Science and Technology - Bachelor's theses. Kuni 2024

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    3D Face Reconstruction from a Single 2D Image
    (2021) Salimli, Mehin
    3D face reconstruction is the process of creating a 3D representation of a real human face. 3D face models have several applications like face recognition, 3D games, human-machine interaction, and plastic surgery simulations. Recently there has been a lot of research on deep learning methods for 3D face reconstruction from 2D face images. In this thesis, three deep learning-based methods for 3d reconstruction from a single image are reviewed. A new texturing method for 3D face models that uses the input photo as a UV texture image is proposed. Image warping is used to modify the input photo for this purpose. Warping is achieved using facial landmark detection and triangle meshes. A survey is conducted to assess the three face reconstruction methods and the proposed texturing method
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    5S rDNA copy number in WGS data
    (2022) Naghiyev, Farid
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    The Absence of GacA/S signal transduction system af-fects the frequency of base substitution and frameshift mutations in Pseudomonas putida KT2400
    (2020) Phan, Huynh Ngoc Chau; Kivisaar, Maia; Ilmjärv, Tanel
    GacA/GacS two-component system can be found in Gram-negative bacteria, including enteric bacteria and Pseudomonas. gacS gene encodes for a membrane-bound sensor kinase GacS, whereas a transcriptional response regulator GacA is encoded by gacA gene. The aim of this thesis was to investigate whether the inactivation of the GacA/GacS two-component system could affect mutation frequency in Pseudomonas putida. Two test systems were employed for measuring mutation frequency: chromosomal RifR assay and a plasmidial test system based on lactose degradation. RifR phenotype of bacteria is a result of mutations that decrease the affinity of rifampicin binding to the β subunit of RNA polymerase. This makes this enzyme insensitive to rifampicin. The second test system is based on the monitoring mutations in lacZ gene encoding for β-galactosidase, which turns the tester strains from Lac- to Lac+ phenotype. Usage of both test systems revealed that the inactivation of the gacA gene elevates mutation frequency in P. putida. In estonian: GacA/GacS kahekomponendiline süsteem on kirjeldatud erinevates Gram negatiivsetes bakteriliikides, kuhu kuuluvad ka enterobakterid ja erinevad Pseudomonase liigid. Geen gacS kodeerib membraan-seoselist sensorkinaasi GacS ning transkriptsiooni regulaator GacA, mis saab signaali GacS-lt, on kodeeritud geeni gacA poolt. Käesoleva bakalaureusetöö eesmärgiks oli välja selgitada, kas GacA/GacS süsteemi inaktiveerimine mõjutab bakteris Pseudomonas putida mutatsioonisagedust. Mutatsioonisageduse mõõtmiseks kasutati kahte testsüsteemi: kromosomaalset RifR süsteemi ja plasmiidset laktoosi lagundamisel põhinevat Lac+ süsteemi. RifR fenotüübiga bakterites on tekkinud mutatsioonid, mis vähendavad rifampitsiini seondumist RNA polümeraasi β-subühikuga, muutes sel viisil ensüümi rifampitsiini suhtes tundetuks. Teine testsüsteem põhineb β-galaktosidaasi kodeerivas geenis lacZ tekkivate mutatsioonide tuvastamisel, mis võimaldavad Lac- testertüvedel hakata lagundama laktoosi (Lac+ reversioon). Töö tulemustena selgus, et gacA geeni inaktiveerimine bakteris P. putida põhjustas mutatsioonisageduse suurenemist mõlemate testsüsteemide rakendamisel.
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    Activity of macrolides against uropathogenic Escherichia coli
    (Tartu Ülikool, 2023) Shahpazir, Ana; Kaldalu, Niilo, juhendaja
    Azithromycin is a macrolide antibiotic extensively used to treat several infections attributa- ble to Gram-positive bacteria. Exceptionally, azithromycin has proven to be effective in clin- ical treatment of widespread chronic infections caused by Gram-negative bacterium, Salmo- nella. While the underlying mechanisms of azithromycin’s activity against this Gram-nega- tive bacterium remain enigmatic, its efficacy brings up the question of whether this macro- lide can be used in treatment of other Gram-negative bacterial infections as well. The goal of this work was to investigate the possibility of utilizing azithromycin against uropatho- genic Escherichia coli. For this purpose, we determined the minimum inhibitory concentra- tion of azithromycin in conditions resembling intracellular infection sites. Additionally, we validated the use of four macrolide bioreporters that were based on the regulatory leader peptide coding sequence of the macrolide resistance gene, ermCL.
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    Acylation of N-Boc-N’-COCF3 protected hydrazine
    (Tartu Ülikool, 2024) Kurbanova, Karina; Mastitski,Anton, juhendaja; Tartu Ülikool. Loodus- ja täppisteaduste valdkond; Tartu Ülikool. Tehnoloogiainstituut
    Within the scope of the present thesis acylation of N-Boc-N’-COCF3 protected hydrazine was investigated. Acetic anhydride, benzoyl and butanoyl chlorides, activated esters and benzyl chloroformate were tested as acylating agents. The implementation of highly reactive acyl chlorides led to very good yields of hydrazines monoacylated at the Boc-protected nitrogen. Application of an excess of acyl chlorides promoted the formation of diacylated Boc-protected hydrazines and an unexpected loss of the trifluoroacetic group. Acylation by activated esters or benzyl chloroformate resulted solely in monoacylated products isolated in fair to poor yields. Reactions utilizing acetic anhydride gave no product irrespective of reaction conditions.
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    Analysis of Clb6 degradation mechanisms
    (2022) Aghayari, Avishan
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    Analysis of the Impact of Human Papillomavirus Type 5 E2 Serine 255 Phosphorylation on the Viral Genome Replication and E2 Protein Stability
    (2021) Ibragimov, Ruslan
    Human papillomaviruses (HPVs) are associated with the number of diseases from genital warts to cancer. While vaccination grants immunity to the wide range of HPV strains, it is important to develop effective treatment strategies to counter already established infections in order to prevent the egress of new strains of the virus. E2 is one of the most promising targets for development of therapeutic agents against the established HPV infections and, as many other proteins, it undergoes post-translational modifications changing the properties and the functions of this protein. This work is focused on investigating the effects of the phosphorylation at Serine 255 residue on the stability of HPV type 5 E2 protein and replication of the viral genome. The results of this work can benefit the projects focused on the treatment of HPV infection through the disruption of E2 functions and synthesis.
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    Animal recognition using deep learning
    (2021) Pavlovs, Ilja
    Camera traps are widely used for wildlife monitoring. In this work machine learning based data processing pipeline is assembled for animal detection on the camera trap images focusing on the ungulate species. The typical animal detection challenges are noted, and available solutions are evaluated. As the result of this work, two different deep neural networks Faster R-CNN and RetinaNet were trained, achieving 0.2786 mAP@0.5:0.05:0.95 and 0.4562 mAP@0.5 on the dataset of interest gathered in the Latvian forest regions during the ”ICT-based wild animal census approach for sustainable wildlife management” project. Additionally, different learning optimization techniques such as data augmentation and oversampling were implemented and assessed.
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    Antibiotic detection using bioreporters based on SOS and cold shock responses
    (2020) Aedla, Jüri; Hinnu, Mariliis
    With emerging antibiotic resistance, development of methods for screening new antibiotics in environmental and metabolite samples is necessary. Whole-cell bacterial bioreporters are a unique tool in that they only detect the bioavailable fraction of antibiotic concentration and can also aid with investigating the mechanism of action. In this study, two reporters were constructed based on SOS and cold shock stress promoters to detect genotoxic compounds and C group translation inhibitors. Both reporters displayed specific and dose-dependent response to sub-inhibitory antibiotic concentrations. Antibiootikumresistentsuse kasvuga kasvab ka vajadus arendada välja meetodeid uute antibiootikumide tuvastamiseks keskkonnast ja mikroobide metaboliitide seast. Bioreporterid kui elusorganisme teeb eriliseks nende võime tuvastada just elusorganismile mõjuvat antibiootikumi kontsentratsiooni ning uurida selle toimemehhanismi. Käesolevas töös konstrueeriti kaks bioreporterit kasutades SOS ja külmašoki stressipromootoreid, et tuvastada genotoksilisi ühendeid ja C-grupi translatsiooni inhibiitoreid. Mõlema bioreporteri puhul nähti spetsiifilist ja annusest sõltuvat vastust subinhibitoorsetele antibiootikumide kontsentratsioonidele.
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    Antibodies targeting glucose transporter GLUT1 developed through the methods of Phage Display
    (Tartu Ülikool, 2024) Planken, Jaan Eerik; Teyra, Joan, juhendaja; Tenson, Tanel, juhendaja; Tartu Ülikool. Loodus- ja täppisteaduste valdkond; Tartu Ülikool. Tehnoloogiainstituut
    Cancer immunotherapy has emerged as a major treatment approach to combat malignant cells. Among the potential targets, the glucose transporter 1 (GLUT1) stands out due to its role in facilitating the increased glucose uptake characteristic of cancer cells. In this thesis, we use the methods of phage display technology to isolate GLUT1-specific antibodies from a diverse phage library constructed from a previously immunized chickens spleen cells. Through four rounds of panning against a GLUT1-overexpressing virus-like particle (VLP), with each round increasing in stringency, we were able to identify 27 unique antibody sequences. All obtained unique antibodies show great specificity towards the GLUT1 VLP, with signals averaging 11 times higher, on an ELISA based binding assay, in comparison to an off-target antigen control.
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    Artificial Intelligence Based Profession Prediction Using Facial Analysis
    (2020) Mert, Gülce Naz; Anbarjafari, Gholamreza; Karabulut, Doğuş
    Youth unemployment is a global problem which affects millions of young people. One of the reasons for this is that young people are often misguided, or have adopted professions that are not a good fit for them. If an association between facial features and certain professions can be established using artificial intelligence, it is possible to guide young people into suitable career paths, providing them a better future with more satisfying jobs. In order to achieve this goal, different neural network models that employ deep learning and transfer learning were built, alongside with a dataset consisting of face images of people who are professionals in their fields. This data was then fed into these neural networks, testing effects of different networks and their parameters on the accuracy of predicting professions based on face images. The experiments however, did not lead to high accuracy rates. The results and networks are then analyzed and limitations are brought up. The possible solutions to what could have caused low accuracy rates are discussed. In estonian: Noorte tööpuudus on globaalne probleem mis mõjutab miljoneid noori. Üks põhjustest on kuna noori inimesi on tihti valesti juhitud või nad on omastanud ameteid mis pole neile sobilikud. Kui on võimalik leida assotsiatsioone näojoonte ja kindlate ametite vahel kasutades tehisintellekti, kas siis on võimalik juhtida noori inimesi parematele ametikohtadele, varustades neid parema tulevikuga, kus on rohkem rahuldavad töökohti. Et sellise saavutusega hakkama saada, ehitati erinevaid närvivõrgud mudeleid mis kasutavad süvaõpet ja ülekandmise õpe koos andmetega, mis koosnevad inimeste näo piltidest kes on oma ala professionaalid. See informatsioon siis sisestati närvi võrkudesse, katsetades erinevate võrkude efekte ja nende parameetreid näo järgi ameti valimise täpsuses. See katse kahjuks ei viinud kõrge täpsusega tulemusteni. Tulemused ja võrgud siis analüüsiti ja leiti limiidid. Võimalike lahendusi arutatakse selle üle mis võiksid tekitada vähese täpsusega tulemusi.
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    Assessing the single cell sorting capability of BD FACSMelody cell sorter and its effects on the viability of different human cancer cell lines
    (2021) Alhana, Zafer
    The differences between cells in a population are often overlooked because they are obscured by the behavior of the entire population, however, the variation in the genome and transcriptome of every individual cell provides a comprehensive genetic insight. Single cell sorting is a robust technique that enables scientists to identify and sort individual cells for further downstream analysis or monoclonal cell culturing. The present study utilizes a BD FACSMelody cell sorter to sort different human cancer cells. The sorter’s efficiency as well as the viability of the sorted cells were assessed.
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    Audio System for the Social Humanoid Robot SemuBot
    (Tartu Ülikool, 2024) Nizamov, Timur; Kruusamäe, Karl, juhendaja; Tartu Ülikool. Loodus- ja täppisteaduste valdkond; Tartu Ülikool. Tehnoloogiainstituut
    A huge and important part of a human companion robot is related to communication abilities. The humanoid robot should be able to hear the incoming speech, understand it and respond to it in the direction of a human that starts the interaction. To provide for such a solution, this thesis focuses on the design, testing and implementation of such a sound system for a real human companion robot. The proposed sound system is composed of a microphone array board, a speaker system, a digital amplifier, and the Arduino MEGA for testing amplifier volume gain. Additionally, the ROS2 Humble is utilised for uniting the coded scripts and better communication with other parts of the robot. The result of this work is shown on a real robot and together with other team members presented as a working prototype.
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    Automated Detection and Quantification of Stomata
    (Tartu Ülikool, 2024) Gorbachenko, Ivan; Hõrak, Hanna, juhendaja; Haamer, Rain Eric, juhendaja; Tartu Ülikool. Loodus- ja täppisteaduste valdkond; Tartu Ülikool. Tehnoloogiainstituut
    This thesis presents an approach for the automated detection and quantification of stomata using machine learning techniques. The study focuses on employing the YOLOv8 model to analyse video data of leaf epidermal imprints, significantly improving the efficiency and accuracy of stomatal detection compared to traditional manual methods. The results highlight the model's ability to handle varying focal depths within video frames, ensuring consistent stomatal counts. Future research directions include expanding the dataset and incorporating advanced image analysis techniques to further enhance detection accuracy.
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    Automating assessment of silver-enhanced in situ hybridization for evaluation of cancer properties
    (Tartu Ülikool, 2023) Kuklianov, Danila; Haamer, Rain Eric, juhendaja; Haamer, Sisi Carmen, juhendaja
    To correctly assess breast cancer properties, doctors have to compare and evaluate histopathological slides stained for the presence of certain proteins; in the event that the initial evaluation is inconclusive, additional assessment is done. The assessment is necessary to accurately determine the type of cancer and select fitting treatment that increases the likelihood of the patient’s recovery. In this paper, approaches to automate different steps of this assessment are explored with the immediate goal of implementing an end-to-end algorithm pipeline capable of performing this task with minimal human input, with the potential goal of incorporating this pipeline into an existing larger slide processing software.
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    Bioleaching of platinum group metals from electronic waste
    (2020) Khan, Jawad; Menert, Anne
    The rapid economic development together with the short life span of electronic products lead to the generation of ever more electronic waste (e-waste). In this context, the researchers from all over the world have paid much attention to the study of metals and metalloids present in the composition of e-waste. In the present thesis methods for disposing of e-waste are introduced, including physical, mechanical, and biological technologies. Considering advantages in energy savings and eco-friendliness, biological approaches appear be the most effective ones. This thesis evaluated the worldwide generation of e-waste and the implementation of multiple technologies in the recovery of e-waste, specifically, the different applications of the biological method which utilizes microorganisms to extract the platinum group metals. The mechanisms as well as influencing factors for the biological method are discussed, some examples of the method are also introduced. Finally, the conclusions on the implementation of the biological treatment method for e-waste and the prospects for its further use are presented. In estonian: Kiire majandusareng koos elektroonikaseadmete lühikese elueaga tekitab üha enam elektroonikaromusid (e-jäätmeid). Sellega seoses on kogu maailma teadlased pööranud palju tähelepanu e-jäätmete koostises olevate metallide ja metalloidide uurimisele. Käesolevas lõputöös tutvustatakse e-jäätmete kõrvaldamise meetodeid, sealhulgas füüsikalisi, mehaanilisi ja bioloogilisi tehnoloogiaid. Arvestades energiasäästu ja keskkonnasõbralikkuse eeliseid, näivad kõige tõhusamad olevat bioloogilised lähenemisviisid. Selles lõputöös hinnati e-jäätmete ülemaailmset teket ning mitmete tehnoloogiate rakendamist e-jäätmete taaskasutamisel, täpsemalt bioloogilise meetodi erinevaid rakendusi, milles plaatina rühma metallide eraldamiseks kasutatakse mikroorganisme. Käsitletakse bioloogilise meetodi mehhanisme ja mõjutegureid, toodud on ka mõned meetodi näited. Lõpuks tutvustatakse järeldusi e-jäätmete bioloogilise töötlusmeetodi rakendamise kohta ja selle edasise kasutamise väljavaateid.
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    Bismuth Metal-Organic Framework Based Catalyst for CO2 Electroreduction
    (2021) Assafrei, Jürgen-Martin
    Electrochemical reduction of CO2 into different fuels and other valuable chemicals is a highly promising method of CO2 valorisation. Among the many possible compounds that CO2 can be reduced to, formic acid is especially attractive because it already has quite a large market in agriculture and the pharmaceutical industry. It can be used directly in a formic acid fuel cell or as hydrogen storage for hydrogen fuel cells. The catalysts used for this reduction process need to strongly absorb CO2 and show poor activity towards the hydrogen evolution reaction (HER) so that it would not interfere. This work focuses on Bi-N-C electrocatalysts fabricated by carbonization of TAL33 MOF compounds at different temperatures. The electrochemical activity of the catalysts was measured, and some samples showed Faradaic efficiencies up to 100 % and formed formic acid at concentrations up to 20 mM after 90 minutes. To investigate why samples at different carbonization temperatures showed different results, surface morphological studies were conducted. Results obtained in electrochemical experiments were further confirmed by theoretical calculations.
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    Cdk1-mediated phosphoregulation of NLS-NES modules
    (2022) Kiselev, Viacheslav