RNA SPLICING IN NEURON PHYSIOLOGY AND NEURODEGENERATIVE DISEASES

Gene expression is regulated at multiple levels, including transcription, RNA editing, pre-mRNA splicing, mRNA export, translation, and posttranslational modifications. Alternative splicing is a process by which exons can be included or excluded, giving rise to multiple mRNA isoforms from the same transcript. Alternative splicing is an important mechanism in developmental, tissue- and cell-specific control of gene expression, and it is key for expanding proteomic diversity and complexity from a limited number of genes. Moreover, more than 95% of multiexon genes undergo alternative splicing in humans, and about half of all disease-causing point mutations in humans affect pre-mRNA splicing, including neurological disorders and cancer. The central nervous system comprises the tissues and cells with the highest rate of alternative splicing in the body, and RNA-binding proteins play a major functional role in neurons. However, the regulatory mechanisms of splicing are still poorly understood. This dissertation specifically aims to advance the understanding of regulatory mechanism of pre-mRNA splicing. To this end, we collaboratively performed two projects. In the first project, we investigated how NOVA, a neuron-specific splicing factor, regulates nerve cell-specific alternative splicing of Z+ Agrin — a molecule that is the master architect of nerve-muscle synapses at the neuromuscular junction (NMJ). We cloned the Ciona ortholog of NOVA, which is present as a single copy gene in tunicates, and that of Agrin, and dissected the regulatory mechanism of alternative splicing of Z+ Agrin by Nova. Moreover, we characterized their function and expression pattern during larval development, which we will discuss in detail in Chapter 2 of this dissertation. The second project was a case study where we investigated how mutations in the SLC25A10 gene cause epileptic encephalopathy by disrupting pre-mRNA splicing. SLC25A10 codes for a solute carrier protein and is a part of complex I in mitochondria. The patient inherited 3 mutations: 1 from the mother and 2 from the father. The maternal-derived mutation introduces a stop codon in exon 3. Mutations from the paternal allele are located in exon 9 and intron 10. Although the exonic mutation is a synonymous mutation, the patient had very low levels of SLC25A10 mRNA and lacked protein at detectable levels. Using minigene splicing assay we investigated the molecular mechanism underlying disease pathology in the patient. In Chapter 3 of this dissertation, we will discuss how paternal-derived mutations lead to aberrant splicing

GR-136 - Students Certification Management (SCM): Hyperledger Fabric-Based Digital Repository

Abstract: The higher education sector has been heavily impacted financially by the economic downturn caused by the pandemic that has resulted a decline in student enrollments. Finding cost-effective novel technology for storing and sharing student\u27s credentials among academic institutions and potential employers is a demand. Within the current conventional approach, ensuring authentication of a candidate’s credentials is costly and time-consuming which gives burdens to thousands of prospective students and potential employees. As a result, candidates fail to secure opportunities for either delay or non-submission of credentials all over the world. Blockchain technology has the potential for students\u27 control over their credentials; degrees and transcripts for instance that will allow seamless streamlining of the sharing of educational records during changing and transferring schools, higher education, or even employment processes when need to show credentials. To implement the novel idea, we conduct a preliminary survey, study the existing applications, and investigate the feasibility of a Blockchain-based system to exploit the potential. Based on our findings, we propose a Students Certification Management System (SCM) by adopting Emerging Hyperledger Fabric that will offer a universal, tamper-evident, immutable, and secure educational certificate storing and sharing network. Our primary aim is to construct the proposed system into an educational certificate repository network using consortium blockchain for different entities including, (i) educational institutes to manage the network (ii) students and authorized third parties to access verifiable digital certificates and transcripts. Initially, we introduce an advanced architectural framework of the proposed system that has the potential in improving data flow between academic institutions, students, and potential employers. For ensuring transparency, each attempt in storing, sharing, and accessing credentials by the authenticated users within the proposed network shall be stored in the ledger which is secure and non-corruptible. Our future direction is to implement the architectural framework into an educational certification repository network within a private blockchain network.Department: Software Engineering and Game Design and DevelopmentSupervisor: Dr. Hossain Shahriar Dr. Maria ValeroTopics: Software Engineerin

GR-342 Integration of Blockchain in Computer Networking: Overview, Applications, and Future Perspectives for Software-defined Networking (SDN), Network Security and Protocols

The rapid advancement and increasing complexity of computer networks have created a need for robust, secure, and scalable solutions to manage and protect network resources. Blockchain, an emerging distributed ledger technology, offers enhanced security, transparency, and privacy preservation, making it a promising solution for addressing networking challenges. This paper presents a comprehensive survey of blockchain integration in computer networking, focusing on its potential applications, benefits, and future perspectives in Software-defined Networking (SDN), network security, and networking protocols. We identify that blockchain\u27s tamper-proof nature could significantly improve network security by mitigating risks associated with centralized control and single points of failure. The integration of blockchain in computer networking has the potential to increase trust and transparency among network participants, as it allows for secure, verifiable, and auditable transactions and communication. Blockchain also can streamline the management of Software-defined Networking (SDN) by enabling decentralized and automated network control, resource allocation, and orchestration. We also find that utilizing blockchain can address network challenges, such as mitigating DDoS attacks, enhancing intrusion detection and prevention, and securing routing protocols. However, we identify potential limitations of blockchain integration in computer networking, such as scalability challenges arising from the growing size of the distributed ledger and increasing network traffic. We emphasize the need for further research in optimizing consensus mechanisms, enhancing scalability and privacy preservation techniques interoperability, and facilitating standardization of networking protocols and practices

GC-250 Object Detection and Tracking: Deep Learning-based Framework with Euclidean Distance, IoU, and Hungarian Algorithm

Object tracking is an important basis for the logistics industry where multiple packages are moved on conveyor belts at a time. Accurate datasets and efficient benchmarks are a few of the several problems for both object detection and tracking for training the deep learning-based framework. Preparing 100% accurate correspondence between objects throughout different frames by assigning human annotated unique_attributes to train framework efficiently over ground truth data. In this research, we develop an (i) OpenCV-based framework that allows the user to assign human-annotated identification between objects and (ii) a novel application for object detection and tracking. We utilize the assigned attributes to train the deep learning model accurately and adopt various evaluation parameters including euclidean distance, intersection over union (IoU), and scale-invariant feature transform (SIFT) to measure the accuracy of an object correspondence or tracking. We also adopt the Hungarian algorithm to increase the efficiency in determining correspondences between objects and apply our framework to human-annotated ground truth datasets comprising ~1,000 images and the same amount of JSON files. Our demonstration achieved 94.53 % accuracy in object detection, finding correspondence, and object tracking. In future studies, we are aiming to apply a neural network to draw a comparison of identified accuracy

GR-53 An Investigation on Non-Invasive Brain-Computer Interfaces: Emotiv Epoc+ Neuroheadset and Its Effectiveness

Neurotechnology describes as one of the focal points of today’s research around the domain of Brain-Computer Interfaces (BCI). The primary attempts of BCI research are to decoding human speech from brain signals and controlling neuro-psychological patterns that would benefit people suffering from neurological disorders. In this study, we illustrate the progress of BCI research and present scores of unveiled contemporary approaches. First, we explore a decoding natural speech approach that is designed to decode human speech directly from the human brain onto a digital screen introduced by Facebook Reality Lab and University of California San Francisco. Then, we study a recently presented visionary project to control the human brain using Brain-Machine Interfaces (BMI) approach. We also investigate well-known electroencephalography (EEG) based Emotiv Epoc+ Neuroheadset and present experimental studies to identify six emotional parameters using brain signals by experimenting the neuroheadset among three human subjects.Advisors(s): Prof. Maria Valero Prof. Hossain ShahriarTopic(s): Other (explain in the comments section

Factors Affecting Selection of Equity Shares: The Case of Retail Investors in Bangladesh

This study attempts to determine principal factors considered important by retail investors in choosing an equity share traded in Dhaka Stock Exchange (DSE) and to examine whether there are any significant differences in these factors across demographic characteristics of respondents. To achieve the objectives, this study collected a data from a sample of 351 retail investors in the city of Khulna in Bangladesh through convenience sampling and analyzed it using factor analysis, independent sample t-test and a number of ANOVA. The findings of the study reveal that the most important principal factors influencing retail investors are company specific attributes/reputation, net asset value, and accounting information. The next five principal factors ranked fourth, fifth, sixth, seventh, and eighth were trading opportunity, publicity, ownership structure, influence of people, and personal financial needs respectively. Findings also suggest that extent of importance given to each of the factors excluding ownership structure significantly differs with at least one demographic characteristics of sample respondents like gender, age, occupation, income, education, and experience. Keywords: Equity share selection factors, Retail investors, Demographic characteristics, Dhaka Stock Exchange (DSE), Banglades

Students Certification Management (SCM): Hyperledger Fabric-Based Digital Repository

The higher education sector has been heavily impacted financially by the economic downturn caused by the pandemic that has resulted a decline in student enrollments. Finding cost-effective novel technology for storing and sharing student\u27s credentials among academic institutions and potential employers is a demand. Within the current conventional approach, ensuring authentication of a candidate’s credentials is costly and time-consuming which gives burdens to thousands of prospective students and potential employees. As a result, candidates fail to secure opportunities for either delay or non-submission of credentials all over the world. Blockchain technology has the potential for students\u27 control over their credentials; degrees and transcripts for instance that will allow seamless streamlining of the sharing of educational records during changing and transferring schools, higher education, or even employment processes when need to show credentials. To implement the novel idea, we conduct a preliminary survey, study the existing applications, and investigate the feasibility of a Blockchain-based system to exploit the potential. Based on our findings, we propose a Students Certification Management System (SCM) by adopting Emerging Hyperledger Fabric that will offer a universal, tamper-evident, immutable, and secure educational certificate storing and sharing network. Our primary aim is to construct the proposed system into an educational certificate repository network using consortium blockchain for different entities including, (i) educational institutes to manage the network (ii) students and authorized third parties to access verifiable digital certificates and transcripts. Initially, we introduce an advanced architectural framework of the proposed system that has the potential in improving data flow between academic institutions, students, and potential employers. For ensuring transparency, each attempt in storing, sharing, and accessing credentials by the authenticated users within the proposed network shall be stored in the ledger which is secure and non-corruptible. Our future direction is to implement the architectural framework into an educational certification repository network within a private blockchain network

Machine Learning-Oriented Predictive Maintenance (PdM) Framework for Autonomous Vehicles (AVs): Adopting Blockchain for PdM Solution

Autonomous Vehicles (AVs) refers to smart, connected and multimedia cars with technological megatrends of the fourth industrial revolution (Industry 4.0) and have gained huge strive in today\u27s world. AVs adopt automated driving systems (ADS) technique that permits the vehicle to manage and control driving points without human drivers by utilizing advanced equipment including a combination of sensors, controllers, onboard computers, actuators, algorithms, and advanced software embedded in the different parts of the vehicle. These advanced sensors provide unique inputs to the ADS to generate a path from point A to point B. Ensuring the safety of sensors by limiting maintenance costs has become a major challenge for AVs community. The predictive maintenance (PdM) approach has the potential to address the AVs failures. In this paper, we propose a novel, conceptual, and high-level domain-specific software architecture for the machine learning-oriented predictive maintenance (PdM) framework that shall enable predicting early malfunctioning, quality, safety, and performance deficiencies of AVs. The novel framework collects the data from sensors and major equipment and stores the collected data in immutable and transparent blockchain technology. Collected data shall be validated, extracted, and classified by adopting machine learning (ML) techniques. ML module shall predict the possible malfunctioning of the sensors while providing potential solutions from the stored data in the blockchain network. In this paper, our effort was to conduct a feasibility study, elicit and specify all the requirements for the proposed framework. In future research, we aim to extend the conceptual work and implement a prototype in real-world scenarios

GR-100 - Non-Invasive Monitoring of Human Hygiene using Vibration Sensor and Classifiers

Abstract: Personal hygiene is how people take care of their bodies. Maintaining hygiene practice reduces the spread of illness and the risk of medical conditions. With the current pandemic situation, practices like washing hands and taking regular showers have taken major importance among people, especially for senior populations that live alone at home. Having an understanding of the human hygiene habits of our seniors is fundamental to monitoring health conditions.This research work presents the concept and idea of a noninvasive monitoring system for human hygiene using only vibration sensors. The approach is based on a geophone, a digitizer, and a cost-efficient computer board (raspberry pi). We capture the vibration of the water flow while people perform activities in the bathroom (open faucet, flush toilets) and kitchen (open kitchen sink). Results show that our approach can distinguish from these different activities with an accuracy higher than 90%. With this approach, we hope to start a new tendency of monitoring people activities without using cameras or other privacy-invasive methods.Department: Information TechnologySupervisor: Dr. Maria ValeroTopics: IoT/Cloud/Networkin

Addressing the Loopholes of Female Education: A Study on the SSC and HSC Level Students of Rural Bangladesh

Holistic development of a country requires diligent participation from every section of people regardless of race, class or gender. In this respect, female education is considered as a dynamic ladder for human resource development in the truest sense. This study aimed at revealing the loopholes of female education among the secondary and higher secondary level female students in rural Bangladesh. This qualitative research followed a semi-structured way of interviewing the participants who were basically the female students of SSC and HSC level and some other persons associated to their education. The participants were primarily chosen from Shariatpur district and Madaripur district of central Bangladesh as the representatives of rural areas. The findings of the research revealed a number of barriers faced by female students including familial inclination to female education, lack of social awareness, financial insufficiency, misinterpretation of religious values, sometimes the psychological ignorance of the students themselves as well. This research also shed some light on the reduction of the obstacles. It recommended some crucial moves like the initiation of educational workers, enough financial assistance, ensuring moral and religious support etc. to smoothen the way to female enrichment through education. Keywords: Secondary and Higher Secondary Level of Education, Female Education, Dropout, Rural Banglades