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Changes in trade between the European Union and selected Eurasian countries due to anti-Russia sanctions
No full textEttevõtete kriisijuhtimine väliste šokkide tingimustes: Ukraina energeetikaettevõtete juhtum pärast Venemaa ja Ukraina sõda
No full textMaakivimüüride vuukimine ajalooliste ja tänapäevaste vahenditega
No full textThe master’s thesis titled “Pointing of Fieldstone Walls with Historical and Contemporary Methods” addresses a topic that has so far received little attention in Estonia – the pointing of fieldstone walls – examining it from both historical and contemporary perspectives. The focus is on joint fillers, materials, and techniques used in fieldstone buildings constructed since the 19th century, with attention to regional variations and changes in working practices over time. Pointing is not viewed merely as a finishing step but as a significant structural and aesthetic element that affects the wall’s durability, weather resistance, and visual coherence. The aim of the study was to document terminology related to pointing, analyze working methods, compare traditional and modern techniques, and provide practical support for those involved in restoring fieldstone buildingshttps://www.ester.ee/record=b575239
Tööstusspionaaži-vastased meetmed kaitsetööstuse kaitsel
No full texthttps://www.ester.ee/record=b5752580*es
Generation Z in the labor market: challenges and opportunities in shaping the work environment
No full textCritiquing the pre-degree arts students' partnership with ChatGPT, as a tool for authentic inquiry
No full texthttps://www.ester.ee/record=b5755957*es
Inimese genoomi uuringud k-mer sagedustega
No full textVäitekirja elektrooniline versioon ei sisalda publikatsiooneInimese genoom on keeruline ja pidevas muutumises – seal toimuvad mutatsioonid kogu aeg. Kuigi genoomi uurimine oli veel 25 aastat tagasi aeglane ja kallis, on tehnoloogia areng toonud kaasa suure läbimurde. Varem kasutati peamiselt DNA mikrokiipe, mis tuvastasid üheaegselt üksikuid muutusi ehk SNP-sid. Tänapäeval saab järjestada terve genoomi ja analüüsida miljardeid andmepunkte korraga.
Selles töös kasutati uudset lähenemist, mis põhineb nn k-meride analüüsil. K-merid on lühikesed DNA lõigud (25 tähte), mille esinemissagedust saab arvutada ilma kõigi ühe inimese järjestusi eelnevalt ajakulukalt standardiga võrdlemata. See teeb andmetöötluse kiiremaks ja võimaldab tuvastada ka selliseid muutusi, mida varasemad meetodid ei näinud – eriti korduvates või tehniliselt keerulistes piirkondades.
Töö üks olulisemaid uuendusi on Y-kromosoomi põlvnevusgruppide määramine väga väikese DNA koguse põhjal. Kui tavaliselt vajatakse usaldusväärseks analüüsiks 20-kordset kordust üle andmete, siis siin kasutati vähem kui 1% juhuslikku osa genoomist. See oli võimalik tänu korduvatele DNA järjestustele Y-kromosoomis, mida varem peeti analüüsimiseks liiga keeruliseks.
Uuringus käsitletud meetod kasutab neid kordusi omamoodi loodusliku "võimendusena", nagu DNA paljundamine laboris. Aja jooksul on need piirkonnad kogunud unikaalseid muutusi, mis aitavad määrata inimese isaliini ehk haplogruppi.
See tehnoloogiline lähenemine – k-meride sagedusel põhinev, joondusvaba ja suure ulatusega – avab uusi võimalusi genoomi uurimisel, eriti olukordades, kus andmeid on vähe või kus traditsioonilised meetodid jäävad hätta.The human genome is complex and constantly changing – mutations occur all the time. Just 25 years ago, studying the genome was slow and expensive, but advances in technology have brought major breakthroughs. In the past, researchers mainly used DNA microarrays, which could detect individual changes called SNPs. Today, it’s possible to sequence the entire genome and analyze billions of data points at once.
This study used an innovative approach based on k-mer analysis. K-mers are short DNA fragments (25 letters long), and their frequency in the genome can be calculated without the time-consuming process of comparing all sequences to a reference. This speeds up the analysis and allows researchers to detect changes that older methods often missed – especially in repetitive or technically difficult regions.
One of the key innovations in this work is identifying Y chromosome haplogroups using a very small amount of DNA. While traditional methods usually require about 20× coverage for reliable results, this study used less than 1% of randomly selected genome data. This was possible thanks to repetitive sequences on the Y chromosome, which were previously considered too complex to analyze.
The method presented in this study uses these repeats as a kind of natural “amplifier,” similar to how DNA is copied in a lab. Over time, these regions have accumulated unique mutations that help identify a person’s paternal lineage, or haplogroup.
This technological approach – based on k-mer frequency, alignment-free, and scalable—opens up new possibilities for genome research, especially in cases where only limited data is available or where traditional methods fall short.https://www.ester.ee/record=b575449
Uuriva geneetilise genealoogia kasutamine eesti kriminaalmenetluses
No full texthttps://www.ester.ee/record=b5755545*es
Comparative analysis of traditional time series, machine learning, deep learning and hybrid models for profit forecasting in financial markets
No full textThis thesis compared the forecasting performance of traditional time series, machine learning, deep learning and hybrid models on daily banking profit data in financial markets area aggregated on three different levels. To evaluate different methods, this thesis used a novel performance metric - corrected mean average scaled error (cMASE), which improves interpretability of MASE by using T one-step naive forecasts instead of T −1, which results in naive method always having a score of cMASE = 1.
Despite advancements in computational power, traditional time series method SARIMA still outperformed other models, also showing the most consistent results between average cross-validation cMASE and testing cMASE.
For best hybrid models, gradient boosting methods complemented SARIMA by correcting forecasts using long lags, rolling means and standard deviations. While SARIMA models required refitting after every forecast, the machine learning, deep learning and non-linear parts of hybrid models performed best when refit only on average once every two weeks, which reduced the overall
computing cost significantly
Põlve osteoartroosi molekulaarsete markerite CILP-2, DDR2 ja C2C seos koekahjustuse raskusastmega
Get PDFVäitekirja elektrooniline versioon ei sisalda publikatsiooneOsteoartroos (OA) on kõige sagedamini esinev krooniline liigeshaigus, mis mõjutab miljoneid inimesi maailmas. Kõige sagedamini kahjustab OA põlveliigest. Pikalt arvati, et OA on tingitud kõhrkoe kulumisest, kuid tänaseks on teada, et OA algab molekulaarsetest muutustest, mis mõjutavad liigese erinevaid kudesid (kõhr, luu, sünoviaalkest, menisk, sidemed). Varase OA-ga seotud molekulaarsed muutused toimuvad faasis, kus haigusele iseloomulikud sümptomid puuduvad. Seetõttu on OA uurimisel olulisel kohal molekulaarsed markerid, mis peegeldavad haiguse käigus toimunud muutusi ja ideaalis aitavad tuvastada OA varast haigestumist või sobivad haigust modifitseeriva ravi kandidaadiks.
Uuringuks valiti järgmised eeldatavalt OA-ga seotud markerid: CILP-2 (kõhre vahekihi valk 2), DDR2 (diskoidiini domeeni retseptor 2) ja C2C (teist tüüpi kollageeni lõhustumise neoepitoop). Käesolevas uurimuses hindasime nende biomarkerite esinemist OA patsientidelt põlveliigese endoproteesimisel kogutud kõhrkoe proovides. Hindasime nii kõhrkoe lokaalset kui makroskoopilist kahjustust OARSI (Rahvusvahelise Osteoartriidi Uurimise Ühingu) väljatöötatud hindamissüsteemi alusel ja võrdlesime kahjustusastmeid biomarkerite ekspressiooniga. Eraldi metoodilises uurimuses leidsime sobivaima antigeeni esiletoomise meetodi CILP-2 immunohistokeemiliseks värvinguks.
Uurimistöö tulemused näitavad, et CILP-2 ja C2C on paljulubavad põlveliigese OA raskuseastme biomarkerid. CILP-2 ja DDR2 ekspressiooni võrdlemisel selgus, et kui CILP-2 seostus mitmete kõhrekahjustuse parameetritega, siis DDR2 näitas kõhrekahjustusega ainult nõrka seost. Seega võib antud uuringu valgusel pidada CILP-2 paremaks OA lokaalse kahjustuse markeriks kui DDR2. C2C immunohistokeemilistes uuringutes, kus kasutati uriinis C2C testides rakendatavat antikeha, leiti C2C seostumine liigeskõhre kahjustuse ulatusega. Seega võib C2C pidada arvestatavaks OA markeriks ja uriinis määratud C2C tase võiks peegeldada koetasandil toimuvaid muutusi.Osteoarthritis (OA) is the most common chronic joint disease, impacting millions globally, with the knee being the most commonly affected. Traditionally viewed as a “wear and tear” condition, OA is now recognized to originate from molecular changes that affect all joint tissues, including cartilage, bone, synovium, menisci, and ligaments. These molecular changes occur well before clinical symptoms become apparent. Consequently, molecular markers that can reflect changes during OA pathogenesis and potentially aid in early detection or serve as targets for disease-modifying therapy are crucial in OA research.
This study focused on the following putative OA markers: CILP-2 (cartilage intermediate layer protein 2), DDR2 (Discoidin Domain Receptor 2) and C2C (collagen type-II C-terminal cleavage neoepitope). We evaluated the expression of these biomarkers in cartilage samples obtained from OA patients who underwent total knee replacement. We assessed the local cartilage pathology and the extent of macroscopic damage using the OARSI OA Cartilage Histopathology Assessment System and compared the damage levels with the expression of biomarkers. In a separate methodological study, we identified the most suitable antigen retrieval method for CILP-2 immunohistochemistry.
Our findings indicate that CILP-2 and C2C are promising biomarkers for assessing knee OA severity. When comparing CILP-2 with DDR2, we found that while CILP-2 correlated with the several indicators of articular cartilage damage, DDR2 showed only a weak association. Thus, CILP-2 may be considered a superior OA marker compared to DDR2 based on our study. The C2C immunohistochemical study, using the antibodies applied in urine C2C ELISA assays, revealed a correlation of tissue-level expression and cartilage damage. Therefore, C2C can be considered a reliable OA marker, with urine assays detected C2C levels potentially reflecting the tissue-level changes.https://www.ester.ee/record=b575659