Browsing by Subject "3D-malli"

Nemaline myopathy (NM) is a rare congenital disorder, the most common of congenital myopathies. It affects primarily the skeletal muscles and it is recognised by nemaline bodies in muscle tissue samples and muscle weakness. Mutation of eleven genes are known to lead to NM and the most frequent disease-causing variants are either recessive NEB variants or dominant ACTA1 variants. Variants in NEB are thought to be well tolerated and only 7% of them are hypothesized to be pathogenic. Over 200 pathogenic NEB-variants have been identified in Helsinki and the majority occurred in patients as a combination of two different variants. The missense variants were speculated to have a modifying effect on pathogenicity by affecting nebulin-actin or nebulin-tropomyosin interactions. Nebulin is a gigantic protein coded by NEB and is one of the largest proteins in vertebrates. It is located in the thin filament of the skeletal muscle sarcomere. Enclosed by terminal regions, nebulin has an extensive repetitive modular region that covers over 90% of the protein. The repetitive zone comprises of 26 modules called super repeats (SR). SRs consist of seven simple repeats. There are seven conserved SDXXYK actin-binding sites at each super repeat, one per simple repeat, and one conserved WLKGIGW tropomyosin-binding site. Due to its enormous size and highly repetitive sequence, nebulin is one of the least studied proteins in vivo, in vitro or in silico. In the NM patient database used for this study, there are 70 families with verified pathogenic mutations and in 30 of them, there were additional missense variants in NEB. These missense variants can be pathogenic modifying factors or have no impact on the phenotype. Seven missense variants were selected to study the effect of these mutations on actin-binding capacity compared to wild-type nebulin using the SR panel constructed previously by Laitila and Lehtonen. Also, due to the differences in actin-binding capacity of SRs compared to each other, one of the aims was to determine whether corresponding mutations in different SRs would have a similar or different effect on actin-binding capacity. For this aim, one missense mutation in the strongly actin-binding SR 1, and one in the weakly actin-binding SR 7 were selected from the NM database, and corresponding variants were created. Also, an in-frame deletion in SR7 found in the ExAC database and the corresponding mutation in SR1 were constructed for this study. The actin-binding strength was determined using actin co-sedimentation assay and actin affinity assay. The results for co-sedimentation assay indicate that missense variants can have an effect on nebulin-actin interactions and, therefore, can be a possible cause for NM. The corresponding mutations had no correlation in their effect on actin-binding strength, just the opposite. S1-m-2 decreased actin-binding strength of SR1 and S7-m-2 had no effect on SR7. Likewise, S7-m-1 and S7-del-1 decreased actin-binding strength of SR7 and corresponding mutations had no effect on SR1. The selected missense mutations found in NM patients in SRs 2 and 4 decreased actin-binding strength, if located at the actin-binding sites and in SR 10 increased the actin-binding strength, if located at the actin-binding site. The change in actin binding strength was defined as significant if the P-value was below 0.005. The more accurate affinity assay was performed as a trial only for S16 and S16-m-1, a variant at a tropomyosin-binding site close to an actin-binding site. It indicated a difference in actin-binding affinity missed by the actin co-sedimentation assay. The results are preliminary, but show big promise and should be optimized and implemented in the future missense mutation affinity studies. In an attempt to understand if the effect missense mutations have on nebulin-actin interaction is based on the change in nebulin structure, the 3D-structure of each produced fusion protein was predicted in silico. Considering that the variants were produced as GST-fusion proteins, the position and effect of GST in them is also a point of interest. In order to predict the structure of these large proteins, a combined approach was implemented using I-TASSER (Iterative Threading ASSEmbly Refinement) software. The software uses ab initio modeling, threading methods and atomic-level structure refinement to build an accurate 3D-model of a protein from sequence. According to the predicted 3D models of the fusion proteins, the GST-part of the proteins folds into a globular structure and acts as a core around which the nebulin fragments fold. The GST does not bind to actin and is positioned on the inside, which indicates minimal effect on nebulin-actin interaction, but may be a reason for an alternative nebulin fragment folding. The accuracy of the default set of programs in software does not give the definitive answer of the possible effect missense mutations can have on structural changes. However, I-TASSER approach for 3D-modeling is promising with further software optimization and can possibly serve as an effective bioinformatic tool in the future.

Etelä-Pohjanmaalla Kurikassa maaperän rakennettavuusominaisuudet ovat hankalat maaperän mittavien hienoaineskerrostumien vuoksi. Näiden kerrostumien alueellista jakautumista ei tiedetä, joten tämän työn tarkoituksena on toteuttaa maaperästä geoteknisiin pohjatutkimuksiin perustuva alueellinen 3D-malli Kurikan kaupungin rakennuslupaa-arkiston pohjatutkimusaineistoja käyttäen. Pohjatutkimukset koostuvat yksittäisiin rakennuskohteisiin toteutetuista maaperäkairauksista. Aineistona käytettäviä tutkimuskohteita on yhteensä kymmenen ja kairauksia 3D-mallissa on käytössä 112. Pohjatutkimusaineistoista digitoitiin kohde ja kairaus kerrallaan maalajitieto sekä kairauksen kuormitusominaisuudet. Digitointiin käytettiin suomalaisen 3D-Systemsin 3D-Win –ohjelmistoa. 3D-malli toteutettiin Leapfrog Geo® -ohjelmistolla. Mallin ensimmäisessä vaiheessa maaperä jaettiin kahdeksaan yksikköön. Lopullisessa yksinkertaistetussa mallissa maaperän hienoainesyksiköt yhdistettiin yhdeksi yksiköksi. Saatuja malleja verrattiin alueelta olevaan tyyppileikkaukseen. Malleilla arvioidaan millä aineiston resoluutiolla saadaan mallille paras ennustusvoima. 3D-mallien toteutus onnistui. Mallin mukaan alueella on kahdeksan maalajiyksikköä (vanhimmasta nuorimpaan): moreenit, hiekat, siltit, savet, liejusavet, siltit 2, savet 2 sekä pinnassa humus- ja täyttömaat. Useilla mallin yksiköistä (siltit, savet ja liejusavet) on samankaltaiset geotekniset ominaisuudet, joten ne yhdistettiin yhdeksi hienoainesyksiköksi. Yksinkertaistetun mallin yksiköitä verrattiin alueelta olevaan tyyppileikkaukseen. Tyyppileikkauksen sedimenttisarja ja mallin hienoainesyksikkö vastaavat hyvin toisiaan. Tämän työn tulosten perusteella geoteknisiin pohjatutkimuksiin perustuvassa maaperän 3D-mallinnuksessa hienoainesyksiköiden osalta yksinkertaistettu malli on ennustettavuuden kannalta luotettavampi kuin kompleksinen malli.

The number of drones has increased in both the private and corporate sectors. There is also an interest in the use of drones in agriculture since by using them the large fields can be monitored easily. Automatic flight systems of drones are simple to use. More accurate overview of the field can be got by utilizing the drones than by making observations from the side of the field. With aerial photographs the measures for the field can be planned further. For example, based on the photos pesticide spraying or fertilize spreading can be planned for the field. Drones can also be used to estimate crop biomasses. With drones the development of the crops is possible to observe as a timeseries during the growing season. The aim of this study was to explore the use of multispectral images and 3D models in crop monitoring. Crop leaf area index (LAI), biomass and chlorophyll content were measured. There were 8 different plants/fertilization levels in this study. In this study, a multispectral camera and a RGB-camera were used to estimate crops features. With a multispectral camera the reflectance values of the vegetation, which described how much of the incoming sun radiation was reflected back from the vegetation, were able to determine. The multispectral camera had five spectral bands (blue, green, red, red edge and NIR). Based on these bands NDVI vegetation index was calculated. The reflectance values and vegetation indices were compared to the dry matter mass, LAI, and chlorophyll content determinations of the vegetation. From the images of the RGB-camera 3D-models were created to calculate crop volumes. Calculated volumes were compared to crop dry matter mass and LAI measurements. Linear regression analysis was used to examine the relationship between the variables calculated from the images and the parameters determined from the crops on the field. According to these results, the variables determined from the multispectral images explained the dry matter mass and leaf area index of the crop slightly less than the 3D-models determined from the RGB images. The strongest determined dependence of the data recorded by the multispectral camera was between the faba bean LAI and NDVI (R2 = 0,85). The relationship between the reflection/index data of multispectral camera and crop parameter was weak: average coefficient of determination for dry matter mass of the crop was 0.15, for chlorophyll content 0.14, and for LAI 0,21. The highest coefficient of determination for 3D model of crop volume was between the dry matter mass of oats (R2 = 0.91). The mean coefficient of dependence was 0.69 for the relationship between the plant dry matter masses and 3D model volumes. The mean coefficient of determination for the relationship between the leaf area index of plants and the 3D model volumes was 0.57. Based on these results, from the multispectral camera data, the NDVI index was best suited to determine the crops dry matter mass, leaf area index, and chlorophyll content. However, there were differences in the dependencies between different spectral bands/NDVI index and plant properties determined from different crops. 3D models produced stronger dependences for estimating crop dry matter mass and leaf area index than the quantities determined from multispectral images. Analyzing the data with more sophisticated calculation methods utilizing the values of several spectral bands and the indices in the same time would probably have been a more efficient method to analyzing the data than the current used linear regression used in this study. Removing errors, caused by external factors, from multispectral images was found to be very difficult. Especially reflectance values of dry soil differed clearly from vegetations values. Further studies are needed to develop vegetation indices that can reduce errors caused by external factors. In addition, data processing of images should be developed to utilize multiple spectral bands and vegetation indices to determine the relationship between crop characteristics and variables measured from images. In addition, different plant species imaging techniques should be investigated, as different plants have different reflection values.

Tutkielmassa tarkastellaan 3D-tulostusteknologian mallioikeudellisia ulottuvuuksia. Tarkoituksena on selvittää, millaisia mallioikeudellisia kysymyksiä 3D-tulostamiseen liittyy. Erityisesti tarkastellaan, kuinka 3D-tulostukselle keskeistä CAD-tiedostoa kohdellaan mallioikeudellisen lainsäädännön valossa. 3D-tulostus herättää kysymyksiä siitä, missä oikeudenhaltijan yksinoikeuden raja kulkee ja millaisia uusia mallioikeuden loukkauksen muotoja teknologia on tuonut tullessaan. Tutkielman perusteella CAD-tiedosto voi sisältää mallioikeudessa suojatun mallin. Tämä tarkoittaa, että julkaistu CAD-tiedosto voi saada rekisteröimättömän mallioikeuden suojaa. Toisaalta CAD-tiedoston julkiseksi tekeminen tarkoittaa sellaista mallin tunnetuksi tekemistä, joka estää sen, että myöhemmin julkaistua mallia voitaisiin pitää uutena tai yksilöllisenä. Oikeudentila on kuitenkin epäselvä sen suhteen, suojataanko CAD-tiedostoa sellaisena mallioikeudessa tarkoitettuna tuotteena, jonka taloudellinen hyväksikäyttö on oikeudenhaltijan yksinoikeus. Mallioikeuden poikkeukseksi säädetty oikeus käyttää suojattua mallia yksityiseen käyttöön ilman kaupallista tarkoitusta johtaa siihen, että mallista voi laillisesti 3D-tulostaa kopion ilman oikeudenhaltijan lupaa. Suojattua mallia ei voi kuitenkaan valmistaa kolmannen henkilön, kuten 3D-tulostuspalvelun välityksellä, sillä yksityisen käytön salliva mallioikeuden rajoitus ei koske oikeushenkilöiden toimintaa. Tutkielmassa käsitellään erilaisia mallioikeuden loukkaustilanteita, jotka nousevat esille erityisesti 3D-tulostuksen kontekstissa. CAD-tiedoston epäselvä oikeudentila johtaa siihen, ettei oikeudenhaltija voi tehokkaasti valvoa ja suojata oikeuksiaan. Erityisesti verkossa tapahtuvaan mallioikeuden loukkaukseen on nykyisen lainsäädännön perusteella vaikea puuttua.