The aim of this study is to provide information regarding the development of aDNA research. The essay also strives to distinguish eventual impact on previous and contemporary conceptions concerning Neanderthal and modern human genetic divergence and possible interbreeding between the two species. Relatively recent Neanderthal genetic research will provide a glimpse into future explorations. Hominin species, other than Neanderthals, will be excluded from this paper as well as morphological studies and modern human evolution theories. Nature, Cell, Science, American anthropologist are examples of important publications constituting the study’s source material generated through the mandatory literature search. Genetic data results reveal genetic divergence between Neanderthals and modern humans approximately around 270 000 to 440 000 years ago or 550 000 to 765 000 years ago. The estimations for genetic divergence continue to alter with the advent of additional data. Contemporaneous genomic data results show interbreeding between Neanderthals and modern humans which contradict some prior perceptions surrounding the subject. New engendered Neanderthal genomic data indicate further exploration concerning the Neanderthal inherited genes effect on modern day human biology and physiology. / Syftet med denna studie är att delge informativ upplysning kring utvecklingen av aDNA forskning. Uppsatsen strävar även efter att urskilja eventuell påverkan på föregående och nuvarande uppfattningar angående genetisk splittring mellan Neandertalare och moderna människor och möjlig korsning mellan de två arterna. Relativt ny genetisk Neandertal forskning kommer att ge en inblick i framtida utforskningar. Andra homininer, undantagsvis för Neandertalarna, kommer att exkluderad från denna uppsats liksom morfologiska studier och teorier kring den moderna människans evolution. Nature, Cell, Science, American anthropologist är exempel på viktiga publiceringar som utgör studiens källmaterial vilket genererats genom den obligatoriska litteratursökningen. Genetiska data resultat visar genetisk splittring mellan Neandertalare och moderna människor proximalt kring 270 000 till 440 000 år sedan eller 550 000 till 765 000 år sedan. Beräkningarna för genetisk splittring ändras kontinuerligt på grund av ankomsten av nytillkommande data. Nya genomiska data resultat visar korsning mellan Neandertalare och moderna människor vilket motsäger en del föregående föreställningar kring ämnet. Ny framställd Neandertal genomiska data indikerar vidare utforskning av de ärvda Neandertal genernas möjliga påverkan på den moderna människans biologi och fysiologi.

This thesis identifies the effect of traditional political coalitions on the left-right spectrum in Swedish municipal politics on economic outcomes such as Municipal Revenues, Expenditures, Net-expenditures, Municipal Tax-rates, Unemployment, and the share of Municipal Employment. To do so, varying time spans of Swedish municipal data from 1994-2017 are used in a regression discontinuity design, basing its identification on quasi-random variation created by close municipal elections. The results indicate that the left-leaning Red-Green coalition has no isolated impact on economic variables when considering the entire sample, but seems to have a significant impact on some economic variables compared to others when the sample is restricted to decrease the number of mixed coalitions in the sample. These results indicate that the increase in mixed governing coalitions in recent years could have watered down the clear left-right dimension in Swedish politics found in previous research.

In recent years, voxel-based modelling has seen a reintroduction to computer game development through massive graphics hardware improvements. Never- theless, polygons continue to be the default building block of 3D objects, intro- ducing a need for the transformation of polygon meshes into voxel-based models; this process is known as voxelization. Efficient voxelization algorithms take ad- vantage of the flexibility and control offered by modern, programmable GPU pipelines. However, the variability in possible approaches poses the question of how different GPU-based implementations affect voxelization performance.This thesis explores the impact of GPU-based improvements by comparing four different implementations of a solid voxelization algorithm. The implemen- tations include a naive transition from the CPU to the GPU, a non-branching execution path approach, data pre-processing, and a combination of the two previous approaches. Benchmarking experiments run on four, standard polygo- nal models and three graphics cards (NVIDIA and AMD) provide runtime and memory usage data for each implementation. A comparative analysis is per- formed on the basis of this data to determine the performance impact of the GPU-based adjustments to the voxelization algorithm implementation.Results indicate that the non-branching execution path approach yields clear improvements over the naive implementation, while data pre-processing has in- consistent performance and a large initial performance cost; the combination of the two improvements unsurprisingly leads to combined results. Therefore, the conclusive recommendation is using the non-branching execution path technique for GPU-based improvements. / Voxel-baserad modellering har på senare år blivit återintroducerat till datorspelsutveckling tack vare massiva förbättringar i grafikhårdvara. Trots detta fortsätter polygoner att vara standarden för uppbyggnaden av 3D-objekt. Detta gör det nödvändigt att kunna transformera polygonytor till voxel-baserade modeller; denna process kallas för voxelisering. Effektiva voxeliseringsalgoritmer tar vara på den flexibilitet och kontroll som ges av moderna, programmerbara GPU-pipelines. Variationen i möjliga tillvägagångssätt gör det dock intressant att veta hur olika GPU-baserade implementationer påverkar prestandan av voxeliseringen. Denna avhandling undersöker påverkan av GPU-baserade förbättringar genom att jämföra fyra olika implementationer av en solid-voxeliseringsalgoritm. Implementationerna inkluderar en naiv övergång från CPU:n till GPU:n, en metod med en non-branching exekveringsväg, förbehandling av data, och en kombination av det två tidigare metoderna. Benchmarkingexperiment görs på fyra standardpolygonmodeller och tre grafikkort (NVIDIA och AMD) förser data för exekveringstid och minnesåtgång för varje implementation. En jämförande analys görs med detta data som grund för att bestämma den påverkan som de GPU-baserade ändringarna har på prestandan av voxeliseringsalgoritmens implementation. Resultaten indikerar att implementationen med en non-branching exekveringsväg ger klara förbättringar över den naiva implementationen, medans förbehandlingen av data presterar inkonsekvent och har en stor initial prestandakostnad; kombinationen av dem båda ledde, inte överraskande, till blandade resultat. Den slutgiltiga rekommendationen är således att använda tekniken med en non-branching exekveringsväg för GPU-baserade förbättringar.

Infrared divergences arising in theories with massless gauge bosons have been shown to cancel in scattering amplitudes when using dressed states constructed from the Faddeev- Kulish approach to the asymptotic states. It has been established that these states are closely related to asymptotic symmetries of the theory, that is, non-vanishing gauge trans- formations at the asymptotic boundary. In this thesis, we review both of these aspects for QED and non-Abelian gauge theories. We also investigate the expectation value of the non-Abelian field strength tensor using dressed states. We then present a novel con- struction of the dressing operator for non-Abelian gauge theories using Wilson lines. We demonstrate, to order O(g2), that each term of the dressing operator is reproduced in the presented Wilson line approach, along with additional terms that warrant a more thorough understanding. This work extends previous results that pertained to QED and gravity.

L'évolution répétée et indépendante de la différenciation phénotypique entre espèces divergentes, suggérant des pressions sélectives similaires, constitue un contexte propice à l'étude de l'architecture génomique de la spéciation parallèle. L'objectif principal de cette thèse est d'apporter des éléments de réponses concernant les bases génomiques impliquées dans la différenciation phénotypique, et leur influence sur l’évolution de la divergence entre deux complexes d'espèces apparentés, le Grand Corégone (Coregonus clupeaformis) et le Corégone Lavaret (C. lavaretus). Plus précisément, il était nécessaire d'élucider l'origine du polymorphisme de chacune des populations, le rôle de cette variation génétique, son maintient durant la divergence et la différenciation phénotypique entre paires d'espèces. Une analyse génomique a permis de réaliser des inférences démographiques historiques, mettant en évidence la contribution simultanée de processus démographiques et sélectifs qui ont façonné les paysages génomiques de différenciation entre paires d'espèces. Ensuite, une analyse transcriptomique a permis d'identifier des bases polygéniques partagées impliquées dans la différenciation phénotypique parallèle entre paires d'espèces. De plus, ces bases polygéniques indiquent une forte rétention du polymorphisme ancestral sous l’action de la sélection divergente. Finalement, un parallélisme de régions d’ADN différentiellement méthylées entre espèces a été identifié. Bien que cette méthylation repose sur des bases génomiques, ces régions différentiellement méthylées sont associées à une différenciation transcriptionnelle entre espèces des complexes d'espèces du Corégone Lavaret et du Grand Corégone. Ces travaux montrent que la sélection naturelle est contrainte par certains génotypes permettant d'acquérir un parallélisme phénotypique de façon indépendante, et agir sur du polymorphisme ancestral, notamment dans un contexte de spéciation parallèle. Enfin, cette thèse permet de lever le voile et de contribuer à la compréhension des mécanismes génomiques associés à la divergence adaptative pouvant mener à la spéciation écologique, notamment en utilisant une approche intégrative. / Repeated evolution of phenotypic differentiation between diverging species pairs provides an ideal context for the study of the genomic architecture of parallel speciation. The main objective of this thesis is to provide evidence concerning the genomic bases involved in phenotypic differentiation, and their influence on the evolutionary potential of species complexes belonging to two related lineages, the Lake Whitefish (Coregonus clupeaformis) and European Whitefish (C. lavaretus). Specificaly, it is necessary to elucidate the origin of the genetic polymorphism of each population from both whitefish lineages, and to which extend this polymorphism was involved in the genetic divergence and phenotypic differentiation between species pairs. A genome-wide analysis allowed to infer the divergence history combining the effects of historical demograhy and selective pressure that collectively shape the genomic landscape of differentiation between species pairs. Then, transcriptomic analyses revealed parallel polygenic bases involved in the phenotypic differentiation of species pairs, and such genes were enriched in shared ancestral polymorphism. Finaly, a parallel differential methylation level has been identified between species. Although this methylation is genomicaly based, these differentially methylated regions are associated with a transcriptional differentiation between the limnetic and benthic species. This work shows that selection is constrained by some genotypes which could lead to an independent parallel phenotypic aquisition, but also act on the maintainance of ancestral genetic polymorphism, particularly in a context of parallel speciation. This thesis allows to highlight and to contribute to the understanding of the genomic mechanisms generating biodiversity, notably by using an integrative approach.

GLIC är en pH-känslig pentamerisk ligandstyrd jonkanal (pLGIC) som finns i cellmembranet hos prokaryoten Gloeobacter violaceus. GLIC är en bakteriell homolog till flera receptorer som är viktiga i nervsystemet hos de flesta eukaryotiska organismer. Dessa receptorer fungerar som mallar för utvecklingen av målstyrda bedövnings- och stimulerande läkemedel som påverkar nervsystemet. Förståelsen av ett proteins mekanismer har därför hög prioritet inför läkemedelsutvecklingen. Eukaryota pLGICs är dock mycket komplexa eftersom några av de är heteromera, har flera domäner, och de pågår eftertranslationella ändringar. GLIC, å andra sidan, har en enklare struktur och det räcker att analysera strukturen av en subenhet - eftersom alla subenheter är helt lika. Flertalet möjliga grindmekanismer föreslogs av vetenskapen men riktiga öppningsmekanismen av GLIC är fortfarande oklar. Projektets mål är att genomföra maskininlärning (ML) för att upptäcka nya grindmekanismer med hjälp av datormetoder. Urspungsdatan togs från tidigare forskning där andra ML-redskap såsom molekyldynamik (MD), elastisk nätverksstyrd Brownsk dynamik (eBDIMS) och Markovstillståndsmodeller (MSM) användes. Utifrån dessa redskap simulerades proteinet som vildtyp samt med funktionsförstärkt mutation vid två olika pH värden. Fem makrotillstånd byggdes: två öppna, två stängda och ett mellanliggande. I projektet användes ett annat ML redskap: KL-divergens. Detta redskap användes för att hitta skillnader i avståndfördelning mellan öppet och stängt makrotillstånd. Utifrån ursprungsdatan byggdes en tensor som lagrade alla parvisa aminosyrornas avstånd. Varje aminosyrapar hade sin egen metadata som i sin tur användes för att frambringa alla fem avståndsfördelningar fråm MSMs som byggdes i förväg. Sedan bräknades medel-KL-divergens mellan två avståndfördelningar av intresse för att filtrera bort aminosyropar med överlappande avståndsfördelningar. För att se till att aminosyror inom aminosyrapar som låg kvar kan påverka varandra, filtrerades bort alla par vars minsta och medelavstånd var stora. De kvarvarande aminosyroparen utvärderades i förhållande till alla fem makrotillstånd Viktiga nya grindmekanismer som hittades genom både KL-divergens och makrotillståndsfördelningar innefattade loopen mellan M2-M3 helixarna av en subenhet och både loopen mellan sträckor β8 och β9 (Loop F)/N-terminal β9-sträckan och pre-M1/N-terminal M1 av närliggande subenheten. Loopen mellan sträckor β8 och β9 (Loop F) visade höga KL-värden också med loopen mellan sträckor β1 och β2 loop samt med loopen mellan sträckor β6 och β7 (Pro-loop) och avståndet mellan aminosyror minskade vid kanalens grind. Övriga intressanta grindmekanismer innefattade parning av aminosyror från loopen β4-β5 (Loop A) med aminosyror från sträckor β1 och β6 samt böjning av kanalen porangränsande helix. KL-divergens påvisades vara ett viktigt redskap för att filtrera tillgänglig data och de nya grindmekanismer kan bli användbara både för akademin, som vill reda ut GLIC:s fullständiga grindmekanismer, och läkemedelsföretag, som letar efter bindningsställen inom molekylen för att utveckla nya läkemedel. / GLIC is a transmembrane proton-gated pentameric ligand-gated ion channel (pLGIC) that is found in the prokaryote Gloeobacter violaceus. GLIC is the prokaryotic homolog to several receptors that are found in the nervous system of many eukaryotic organisms. These receptors are targets for the development of pharmaceutical drugs that interfere with the gating of these channels - such drugs involve anesthetics and stimulants. Understanding the mechanism of a drug’s target is a high priority for the development of a novel medicine. However, eukaryotic pLGICs are complex to analyse, because some of them are heteromeric, have more domains, and because of their post-translational modifications (PTMs). GLIC, on the other hand, has a simpler structure and it is enough to study the structure of only one subunit - since all subunits are identical. Several possible gating mechanisms have been proposed by the scientific community, but the complete gating of GLIC remains unclear. The goal of this project is to implement machine learning (ML) to discover novel gating mechanisms by computational approaches. The starting data was extracted from a previous research where computational tools like unbiased molecular dynamics (MD), elastic network-driven Brownian Dynamics (eBDIMS), and Markov state models (MSMs) were used. From those tools, the protein was simulated in wild-type and in a gain-of-function mutation at two different pH values. Five macrostates were constructed: two open, two closed, and an intermediate. In this project another ML tool was used: KL divergence. This tool was used to score the difference between the distance distributions of one open and one closed macrostate. The starting data was used to create a tensor that stored all residue-residue distances. Each residue pair had its own metadata, which in turn was used to yield the distance distributions of all five pre-build MSMs. Then the average KL scores between two states of interest were calculated and were used to filter out the residue pairs with overlapping distance distributions. To make sure that the residues within a pair can interact with each other, all residue pairs with very high minimum and average distance were filtered out as well. The residue pairs that remained were later evaluated across all five macrostates for further studies. Important novel mechanisms discovered in this project through both the KL divergence and the macrostate distributions involved the M2-M3 loop of one subunit and both the β8-β9 loop/N-terminal β9 strand and the preM1/N-terminal M1 region of the neighboring subunit. The β8-β9 loop (Loop F) showed high KL scores with the β1-β2 and β6-β7 (Pro-loop) loops as well with decreasing distances upon the channel’s opening. Other notable gating mechanisms involved are the pairing of residues from the β1-β2 loop (Loop A) with residues from the strands β1 and β6, as well as the kink of the pore-lining helix. KL divergence proved a valuable tool to filter available data and the novel mechanisms can prove useful both to the academic community that seeks to unravel the complete gating mechanism of GLIC and to the pharmaceutical companies that search for new binding sites within the molecule for new drugs.

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This dissertation consists of four independent but related parts, each in a Chapter. The first part is an introductory. It serves as the background introduction and offer preparations for later parts. The second part discusses two population multivariate normal distributions with common covariance matrix. The goal for this part is to derive objective/non-informative priors for the parameterizations and use these priors to build up constructive random posteriors of the Kullback-Liebler (KL) divergence of the two multivariate normal populations, which is proportional to the distance between the two means, weighted by the common precision matrix. We use the Cholesky decomposition for re-parameterization of the precision matrix. The KL divergence is a true distance measurement for divergence between the two multivariate normal populations with common covariance matrix. Frequentist properties of the Bayesian procedure using these objective priors are studied through analytical and numerical tools. The third part considers the star-shape Gaussian graphical model, which is a special case of undirected Gaussian graphical models. It is a multivariate normal distribution where the variables are grouped into one "global" group of variable set and several "local" groups of variable set. When conditioned on the global variable set, the local variable sets are independent of each other. We adopt the Cholesky decomposition for re-parametrization of precision matrix and derive Jeffreys' prior, reference prior, and invariant priors for new parameterizations. The frequentist properties of the Bayesian procedure using these objective priors are also studied. The last part concentrates on the discussion of objective Bayesian analysis for partial correlation coefficient and its application to multivariate Gaussian models. / Ph. D.

Security threats to cyber-physical systems are targeting institutions and infrastructure around the world, and the frequency and severity of attacks are on the rise. Healthcare manufacturing, financial services, education, government, and transportation are among the industries that are the most lucrative targets for adversaries. Hacking is not just about companies, organizations, or banks; it also includes critical infrastructure. Wireless Sensors Networks, Vehicle-to-everything communication (V2X), Dynamic Message Signs (DMS), and Traffic Signal Controllers are among major Intelligent Transportation Systems (ITS) infrastructure that has already been attacked or remain vulnerable to hacking. ITS has been deployed with a focus on increasing efficiency and safety in the face of dramatic increases in travel demand. Although many studies have been performed and many security primitives have been proposed, there are significant concerns about flawless performance in a dynamic environment. A holistic security approach, in which all infrastructure performs within the satisfactory level of security remains undiscovered. Previously, hacking of road infrastructure was a rare event, however, in recent years, field devices such as DMS are hacked with higher frequency. The primary reason that transportation assets are vulnerable to cyber-attacks is due to their location. A more dramatic scenario occurs when hackers attempt to convey tampered instructions to the public. Analyzing traveler behavior in response to the hacked messages sign on the basis of empirical data is a vital step toward operating a secure and reliable transportation system. There may be room for improvement by policymakers and program managers when considering critical infrastructure vulnerabilities. With cybersecurity issues escalating every day, road users' safety has been neglected. This dissertation overcomes these challenges and contributes to the nascent but growing literature of Intelligent Transportation System (ITS) security impact-oriented risk assessment in threefold. • First, I employ a risk-based approach to conduct a threat assessment. This threat assessment performs a qualitative vulnerability-oriented threat analysis. The objective is to scrutinize safety, security, reliability, and operation issues that are prompted by a compromised Dynamic Message Signs (DMS). • Second, I examine the impact of drivers' attitudes and behaviors on compliance, route diversion behavior, and speed change behavior, under a compromised DMS. We aim to assess the determinants that are likely to contribute to drivers' compliance with forged information. To this extent, this dissertation evaluates drivers' behavior under different unauthentic messages to assess in-depth the impact of an adversarial attack on the transportation network. • Third, I evaluate distracted driving under different scenarios to assess the in-depth impact of an adversarial attack on the transportation network. To this extent, this dissertation examines factors that are contributing to the manual, visual, and cognitive distractions when drivers encountering fabricated advisory information at a compromised DMS. The results of this dissertation support the original hypothesis and indicate that with respect to the forged information drivers tend to (1) change their planned route, (2) become involved in distracting activities, and (3) change their choice speed at the presence of a compromised DMS. The main findings of this dissertation are outlined below: 1. The DMS security vulnerabilities and predisposing conditions allow adversaries to compromise ITS functionality. The risk-based approach of this study delivers the impact-likelihood matrix, which maps the adverse impacts of the threat events onto a meaningful, visual, matrix. DMS hacking adverse impacts can be categorized mainly as high-risk and medium-risk clusters. The safety, operational (i.e., monetary losses) and behavioral impacts are associated with a high-risk cluster. While the security, reliability, efficiency, and operational (i.e., congestion) impacts are associated with the medium-risk cluster. 2. Tech friendly drivers are more likely to change their route under a compromised DMS. At the same time, while they are acquiring new information, they need to lowering their speed to respond to the higher information load. Under realistic-fabricated information, about 65% of the subjects would depart from their current route. The results indicate that females and subjects with a higher driving experience are more likely to change their route. In addition, those subjects who are more sensitive to the DMS's traffic-related messages and those who use DMS under congested traffic condition are more likely to divert. Interestingly, individuals with lower education level, Asians, those who live in urban areas, and those with trouble finding their direction in new routes are less likely to pick another route rather the one they planned for. 3. Regardless of the DMS hacking scenarios, drivers would engage in at least one of the distractive activities. Among the distractive activities, cognitive distraction has the highest impact on the distracted driving likelihood. Meaning, there is a high chance that drivers think of something other than driving, look at surrounding traffic and scenery, or talk to other passengers regarding the forged information they saw on the DMS. Drivers who rely and trust in technology, and those who check traffic condition before starting their trips tend to become distracted. In addition, the result identified that at the presence of bogus information, drivers tend to slow down or stop in order to react to the DMS. That is, they would either (1) become involved in activities through the means of their phone, (2) they would mind wander, look around, and talk to a passenger about the sign, and (3) search for extra information by means of their vehicle's radio or internet. 4. Females, black individuals, subjects with a disability, older, and those with high trust in DMS are less likely to ignore the fabricated messages. In contrary, white, those who drive long hours, and those who see driving as a tedious task are more likely to ignore the bogus messages. Drivers who comply with traffic regulations and have a good driving record are likely to slow down under the tampered messages. Furthermore, female drivers and those who live in rural areas are more likely to slow down under fabricated advisory information. Furthermore, this dissertation identifies that planning for alternative route and involvement in distractive activities cause speed variation behaviors under the compromised DMS. This dissertation is the first to investigate the adverse impact of a compromised DMS on the road users and operators. I attempt to address the current gap in the literature by assessing and evaluating the impact of ITS security vulnerabilities. Broader impacts of this study include (1) to systematically raising awareness among policy-makers and engineers, (2) motivating further simulations and real-world experiments to investigate this matter further, (3) to systematically assessing the adverse impact of a security breach on transportation reliability and safety, and drivers' behavior, and (4) providing insights for system operators and decision-makers to prioritize the risk of a compromised DMS. Additionally, the outcome can be integrated with the nationwide connected vehicle and V2X implementations and security design. / Doctor of Philosophy / Security threats are targeting institutions and infrastructure around the world, and the frequency and severity of security attacks are on the rise. Healthcare manufacturing, financial services, education, government, and transportation are among the industries that are the most lucrative targets for adversaries. Hacking is not just about companies, organizations, or banks; it also includes critical infrastructure. Intelligent Transportation Systems have been deployed with a focus on increasing efficiency and safety in the face of dramatic increases in traffic volume. Although many studies have been performed and many security primitives have been proposed, there are significant concerns about flawless performance in a dynamic environment. A holistic security approach, in which all infrastructure performs within the satisfactory level of security remains undiscovered. Previously, hacking of road infrastructure was a rare event, however, in recent years, field devices, such as dynamic message signs, are hacked with higher frequency. The primary reason that transportation assets are vulnerable to cyber-attacks is that of their location in public. A more dramatic scenario occurs when hackers attempt to convey tampered instructions to the public. Analyzing traveler behavior in response to the hacked messages sign on the basis of empirical data is a vital step toward operating a secure and reliable transportation system. This study is the first to investigate the adversarial impact of a compromised message sign on the road users and operators. I attempt to address the current gap in the literature by assessing and evaluating the impact of ITS security vulnerabilities.