loads of −0.39 and −0.44, respectively. The principal negative driving factor of soil N content in PS and MES is Map, with loads of 0.38 and 0.2, respectively. In the SEM model of soil nitrogen content in KFS, no environmental variables had a significant effect on N content, and the model's R2 value was 0.08, indicating an average fit. [ABSTRACT FROM AUTHOR]

The aim of this paper is to add to existing work on the theme of power, emotion, and organizational learning. The study was undertaken in Kazakhstan, where tensions between old and new regimes provide an environment that is rich in emotion and power/politics; and offer an opportunity to study the interplay between emotion and power during individual and organizational attempts to learn. The social unconscious is used as a conceptual frame to identify underlying dynamics that impact on organizational learning. The empirical study illustrates a social fantasy concerning the fear of mistakes and its consequences. This fantasy is sustained through blaming and punishing the people who make mistakes, and through feelings of internalised embarrassment and guilt that are enacted through interpersonal relations of shaming and being ashamed. Our contribution to knowledge arises from employing a concept (social unconscious) that has not been used to study organizational learning within a social and organizational context for organizational learning (Kazakhstan) that has not yet been studied. The practical purpose of this paper is to improve our knowledge of the social and political context of organizational learning in post-Soviet Kazakhstan through understanding unconscious dynamics that both inform and undermine attempts to learn. [ABSTRACT FROM AUTHOR]

In the current times of rapid technological progress, the development of quality education and encouragement of educated youth are extremely important. For this reason, a number of state projects and programs were developed in the education system of modern Kazakhstan. This paper is devoted to the problems of multilingual education and emergency remote learning in this country. The primary objectives were to examine the language competence and preferences of undergraduates and to explore the impact of the COVID-19 pandemic on remote language learning. Here, we present the survey and interview results of non-linguistic specialty students regarding their language preferences in various spheres, as well as the difficulties encountered during distance learning. [ABSTRACT FROM AUTHOR]

This paper presents a deep analysis of the accessory genome of an economically promising strain of Ensifer (Sinorhizobium) meliloti, L6-AK89, obtained as a result of next-generation high-throughput sequencing (MiSeq, MinIon). Strain L6-AK89 is a StrR mutant of the native strain CIAM1775, a symbiont of Medicago lupulina that adapted to a saline and arid habitat in NW Kazakhstan. CIAM1775 is an effective inoculant of M. lupulina cv. Mira (fodder type standard), cultivated on moderately acid soils in the NW agricultural region of Russia. Strain L6-AK89 makes it possible to obtain the expected high (>150%) increases in dry mass of the same plant variety in plant tests. The L6-AK89 genome has an increased proportion of sequences related to the accessory elements relative to reference strain Rm1021, 7.4% versus 4.8%. A set of 53 nod/noe/nol/nif/fdx/fix genes and 32 genes involved in stress tolerance together with 16S rRNA and recA–atpD–glnII–gyrB–dnaJ were evaluated. The high symbiotic efficiency of L6-АК89 with hop clover is most likely due to unique features of its genome, in combination with structural differences in its nod and stress-related genes, as well as unique clusters of quorum-sensing genes and osmoprotector synthesis. [ABSTRACT FROM AUTHOR]

In recent years, the warming–wetting trend in the arid region of Northwest China has attracted widespread attention. To reveal whether this phenomenon exists in the whole Pan-Central-Asia arid region, this paper adopts the latest monthly gridded dataset of the Climate Research Unit Time Series version 4.05 (CRU TS v4.05) and the multi-model ensemble data of the Coupled Model Intercomparison Project Phase 6 (CIMP6) for discussion from multiple perspectives. The results show that the Pan-Central-Asia arid region has been getting warmer and wetter in the last 80 years. Since the turn of the 21st century, there has been an apparent slowdown in the regional wetting trend despite the acceleration of precipitation increase, mainly caused by the growth in evapotranspiration potential. The interannual scale dominates the precipitation change, including significant quasi-three-year and quasi-six-year cycles. The interannual variability in precipitation is mainly affected by the change in the phases of Pacific decadal oscillation (PDO), while long-term variation dominates the temperature change, which is significantly related to the variations in the Arctic oscillation (AO). Thus, future research and predictions of regional precipitation should focus on the PDO variations, followed by the Southern Oscillation Index (SOI), whereas for research on, and predictions of, temperature, the effect of AO variations should be emphasized. Except for a few regions in Central-Eastern Mongolia and Central Kazakhstan, precipitation levels in most parts of the Pan-Central-Asia region have been increasing. The regional temperature exhibits a distribution pattern which decreases from northwest to southeast. The increase in precipitation in the Pan-Central-Asia arid region alleviates the drought in most regions, including most of Northwest China. However, the arid and semi-arid climate patterns in this region have not changed. The warming–wetting trend will significantly accelerate in medium-emissions scenarios in the next 80 years. Although the increase in precipitation may be a positive aspect of this trend, the rise in potential evapotranspiration caused by sharp warming may cause greater challenges to the regional climate and ecological environment. [ABSTRACT FROM AUTHOR]

The main objective of this paper is to examine the effect growth has on CO2 emissions in Kazakhstan, controlling for energy consumption, in the autoregressive distributed lag (ARDL) cointegration framework. We find that the environmental Kuznets curve (EKC) hypothesis seems to hold for Kazakhstan; this effect at a low level of income increases CO2 but at a high level decreases it. We also find that energy consumption increases CO2 emissions. [ABSTRACT FROM AUTHOR]