Miracle-dz/UniFAR-FTUs huggingface dataset:
Whistler modes in highly nonuniform magnetic fields. III. Propagation near mirror and cusp fields

The properties of helicon modes in highly nonuniform magnetic fields are studied experimentally. The waves propagate in an essentially unbounded uniform laboratory plasma. Helicons with mode number m = 1 are excited with a magnetic loop with dipole moment across the dc magnetic field. The wave fields are measured with a three-component magnetic probe movable in three orthogonal directions so as to resolve the spatial and temporal wave properties. The ambient magnetic field has the topology of a mirror or a cusp, produced by the superposition of a uniform axial field B0 and the field of a current-carrying loop with the axis along B0. The novel finding is the reflection of whistlers by a strong mirror magnetic field. The reflection arises when the magnetic field changes on a scale length shorter than the whistler wavelength. The simplest explanation for the reflection mechanism is the strong gradient of the refractive index which depends on the density and magnetic field. More detailed observations show that the incident wave splits when the k vector makes an angle larger than 90° with respect to B0 which produces a parallel phase velocity component opposite to that of the incident wave. The reflection coefficient has been estimated to be close to unity. Interference between reflected and incident waves creates nodes in which the whistler mode becomes linearly polarized. When the magnetic field topology is that of a reversed field configuration (FRC), the incident wave is absorbed near the three-dimensional (3D) magnetic null point which prevents wave reflections. However, waves outside the separatrix are not absorbed and continue to propagate around the null point. When waves are excited inside the FRC, their polarization and helicon mode are reversed. Implications of these observations on research in space plasmas and helicon sources are pointed out.The properties of helicon modes in highly nonuniform magnetic fields are studied experimentally. The waves propagate in an essentially unbounded uniform laboratory plasma. Helicons with mode number m = 1 are excited with a magnetic loop with dipole moment across the dc magnetic field. The wave fields are measured with a three-component magnetic probe movable in three orthogonal directions so as to resolve the spatial and temporal wave properties. The ambient magnetic field has the topology of a mirror or a cusp, produced by the superposition of a uniform axial field B0 and the field of a current-carrying loop with the axis along B0. The novel finding is the reflection of whistlers by a strong mirror magnetic field. The reflection arises when the magnetic field changes on a scale length shorter than the whistler wavelength. The simplest explanation for the reflection mechanism is the strong gradient of the refractive index which depends on the density and magnetic field. More detailed observations show tha.
Multi arrival wavefront tracking and seismic imaging

Multi Arrival Wavefront Tracking and Seismic Imaging Multi valued travel times have traditionally not been used in seismic imaging, with only a handful of notable exceptions in the field of exploration geophysics. For studies on local and regional scales (e.g. local earthquake/teleseismic tomography), the focus has largely been on first arrivals. Numerous ray and grid based schemes have been developed for predicting this class of data. However, later arrivals often contribute to the length and shape of a recorded wavetrain, particularly in regions of complex geology. These arrivals are likely to contain additional information about seismic structure, as their two point path differs from that of the first arrival; in particular, they are more amenable to sampling regions of lower velocity. Recently, several grid based schemes have been proposed for solving the multi valued travel time problem. Here a level set based scheme is investigated for its potential to accurately and robustly compute travel times in a seismological context. Although promising, it is shown that it, and other grid based multi arrival solvers, currently require significant computational resources for crustal scale problems, and further development is required before practical application becomes feasible. The main focus of this work is therefore on an alternative approach, sometimes referred to as wavefront construction. The wavefront construction principle is used as the basis of a new scheme for computing multi valued travel times that arise from smooth variations in both velocity structure and interface geometry. The idea is to represent the wavefront as a set of points, and use local ray tracing and interpolation to advance the wavefront in a series of time steps. The wavefront tracking is performed in reduced phase space, which significantly enhances the method’s ability to correctly resolve complex features such as triplications. The scheme is robust in the presence of strong velocity heterogeneity and interface curvature, with phases comprising multiple reflections, refractions and triplications successfully tracked. It is shown that using later arrivals in seismic tomography can result in better images of the subsurface. They not only improve the quality of velocity models but also of interface structure. Identifying later arrivals in observations, however, is a problem in itself. The wavefront tracking scheme is therefore extended to compute relative amplitudes and ray based seismograms which may help to facilitate this process.
Numerical models of the early stages of planet formation

This PhD thesis deals with the early stages of planet formation and the growth from micrometer dust grains to kilometer-sized planetesimals. Dust grains are diffused by the turbulence in the protoplanetary disc. We measure the diffusion coefficient of magnetorotational turbulence and relate it to the turbulent viscosity. Diffusion is surprisingly as strong as viscosity, even though most of the viscosity comes from magnetic stresses that do not directly affect diffusion. The ratio between turbulent viscosity and turbulent diffusion (the Schmidt number) is found to depend strongly on the strength of an imposed vertical magnetic field. Large field strengths yield a Schmidt number that is much larger than unity. Larger solid particles, i.e. rocks and boulders, are not only diffused by magnetorotational turbulence, but also experience concentrations in transient high pressure regions of the turbulent gas, reaching local densities two orders of magnitude higher than the average. Discs that are not susceptible to the magnetorotational instability can develop turbulence due to the sedimentation of solids. The radial pressure gradient of the gas, together with a vertical gradient in the solids-to-gas ratio, leads to a vertical shear in the orbital velocity of the gas, unstable to the Kelvin-Helmholtz instability. The turbulent state is characterised by a number of dense clumps of solids that form due to the dependence of the orbital velocity on the local solids-to-gas ratio, making denser regions plough through less dense regions and scoop up the material at the full Keplerian speed. Isolating the effect of this streaming instability, by ignoring vertical stratification, we find that the turbulent state depends strongly on the background solids-to-gas ratio and on the friction time of the particles. Marginally coupled solids display huge overdensities and a diffusion coefficient that approaches that of the magnetorotational turbulence, more tightly coupled solids develop only a very weak non-linear state.
Earnings News and Over-the-Counter Markets

We document significant increases in bond market liquidity around earnings announcements. These increases are attributed to decreased search and bargaining costs, which arise from the over‐the‐counter (OTC) nature of bond markets and outweigh increases in information asymmetry during these periods. Our evidence traces reductions in search and bargaining costs to two sources around earnings announcements: (1) improved access to dealers and (2) increased participation from institutional investors, who can more easily transact with multiple dealers. Overall, our findings highlight a novel channel through which firm‐specific information affects asset prices.
Meta Style Adversarial Training for Cross-Domain Few-Shot Learning

To better help understand our proposed progressive attacking strategy, we compare it with the vanilla individual attacking approach. The illustrations are provided in Figure 4. For simplification, we use S1, S2, and S3 to represent the styles extracted from blocks E1, E2, and E3, respectively. Correspondingly, S 1 , S 2 , and S 3 represent the adversarial styles. We would like to highlight two points: 1. The vanilla individual attacking method takes each block separately, which may lead to inconsistencies between features in different blocks. 2. By contrast, our progressive attacking method accumulates the adversarial signals, generating smooth adversarial features. Overall, we take the dependencies between blocks into account and produce a more coherent set of adversarial features via the progressive attacking way.
Methods and Tools for Bayesian Variable Selection and Model Averaging in Normal Linear Regression

In this paper, we briefly review the main methodological aspects concerned with the application of the Bayesian approach to model choice and model averaging in the context of variable selection in regression models. This includes prior elicitation, summaries of the posterior distribution and computational strategies. We then examine and compare various publicly available R‐packages, summarizing and explaining the differences between packages and giving recommendations for applied users. We find that all packages reviewed (can) lead to very similar results, but there are potentially important differences in flexibility and efficiency of the packages.
Music Retrieval System Using Query-by-Humming

Music Retrieval System Using Query-by-Humming By Parth Patel Music Information Retrieval (MIR) is a particular research area of great interest because there are various strategies to retrieve music. To retrieve music, it is important to find a similarity between the input query and the matching music. Several solutions have been proposed that are currently being used in the application domain(s) such as Queryby-Example (QBE) which takes a sample of an audio recording playing in the background and retrieves the result. However, there is no efficient approach to solve this problem in a Query-by-Humming (QBH) application. In a Query-by-Humming application, the aim is to retrieve music that is most similar to the hummed query in an efficient manner. In this paper, I shall discuss the different music information retrieval techniques and their system architectures. Moreover, I will discuss the Query-by-Humming approach and its various techniques that allow for a novel method for music retrieval. Lastly, we conclude that the proposed system was effective combined with the MIDI dataset and custom hummed queries that were recorded from a sample of people. Although, the MRR was measured at 0.82 – 0.90 for only 100 songs in the database, the retrieval time was very high. Therefore, improving the retrieval time and Deep Learning approaches are suggested for future work.
Intermediate Input Prices and the Labor Share

We explore how the labor share relates to the price of materials in the economy, and highlight a negative relationship between them under conditions of imperfect competition and complementarity between materials and primary inputs. We show that fluctuations in the price of materials align with aggregate trends in the US labor share, including a sharp decline during the 2000s commodity boom and stabilization in recent years. Consistent with these trends, we provide causal evidence for the negative effect of materials prices on the labor share. We decompose changes in the labor share to identify the role of materials prices relative to other explanations and show that its decline in recent decades would have been smaller and smoother under constant material prices. We extend our framework to a multi-country setting and demonstrate, theoretically and empirically, how shocks to global commodity markets yield heterogeneous changes in the labor share across countries.
THE HABITAT SELECTION OF HOLE-NESTING BIRDS IN RIVERINE FORESTS ALONG THE DRAVA RIVER IN CROATIA Izbor staništa ptica dupljašica u poplavnim nizinskim šumama uz rijeku Dravu u Hrvatskoj

The influence of floristic and structural habitat characteristics on primary and secondary hole-nesting bird community characteristics was studied. Research was conducted at 66 points in riverine forest stands near the Drava River in Croatia. The standard point count method was used to study bird communities, and the circular plot method to study habitat characteristics. The average tree basal area was used as an indicator of age. The studied points were classified into four groups according to the dominant tree species. Forest habitat was found to be very heterogeneous. A total of 13 bird species were recorded (five primary and eight secondary hole-nesters). The results showed that the number of bird species, as well as their abundance, depend on both structural and floristic compositions of forest communities. Older forest stands had higher diversity of bird communities and higher abundance. Birds selected mixed and ash forest, and floristic characteristics had greater impact on the composition of secondary hole-nesters community. The number of species and the abundance of secondary hole-nesters were positively correlated with the number of species and the abundance of primary hole-nesters. The results may serve as a guideline for sustainable forest management.
Eulerian-Lagrangian Modeling of contamination on exterior of a NEVS Vehicle

The rear view mirror design plays an important role for the resulting cleanliness of the driver’s side-window when cruising in rainy conditions. The visible field and the mirror glass must be as clean as possible. The flow around a rear-view mirror is inherently unsteady and vortex dominated. The contaminant particles (rain droplets) hit the mirror body and moves as wall film to a separation point that is governed by the mirror design. When the droplets separate, they can either enter the mirror wake or follow the ambient flow to leave the car. In this thesis, the complete process was modeled. It is shown how mirror design can be used to minimize the contamination areas to have maximum visibility. First, a benchmark study was done to understand the governing parameters of droplet and fluid film flow on a simplified geometry using the CFD software Star-CCM+. The flow was modeled using unsteady RANS and droplets were tracked using Lagrangian Particle Tracking (LPT). The conclusions from the benchmark study were implemented on the full vehicle model of NEVS vehicle. The simulation results were compared with a contamination test performed at NEVS climate tunnel.
SWITCH-NERF: LEARNING SCENE DECOMPOSITION

The Neural Radiance Fields (NeRF) have been recently applied to reconstruct building-scale and even city-scale scenes. To model a large-scale scene efficiently, a dominant strategy is to employ a divide-and-conquer paradigm via performing scene decomposition, which decomposes a complex scene into parts that are further processed by different sub-networks. Existing large-scale NeRFs mainly use heuristic hand-crafted scene decomposition, with regular 3D-distance-based or physical-street-block-based schemes. Although achieving promising results, the hand-crafted schemes limit the capabilities of NeRF in large-scale scene modeling in several aspects. Manually designing a universal scene decomposition rule for different complex scenes is challenging, leading to adaptation issues for different scenarios. The decomposition procedure is not learnable, hindering the network from jointly optimizing the scene decomposition and the radiance fields in an end-to-end manner. The different sub-networks are typically optimized independently, and thus hand-crafted rules are required to composite them to achieve a better consistency. To tackle these issues, we propose Switch-NeRF, a novel end-to-end large-scale NeRF with learning-based scene decomposition. We design a gating network to dispatch 3D points to different NeRF sub-networks. The gating network can be optimized together with the NeRF sub-networks for different scene partitions, by a design with the Sparsely Gated Mixture of Experts (MoE). The outputs from different sub-networks can also be fused in a learnable way in the unified framework to effectively guarantee the consistency of the whole scene. Furthermore, the proposed MoE-based Switch-NeRF model is carefully implemented and optimized to achieve both high-fidelity scene reconstruction and efficient computation. Our method establishes clear state-ofthe-art performances on several large-scale datasets. To the best of our knowledge, we are the first to propose an applicable end-to-end sparse NeRF network with learning-based decomposition for large-scale scenes. Codes are released at https://github.com/MiZhenxing/Switch-NeRF.
The Drivers and Implications of Retail Margin Trading∗

Using granular data covering both regulated (brokerage-financed) and unregulated (shadowfinanced) margin accounts in China, we provide novel evidence on retail investors’ margin trading behavior and its price implications. First, we show that retail investors’ decisions to lever up in stock trading despite the hefty borrowing cost is likely driven by overconfident beliefs and lottery preferences. We then show that margin borrowing indeed affects investors’ trading behavior: investors are more likely to liquidate their holdings as they inch closer to margin calls. Third, we show that margin-induced trading aggregates up to affect asset prices and contributes to shock spillovers across stocks.
Redistributive effects of pension reforms: who are the winners and losers?

As the heterogeneity in life expectancy by socioeconomic status increases, many pension systems imply a wealth transfer from short- to long-lived individuals. Various pension reforms aim to reduce inequalities that are caused by ex-ante differences in life expectancy. However, these pension reforms may induce redistribution effects. We introduce a dynamic general equilibrium-overlapping generations model with heterogeneous individuals that differ in their education, labor supply, lifetime income, and life expectancy. Within this framework we study six different pension reforms that foster the sustainability of the pension system and aim to account for heterogeneous life expectancy. Our results highlight that pension reforms have to be evaluated at various dimensions. Reforms that may increase the sustainability of the pension system are not necessarily conducive to reduce the redistributive wealth transfers from short- to long-lived individuals. Our paper emphasizes the need for studying pension reforms in models with behavioral feedback and heterogeneous socioeconomic groups.
Self-channeling of a powerful microwave beam in a preliminarily formed plasma

The self-channeling of a high power (≤500 MW) sub-nanosecond microwave beam in the plasma formed by a neutral gas (>103 Pa) ionization was demonstrated by Shafir et al. [Phys. Rev. Lett. 120, 135003 (2018)]. In the present research, this effect is observed and studied in detail in a plasma, preliminarily formed by an rf discharge, in a low ( 103 Pa) ionization was demonstrated by Shafir et al. [Phys. Rev. Lett. 120, 135003 (2018)]. In the present research, this effect is observed and studied in detail in a plasma, preliminarily formed by an rf discharge, in a low (<150 Pa) pressure gas. The results of analytical modeling and numerical particle-in-cell simulations show that ionization-induced channeling can be realized at a significantly lower power of the microwave beam and gas pressure if the preliminarily formed plasma is radially non-uniform with minimal on axis density.
GSI‐based ensemble‐variational hybrid data assimilation for HWRF for hurricane initialization and prediction: impact of various error covariances for airborne radar observation assimilation

The hybrid Ensemble Kalman Filter ‐ Variational (EnKF‐Var) data assimilation (DA) system based on Grid‐point Statistical Interpolation (GSI) is extended for the Hurricane‐WRF model (HWRF). Background ensemble forecasts initialized by the EnKF are used to provide the flow‐dependent error covariance to be ingested by GSI using the extended control variable method. The hybrid system is then applied to assimilate airborne radar data.
Some numerical invariants of multilinear identities

We consider non-necessarily associative algebras over a field of characteristic zero and their polynomial identities. Here we describe most of the results obtained in recent years on two numerical sequences that can be attached to the multilinear identities satisfied by an algebra: the sequence of codimensions and the sequence of colengths.
Oscillation of fast growing solutions of linear differential equations in the unit disc

In this paper, we investigate the relationship between solu- tions and their derivatives of the differential equation f (k) + A (z)f = 0, k ≥ 2, where A (z) 6≡ 0 is an analytic function with finite iterated p- order and analytic functions of finite iterated p-order in the unit disc � = {z ∈ C : |z| < 1}. Instead of looking at the zeros of f (j) (z) - z (j = 0,.,k), we proceed to a slight generalization by considering zeros of f (j) (z) - ' (z) (j = 0,.,k), where ' is a small analytic function relative to f such that ' (k-j) (z) 6≡ 0 (j = 0,.,k), while the solution f is of in- finite iterated p-order. This paper improves some very recent results of T. B. Cao and G. Zhang, A. Chen.