“BILIM SOURCE": WEB-BASED K-12 DIGITAL RESOURCE LIBRARY

Kazakhstan has a substantial portion of its population composed of children, with approximately 31% of the populace under the age of 17 (Eurasia Expert, 2023). There is a consistent annual rise in its birth rate, which emphasizes the need to promote the focus on the education system as a crucial factor in the country's development. Currently, the educational sector faces challenges, and one of these issues is the quality of teacher training (Abishev, 2020). To address this concern, several governmental programs have been initiated. Notably, the Nazarbayev Intellectual Schools educational project was established, introducing a new teaching format. Teachers selected to work in these schools enhance their knowledge through continuous professional development such as training sessions and workshops. As a result, 90% of NIS students receive scholarships at further educational institutions. Many of them participate in international competitions and apply to foreign universities (Eldesov, 2022). However, the NIS program does not fully resolve the issue of quality education for Kazakhstani children, as only 2% of children in Kazakhstan attend NIS schools. These schools are not available in rural areas, with only 21 schools across the country, leading to limited enrollment (Wikipedia contributors, 2023). Additionally, the budget allocated to them faces criticism, as there is a considerable difference compared to the average school budget - in 2020-2021, the NIS school got 23 times more financial budget than the average school (Wikipedia contributors, 2023). Digitalization of resources, including platforms like BILIM Land, Online Mektep, and others, helps address limited access to educational materials. However, despite numerous online resources for children, there is a lack of services designed for teachers. As part of the government program "Digital Kazakhstan," digitalization is expected to continue assisting educators in their jobs. To bridge this gap, we propose the "Bilim Source" project, an online portal facilitating collaboration and sharing of high-quality educational materials among teachers. This platform aims to connect educators with various teaching methodologies gained through special training, workshops, or experience, enabling them to share their materials with others

Blended learning adoption in Kazakhstan

This study investigates the impact of secondary school teachers’ attitudes towards technology on the adoption of blended learning in Northern Kazakhstan, guided by the main research question: “What are the attitudes of secondary school teachers in Kazakhstan towards the use of technology in education?”. I used a qualitative research design, and it was informed by the Technology Acceptance Model and Social Cognitive Theory. I conducted in-depth interviews with ten teachers, selected through stratified sampling from various subjects and experience levels. The thematic analysis revealed a clear connection between teachers’ positive attitudes towards technology and the adoption of blended learning. The participants recognized technology’s potential to enhance student engagement in education but highlighted challenges such as technical difficulties and unequal access to technology. Moreover, the resistance towards technology integration demonstrated by some participants was rooted in a preference for traditional methods and concerns over technology’s impact and further compounded by a significant gap in professional development. The combination resulted in the hesitancy in adopting blended learning approaches. The findings also suggest that participants who view technology positively are more likely to support and adopt blended learning approaches. This indicates that positive attitudes towards technology can significantly enhance the integration of blended learning methods. These attitudes were influenced by factors such as prior technology experiences, training, and peer support. Overall, the findings call for the urgent need for targeted professional development and infrastructure improvements to address these barriers and enhance digital literacy among teachers, facilitating more effective blended learning environments

EXPLORING DATA DISTRIBUTION AND VALUE FUNCTION APPROXIMATION IMPACTS IN OFFLINE REINFORCEMENT LEARNING(RL): FROM GRIDWORLD ENVIRONMENTS

In the emerging landscape of off-policy reinforcement learning (RL), challenges arise due to the significant costs and risks tied to data collection. To address these issues, there is an alternative path for transitioning RL from off-policy to offline, which is known for its fixed data collection practices. This stands in contrast to online algorithms, which are sensitive to changes in data during the learning phase. However, the inherent challenge of offline RL lies in its limited interaction with the environment, resulting in inadequate data coverage. Hence, we underscore the convenient application of offline RL, 1) starting from the collection and preprocessing of a static dataset from online RL interactions, 2) followed by the training of offline RL models, and 3) culminating with testing in the same environment as the off-policy RL algorithm. Specifically, the dataset collection involves the utilization of a uniform dataset gathered systematically via non-arbitrary action selection, covering all possible states of the environment. Furthermore, we incorporate Q-values into the static dataset, representing the action distribution across the state-action space. This allows the offline RL model to directly update weights by comparing learned model Q-values with collected Q-values. Utilizing the proposed approach, the Offline RL model employing a Multi-Layer Perceptron (MLP) achieves a testing accuracy that falls within 1% of the results obtained by the off-policy RL agent. Additionally, we provide a practical guide with datasets, offering valuable tutorials on the application of Offline RL in a Gridworld-based environment

STUDYING EFFECTS OF ZEB1 KO IN TRIPLE-NEGATIVE BREAST CANCER CELLS MDA-MB-231

One of the main problems in cancer therapy is the resistance of cancer cells to various anticancer drugs. Targeted anticancer drugs categorized on their effect to cancer hallmarks. According to the principles of functioning, anticancer drugs are divided into: growth factor inhibitors, pro-apoptotic drugs, immune checkpoint inhibitors, telomerase inhibitors, inhibitors of VEGF signaling, PARP inhibitors, metastasis suppressors, inhibitors of glycolysis and aerobic metabolism, inactivators of drug efflux and detoxication machinery etc (Dembic, 2020). The main mechanisms of resistance to them are: increased DNA repair, increased efflux of drugs, enhanced metabolism of drugs, growth factor compensation, genetic and epigenetic factors modification (Holohan et al., 2013; Kachalaki et al., 2016; Mansoori et al., 2017). One of these mechanisms which helps to avoid drugs effect is epithelial-mesenchymal transition (EMT) (Hashemi et al., 2022). EMT can give resistance to such drugs as doxorubicin via AMPK overexpression (Andugulapati et al., 2022), cisplatin via 14,15-epoxyeicosatrienoic acid (Luo et al., 2018), tamoxifen via Cx43 loss (Wu et al., 2021) etc. Also EMT is activated for metastasis of cancer cells and as a result, unfavorable prognosis in treatment. That’s why EMT has particular importance in treating of triple-negative breast cancer (TNBC) (Grasset et al., 2022) the most aggressive type of breast cancer. TNBC is characterized by high heterogeneity and the absence of major target receptors: estrogen receptor (ER), progesterone receptor (PR) and human epidermal growth factor receptor 2 (HER2). Many research groups reported about mesenchymal gene expression in TNBC, suggesting EMT (Jang et al., 2015). One of the regulators of EMT are Zinc finger E-Box binding homeobox 1 (ZEB1), proteins that encoded by ZEB1 gene, located on chromosome 10p11.2 (Williams et al., 1992). Main function of this transcription factor is linked to the promotor region of the epithelial cell marker protein E-cadherin, causing the cells to lose their epithelial properties (Larsen et al., 2016). The importance of ZEB1 in TNBC therapy is due to its ability to promote chemoresistance through various mechanisms such as activated ataxia-telangiectasia mutated (ATM) kinase expression by forming a ZEB1/p300/PCAF complex (X. Zhang et al., 2018) or by repression of E-cadherin in AR-negative docetaxel-resistant sublines (Hanrahan et al., 2017). This work shows the effect of a knockout of the gene responsible for the synthesis of ZEB1 using the CRISPR-CAS-9 technology

NUMERICAL STUDY ON PUNCHING SHEAR RESPONSES OF FLAT PLATE STRUCTURES STRENGTHENED WITH ENGINEERED CEMENTITIOUS COMPOSITES

Flat plates are one of the conventional structural systems found in the construction sector due to their several advantages including simplicity, lowered expenses, and architectural mobility. However, the flat plate systems are vulnerable to punching shear failures which happen suddenly and catastrophically. Thus, it is crucial to develop strengthening techniques to augment the punching shear resistance of such structures. The strengthening techniques include shear reinforcement, drop panels, and column capital. One of the modern techniques for retrofitting flat plates is the use of engineered cementitious composites (ECC), applied as thin layers on both sides of slab surfaces. There are only limited studies that examined the response of flat plates with ECC retrofitting that improved the punching shear resistance. Most previous research has employed experimental methods to assess the impact of ECC on the punching shear capacity of the slab considering limited design parameters due to economic constraints. Furthermore, some inconsistent results were reported from two separate studies. In one study, the tension side retrofitting with ECC showed a noticeable contribution to punching shear resistance but in another, it was insignificant. Therefore, it is necessary to investigate the behavior of flat plates subjected to concentric vertical loading and examine if the ECC is valid as a retrofitting technique through numerical simulations considering various design parameters. This thesis evaluates the impact of the ECC strengthening technique on the punching shear response of flat plate structures. For that purpose, analytical models of the interior slab-column assemblage were developed in finite element software ABAQUS. First, the model was calibrated from test results in the literature. The numerical simulations were carried out on flat plate models subjected to gravity loading to investigate the global response of the flat plate and its failure mechanism. The contributions of concrete and ECC were determined to examine the effectiveness of ECC strengthening. Moreover, the cracking pattern was visualized by presenting the contour plots that displayed the flat plate model’s maximum principal equivalent plastic strain. In this thesis, the main study parameter was the placement of the retrofitting: on the tension, compression, and both slab surfaces. The other study parameters include compressive strength, thickness, and width of the ECC. The numerical study results showed that the punching shear behavior of flat plates was improved with the application of the ECC retrofitting technique. The addition of a thin layer of ECC on the compression side of the slab provided a direct shear strength contribution near the column face, therefore no improvement was observed as the width of the ECC increased. Moreover, the deformation capacity of the slab improved with low-strength ECC retrofitting of the slab on the compression side, whereas normal-strength ECC showed a more brittle response. The addition of a thin layer of ECC on the tension side of the slab has no direct shear force resistance contribution. However, it can lower the neutral axis and enlarge the concrete compression zone, increasing the concrete contribution to the punching shear strength. This increase is only effective if the ECC width is large enough to cover the punching cracking region. The double-sided retrofitting can significantly increase the strength and deformation capacity of the flat plate, resulting in a better performance under punching load. However, it must be noted that the strength does not result from the superposition of strengths of one-sided retrofitting since peak strengths occur at different displacements for ECC retrofitting on the tension and compression sides. Overall, the parametric results revealed that the higher the compressive strength and thickness of the ECC, the greater the punching shear response of the slab. Accordingly, the compressive strength of 20 MPa, thickness of 30 mm, and width of full slab length applied on both sides of the slab were determined to be optimal parameters for improving both strength and deformation capacity

SIMULATOR FOR TIME-SLOTTED LORA NETWORKS

A new simulator for evaluating Time-Slotted (TS) LoRa networks is presented. Traditional testing limitations, due to node scarcity, are overcome by enabling virtual analysis under diverse conditions. The simulator features optimized code, removes unnecessary phases, and implements a dynamic retransmission policy with Reinforcement Learning for improved performance. This user-configurable tool empowers researchers to explore TS-LoRa behavior and optimize this emerging technology

QAZAQ SIGN LANGUAGE DICTIONARY

Our project aims to deliver a comprehensive digital platform focused on learning and using sign language to revolutionize access for the Deaf community. This platform ensures inclusiveness and improved communication by integrating multiple resources to address different learning styles and needs. The main feature of our platform is the Sign Language Dictionary, which includes several categories. These categories cover various aspects of daily life such as greetings, emotions, nutrition, activities and more. Each category is a collection of carefully selected sign language videos, each containing a particular hand or word associated with that category. These videos are designed to be informative, engaging, and accessible, allowing users to learn sign language and learn at their own pace. The Sign Language Dictionary also has a search function that allows users to search for specific words or specific gestures they want to see or find quickly. This feature enhances the usability and efficiency of the platform by allowing users to easily navigate through a large database of sign language content. In addition, our platform includes user-generated content through licensed downloads. This feature allows qualified professionals, such as certified sign language instructors to upload videos to the platform. These videos go through a process of verification and quality, enhance the content of the platform, and enhance the user’s learning experience. In addition to the dictionary and custom content, our platform offers a reverse dictionary feature. Our platform allows you to record hand gestures and use them to search for words in a large database of words. We achieved this using a model through which we conducted video clips and output them for all possible predictions and saved them in the database

TIME SERIES FORECASTING METHODS FOR SOCIO-ECONOMIC INDICATORS: A CASE STUDY OF KAZAKHSTAN

This study compares traditional statistical methods (ARIMA, ETS) with LSTM, a deep learning approach, to forecast key socio-economic indicators (GDP, Population Growth, Price Index, Income per Capita, Housing prices) in Kazakhstan. Using historical data from the Bureau of National Statistics, the models are trained and evaluated using metrics MAE, MAPE and RMSPE. The research aims to understand the strengths and limitations of each method in the context of Kazakhstan's socio-economic data, providing insights for future forecasting in the region

NEURAL NETWORK BASED FILTER MODELING AND OPTIMIZATION FOR 5G AND BEYOND APPLICATIONS

Designing high-performance microwave and millimeter-wave filters is difficult because small changes in geometric dimensions and electrical sizes can significantly affect the filter’s characteristic. Typically, in filter design, the initial values of design variables are optimized to achieve the desired performance. In the field of high-frequency RF device modeling, the use of machine learning (ML) through artificial neural networks (ANN) has gained popularity in recent years. Unlike other RF modeling techniques, ANN-based models require training with sufficient datasets to achieve the desired accuracy level. The input data could be the device’s dimensions, while the output could be the S-parameters. Once trained, the ANN-based model can provide EM-level accuracy and equivalent-circuit-level speed. Additionally, it is highly scalable, allowing for the introduction of more input parameters to make the model more versatile and complex. Therefore, the ANN-based model is an excellent option for high-frequency RF modeling compared to other techniques. The main objective of this research project is to develop an AAN that can be used in design of RF Filters

СНИЖЕНИЕ ЯВКИ НА ПРЕЗИДЕНТСКИХ ВЫБОРАХ: КАЧЕСТВЕННЫЙ АНАЛИЗ СУБНАЦИОНАЛЬНЫХ РАЗЛИЧИЙ В УЧАСТИИ ИЗБИРАТЕЛЕЙ В НИГЕРИИ

Voter turnout has been declining globally. This raises concerns for democracies, especially unconsolidated democracies as it speaks to the erosion of democratic institutions within the society. Presidential democracies place great power in the hands of the citizens, in a bid to ensure that the choice of the people is duly represented. However, turnout decline signals that there are democratic challenges faced within the country, which raises an issue as turnout is essential for representative politics. This study seeks to understand the factors that lead to voter turnout decline in presidential elections. By focusing on the role of the electoral commission, poverty and lack of trust in the electoral process, it makes the argument that turnout decline in presidential elections do not arise from simple disinterest of the electorates in politics but rather an interplay of the aforementioned factors. This study identifies three major findings. Firstly, the ineffectiveness of the electoral commission inhibits voter turnout. Given the important role the electoral commission plays in the elections, failure to carry out their essential duties effectively serves as a barrier to voter turnout. Secondly, this study shows that poverty inhibits voter turnout, especially in rural communities, where the citizens have experienced issues with the electoral commission and would rather prioritize their personal gains and interest over civic engagement. Thirdly, the irregularities perceived by the electorates due to the ineffectiveness of the electoral commission, erodes the trust of the citizens in the electoral process, as they have doubts about the credibility and transparency of the elections. These findings emerge from series of interviews with political activists, party members, civil society members and the Independent National Electoral Commission (INEC) officials. I carry out a comparative analysis of the selected cases utilizing a most similar systems design, where I identified these cases based on shared similarities and variations in the dependent variable at the subnational level. This study develops a theoretical framework that accounts for turnout decline in presidential elections, contributing to a deeper understanding of the challenges and factors that impede voter turnout in presidential elections