We present a statistical image-based shape + structure model for Bayesian visual hull reconstruction and 3D structure inference. The 3D shape of a class of objects is represented by sets of contours from silhouette views simultaneously observed from multiple calibrated cameras. Bayesian reconstructions of new shapes are then estimated using a prior density constructed with a mixture model and probabilistic principal components analysis. We show how the use of a class-specific prior in a visual hull reconstruction can reduce the effect of segmentation errors from the silhouette extraction process. The proposed method is applied to a data set of pedestrian images, and improvements in the approximate 3D models under various noise conditions are shown. We further augment the shape model to incorporate structural features of interest; unknown structural parameters for a novel set of contours are then inferred via the Bayesian reconstruction process. Model matching and parameter inference are done entirely in the image domain and require no explicit 3D construction. Our shape model enables accurate estimation of structure despite segmentation errors or missing views in the input silhouettes, and works even with only a single input view. Using a data set of thousands of pedestrian images generated from a synthetic model, we can accurately infer the 3D locations of 19 joints on the body based on observed silhouette contours from real images.

<p>In this project a web-based system called 3DPOPS have been designed, developed and implemented. The system creates initial 3D structures of oligosaccharides according to user input data and is intended to be integrated with an automatized 3D prediction system for saccharides. The web interface uses a novel approach with a dynamically updated graphical representation of the input carbohydrate. The interface is embedded in a web page as a Java applet. Both expert and novice users needs are met by informative messages, a familiar concept and a dynamically updated graphical user interface in which only valid input can be created.</p><p>A set of test sequences was collected from the CarbBank database. An initial structure to each sequence could be created. All contained the information necessary to serve as starting points in a conformation search carried out by a 3D prediction system for carbohydrates.</p>

Plant breeders have focused on improving maize resistance to Aspergillus flavus infection and aflatoxin accumulation by breeding with genotypes having the desirable traits. Various maize inbred lines have been developed for the breeding of resistance. Identification of differentially expressed proteins among such maize inbred lines will facilitate the development of gene markers and expedite the breeding process. Computational biology and proteomics approaches on the investigation of differentially expressed proteins were explored in this research. The major research objectives included 1) application of computational methods in homology and comparative modeling to study 3D protein structures and identify single nucleotide polymorphisms (SNPs) involved in changes of protein structures and functions, which can in turn increase the efficiency of the development of DNA markers; 2) investigation of methods on total protein profiling including purification, separation, visualization, and computational analysis at the proteome level. Special research goals were set on the development of open source computational methods using Matlab image processing tools to quantify and compare protein expression levels visualized by 2D protein electrophoresis gel techniques.

Machine learning models such as AlphaFold can generate protein 3D conformation from primary sequence up to experimental accuracy, which gives rise to a bunch of research works to predict protein functions from 3D structures. Almost all of these works attempted to use graph neural networks (GNN) to learn 3D structures of proteins from 2D contact maps/graphs. Most of these works use rich 1D features such as ESM and LSTM embedding in addition to the contact graph. These rich 1D features essentially obfuscate the learning capability of GNNs. In this thesis, we evaluate the learning capabilities of GCNs from contact map graphs in the existing framework, where we attempt to incorporate distance information for better predictive performance. We found that GCNs fall far short with 1D-CNN without language models, even with distance information. Consequently, we further investigate the capabilities of GCNs to distinguish subgraph patterns corresponding to the InterPro domains. We found that GCNs perform better than highly rich sequence embedding with MLP in recognizing the structural patterns. Finally, we investigate the capability of GCNs to predict GO-terms (functions) individually. We found that GCNs perform almost on par in identifying GO-terms in the presence of only hard positive and hard negative examples. We also identified some GO-terms indistinguishable by GCNs and ESM2-based MLP models. This gives rise to new research questions to be investigated by future works.

In today’s society cities grow increasingly larger, not only on the ground but vertically as well. Utilizing height means taller buildings, which often are large steel- and concrete constructions. Why not construct tall buildings out of timber instead, a material by many believed to be far better from an environmental perspective than steel and concrete? The answer lies in the lack of knowledge regarding tall timber constructions and the stresses they need to withstand. The report was conducted at the construction consulting company Bjerking AB, Uppsala. The focus in this report was to examine accelerations and deformations as an effect of wind loads. The issue at hand was whether the connections between building elements affect the dynamic responses that occur. The chosen model was a 15 storey timber building whose walls and floors consisted mainly of cross laminated timber elements as the load bearing structure. As a large amount of the analyses were complex, the calculations were made in the computer program FEM-Design, which is a finite element program. After performing numerous calculations with different settings, a result emerged. Clear trends could be seen in the connections’ influence on accelerations and deformations. A stiffer connection makes the building more resistant to wind loads. This result has to be considered when constructing tall timber buildings to avoid problems with accelerations and deformations. However, merely adjusting the connections to meet requirements is not sufficient, other measures are also needed. / I dagens samhälle växer sig städer allt större, inte bara till ytan utan även på höjden. För att kunna exploatera på höjden krävs högre hus vilka ofta byggs av stora stål- och betongkonstruktioner. Men varför byggs inte höghus istället av trä som av många anses vara mycket bättre ur bland annat miljösynpunkt? Svaret ligger i kunskapsbristen som finns kring hur höga trähus ska konstrueras för att klara de olika påfrestningarna det utsätts för. Arbetet genomfördes i samarbete med konsultföretaget Bjerking AB, Uppsala. En del av de problemen som finns har undersökts, nämligen accelerationer och deformationer som en effekt av vindlaster. Frågeställningen är huruvida infästningarna och dess inspänningsgrad mellan olika byggnadselement påverkar de statiska respektive dynamiska effekterna som uppstår. Den valda modellen, ett 15-våningar högt trähus, bestod i huvudsak av CLT-element, Cross Laminated Timber, i både väggar och bjälklag som hade till uppgift att föra ner lasterna till grunden. Då analysen är komplex utfördes en stor del av beräkningarna i FEM-Design som är ett avancerat beräkningsprogram. För att säkerställa indata samt komplettera kunskapen inom området utfördes en bakgrundsstudie. Efter utförta beräkningar på den bestämda modellen fastslogs resultatet. En tydlig trend kunde följas vid beaktning av accelerationer och deformationer vid olika värden på inspänningen mellan byggnadselementen. Styvare förband gör byggnaden mer beständig gentemot vindlaster. Ett resultat som måste beaktas för att kunna lösa en del av de problem som uppstår med höga hus i trä. Dock räcker det inte att enbart justera inspänningsgraden för att klara gällande krav och normer, utan ytterligare åtgärder krävs.

<p>RNA, or ribonucleic acid, is one of the three biological macromolecule types essential for all known life forms, and is a critical part of a variety of cellular processes. The well known functions of RNA molecules include acting as carriers of genetic information in the form of mRNAs, and then assisting in translation of that information to protein molecules as tRNAs and rRNAs. In recent years, many other kinds of non-coding RNAs have been found, like miRNAs and siRNAs, that are important for gene regulation. Some RNA molecules, called ribozymes, are also known to catalyze biochemical reactions. Functions carried out by these recently discovered RNAs, coupled with the traditionally known functions of tRNAs, mRNAs, and rRNAs make RNA molecules even more crucial and essential components in biology.</p><p>Most of the functions mentioned above are carried out by RNA molecules associ- ating themselves with proteins to form Ribonucleoprotein (RNP) complexes, e.g. the ribosome or the splicesosome. RNA molecules also bind a variety of small molecules, such as metabolites, and their binding can turn on or off gene expression. These RNP complexes and small molecule binding RNAs are increasingly being recognized as potential therapeutic targets for drug design. The technique of computational structure-based rational design has been successfully used for designing drugs and inhibitors for protein function, but its potential has not been tapped for design of RNA or RNP complexes. For the success of computational structure-based design, it is important to both understand the features of RNA three-dimensional structure and develop new and improved algorithms for protein and RNA design.</p><p>This document details my thesis work that covers both the above mentioned areas. The first part of my thesis work characterizes and analyzes RNA three-dimensional structure, in order to develop new methods for RNA validation and refinement, and new tools for correction of modeling errors in already solved RNA structures. I collaborated to assemble non-redundant and quality-conscious datasets of RNA crystal structures (RNA09 and RNA11), and I analyzed the range of values occupied by the RNA backbone and base dihedral angles to improve methods for RNA structure correction, validation, and refinement in MolProbity and PHENIX. I rebuilt and corrected the pre-cleaved structure of the HDV ribozyme and parts of the 50S ribosomal subunit to demonstrate the potential of new tools and techniques to improve RNA structures and help crystallographers to make correct biological interpretations. I also extended the previous work of characterizing RNA backbone conformers by the RNA Ontology Consortium (ROC) to define new conformers using the data from the larger RNA11 dataset, supplemented by ERRASER runs that optimize data points to add new conformers or improve cluster separation.</p><p>The second part of my thesis work develops novel algorithms for structure-based</p><p>protein redesign when interactions between distant residue pairs are neglected and the design problem is represented by a sparse residue interaction graph. I analyzed the sequence and energy differences caused by using sparse residue interaction graphs (using the protein redesign package OSPREY), and proposed a novel use of ensemble-based provable design algorithms to mitigate the effects caused by sparse residue interaction graphs. I collaborated to develop a novel branch-decomposition based dynamic programming algorithm, called BWM*, that returns the Global Minimum Energy Conformation (GMEC) for sparse residue interaction graphs much faster than the traditional A* search algorithm. As the final step, I used the results of my analysis of the RNA base dihedral angle and implemented the capability of RNA design and RNA structural flexibility in osprey. My work enables OSPREY to design not only RNA, but also simultaneously design both the RNA and the protein chains in a RNA-protein interface.</p> / Dissertation

This thesis has been executed in cooperation with Abetong which is a leading company in the prefabrication of concrete structures. For a prefabricated concrete building the design engineer must take into consideration the connections between the concrete elements in order to make sure that the building will possess a sufficient structural stability. Therefore the structural engineer might have to re-calculate the original structure that often has been designed as an on site-built building. The purpose of this thesis is to examine the forces between elements related to different models to see if the structural engineer has to make a re-design. To get results for this study we have used FEM-design 3D Structure. The results of forces from the program were compared with Abetongs standard forces of point connections and recess lists and showed that the structural engineer can use the original calculation up to around five stories when a prefabricated shall be erected.

L’objectif de ce travail de thèse est la formalisation des relations entre la structure et les propriétés de transfert de matière (sorption, diffusion, perméabilité) dans des matériaux biocomposites pour l’emballage alimentaire. Pour cela, la thèse se focalise sur deux questions scientifiques majeures : (i) comment évaluer les propriétés de transfert de vapeur d’eau et de gaz dans des particules végétales de taille micrométrique et (ii) comment formaliser l’influence de l’interphase sur les propriétés de transfert de matière en utilisant des approches expérimentales et de modélisation. Pour cela, a système composite modèle a été utilisé : un biocomposite polypropylène (PP) / particules de cellulose micrométrique produit par extrusion. La première partie de ces travaux est axée sur le développement d’une méthodologie fiable pour caractériser les propriétés de transfert dans des particules de taille micrométrique. Une nouvelle méthode ad hoc couplant microbalance à quartz et cellule d’absorption a été développée et comparée aux méthodes gravimétriques classiques telles que la DVS. La caractérisation fine de la taille / distribution en taille des particules est une étape essentielle pour garantir la fiabilité de l’estimation des paramètres de diffusion. Le deuxième objectif s’appuie sur une caractérisation quantitative fine de la structure 3D des matériaux composites (micro-tomographie X). En finalité, ces travaux de thèse permettent d’aller plus loin dans le développement de modèles prédictifs des relations entre structure et propriétés de transfert de matière, ce qui est l’étape nécessaire pour développer des matériaux biocomposites basés sur une approche d’ingénierie inverse. / The objective of this thesis is to formalize the relationships between the structure and mass transfer properties (sorption, diffusion, permeability) in biocomposites for food packaging. It raises two main scientific questions: (i) how to evaluate the mass transfer properties in micrometric size vegetal particles and (ii) how to formalize the impact of the interphase on mass transfer properties by using experimental and modeling approaches. For this purpose, a model system has been considered, i.e. a biocomposite polypropylene (PP)/ micrometric cellulose particles, produced by melt extrusion. The first part of this work focuses on the development of reliable methodologies to characterize mass transfer properties in micrometer size particles. A new method based on the use of a quartz crystal microbalance coupled to an absorption system has been developed and critically compared to classical methods such as DVS. The accurate characterization of the particle morphology distribution is a key point for estimating diffusivity parameters. The second objective is dedicated to the quantitative characterization of the 3D microstructure using X-ray micro-tomography. Structural parameters are used in biphasic and triphasic (consideration of the interphase) models of mass transfer. This thesis brings new knowledge in the modeling of structure / mass transfer properties relations in biocomposites, which is the necessary step for developing biocomposites based on a reverse engineering approach.

We present an image-based approach to infer 3D structure parameters using a probabilistic "shape+structure'' model. The 3D shape of a class of objects may be represented by sets of contours from silhouette views simultaneously observed from multiple calibrated cameras. Bayesian reconstructions of new shapes can then be estimated using a prior density constructed with a mixture model and probabilistic principal components analysis. We augment the shape model to incorporate structural features of interest; novel examples with missing structure parameters may then be reconstructed to obtain estimates of these parameters. Model matching and parameter inference are done entirely in the image domain and require no explicit 3D construction. Our shape model enables accurate estimation of structure despite segmentation errors or missing views in the input silhouettes, and works even with only a single input view. Using a dataset of thousands of pedestrian images generated from a synthetic model, we can perform accurate inference of the 3D locations of 19 joints on the body based on observed silhouette contours from real images.

Nucleic acids play important roles in living systems by storing and transferring genetic information and directing protein synthesis. Recently, it was found that nucleic acids can catalyze chemical and biochemical reactions similar to protein enzymes. In addition, they can also serve as drug targets for the treatment of deadly diseases such as AIDS and cancers. As a result, the 3D structure study of nucleic acids and proteinnucleic acids complexes by X-ray crystallography has become one of the most active research areas. However, the two intrinsic bottlenecks of macromolecule X-ray crystallography, including crystallization and phase determination, have significantly limited its application in study and discovery of the new structures and folds, as well as in exploration of the biological mechanisms. So far, the selenium derivatization (Se-Met) of proteins and multiple anomalous dispersion (MAD) or single anomalous dispersion (SAD) technology have revolutionized the protein crystallography field by providing a rational solution to solve the phase determination problem. Similarly, it’s important and urgent to develop a corresponding methodology for nucleic acid X-ray crystallography. The work presented here includes two general research directions: the selenium derivatized nucleic acids (SeNA) and tellurium derivatized nucleic acids (TeNA): 1) The SeNA strategy by site-specifically replacing oxygen with selenium at the 2’ and 4 positions of thymidine and uridine has been developed. We found that the selenium derivatization at both sites are relatively stable and doesn’t cause significant structure perturbations by comparing with their corresponding native counterparts. In addition to the phase determination, the 2’-Se modification can also facilitate crystal growth of many oligonucleotides. Moreover, we have observed colorful DNAs and RNAs with the 4-Se modification for the first time. 2) The TeNA strategy by covalently incorporating tellurium functionalities into different positions of nucleic acids, particularly at the 2’ and 5 position of thymidine, has been developed. We have demonstrated the compatibility of the tellurium modification and solid-phase synthesis, as well as the potential application of the tellurium modifications in anti-viral drug synthesis and DNA-damage investigation.