Miracle-dz/UniFAR-FTUs huggingface dataset:
PHENOMENOLOGICAL STUDY OF THE MINIMAL R-SYMMETRIC SUPERSYMMETRIC STANDARD MODEL

The Standard Model (SM) of particle physics gives a comprehensive description of numerous phenomena concerning the fundamental components of nature. Still, open questions and a clouded understanding of the underlying structure remain. Supersymmetry is a well motivated extension that may account for the observed density of dark matter in the universe and solve the hierarchy problem of the SM. The minimal supersymmetric extension of the SM (MSSM) provides solutions to these challenges. Furthermore, it predicts new particles in reach of current experiments. However, the model has its own theoretical challenges and is under fire from measurements provided by the Large Hadron Collider (LHC). Nevertheless, the concept of supersymmetry has an elegance which not only shines in the MSSM. Hence, it is also of interest to examine non-minimal supersymmetric models. They have benefits similar to the MSSM and may solve its shortcomings. R-symmetry is the only global symmetry allowed that does not commutate with supersymmetry and Lorentz symmetry. Thus, extending a supersymmetric model with R-symmetry is a theoretically well motivated endeavor to achieve the complete symmetry content of a field theory. Such a model provides a natural explanation for non-discovery in the early runs of the LHC and leads to further predictions distinct from those of the MSSM. The work described in this thesis contributes to the effort by studying the minimal R-symmetric supersymmetric extension of the SM (MRSSM). Important aspects of its physics and the dependence of observables on the parameter space of the MRSSM are investigated. The discovery of a scalar particle compatible with the Higgs boson of the SM at the LHC was announced in 2012. It is the first and crucial task of this thesis to understand the underlying mechanisms leading to the correct Higgs boson mass prediction in the MRSSM. Then, the relevant regions of parameter space are investigated and it is shown that they are also in agreement with other Higgs observables. Another observable that is measured with great accuracy and especially sensitive to corrections from additional supersymmetric states is the mass of the W boson. Contributing effects within the MRSSM are identified and their dependency on the model parameters is studied. The presence of a stable supersymmetric particle as candidate for dark matter is a prediction of the MRSSM. The interplay of the relevant processes generating the correct abundance of dark matter in the universe and explaining the non-discovery by direct searches is investigated. Moreover, results of Run 1 of the LHC are used to study the electroweak MRSSM sector. This leads to a classification of viable regions of parameter space consistent with dark matter and LHC constraints. In the last part of this thesis the different observables are analyzed in coherence. This allows to identify valid regions of parameter space and highlights promising predictions of the MRSSM for the coming runs of the LHC and other experiments.
MULTIPLE-FACTOR ANALYSIS OF THE DYNAMIC INTERACTION BETWEEN RAILROAD CARS AND JOINT IRREGULARITY

Mechanical models of “railroad car-track” transport system for each phase of motion are developed. Particularities of dynamic interaction between the four-axle car and the track are studied by considering four phases of motion over joint irregularity. Methods for solving differential equations of the discretecontinuous system fluctuation are developed. Numerical analysis is used to determine deflections of the trailing rail under the first sleeper for each phase of motion depending on motion phases, and car load and speed.
Coordination on Networks

We study a coordination game among agents on a network, choosing whether or not to take an action that yields value increasing in the actions of neighbors. In a standard global game setting, players receive noisy information of the technology's common state-dependent value. We show the existence and uniqueness of a pure equilibrium in the noiseless limit. This equilibrium partitions players into coordination sets, within members take a common cutoff strategy and are path connected. We derive an algorithm for calculating limiting cutoffs, and provide necessary and sufficient conditions for agents to inhabit the same coordination set. The strategic effects of perturbations to players' underlining values are shown to spread throughout but be contained within the perturbed players' coordination sets.
SCALING ANALYSIS AND SIMULATION OF STABLY STRATIFIED FLOWS

Strongly stratified turbulent flows have been analysed and simulated. Scaling analysis has been applied to the governing equations and suggests the existence of two regimes with different dynamics. The determing parameter is R = ReF 2 h , where Re and Fh are the Reynolds number and horizontal Froude number, respectively. If R À 1, viscous effects are unimportant and three-dimensional but strongly anisotropic turbulence with a forward energy cascade can develop. The vertical length scale lv scales in this case as lv ∼ U/N (U is a horizontal velocity scale and N is the Brunt-Väisälä frequency). If R ¿ 1, the dynamics of the flow is determined by a balance between vertical viscous shearing and horizontal inertial forces. The vertical length scales behaves as lv ∼ lhRe −1/2 and is thus independent of the stratification strength. Direct numerical simulations with various values of Re and Fh have been carried and are consistent with the results of the scaling analysis. Horizontal one-dimensional spectra have been computed and show an approximate k −5/3 h range when R À 1 and very steep slopes when R ¿ 1. A more comprehensive discussion of the scaling analysis and a large series of DNS of stratified turbulent flows are presented in Brethouwer et al. (2007).
Person re-identification across aerial and ground-based cameras by deep feature fusion

Person re-identification is the task of correctly matching visual appearances of the same person in image or video data while distinguishing appearances of different persons. The traditional setup for re-identification is a network of fixed cameras. However, in recent years mobile aerial cameras mounted on unmanned aerial vehicles (UAV) have become increasingly useful for security and surveillance tasks. Aerial data has many characteristics different from typical camera network data. Thus, re-identification approaches designed for a camera network scenario can be expected to suffer a drop in accuracy when applied to aerial data. In this work, we investigate the suitability of features, which were shown to give robust results for re- identification in camera networks, for the task of re-identifying persons between a camera network and a mobile aerial camera. Specifically, we apply hand-crafted region covariance features and features extracted by convolu- tional neural networks which were learned on separate data. We evaluate their suitability for this new and as yet unexplored scenario. We investigate common fusion methods to combine the hand-crafted and learned features and propose our own deep fusion approach which is already applied during training of the deep network. We evaluate features and fusion methods on our own dataset. The dataset consists of fourteen people moving through a scene recorded by four fixed ground-based cameras and one mobile camera mounted on a small UAV. We discuss strengths and weaknesses of the features in the new scenario and show that our fusion approach successfully leverages the strengths of each feature and outperforms all single features significantly.
Converging on the Initial Mass Function of Stars

Understanding the origin of stellar masses—the initial mass function (IMF)— remains one of the most challenging problems in astrophysics. The IMF is a key ingredient for simulations of galaxy formation and evolution, and is used to calibrate star formation relations in extra-galactic observations. Modeling the IMF directly in hydrodynamical simulations has been attempted in several previous studies, but the most important processes that control the IMF remain poorly understood. This is because predicting the IMF from direct hydrodynamical simulations involves complex physics such as turbulence, magnetic fields, radiation feedback and mechanical feedback, all of which are difficult to model and the methods used have limitations in terms of accuracy and computational efficiency. Moreover, a physical interpretation of the simulated IMFs requires a numerically converged solution at high resolution, which has so far not been convincingly demonstrated. Here we present a resolution study of star cluster formation aimed at producing a converged IMF. We compare a set of magnetohydrodynamical (MHD) adaptive-mesh-refinement simulations with three different implementations of the thermodynamics of the gas: 1) with an isothermal equation of state (EOS), 2) with a polytropic EOS, and 3) with a simple stellar heating feedback model. We show that in the simulations with an isothermal or polytropic EOS, the number of stars and their mass distributions depend on the numerical resolution. By contrast, the simulations that employ the simple radiative feedback module demonstrate convergence in the number of stars formed and in their IMFs.
On the elementary theories of the Muchnik and Medvedev lattices of Π 0 1 classes

by Joshua A. Cole Recently, researchers in the foundations of mathematics have become interested in the distributive lattices Pw and Ps, the study of which is a major part of the field of “mass problems. ” In general, a mass problem U is a subset of ω (Baire space). We define U ≤s V if there is an index e for a computable functional so that ∀f ∈ V(Φe ∈ U). If we do not require the same e for every f , we get a “weak” version: U ≤w V if for all f ∈ V there is an e so that Φe ∈ U . The relations≤s and≤w naturally induce equivalence relations≡s and≡w. We define Ps to be the collection of ≡s degrees of nonempty Π1 subsets of 2 (Cantor space); similarly, we define Pw to be the collection of ≡w degrees of nonempty Π1 subsets of 2. An important open question is whether Pw is dense. The result of Chapter 2 is that the embedding of the free distributive lattice on countably many generators into Ps can be done densely. The way it is done gives indirect evidence that the kinds of priority arguments that show the density of Ps are probably not strong enough to show the density of Pw. The result of Chapter 3 applies these priority arguments to show the decidability of the elementary ∀∃-theory of Ps as a partial order. The result of Chapter 5 is that certain index sets related to Pw are Joshua A. Cole Π1-complete. This leads to a conjecture that the Turing degree of its elementary theory is as high as possible.
Developing a Convective-Scale EnKF Data Assimilation System for the Canadian MEOPAR Project

AbstractThis study discusses the construction of a high-resolution ensemble Kalman filter system (the HREnKF) developed for the Marine Environmental Observation Prediction and Response (MEOPAR) network. The HREnKF runs at a horizontal resolution of 2.5 km and is intended to provide forecasts at lead times up to 12 h. This system was adapted from the global EnKF system in operation at Environment and Climate Change Canada. As a first development step, only the most necessary modifications have been implemented. The changes include an hourly cycling frequency, smaller localization radii, and the explicit representation of microphysical processes. To assess its performance and orient future developments, the HREnKF was continuously cycled for a period of 12 days. Verification against surface observations reveals that the skill of the forecasts initialized from the HREnKF is comparable to that of control forecasts also integrated at a resolution of 2.5 km. A key component of this study is the comparison of co.
Mapping rice extent and cropping scheme in the Mekong Delta using Sentinel-1A data

ABSTRACT Synthetic aperture radar (SAR)-based multi-temporal backscatter analysis is a common approach that has been widely used for rice mapping. Co-polarized C-band microwave backscatter (HH or VV) and the co-polarization ratio (HH/VV) are the most commonly used data sets for rice mapping due to their high data availability while the utilization of cross-polarized backscatter (HV or VH) has received less attention. In this study, Sentinel 1A time series – acquired in the dual-polarized (VV/VH) Interferometric Wide (IW) swath mode during the spring growing season (October 2015 to March 2016) in the Mekong Delta – were used to analyse the relationship between the growing cycle of rice plants and the temporal variation of SAR backscatter at different polarizations. Results show that VH backscatter is more sensitive to rice growth than VV backscatter. Several vegetation phenological parameters including beginning date, heading date and the length of the growing season were extracted from the VH backscatter time series. A decision tree approach was applied to delineate rice-cultivated areas based on seasonal phenological parameters. The classification result was validated against a 2015 land use map. The overall classification accuracy is 87.2% (kappa coefficient – κ = 0.71). In addition, the SAR-derived rice area was compared against ground statistical data at the provincial level (coefficient of determination R2 = 0.98).
Irreducible weight modules for the Virasoro-like algebra and its q-analog

ABSTRACT In this paper, using Larsson’s functor with irreducible 𝔰𝔩2-modules V, we construct a class of ℤ2-graded modules for the Virasoro-like algebra and its q-analogs. We determine the irreducibility of these modules for finite-dimensional or infinite-dimensional V using a unified method. In particular, these modules provide new irreducible weight modules with infinite-dimensional weight spaces for the corresponding algebras.
1D contaminant transport using element free Galerkin method with irregular nodes

The present study deals with the numerical modelling for the one dimensional contaminant transport through saturated homogeneous and stratified porous media using meshfree method. A numerical algorithm based on element free Galerkin method is developed. A one dimensional form of the advective-diffusive transport equation for homogeneous and stratified soil is considered for the analysis using irregular nodes. A Fortran program is developed to obtain numerical solution and the results are validated with the available results in the literature. A detailed parametric study is conducted to examine the effect of certain key parameters. Effect of change of dispersion, velocity, porosity, distribution coefficient and thickness of layer is studied on the concentration of the contaminant
A NOTE ON INTUITIONISTIC FUZZY MAPPINGS

In this paper, the concept of intuitionistic fuzzy mapping as a gen- eralization of fuzzy mapping is presented, and its' relationship with intuitionis- tic fuzzy relations is derived. Moreover, some basic operations of intuitionistic fuzzy mappings are dened, hence we can conclude that all of intuitionistic fuzzy mappings constitute a soft algebra with respect to these operations. Af- terwards, the Atanassov's operator is applied to intuitionistic fuzzy mappings and the corresponding properties are examined. Finally, the decomposition and representation theorems of intuitionistic fuzzy mappings are established.
Head related transfer function experiment and modeling

Disclaimer This document contains a student thesis (bachelor's or master's), as authored by a student at Eindhoven University of Technology. Student theses are made available in the TU/e repository upon obtaining the required degree. The grade received is not published on the document as presented in the repository. The required complexity or quality of research of student theses may vary by program, and the required minimum study period may vary in duration.
New parametrization of cosmic neutrino oscillations

A new parameterization of neutrinos oscillations in vacuum, assuming the conventional three flavor scheme, is proposed and discussed. Applications of this parameterization are considered, that concern the study of the flavor ratios, of their uncertainties, the expectations for the signal due to Glashow resonance. It is shown that a Gaussian treatment describes to a good level of approximation the effects of the uncertainties on the mixing angles and on the CP violating phase. The recently obtained agreement of observations with the hypothesis of cosmic neutrino oscillations is confirmed.
Effect of Active Self-Motion on Auditory Space Perception

This study investigated how auditory space is represented during linear self-motion. Results of several studies suggest that whether the listener’s motion is active or passive affects sound localization. Therefore, we investigated whether the style of the self-motion affects the perceived auditory space. As the passive condition, observers were transported automatically forward by a robotic wheelchair. In contrast, observers controlled the movement of the robotic wheelchair or walked straight ahead in active conditions. The observers indicated the direction in which the sound was perceived relative to their coronal plane (i.e., a two-alternative forced-choice task). The results of experiments demonstrated that the sound position aligned with the subjective coronal plane was displaced backward relative to the observers’ physical coronal plane both in active and passive motion conditions. These results suggest that perceived self-motion itself affects auditory space representation irrespective of the intention of the movement.
A Neural Network Tool for Predicting Wave Reflection, Overtopping and Transmission

This contribution presents a new Artificial Neural Network (ANN) tool that is able to predict the main parameters describing the wave-structure interaction processes: the mean wave overtopping discharge (q), the wave transmission and wave reflection coefficients (Kt and Kr). This ANN tool is trained on an extended database (based on the CLASH database) of physical model tests, including at least one of the three output parameters, for a total number of nearly 18,000 tests. The selected 15 nondimensional ANN input parameters represent the most significant effects of the structure type (geometry, amour size and roughness) and of the wave attack (wave steepness, breaking, shoaling, wave obliquity). The model can be used for design purposes, leading to a greater accuracy than existing formulae and similar tools for complex geometries for the prediction of Kr and Kt , and it has a similar accuracy as the CLASH ANN for predicting q.
Experimental control of swept-wing transition through base-flow modification by plasma actuators

Control of laminar-to-turbulent transition on a swept-wing is achieved by base-flow modification in an experimental framework, up to a chord Reynolds number of 2.5 million. This technique is based on the control strategy used in the numerical simulation by Dörr & Kloker (J. Phys. D: Appl. Phys., vol. 48, 2015b, 285205). A spanwise uniform body force is introduced using dielectric barrier discharge plasma actuators, to either force against or along the local cross-flow component of the boundary layer. The effect of forcing on the stability of the boundary layer is analysed using a simplified model proposed by Serpieri et al. (J. Fluid Mech., vol. 833, 2017, pp. 164–205). A minimal thickness plasma actuator is fabricated using spray-on techniques and positioned near the leading edge of the swept-wing, while infrared thermography is used to detect and quantify transition location. Results from both the simplified model and experiment indicate that forcing along the local cross-flow component promotes transition while forcing against successfully delays transition. This is the first experimental demonstration of swept-wing transition delay via base-flow modification using plasma actuators.
Analysis of inverse boundary value problems for elastic waves

Analysis of inverse boundary value problems for elastic waves by Jian Zhai In seismology, people use waves generated by earthquakes, artificial explosions, or even “noises”, to detect the Earth’s interior structure. The waves traveling in rocks, which are the main components of Earth’s crust and mantle, are elastic waves. A key problem in seismology is whether the interior structures of interest could be uniquely determined by the measurements people can collect. Since in most situations, people can only record the vibrations at the surface, such problems usually are formulated as inverse boundary value problems for the elastic wave equation. We study several inverse boundary value problems for the elastic wave equation and give some uniqueness and stability results for them. In Chapter 2, we consider the inverse problem of determining the Lamé parameters and the density of a three-dimensional elastic body from the time-harmonic Dirichletto-Neumann map. We prove uniqueness and Lipschitz stability of this inverse problem when the Lamé parameters and the density are assumed to be piecewise constant on a given domain partition. In Chapter 3 and 4, we study the recovery of the density and stiffness tensors of a three-dimensional domain from the dynamical Dirichlet-to-Neumann map. We give explicit reconstruction schemes for the determination of stiffness tensors and the density at the boundary under certain assumptions. In Chapter 4, we prove uniqueness of piecewise analytic parameters in the interior for which we have boundary determination. In Chapter 5, we give a semiclassical description of surface waves or modes in an elastic medium that is stratified near its boundary at some scale comparable to the wave length. The analysis is based on the work of Colin de Verdière [48] on acoustic surface waves. In Chapter 6, we consider a Riemannian manifold in dimension n ≥ 3 with strictly convex boundary. We prove the local invertibility, up to potential fields, of the geodesic X-ray transform on tensor fields of order four near a boundary point. Under the condition that the manifold can be foliated with a continuous family of strictly convex surfaces, the local invertibility implies a global result.
: Leveraging Collective Human Intelligence to Study Large Language Models

Writing effective instructions (or prompts) is rapidly evolving into a dark art, spawning web-sites dedicated to collecting, sharing, and even selling instructions. Yet, the research efforts evaluating large language models (LLMs) either limit instructions to a predefined set or worse, make anecdotal claims without rigorously testing sufficient instructions. In reaction to this cottage industry of instruction design, we introduce L EET - P ROMPT : a platform where people can interactively explore the space of instructions to solve problems. L EET P ROMPT automatically evaluates human-LLM interactions to provide insights about both LLMs as well as human-interaction behavior. With L EET P ROMPT , we conduct a within-subjects user study ( N = 20 ) across 10 problems from 5 domains: biology, physics, math, programming, and general knowledge. By analyzing 1178 instructions used to invoke GPT-4, we present the following findings: First, we find that participants are able to design instructions for all tasks, including those that problem setters deemed unlikely to be solved. Second, all automatic mechanisms fail to generate instructions to solve all tasks. Third, the lexical diversity of instructions is significantly correlated with whether people were able to solve the problem, highlighting the need for diverse instructions when evaluating LLMs. Fourth, many instruction strategies are unsuccessful, highlighting the misalignment between partic-ipant’s conceptual model of the LLM and its functionality. Fifth, participants with prompting and math experience spend significantly more time on L EET P ROMPT . Sixth, we find that people use more diverse instruction strategies than these auto-*