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IMPROVED RESULTS ON FINITE-TIME SYNCHRONIZATION OF SHUNTING INHIBITORY CELLULAR NEURAL NETWORKS WITH TIME-VARYING DELAYS VIA HYBRID IMPULSIVE PINNING CONTROL
No full textThis thesis explores finite-time synchronization in shunting inhibitory cellular neural networks (SICNNs) with time-varying delays. An advanced hybrid controller is introduced to achieve this, serving as a state-feedback and pinning-impulsive controller during impulsive intervals and instants, respectively. Considering the basic Lyapunov function, the paper proposes finite-time synchronization for the SICNNs-based master-slave model structured along with the hybrid controller. This proposition is validated through a series of case studies highlighting the effectiveness of the hybrid controller. Furthermore, this paper compares the settling time of finite-time synchronization using the proposed hybrid controller against the classic state-feedback and pinning-impulsive controller, demonstrating the advantages of the hybrid approach. The effectiveness of the proposed hybrid controller is exemplified through a numerical example, showcasing consensus between MATLAB software simulations and manual computations. The comparison analysis includes assessing the proposed hybrid controller against the classic state-feedback and pinning-impulsive controllers
WE DON’T THE LAMB, WE SELL THE SHOW: THE CASE STUDY OF QAZAQ GRILL’S CULTURAL COMMODIFICATION IN KAZAKHSTAN
No full textThis capstone project explores the commodification of Kazakh culture through the lens of Qazaq Grill, a case study that illuminates broader socio-economic disparities, identity transformation, and the effects of globalization within Kazakhstan's food industry. By analyzing Qazaq Grill's business insights, the research underscores the role of food as a medium for cultural commodification and the socio-economic divisions it stimulates. Using the qualitative interviews, participant observations, and social media analysis, the study reveals how Qazaq Grill serves roles of a both a provider of cultural experience and a symbol of capitalist exploitation, reflecting on the complexities of national identity in the global capitalist era. This research contributes to the discourse on food, culture, and capitalism, offering new insights into the commercialization of culture and its implications for socio-economic dynamics and national identity
Role of ZEB1 Knockout in MDA-MB-231 Triple-Negative Breast Cancer
No full textEpithelial-mesenchymal transition (EMT) is a cellular mechanism that involves the conversion of epithelial cells into mesenchymal. Epithelial cells express high levels of cell-cell adhesion molecules. They are polarized and not motile. Through the EMT process, these cells become mesenchymal and lose their polarity, cell adhesion to the extracellular matrix (ECM), and acquire migratory capacity (Heerboth et al., 2015).
It is important to study EMT mechanisms for cancer development and metastasis. Triple-negative breast cancer is a type of breast cancer that lacks the expression of estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor-2 (HER2) (Cleator et al., 2007). Breast cancer treatment typically works by blocking ER, PR, and HER2 therefore the absence of these biomarkers makes it difficult to find an effective treatment option without the risk of metastasis and disease recurrence (Maqbool et al., 2022).
In vitro and in vivo studies conducted in preclinical and clinical tumor models show that EMT contributes to drug resistance development. This resistance refers to all types of cancer treatment including chemotherapy, radiotherapy, immunotherapies, and targeted therapies. Therefore, it is crucial to identify what specifically to target to avoid therapy resistance, the risk of distant tumor migration, and cancer relapse (Rivas et al., 2021).
ZEB1 protein is currently considered a potential biomarker that could be specifically targeted to treat TNBC (Jang et al., 2015). Cells going through the EMT process have reduced levels of epithelial genes including E-cadherin, ZO-1, and occludin whereas the expression levels of mesenchymal genes are increased (N-cadherin, vimentin, and fibronectin) (Du and Shim, 2016). ZEB1 acting as a transcription factor works by repressing epithelial genes (such as E-cadherin). ZEB1 protein normally functions to allow multiple tissue differentiation. Overexpression of ZEB1 has been observed in pancreatic cancer, lung cancer, and most importantly breast cancer. Thus making it an important target for studying its effects on TNBC (Wu et al., 2020). This paper describes the role of Zeb1 in TNBC by knocking out this gene using CRISPR-Cas9.
Keywords: Zinc fnger E-box binding homeobox 1 (ZEB1), Epithelial-mesenchymal transition (EMT), Triple-negative breast cancer (TNBC), Metastasis, Drug resistanc
DESIGN AND PERFORMANCE ANALYSIS OF HIGH GAIN CASCADED BOOST CONVERTER FOR DC MICROGRID
No full textDue to their increased efficiency, stability, reduced component count, and lower cost, boost converters are growing in popularity. Additionally, a variety of electrical equipment, including huge machines that require high power and low-power devices, can be used with boost converters. Given the wide range of applications that microgrids have nowadays, this project takes into consideration the development of a cascaded boost converter design for the DC microgrid. The most crucial application is that a converter is a great way to increase voltage while using renewable energy sources. This project comprises the comparison of results extracted from simulation part and hardware implementation. Generally, this project demonstrates the steps that were used to develop the hardware design and the challenges encountered during the process
INFLUENCE OF UNSATURATED SOIL PROPERTIES ON ENERGY PILES IN DIFFERENT CLIMATIC CONDITIONS
No full textGlobal warming has been a hot topic of discussion and focus for research among scientists in recent decades because of threats to human health, biodiversity, natural disasters, and so on. One of the primary drivers of global warming is human dependence on the combustion of fossil fuels for energy generation emitting carbon dioxide and other pollutants. The are numerous technologies and new ones emerging that produce green energy without emissions. However, nowadays, green technologies are in the minority. One of the new sustainable technologies is energy piles. The energy pile exploits the thermal stability of deep ground for temperature control inside buildings. This new technology consumes significantly less energy for warming or cooling the building in comparison with conventional methods. The effectiveness of the energy pile can be influenced by external factors, namely initial ground temperature, climatic conditions, heat capacities, and thermal conductivities of the energy pile and soil. This present study examines the influence of climatic conditions and unsaturated soil properties on the efficiency of energy piles. A numerical analysis has been conducted using Sigma/W and Temp/W modules of GeoStudio software for the simulation of energy piles in various conditions. The model was built in axisymmetric 2D. The analysis involved testing of the energy pile in three soil materials in saturated and unsaturated states in cold, moderate, and hot climates. The relationship between moisture content and soil suction was represented using the Soil-Water Characteristic Curve (SWCC) and integrated into a numerical model for soil in unsaturated conditions. In unsaturated soils, the unfrozen water content was determined using the Soil Freezing Characteristic Curve (SFCC). It was found that temperatures in saturated soils are higher than in unsaturated in upper soil layers in moderate and hot climates due to higher water content. In cold climates, the temperature difference was negligible. From a long-term perspective, the effectiveness of the energy pile might diminish because of the reduction of the temperature difference between the energy pile and adjacent soil
NUMERICAL STUDY ON CYCLIC SEISMIC RESPONSES OF UNREINFORCED MASONRY WALLS RETROFITTED WITH LOW-STRENGTH ENGINEERED CEMENTITIOUS COMPOSITES
No full textMost of the faults of Tien Shan Mountain are situated in Central Asia. Even the small faults of the mountain may cause risk to the nearby cities, such as Almaty, Kazakhstan, with a population of about 1.8 million people. Over half of the buildings in Almaty are unreinforced masonry buildings, followed by reinforced masonry, confined masonry, and reinforced concrete, and a minority of structures are from wood and steel. Unreinforced masonry buildings may demonstrate brittle behavior under seismic activities. Earthquakes such as those happened in the past of Almaty can damage most of the city and its inhabitants. The catastrophic destruction action of the earthquake can be mitigated by the construction of high strength, and ductile buildings, which can withstand large deformations with minor damages. Thus, to improve the response of existing unreinforced masonry structure, different studies propose the use a retrofitting, which can increase the deformation capacity and ductility of the unreinforced masonry walls. This thesis focuses on parametric study on cyclic responses of unreinforced masonry walls retrofitted with low-strength Engineered Cementitious Composite (ECC). The new retrofitting material, Engineered Cementitious Composite (ECC) with a high tensile strain hardening rate, was retrofitted to the unreinforced masonry wall in this study. Previous experimental studies have shown that the normal strength ECC can increase the strength of URM but has little effect on the deformation capacity due to the incompatibility of the masonry and composite. Moreover, a numerical study by Sailauova (2022) has shown that the low-strength ECC can increase the deformation capacity under monotonic loading because of stiffness compatibility between the masonry wall and composite. Considering the prior studies, this study addresses to the cyclic response of the masonry wall since the earthquake has a cyclic nature. The application of low-strength ECC approved the hypothesis that it can reach more deformation rather than normal-strength ECC, since it matches the stiffness of the masonry wall resulting in more ductile behavior.
This study aims to investigate the cyclic response of unreinforced masonry walls subjected to cyclic seismic loadings. This thesis presents a numerical study on in-plane cyclic behaviors of the unreinforced masonry wall retrofitted with the low-strength ECC. The numerical study was conducted on nonlinear two-dimensional models in ABAQUS software using a simplified micro-modeling approach for the masonry wall and the concrete damage plasticity for the ECC. The dynamic analysis using explicit analysis technique was adopted due to the non-linear behaviors of the masonry wall and ECC. The model was verified from an existing experimental study. The study parameters include the strength of ECC, wall aspect ratios, and vertical pressures, which represent typical wall geometry and gravity loading conditions of unreinforced masonry buildings in Almaty. This study concentrates on 0.5, 0.75, and 1.0 wall aspect ratios and walls subjected to 0.43, 0.60, and 0.78 MPa vertical pressures, or in axial force ratio 0.10, 0.15 and 0.19, respectively. Moreover, the proposed material, Engineered Cementitious Composite (ECC), with different compressive strengths (10, 20, 30, 40, and 50 MPa) was evaluated. The behavior of the retrofitted wall under the cyclic loading was compared to that under the pushover analysis.
The numerical study results concluded that with the increase of ECC compressive strength on the retrofitted masonry wall, deformation capacity and ductility decrease, while wall strength and stiffness increases simultaneously. However, as the ECC becomes stronger, energy dissipation decreases. The effect of ECC for different wall aspect ratios on wall strength decreases with the increasing aspect ratio, but increases with the increase of vertical pressure. This is because the friction between the brick units and mortar increases. Regardless of the aspect ratio and vertical pressure, low strength ECC with compressive strength 10 and 20 MPa improve the lateral deformation capacity of the masonry wall. Moreover, the pushover analysis shows a slower strength reduction than the cyclic loading analysis due to the cumulative damage from the cyclic loading
MACHINE LEARNING TECHNIQUES APPLIED TO ROBUST OPTIMAL CONTROL PROBLEMS
No full textThis project aims to solve the discrete time stochastic optimal control problem of evaluation of Average Value-at-Risk (AVaR) function. AVaR is an important tool in market risk management used to measure the risk. In the paper it was designed as a sequential decision model and solved by formulating an optimal control problem of minimizing the value. Brute force and Approximate Dynamic Programming (ADP) techniques were used for exact and approximate solutions respectively. Golden section search was used to solve the problem completely. The numerical experiments conducted at the end showed the effectiveness of the algorithm in evaluating the AVaR
CLASSIFICATION OF BABY CRIES INTO DISTINCT CATEGORIES USING CONVOLUTIONAL NEURAL NETWORKS(CNN) WITH SOUND AND SPECTROGRAM ANALYSIS
No full textThe act of a baby crying is a complex form of communication that reflects various
physical, medical, and emotional states. Understanding the nuances within baby
cries is essential, as it provides valuable insights into the baby’s needs and can
assist in the early detection of developmental disorders and medical conditions.
Machine Learning (ML) and Deep Learning (DL) techniques, specifically
Convolutional Neural Networks (CNNs), coupled with sound processing and data
augmentation, play a pivotal role in this endeavor. This research explores
methods encompassing data preprocessing, feature extraction, postprocessing,
and classification. A primary focus is acoustic analysis and CNN for automatic
feature extraction
PYTHON CODE GENERATION USING DEEP LEARNING
No full textIn this project, it is proposed to develop a sequence-to-sequence model for Python code generation using deep learning. The aim of this project is to investigate the feasibility of using deep learning to generate functional Python code automatically. It discusses the project’s objectives, methodology, initial findings, and ethical considerations. This report references relevant literature. The significance of this project lies in its attempt to offer a model with a specific task and higher efficiency than general-purpose models
FACTORS INFLUENCING PARENTAL PRIMARY SCHOOL CHOICE IN ASTANA
No full textThe primary purpose of this study is to explore how parents with different incomes, educational backgrounds, and occupations navigate the process of primary school choice and the factors influencing it in the context of Astana, Kazakhstan. Additionally, this research attempts to identify the opportunities and challenges parents experience when deciding on the primary school selection process. The qualitative research study with semi-structured interviews aims to address the following research question and two sub-questions to achieve the study’s objectives: How do parents in Astana navigate the process of primary school choice? 1) What factors influence parental choice of primary school in Astana? 2) What opportunities and challenges do parents experience when selecting primary schools for their children in Astana? Three parents with contrasting socioeconomic and cultural backgrounds whose children studied at three different types of schools in Astana constituted multiple cases of the study. Within these cases, three main common themes emerged: parental involvement, navigating away from mainstream education, and embracing an international curriculum. This study contributes to social inequality research by examining parents’ cultural backgrounds and the interplay of various types of capital (Bourdieu, 1986) in parental decision-making in school choice. The study manifested that a working-class parent was dependent on what public education offered. Upper-middle-class parents greatly impacted their children’s school choice because of their significant cultural capital, making their navigation in the school choice process more like a strategy than a dependence