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This work describes development of a comprehensive methodology for analyzing vibro-acoustic and wear mechanisms in transmission systems. The thesis addresses certain gaps present in the fields of structure dynamics and abrasion mechanism and opens new areas for further research.
The paper attempts to understand new and relatively unexplored challenges like influences of wear on the dynamics of drive train. It also focuses on developing new techniques for analyzing the vibration and acoustic behavior of the drive unit structures and surrounding fluids respectively.
The developed methodology meets the requirements of both the complete system and component level modeling by using specially identified combination of different simulation techniques. Based on the created template model, a three-stage spur plus helical gearbox is constructed and simulated as an application example. In addition to the internal mechanical excitation mechanisms, the transmission model also includes the rotational and translational dynamics of the gears, shafts and bearings. It is followed by illustration of wear among the rotating components.
Different kinds of static and dynamic analyses are performed and coupled at various levels depending on the mechanical complexities involved. Furthermore, the structure dynamic vibration of the housing and the associated sound particle radiations are mapped into the surrounding fluid. Additionally, the approach for selection of the potential parameters for optimization is depicted. Final part focuses on the measurements of different system states used for validation of the model. In the end, results obtained from both simulations and experiments are analyzed and assessed for there respective performances.
The transcription factor Tal1 is a critical activator or repressor of gene expression in hematopoiesis and leukaemia. The mechanism by which Tal1 differentially influences transcription of distinct genes is not fully understood. Here we show that Tal1 interacts with the peptidylarginine deiminase IV (PADI4). We demonstrate that PADI4 can act as an epigenetic coactivator through influencing H3R2me2a. At the Tal1/PADI4 target gene IL6ST the repressive H3R2me2a mark triggered by PRMT6 is counteracted by PADI4, which augments the active H3K4me3 mark and thus increases IL6ST expression. In contrast, at the CTCF promoter PADI4 acts as a repressor. We propose that the influence of PADI4 on IL6ST transcription plays a role in the control of IL6ST expression during lineage differentiation of hematopoietic stem/progenitor cells. These results open the possibility to pharmacologically influence Tal1 in leukaemia.
Asset transaction prices sampled at high frequency are much staler than one might expect in the sense that they frequently lack new updates showing zero returns. In this paper, we propose a theoretical framework for formalizing this phenomenon. It hinges on the existence of a latent continuous-time stochastic process pt valued in the open interval (0; 1), which represents at any point in time the probability of the occurrence of a zero return. Using a standard infill asymptotic design, we develop an inferential theory for nonparametrically testing, the null hypothesis that pt is constant over one day. Under the alternative, which encompasses a semimartingale model for pt, we develop non-parametric inferential theory for the probability of staleness that includes the estimation of various integrated functionals of pt and its quadratic variation. Using a large dataset of stocks, we provide empirical evidence that the null of the constant probability of staleness is fairly rejected. We then show that the variability of pt is mainly driven by transaction volume and is almost unaffected by bid-ask spread and realized volatility.
Congenital lower urinary-tract obstruction (LUTO) is caused by anatomical blockage of the bladder outflow tract or by functional impairment of urinary voiding. About three out of 10,000 pregnancies are affected. Although several monogenic causes of functional obstruction have been defined, it is unknown whether congenital LUTO caused by anatomical blockage has a monogenic cause. Exome sequencing in a family with four affected individuals with anatomical blockage of the urethra identified a rare nonsense variant (c.2557C>T [p.Arg853∗]) in BNC2, encoding basonuclin 2, tracking with LUTO over three generations. Re-sequencing BNC2 in 697 individuals with LUTO revealed three further independent missense variants in three unrelated families. In human and mouse embryogenesis, basonuclin 2 was detected in lower urinary-tract rudiments. In zebrafish embryos, bnc2 was expressed in the pronephric duct and cloaca, analogs of the mammalian lower urinary tract. Experimental knockdown of Bnc2 in zebrafish caused pronephric-outlet obstruction and cloacal dilatation, phenocopying human congenital LUTO. Collectively, these results support the conclusion that variants in BNC2 are strongly implicated in LUTO etiology as a result of anatomical blockage.
This thesis explores a variety of methods of text quantification applicable in the field of educational text technology. Besides the cohort of existing linguistic, lexical, syntactic, and semantic text quantification methods, additional methods based on Bidirectional Encoder Representations from Transformers (BERT) are introduced and analysed. The model, developed in this thesis, is tested on a multilingual data composed of task descriptions used in Test of Understanding in College Economics (TUCE). Quantitative features extracted from raw textual data are analysed using an array of evaluation methods with the goal of finding the best predictors of the target variable - the rate of correct student responses in TUCE.
Event-by-event multiplicity fluctuations in nucleus-nucleus collisions from low SPS up to RHIC energies have been studied within the HSD transport approach. Fluctuations of baryonic number and electric charge also have been explored for Pb+Pb collisions at SPS energies in comparison to the experimental data from NA49. We find a dominant role of the fluctuations in the nucleon participant number for the final hadron multiplicity fluctuations and a strong influence of the experimental acceptance on the final results. Critical Point and Onset of Deconfinement - 4th International Workshop July 9 - 13, 2007 Darmstadt, Germany
The multiplicity fluctuations in A+A collisions at SPS and RHIC energies are studied within the HSD transport approach. We find a dominant role of the fluctuations in the nucleon participant number for the final fluctuations. In order to extract physical fluctuations one should decrease the fluctuations in the participants number. This can be done considering very central collisions. The system size dependence of the multiplicity fluctuations in central A+A collisions at the SPS energy range – obtained in the HSD and UrQMD transport models – is presented. The results can be used as a ‘background’ for experimental measurements of fluctuations as a signal of the critical point. Event-by-event fluctuations of the K/p , K/p and p/p ratios in A+A collisions are also studied. Event-by-event fluctuations of the kaon to pion number ratio in nucleus-nucleus collisions are studied for SPS and RHIC energies. We find that the HSD model can qualitatively reproduce the measured excitation function for the K/p ratio fluctuations in central Au+Au (or Pb+Pb) collisions from low SPS up to top RHIC energies. The forward-backward correlation coefficient measured by the STAR Collaboration in Au+Au collisions at RHIC is also studied. We discuss the effects of initial collision geometry and centrality bin definition on correlations in nucleus-nucleus collisions. We argue that a study of the dependence of correlations on the centrality bin definition as well as the bin size may distinguish between these ‘trivial’ correlations and correlations arising from ‘new physics’. 5th International Workshop on Critical Point and Onset of Deconfinement - CPOD 2009, June 08 - 12 2009 Brookhaven National Laboratory, Long Island, New York, USA
Background: Subarachnoid hemorrhage (SAH) is mainly caused by ruptured cerebral aneurysms but in up to 15% of patients with SAH no bleeding source could be identified. Our objective was to analyze patient characteristics, clinical outcome and prognostic factors in patients suffering from non-aneurysmal SAH.
Methods: From 1999 to 2009, data of 125 patients with non-aneurysmal SAH were prospectively entered into a database. All patients underwent repetitive cerebral angiography. Outcome was assessed according to the modified Rankin Scale (mRS) (mRS 0-2 favorable vs. 3-6 unfavorable). Also, patients were divided in two groups according to the distribution of blood in the CT scan (perimesencephalic and non-perimesencephalic SAH).
Results: 106 of the 125 patients were in good WFNS grade (I-III) at admission (85%). Overall, favorable outcome was achieved in 104 of 125 patients (83%). Favorable outcome was associated with younger age (P < 0.001), good admission status (P < 0.0001), and absence of hydrocephalus (P = 0.001).73 of the 125 patients suffered from perimesencephalic SAH, most patients (90%) were in good grade at admission, and 64 achieved favorable outcome.52 of the 125 patients suffered from non-perimesencephalic SAH and 40 were in good grade at admission. Also 40 patients achieved favorable outcome.
Conclusions: Patients suffering from non-aneurysmal SAH have better prognosis compared to aneurysm related SAH and poor admission status was the only independent predictor of unfavorable outcome in the multivariate analysis. Patients with a non-perimesencephalic SAH have an increased risk of a worse neurological outcome. These patients should be monitored attentively.
This thesis contributes to the field of machine learning with a specific focus on the methods for learning relations between the inputs. Learning relationships between images is the most common primitive in vision. There are many vision tasks in which relationships across images play an important role. Some of them are motion estimation, activity recognition, stereo vision, multi-view geometry and visual odometry. Many of such tasks mainly depend on motion and disparity cues, which are inferred based on the relations across multiple image pairs. The approaches presented in this thesis mainly deal with, but are not limited to, learning of the representations for motion and depth. This thesis by articles consists of five articles which present relational feature learning models along with their applications in computer vision. In the first article, we present an approach for encoding motion in videos. To this end, we show that the detection of spatial transformations can be viewed as detection of coincidence or synchrony between the given sequence of frames and a sequence of features which are related by the transformation we wish to detect. Learning to detect synchrony is possible by introducing "multiplicative interactions'' into the hidden units of single layered sparse coding models.
We show that the learned motion representations employed for the task of activity recognition achieve competitive performance on multiple benchmarks. Stereo vision is an important challenge in computer vision and useful for many applications in that field. In the second article, we extend the energy based learning models, which were previously used for motion encoding, to the context of depth perception. Given the common architecture of the models for encoding motion and depth, we show that it is possible to define a single model for learning a unified representation for both the cues. Our experimental results show that learning a combined representation for depth and motion makes it possible to achieve state-of-the-art performance at the task of 3-D activity analysis, and to perform better than the existing hand-engineered 3-D motion features. Autoencoder is a popular unsupervised learning method for learning efficient encoding for a given set of data samples. Typically, regularized autoencoders which are used to learn over-complete and sparse representations for the input data, were shown to fail on intrinsically high dimensional data like videos. In the third article, we investigate the reason for such a behavior. It can be observed that the regularized autoencoders typically learn negative hidden unit biases. We show that the learning of negative biases is the result of hidden units being responsible for both the sparsity and the representation of the input data. It is shown that, as a result, the behavior of the model resembles clustering methods which would require exponentially large number of features to model intrinsically high dimensional data. Based on this understanding, we propose a new activation function which decouples the roles of hidden layer and uses linear encoding. This allows to learn representations on data with very high intrinsic dimensionality. We also show that gating connections in the bi-linear models and the single layer models from articles one and two of this thesis can be thought of as a way to attain a linear encoding scheme which allows them to learn good representations on videos. Visual odometry is the task of inferring egomotion of a moving object from visual information such as images and videos. It can primarily be used for the task of localization and has many applications in the fields of robotics and navigation. The work in article four was motivated by the idea of using deep learning techniques, which are successful methods for many vision tasks, for visual odometry. The visual odometry task mainly requires inference of motion and depth information from visual input which can then be mapped to velocity and change in direction. We use relational feature models presented in the articles one and two for inferring a combined motion and depth representation from stereo video sequences. The combined representation is then mapped to discrete velocity and change in direction labels using convolutional neural networks. Our approach is an end-to-end deep learning-based architecture which uses a single type of computational model and learning rule. Preliminary results show that the architecture is capable of learning the mapping from input video to egomotion. Activity recognition is a challenging computer vision task with many real world applications. It is well know that it is a hard task to use computer vision research for real-time applications. In the fifth article of this thesis, we present a real-time activity recognition system based on deep learning based methods. Our approach uses energy based relational feature learning models for the computation of local motion features directly from videos. A bag-of-words over the local motion features is used for the analysis of activity in a given video sequence. We implement this system on a distributed computational platform and demonstrate its performance on the iCub robot. Using GPUs we demonstrate real time performance which makes the deployment of activity recognition systems in real world scenarios possible.
The prevention of tau protein aggregations is a therapeutic goal for the treatment of Alzheimer's disease (AD), and hydromethylthionine (HMT) (also known as leucomethylthioninium-mesylate [LMTM]), is a potent inhibitor of tau aggregation in vitro and in vivo. In two Phase 3 clinical trials in AD, HMT had greater pharmacological activity on clinical endpoints in patients not receiving approved symptomatic treatments for AD (acetylcholinesterase (AChE) inhibitors and/or memantine) despite different mechanisms of action. To investigate this drug interaction in an animal model, we used tau-transgenic L1 and wild-type NMRI mice treated with rivastigmine or memantine prior to adding HMT, and measured changes in hippocampal acetylcholine (ACh) by microdialysis. HMT given alone doubled hippocampal ACh levels in both mouse lines and increased stimulated ACh release induced by exploration of the open field or by infusion of scopolamine. Rivastigmine increased ACh release in both mouse lines, whereas memantine was more active in tau-transgenic L1 mice. Importantly, our study revealed a negative interaction between HMT and symptomatic AD drugs: the HMT effect was completely eliminated in mice that had been pre-treated with either rivastigmine or memantine. Rivastigmine was found to inhibit AChE, whereas HMT and memantine had no effects on AChE or on choline acetyltransferase (ChAT). The interactions observed in this study demonstrate that HMT enhances cholinergic activity in mouse brain by a mechanism of action unrelated to AChE inhibition. Our findings establish that the drug interaction that was first observed clinically has a neuropharmacological basis and is not restricted to animals with tau aggregation pathology. Given the importance of the cholinergic system for memory function, the potential for commonly used AD drugs to interfere with the treatment effects of disease-modifying drugs needs to be taken into account in the design of clinical trials.
Schätzungen der WHO zufolge waren 2015 weltweit rund 71 Millionen Menschen von einer chronischen Hepatitis C-Infektion betroffen. Die chronische Hepatitis C ist mit einem erhöhten Risiko für die Entstehung einer Leberzirrhose und eines hepatozellulären Karzinoms assoziiert. Die NS3/4A-Protease als zentraler Bestandteil der Replikationsmaschinerie des Virus spaltet das HCV-Polyprotein und ist in die Inaktivierung antiviraler Proteine involviert. Durch ihren maßgeblichen Einfluss auf die virale Fitness stellt sie einen entscheidenden Faktor für die chronische Persistenz des Virus im Wirtsorganismus dar. Die Protease ist auch eine wichtige Zielstruktur für spezifische antivirale Medikamente in der Behandlung der chronischen Hepatitis C. Der natürlich vorkommende Polymorphismus Q80K in der NS3/4A-Protease ist bei bis zu 47 % der Patienten schon vor Therapiebeginn feststellbar, insbesondere beim Genotyp 1a. Q80K führt zum Therapieversagen bei makrozyklischen Proteaseinhibitoren, insbesondere Simeprevir. Phylogenetische Analysen konnten zeigen, dass 96 % aller HCV-Gensequenzen mit Q80K von einem gemeinsamen, genetischen Vorfahren abstammen und sich die Mutation seit Mitte des 20. Jahrhunderts scheinbar stabil ausgehend vom nordamerikanischen Kontinent etabliert hat. Daneben wurden mit A91S/T und S174N sogenannte second site-Austausche identifiziert, die assoziiert mit Q80K vorkommen. Ziel dieser Arbeit war es herauszufinden, welchen Einfluss diese second site-Austausche auf die Enzymaktivität und Proteinfaltung der Protease haben und ob sie mögliche Veränderungen durch den Q80K-Polymorphismus kompensieren. Nach Expression und Aufreinigung der NS3/4A-Protease wurden die Effekte von Q80K, A91S/T und S174N auf die Enzymaktivität und Thermostabilität mittels fluoreszenzbasierter Verfahren untersucht und im Zusammenhang mit einer in silico-3D-Strukturanalyse der Protease interpretiert. Es zeigte sich, dass A91S/T und S174N jeweils zu einer Angleichung der Thermostabilität des Proteins an den Wildtyp führen und somit Defizite in der Faltung der Protease durch Q80K kompensiert werden. Aufgrund der experimentellen Daten und der Topografie dieser Austausche innerhalb der NS3-Protease-Helikase-Struktur ist von indirekten Effekten der second site-Austausche auf die replikative Fitness der Virusvarianten auszugehen. Die hier charakterisierten Austausche in der NS3/4A-Protease tragen durch eine Stabilisierung der Proteinfaltung kritisch zur Stabilität des Q80K-Polymorphismus im Proteasegen des HCV Genotyp 1a bei.
Mapping cortical brain asymmetry in 17,141 healthy individuals worldwide via the ENIGMA Consortium
(2017)
Motivated by the on-going discussion on the nature of magnetism in the quantum Ising chain CoNb2O6, we present a first-principles-based analysis of its exchange interactions by applying an \textit{ab initio} approach with additional modelling that accounts for various drawbacks of a purely density functional theory ansatz. With this method we are able to extract and understand the origin of the magnetic couplings under inclusion of all symmetry-allowed terms, and to resolve the conflicting model descriptions in CoNb2O6. We find that the twisted Kitaev chain and the transverse-field ferromagnetic Ising chain views are mutually compatible, although additional off-diagonal exchanges are necessary to provide a complete picture. We show that the dominant exchange interaction is a ligand-centered exchange process - involving the eg electrons -, which is rendered anisotropic by the low-symmetry crystal fields environments in CoNb2O6, giving rise to the dominant Ising exchange, while the smaller bond-dependent anisotropies are found to originate from d−d kinetic exchange processes involving the t2g electrons. We demonstrate the validity of our approach by comparing the predictions of the obtained low-energy model to measured THz and inelastic neutron scattering spectra.
The marine hydrocarbonoclastic bacterium Alcanivorax borkumensis is well known for its ability to successfully degrade various mixtures of n-alkanes occurring in marine oil spills. For effective growth on these compounds, the bacteria possess the unique capability not only to incorporate but also to modify fatty intermediates derived from the alkane degradation pathway. High efficiency of both these processes provides better competitiveness for a single bacteria species among hydrocarbon degraders. To examine the efficiency of A. borkumensis to cope with different sources of fatty acid intermediates, we studied the growth rates and membrane fatty acid patterns of this bacterium cultivated on diesel, biodiesel and rapeseed oil as carbon and energy source. Obtained results revealed significant differences in both parameters depending on growth substrate. Highest growth rates were observed with biodiesel, while growth rates on rapeseed oil and diesel were lower than on the standard reference compound (hexadecane). The most remarkable observation is that cells grown on rapeseed oil, biodiesel, and diesel showed significant amounts of the two polyunsaturated fatty acids linoleic acid and linolenic acid in their membrane. By direct incorporation of these external fatty acids, the bacteria save energy allowing them to degrade those pollutants in a more efficient way. Such fast adaptation may increase resilience of A. borkumensis and allow them to strive and maintain populations in more complex hydrocarbon degrading microbial communities.
In der vorliegenden Arbeit wurde der tageszeitkorrelierte Serotonin-Gehalt des SCO, sowie die Expression der 5-HT1A- und 5-HT2A-Rezeptoren und die Synthese- bzw. Sekretionsleistung des SCO bei Goldhamstern untersucht. Serotonin entfaltet im SCO des Goldhamsters eine inhibitorische Wirkung und hemmt die Sezernierungsrate von Glykoproteinen, die den RF formen. Dies bestätigt die Tatsache, dass mit steigender Rezeptorausprägung die Immunreaktivität für AFRU abnimmt. Ob Serotonin beim Hamster auch auf die Synthese von Glykoproteinen wirkt, muss nachfolgend geklärt werden, da in unserem Versuchsaufbau lediglich die Glykoprotein-Sezernierung untersucht wurde. Aussagen bezüglich der Auswirkung von Serotonin auf die Synthese und Sezernierung von löslichen Komponenten des SCO konnten bei dem von uns verwendeten Versuchsaufbau nicht gemacht werden. Deren mögliche Funktionen bleiben noch fraglich und eröffnen neue Optionen. Geklärt ist nun auch die quantitative Relation von 5-HT1A- und 5-HT2A-Rezeptoren im SCO. Es sind deutlich mehr 5-HT1A-Rezeptoren exprimiert. Dies lässt darauf schließen, dass Serotonin im SCO einen entscheidenden Einfluss auf die Glykoprotein-Synthese oder -Sekretion hat. Die tageszeitkorrelierte Rezeptorausprägung muss diskutiert werden. Sie ist tageszeitkorreliert relativ konstant, fraglich bleibt jedoch, wieso die Rezeptorausprägung im zweiten Abschnitt der Tiefschlafphase der Tiere abnimmt, obwohl hier der serotonerge Input weiterhin hoch sein müsste, um in der Aktivitätsphase wieder abzunehmen. Wahrscheinlich ist die Erklärung hierfür in den Expressionsmechanismen der G-Protein-gekoppelten Rezeptoren selbst zu finden. Welche Proteine die geschwindigkeitsbestimmenden Faktoren der 5-HT1A- und 5-HT2A-Rezeptorexpression sind, bleibt zu klären und auch ob sich der Verdacht bestätigt, dass die 5-HT1A-Rezeptorausprägung deutlich schneller voran geht als die der 5-HT2A-Rezeptoren und damit mehr 5-HT1A--Rezeptoren zur Prezeption von Serotonin zur Verfügung stehen. Mit dieser tageszeitkorrelierten Ausprägung schützt sich das SCO unter Umständen vor einer völligen Entleerung der Glykoprotein-Speicher unter erheblichem Serotonin-Einfluss während der Schlafphase. Dieser Aspekt und dessen mögliche Folgen müssen weiter untersucht werden. Weiterhin bleibt fraglich, wie die relative Konstanz in der Glykoprotein-Ausschüttung am Tag und in der Nacht etabliert werden kann, da die Serotonin-Ausschüttung der Raphe-Kerne am SCO nachweislich einer periodischen Rhythmik unterworfen ist. Neben dem Nucleus raphe dorsalis und dem Nucleus raphe medianus ist der Einfluss weiterer Aktivitätszentren auf das SCO denkbar. Auch eine Co-Stimulation der ependymalen und hypendymalen SCO-Zellen mit anderen Transmitterklassen ist möglich und teilweise auch bewiesen. Beide genannten Aspekte könnten Teil eines Feedback-Mechanismus sein, der das SCO vor vollständiger Entspeicherung schützt.
Background: Athletic competition has been a source of interest to the scientific community for many years, as a surrogate of the limits of human ambulatory ability. One of the remarkable things about athletic competition is the observation that some athletes suddenly reduce their pace in the mid-portion of the race and drop back from their competitors. Alternatively, other athletes will perform great accelerations in mid-race (surges) or during the closing stages of the race (the endspurt). This observation fits well with recent evidence that muscular power output is regulated in an anticipatory way, designed to prevent unreasonably large homeostatic disturbances.
Principal Findings: Here we demonstrate that a simple index, the product of the momentary Rating of Perceived Exertion (RPE) and the fraction of race distance remaining, the Hazard Score, defines the likelihood that athletes will change their velocity during simulated competitions; and may effectively represent the language used to allow anticipatory regulation of muscle power output.
Conclusions: These data support the concept that the muscular power output during high intensity exercise performance is actively regulated in an anticipatory manner that accounts for both the momentary sensations the athlete is experiencing as well as the relative amount of a competition to be completed.