3,380 research outputs found

    Differential spectrum modeling and sensitivity for keV sterile neutrino search at KATRIN

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    Starting in 2026, the KATRIN experiment will conduct a high-statistics measurement of the differential tritium β\beta-spectrum to energies deep below the kinematic endpoint. This enables the search for keV sterile neutrinos with masses less than the kinematic endpoint energy m4E0=18.6keVm_\mathrm{4} \leq E_0 = 18.6\,\mathrm{keV}, aiming for a statistical sensitivity of Ue42=sin2θ106|U_\mathrm{e4}|^2=\sin^2\theta\sim 10^{-6} for the mixing amplitude. The differential spectrum is obtained by decreasing the retarding potential of KATRIN\u27s main spectrometer, and by determining the β\beta-electron energies by their energy deposition in the new TRISTAN SDD array. In this mode of operation, the existing integral model of the tritium spectrum is insufficient, and a novel differential model is developed in this work. The new model (TRModel) convolves the differential tritium spectrum using responese matrices to predict the energy spectrum of registered events after data acquisition. Each response matrix encodes the spectral spectral distrortion from individual experimental effects, which depend on adjustable systematic parameters. This approach allows to efficiently assess the sensitivity impact of each systematics individually or in combination with others. The response matrices are obtained from monte carlo simulations, numerical convolution, and analytical computation. In this work, the sensitivity impact of 20 systematic parameters is assessed for the TRISTAN Phase-1 measurement for which nine TRISTAN SDD modules are integrated into the KATRIN beamline. Furthermore, it is demonstrated that the sensitivity impact is significantly mitigated with several beamline field adjustments and minimal hardware modifications

    Proceedings of SIRM 2023 - The 15th European Conference on Rotordynamics

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    It was our great honor and pleasure to host the SIRM Conference after 2003 and 2011 for the third time in Darmstadt. Rotordynamics covers a huge variety of different applications and challenges which are all in the scope of this conference. The conference was opened with a keynote lecture given by Rainer Nordmann, one of the three founders of SIRM “Schwingungen in rotierenden Maschinen”. In total 53 papers passed our strict review process and were presented. This impressively shows that rotordynamics is relevant as ever. These contributions cover a very wide spectrum of session topics: fluid bearings and seals; air foil bearings; magnetic bearings; rotor blade interaction; rotor fluid interactions; unbalance and balancing; vibrations in turbomachines; vibration control; instability; electrical machines; monitoring, identification and diagnosis; advanced numerical tools and nonlinearities as well as general rotordynamics. The international character of the conference has been significantly enhanced by the Scientific Board since the 14th SIRM resulting on one hand in an expanded Scientific Committee which meanwhile consists of 31 members from 13 different European countries and on the other hand in the new name “European Conference on Rotordynamics”. This new international profile has also been emphasized by participants of the 15th SIRM coming from 17 different countries out of three continents. We experienced a vital discussion and dialogue between industry and academia at the conference where roughly one third of the papers were presented by industry and two thirds by academia being an excellent basis to follow a bidirectional transfer what we call xchange at Technical University of Darmstadt. At this point we also want to give our special thanks to the eleven industry sponsors for their great support of the conference. On behalf of the Darmstadt Local Committee I welcome you to read the papers of the 15th SIRM giving you further insight into the topics and presentations

    Mathematical Problems in Rock Mechanics and Rock Engineering

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    With increasing requirements for energy, resources and space, rock engineering projects are being constructed more often and are operated in large-scale environments with complex geology. Meanwhile, rock failures and rock instabilities occur more frequently, and severely threaten the safety and stability of rock engineering projects. It is well-recognized that rock has multi-scale structures and involves multi-scale fracture processes. Meanwhile, rocks are commonly subjected simultaneously to complex static stress and strong dynamic disturbance, providing a hotbed for the occurrence of rock failures. In addition, there are many multi-physics coupling processes in a rock mass. It is still difficult to understand these rock mechanics and characterize rock behavior during complex stress conditions, multi-physics processes, and multi-scale changes. Therefore, our understanding of rock mechanics and the prevention and control of failure and instability in rock engineering needs to be furthered. The primary aim of this Special Issue “Mathematical Problems in Rock Mechanics and Rock Engineering” is to bring together original research discussing innovative efforts regarding in situ observations, laboratory experiments and theoretical, numerical, and big-data-based methods to overcome the mathematical problems related to rock mechanics and rock engineering. It includes 12 manuscripts that illustrate the valuable efforts for addressing mathematical problems in rock mechanics and rock engineering

    Decision-making with gaussian processes: sampling strategies and monte carlo methods

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    We study Gaussian processes and their application to decision-making in the real world. We begin by reviewing the foundations of Bayesian decision theory and show how these ideas give rise to methods such as Bayesian optimization. We investigate practical techniques for carrying out these strategies, with an emphasis on estimating and maximizing acquisition functions. Finally, we introduce pathwise approaches to conditioning Gaussian processes and demonstrate key benefits for representing random variables in this manner.Open Acces

    Geometric Data Analysis: Advancements of the Statistical Methodology and Applications

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    Data analysis has become fundamental to our society and comes in multiple facets and approaches. Nevertheless, in research and applications, the focus was primarily on data from Euclidean vector spaces. Consequently, the majority of methods that are applied today are not suited for more general data types. Driven by needs from fields like image processing, (medical) shape analysis, and network analysis, more and more attention has recently been given to data from non-Euclidean spaces–particularly (curved) manifolds. It has led to the field of geometric data analysis whose methods explicitly take the structure (for example, the topology and geometry) of the underlying space into account. This thesis contributes to the methodology of geometric data analysis by generalizing several fundamental notions from multivariate statistics to manifolds. We thereby focus on two different viewpoints. First, we use Riemannian structures to derive a novel regression scheme for general manifolds that relies on splines of generalized Bézier curves. It can accurately model non-geodesic relationships, for example, time-dependent trends with saturation effects or cyclic trends. Since Bézier curves can be evaluated with the constructive de Casteljau algorithm, working with data from manifolds of high dimensions (for example, a hundred thousand or more) is feasible. Relying on the regression, we further develop a hierarchical statistical model for an adequate analysis of longitudinal data in manifolds, and a method to control for confounding variables. We secondly focus on data that is not only manifold- but even Lie group-valued, which is frequently the case in applications. We can only achieve this by endowing the group with an affine connection structure that is generally not Riemannian. Utilizing it, we derive generalizations of several well-known dissimilarity measures between data distributions that can be used for various tasks, including hypothesis testing. Invariance under data translations is proven, and a connection to continuous distributions is given for one measure. A further central contribution of this thesis is that it shows use cases for all notions in real-world applications, particularly in problems from shape analysis in medical imaging and archaeology. We can replicate or further quantify several known findings for shape changes of the femur and the right hippocampus under osteoarthritis and Alzheimer's, respectively. Furthermore, in an archaeological application, we obtain new insights into the construction principles of ancient sundials. Last but not least, we use the geometric structure underlying human brain connectomes to predict cognitive scores. Utilizing a sample selection procedure, we obtain state-of-the-art results

    Gut-brain interactions affecting metabolic health and central appetite regulation in diabetes, obesity and aging

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    The central aim of this thesis was to study the effects of gut microbiota on host energy metabolism and central regulation of appetite. We specifically studied the interaction between gut microbiota-derived short-chain fatty acids (SCFAs), postprandial glucose metabolism and central regulation of appetite. In addition, we studied probable determinants that affect this interaction, specifically: host genetics, bariatric surgery, dietary intake and hypoglycemic medication.First, we studied the involvement of microbiota-derived short-chain fatty acids in glucose tolerance. In an observational study we found an association of intestinal availability of SCFAs acetate and butyrate with postprandial insulin and glucose responses. Hereafter, we performed a clinical trial, administering acetate intravenously at a constant rate and studied the effects on glucose tolerance and central regulation of appetite. The acetate intervention did not have a significant effect on these outcome measures, suggesting the association between increased gastrointestinal SCFAs and metabolic health, as observed in the observational study, is not paralleled when inducing acute plasma elevations.Second, we looked at other determinants affecting gut-brain interactions in metabolic health and central appetite signaling. Therefore, we studied the relation between the microbiota and central appetite regulation in identical twin pairs discordant for BMI. Second, we studied the relation between microbial composition and post-surgery gastrointestinal symptoms upon bariatric surgery. Third, we report the effects of increased protein intake on host microbiota composition and central regulation of appetite. Finally, we explored the effects of combination therapy with GLP-1 agonist exenatide and SGLT2 inhibitor dapagliflozin on brain responses to food stimuli

    Exoteric effects at nanoscopic interfaces - Uncommon negative compressibility of nanoporous materials and unexpected cavitation at liquid/liquid interfaces

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    This PhD thesis is devoted to the investigation of some peculiar effects happening at nanoscopic interfaces between immiscible liquids or liquids and solids via molecular dynamics simulations. The study of the properties of interfaces at a nanoscopic scale is driven by the promise of many interesting technological applications, including: a novel technology for developing both eco-friendly energy storage devices in the form of mechanical batteries, as well as energy dissipation systems and, in particular, shock absorbers for the automotive market; biomedical applications related to cavitation, such as High-Intensity Focused Ultrasound (HIFU) ablation of cancer tissues and localised drug delivery, and many more. The kinetics of phenomena taking places at these scales is typically determined by large free-energy barriers separating the initial and final states, and even intermediate metastable states, when they are present. Because of such barriers, the phenomena we are interested in are "rare events", i.e. the system attempts the crossing of the barrier(s) many times before finally succeeding when an energy fluctuation makes it possible. At the same time, the magnitude of the barrier is determined by the energetics and dynamics of atoms, which forces us to model the system by taking into account both the femtosecond atomistic timescale and the timescale of the relevant phenomena, typically exceeding the former by several orders of magnitude. These longer timescales are inaccessible to standard molecular dynamics, so, in order to tackle this issue, advanced MD techniques need to be employed. The thesis is divided into two parts, corresponding to the main lines of research investigated, which are (I) the interfaces between water and complex nanoporous solids, and (II) planar solid-liquid and liquid-liquid interfaces. Anticipating some results, atomistic simulations helped uncovering the microscopic mechanism behind the (incredibly rare!) giant negative compressibility exhibited by the ZIF-8 metal organic framework (MOF) upon water intrusion. Molecular dynamics simulations also supported experimental results showing how it is possible to change the intermediate intrusion-extrusion performance of ZIF-8 by changing its grain morphology and arrangement, from a fine powder to compact monolith. Free-energy MD calculations allowed to explain the exceptional stability of surface nanobubbles in water, at undersaturated conditions, on a surprisingly wide variety of substrates, characterized by disparate hydrophobicities and gas affinities; and yet, how they catastrophically destabilize in organic solvents. Finally, through simulations, some light was shed upon the working mechanism behind the novelly discovered phenomenon of how the interface between two immiscible liquids can act as a nucleation site for cavitation

    Brain-based versus external memory stores: influencing factors and underlying neural correlates

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    Technological advancements provide people with more opportunity to rely on external resources to support cognitive processes. These associated processes are defined as cognitive offloading (Risko & Gilbert, 2016). The current thesis aims to explore the psychological processes and neural mechanism of cognitive offloading. In Experiment 1, we developed an ‘optimal reminder’ task by calculating whether people were biased towards using reminders or their own memory, compared with an optimal strategy. If participants were biased, the second purpose of Experiment 1 was to assess whether such bias could be reduced through metacognitive advice. Results revealed people were biased towards setting reminders, and the bias was eliminated by metacognitive advice. Experiment 2 used the optimal reminder task to evaluate the effect of ageing on cognitive offloading. This showed that older people set more reminders than younger adults, but were less biased towards setting reminders when the impaired memory performance of older people was taken into account. Experiment 3 investigated the effects of three factors: delay length, metacognitive judgement, and clock revealability, on cognitive offloading in a time-based task (e.g. remembering to press a specific button after 10 seconds). We found participants’ use of reminders was based on both the characteristics of the task (i.e., delay and clock revealability) and metacognitive judgements. Experiment 4 used fMRI to evaluate whether an instruction to offload information to an external reminder triggered different brain activity to an instruction to forget or remember. Results showed that brain activity associated with an offload cue was similar, but not identical, to brain activity associated with a forget cue. We conclude by suggesting possible applications of the results to finding methods for improving intention offloading and avoiding memory failures
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