Miracle-dz/UniFAR-FTUs huggingface dataset:
On the origin and structure of a stationary circular hydraulic jump

To elucidate the role played by surface tension on the formation and on the structure of a circular hydraulic jump, the results from three different approaches are compared: the shallow-water (SW) equations without considering surface tension effects, the depth-averaged model (DAM) of the SW equations for a flow with a parabolic velocity profile, and the numerical solutions of the full Navier-Stokes (NS) equations, both considering the effect of surface tension and neglecting it. From the SW equations, the jump can be interpreted as a transition region between two solutions of the DAM, with the jump’s location virtually coinciding with a singularity of the DAM’s solution, associated with the inner edge of a recirculation region near the bottom. The jump’s radius and the flow structure upstream of the jump obtained from the NS simulations practically coincide with the results from the SW equations for any flow rate, liquid properties, and downstream boundary conditions, being practically independent of surface tension. However, the structure of the flow downstream of the jump predicted by the SW equations is quite different from the stationary flow resulting from the NS simulations, which strongly depends on surface tension and on the downstream boundary conditions (radius of the disk). One of the main findings of the present work is that no stationary and axisymmetric circular hydraulic jump is found from the NS simulations above a critical value of the surface tension, which depends on the flow conditions, fluid properties, and downstream conditions.To elucidate the role played by surface tension on the formation and on the structure of a circular hydraulic jump, the results from three different approaches are compared: the shallow-water (SW) equations without considering surface tension effects, the depth-averaged model (DAM) of the SW equations for a flow with a parabolic velocity profile, and the numerical solutions of the full Navier-Stokes (NS) equations, both considering the effect of surface tension and neglecting it. From the SW equations, the jump can be interpreted as a transition region between two solutions of the DAM, with the jump’s location virtually coinciding with a singularity of the DAM’s solution, associated with the inner edge of a recirculation region near the bottom. The jump’s radius and the flow structure upstream of the jump obtained from the NS simulations practically coincide with the results from the SW equations for any flow rate, liquid properties, and downstream boundary conditions, being practically independent of sur.
Investigation of Fabrication Accuracy and Repeatability of High- $Q$ Silicon-Micromachined Narrowband Sub-THz Waveguide Filters

This paper investigates the fabrication accuracy and repeatability of micromachined quadruplet filters designed at a center frequency of 270 GHz with a 5-GHz bandwidth using a versatile multilayer chip platform which allows for axially arranged waveguide ports. A large number of narrowband silicon-micromachined filters arranged on multiple chips are investigated for fabrication imperfections, assembly misalignment, and fabrication yield, employing fabrication-prediction and different chip-to-chip self-alignment feature strategies. A numerical technique for characterization of the entire fabrication process of the filters through extracting the error statistics for coupling coefficients of a large number of different samples from separately assembled chips is proposed. A total of 47 test filters in effectively 15 different design variants have been fabricated in two fabrication runs, evaluated, and analyzed. The most critical sources of errors are determined. The expected accuracy of the entire filters fabrication process is demonstrated through the yield analysis based on the collected error statistics.
NUMERICAL SIMULATION OF APPARENT DENSITY EVOLUTION OF TRABECULAR BONE UNDER FATIGUE LOADING: EFFECT OF BONE INITIAL PROPERTIES

Bone remodeling is a physiological phenomenon coupling resorption and formation processes that are mainly mediated by osteoclasts and osteoblasts, in response to mechanical stimuli transduced by osteocytes to biochemical signals activating the bone multicellular unit. Under normal loading conditions, bone resorption and formation are balanced by a homeostasis process. When bone is subjected to overstress, microdamaging occurs, which induces a modification of the structural integrity and microarchitecture. This has drawn significant attention to the mechanical properties of bone. In this context, the current study has been carried out with the aim of numerically investigating the impact of the mechanical properties on the remodeling process of the trabecular bone under cyclic loading, highlighting the effects of different values of the mineral density and the Young’s modulus. This was performed using a mechanobiological model, coupling mechanical and biological approaches, allowing to numerically simulate the effect of the selected parameters for a 20-year-period of cyclic loading for 2D and 3D models of a human femur head. The current work is an explorative numerical study, and the obtained results revealed the changes in the overall stiffness of the bone according to the mechanical properties.
Nano-objects - sculpting and shape in molecular material design (The Pierre Gilles de Gennes ILCS prize lecture)

ABSTRACT Early liquid crystal compounds often had relatively simple molecular structures, but with the invention of electro-optical devices, the design of materials became increasingly important. Property-structure correlations have promoted computer-aided rational design to the point where it is becoming a necessity in the selection of compounds for preparation. For simple molecular architectures, allowable electrostatic interactions in the face of steric repulsion were used in a phenomenological way to generate new mesophases, such as the hexatic phase, and to engineer materials with desirable physical properties. Materials chemists, in the creation of substances of greater complexity, have built upon these forms of research. Interestingly, the larger the system often the more simply it becomes as the molecular bulk and shape begin to dominate over the surface interactions. Nano-objects of unique shapes, such as ‘Janus’ grains, created in the process of design can kindle the formation of new mesophases, such as the twist-bend and splay phases generated through the crowding of molecular particles, and minimisation of the free volume. This article explores the development of the shapes of molecular grains and the mesophases they spawn. GRAPHICAL ABSTRACT
A Note on $(P,Q)$-Analogue Type of Fubini Numbers and Polynomials

In this paper, we introduce a new class of $(p,q)$-analogue type of Fubini numbers and polynomials and investigate some properties of these polynomials. We establish summation formulas of these polynomials by summation techniques series. Furthermore, we consider some relationships for $(p,q)$-Fubini polynomials associated with $(p,q)$-Bernoulli polynomials, $(p,q)$-Euler polynomials and $(p,q)$-Genocchi polynomials and $(p,q)$-Stirling numbers of the second kind.
FAKTOR – FAKTOR FUNDAMENTAL YANG MEMPENGARUHI BETA SAHAM PADA PERUSAHAAN NON-KEUANGAN YANG TERDAFTAR DI BEI

The objectives of this research are to analyze and investigate whether there is influence from financial leverage, liquidity, assets growth, assets size, return on investment and dividend payout ratio to stock beta. This research uses 309 financial statement of non-financial companies listed in Indonesia Stock Exchange during the period of 2011 to 2013. The result of this research shows that assets size has significant influence to stock beta. On the other hand, financial leverage, liquidity, assets growth, return on investment and dividend payout ratio have no significant influence to stock beta.
Gamma Ray Diffuse Emission from the GalacticPlane with HAWC Data

The Galactic $\gamma$-ray diffuse emission is produced by the interaction of cosmic rays (CRs) with ambient gas and radiation fields. Studying this radiation helps us to reconstruct particle transport and distribution in the Galaxy. We will present the analysis of HAWC (High Altitude Water-Cherenkov) data to measure the spectrum and the angular distribution of the diffuse emission from the Galactic Plane. In the future, we will use these HAWC measurements to constrain particle transport properties in different regions of the Galactic Plane, such as close to the Galactic Centre, comparing them to the predictions of transport models implemented with the DRAGON code, which solves the CR transport equation in the Galaxy under general conditions including inhomogeneous and anisotropic diffusion. In particular, we use HAWC results to scrutiny a model based on inhomogeneous diffusion which - better than conventional models - provides a good description of the diffuse emission measured by Fermi-LAT and Milagro along the inner Galactic plane and in the Galactic center region.
On asset-allocation and high-frequency data: are there financial gains from using different covariance estimators?

Abstract We analyze the economic benefits of several covariance estimation approaches on a tactical asset-allocation problem in the presence of high-frequency return data. Our analysis confirms that the use of robust-to-noise and asynchronicity estimators not only gives statistically more accurate results, but the statistical efficiency is reflected into a financial benefit in most cases.
Estimation of solar disk gamma-ray emission based on Geant4

The most important astrophysical mechanism for steady solar gamma-ray emission is the interaction of cosmic rays with solar atmosphere, which has been definitely detected by Fermi-LAT with maximum energy up to 200 GeV. Some studies shown that the effect of the solar magnetic field to solar disk gamma-ray flux is unneglectable. It is valuable to study the physical mechanism between solar disk gamma-ray flux and solar magnetic field. In this paper, we simulated the interaction between cosmic rays and solar atmosphere by G4SOLAR program based on Geant4. A simulated solar disk gamma-ray flux from 1GeV to 1TeV was obtained with taking into account the influence of coronal magnetic field. The PFSS model for “quiet”Sun was employed, and the solar disk gamma-ray below 10GeV was consistent with the Fermi observation. But the simulated spectrum became much softer than Fermi data when >10GeV. Some influence factors were briefly discussed.
Failure of local thermal equilibrium in quantum friction

In the study of non-equilibrium fluctuation-induced interactions (e.g., quantum friction, near-field heat transfer, and non-equilibrium Casimir forces) the local fluctuation-dissipation theorem (FDT) is widely used without much justification. Here, we report the failure of the local FDT in a specific example of quantum friction of an atom moving at constant velocity above a surface. A generalized non-equilibrium FDT is derived, which contains a contribution akin to the local FDT and an additional one corresponding to a velocity-dependent current term. We show that in the low-velocity limit the frictional force arising from the current term is of the same order of magnitude as that predicted by the local FDT, which underestimates the total force by almost 50 percent.
Cross-Network Learning With Fuzzy Labels for Seed Selection and Graph Sparsification in Influence Maximization

To maximize the influence across multiple heterogeneous networks, we propose an innovative cross-network learning model to study the influence maximization problem from two perspectives, namely, seed selection and graph sparsification. On one hand, we consider seed selection as a cross-network node prediction task, by leveraging the greedy seed selection knowledge prelearned in a smaller source network, to heuristically select the nodes most likely to act as seed for the target networks. On the other hand, we consider graph sparsification as a cross-network edge prediction problem, by adapting the influence propagation knowledge previously acquired in the source network to remove the edges least likely to contribute to influence propagation in the target networks. To address domain discrepancy, a fuzzy self-learning algorithm is proposed to iteratively train the prediction model by leveraging not only the fully labeled data in the source network, but also the most confident predicted instances with their predicted fuzzy labels in the target network. With such fuzzy labels, we can differentiate the confident levels of predictions generated by different self-training iterations, thus lowering the negative effects caused by less confident predictions. The performance of the proposed model is benchmarked with the popular influence maximization algorithms for seed selection; and also competed with several graph sparsification algorithms for inactive edge prediction. Experimental results on the real-world datasets show that the proposed cross-network learning model can achieve a good tradeoff between the efficiency and effectiveness of the influence maximization task in the target networks.
Fully Distributed Consensus Control for Linear Multiagent Systems: A Reduced-Order Adaptive Feedback Approach

This paper is concerned with fully distributed consensus control of linear multiagent systems with undirected graphs. Two kinds of reduced-order adaptive output-feedback protocols are proposed. For the edge-based protocol, each edge is adapted by a scalar that is determined by the output information of the associated two agents; for the node-based protocol, each agent multiplies the connecting weights by a scalar that is determined by the relative output information of all neighboring agents. Sufficient conditions in terms of the solvability of some matrix equations are derived for the existence of the two protocols. Furthermore, a tractable algorithm is constructed for designing the protocol gains. Compared with the existing related results, the proposed protocols have the following three merits simultaneously—lower dimension, using relative output information about neighbouring agents, and in the fully distributed fashion. A simulation example on formation flying of spacecrafts is presented to illustrate the efficacy of the proposed method.
Attention Pooling-Based Bidirectional Gated Recurrent Units Model for Sentimental Classification

Faculty of Information Engineering, China University of Geosciences, Wuhan, Hubei 430074, China College of Information and Engineering, Sichuan Agricultural University, Yaan, Sichuan 625014, China School of Computer, Wuhan University, Wuhan, Hubei 430072, China School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore 637553, Singapore Collaborative Innovation Center for Language Research & Service, Guangdong University of Foreign Studies, Guangzhou, Guangdong 510420, China
On the regularization of the collision solutions of the one-center problem with weak forces

We study the possible regularization of collision solutions for one centre problems with a weak singularity. In the case of logarithmic singularities, we consider the method of regularization via smoothing of the potential. With this technique, we prove that the extended flow, where collision solutions are replaced with transmission trajectories, is continuous, though not differentiable, with respect to the initial data.
Misclassification in Binary Choice Models with Sample Selection

Most empirical work in the social sciences is based on observational data that are often both incomplete, and therefore unrepresentative of the population of interest, and affected by measurement errors. These problems are very well known in the literature and ad hoc procedures for parametric modeling have been proposed and developed for some time, in order to correct estimate’s bias and obtain consistent estimators. However, to our best knowledge, the aforementioned problems have not yet been jointly considered. We try to overcome this by proposing a parametric approach for the estimation of the probabilities of misclassification of a binary response variable by incorporating them in the likelihood of a binary choice model with sample selection.
Resonance electron interaction with five-membered heterocyclic compounds: Vibrational Feshbach resonances and hydrogen-atom stripping

Low-energy (0-15 eV) resonance electron attachment to a series of 5-membered heterocyclic rings (isoxazole, imidazole, pyrazole, pyrrole, 1-methyl-, and 2-methylimidazole) is studied under gas-phase conditions by means of electron transmission spectroscopy (ETS) and dissociative electron attachment spectroscopy (DEAS). Experimental spectral features are assigned on the basis of Hartree-Fock and density functional theory (DFT) calculations. Sharp features, with a width of less than 0.1 eV, observed in the electron transmission spectra of imidazole, pyrazole and pyrrole close to 0.45 eV, i.e. well below the energy of their lowest-lying π * shape resonances detected at 1.90, 1.87, and 2.33 eV, respectively, are associated with formation of negative ion states bound by long-range electron-molecule interactions. Effective range theory (ERT) calculations which include both dipolar and polarization interactions support this interpretation. In addition to the general observation of cleavage of the N–H bond at incident electron energies close to 2 eV, elimination of as many as three hydrogen atoms from the molecular negative ions is detected at higher energies by DEAS with the only exception of methylated imidazoles. This complex process is associated with ring opening and formation of diatomic hydrogen as one of the neutral fragments, as indicated by the calculations to satisfy the energetic requirements. The present results are of importance for understanding the basic mechanisms of damages caused in living tissues by high-energy radiations. experimental ETS and DEAS are with the support quantum-chemical calculations. Multichannel calculations experimental low-energy features observed in the DEA spectra, and ascribed to long-range electron-molecule interaction. the of energy in
Assessment of IAAF Racewalk Judges' Ability to Detect Legal and Non-legal Technique

IAAF Rule 230.2 states that racewalkers must have no visible (to the human eye) loss of contact with the ground and that their advancing leg must be straightened from first contact with the ground until the “vertical upright position. ” The aims of this study were first to analyze racewalking judges' accuracy in assessing technique and, second, to measure flight times across a range of speeds to establish when athletes were likely to lose visible contact. Twenty racewalkers were recorded in a laboratory using a panning video camera (50 Hz), a high-speed camera (100 Hz), and three force plates (1,000 Hz). Eighty-three judges of different IAAF Levels (and none) viewed the panned videos online and indicated whether each athlete was racewalking legally. Flight times shorter than 0.033 s were detected by fewer than 12.5% of judges, and thus indicated non-visible loss of contact. Flight times between 0.040 and 0.045 s were usually detected by no more than three out of eight judges. Very long flight times (≥0.060 s) were detected by nearly all judges. The results also showed that what judges generally considered straightened knees (>177°) was close to a geometrically straight line. Within this inexact definition, IAAF World Championship-standard Level III judges were most accurate, being more likely to detect anatomically bent knees and less likely to indicate bent knees when they did not occur. For the second part, the men racewalked down a 45-m indoor track at 11, 12, 13, 14, and 15 km/h in a randomized order, whereas the women's trials were at 10, 11, 12, 13, and 14 km/h. Flight times, measured using an OptoJump Next photocell system (1,000 Hz), increased for the men from 0.015 s at 11 km/h to 0.040 s at 14 km/h and 0.044 s at 15 km/h, and for the women from 0.013 s at 10 km/h to 0.041 s at 13 km/h and 0.050 s at 14 km/h. For judging by the human eye, the threshold for avoiding visible loss of contact therefore occurred for most athletes at ~14 km/h for men and 13 km/h for women.
Symmetry Properties of Mixed and Heat Photo-Assisted Noise in the Quantum Hall Regime

We investigate the photo-assisted charge-heat mixed noise and the heat noise generated by periodic drives in Quantum Hall states belonging to the Laughlin sequence. Fluctuations of the charge and heat currents are due to weak backscattering induced in a quantum point contact geometry and are evaluated at the lowest order in the tunneling amplitude. Focusing on the cases of a cosine and Lorentzian periodic drive, we show that the different symmetries of the photo-assisted tunneling amplitudes strongly affect the overall profile of these quantities as a function of the AC and DC voltage contributions, which can be tuned independently in experiments.
Roller Bearing Degradation Assessment Based on a Deep MLP Convolution Neural Network Considering Outlier Regions

Roller bearings are one of the most safety-critical components in many machines. Predicting the vibration-based remaining useful life of roller bearings allows operators to make informed maintenance decisions and to guarantee reliability and safety. The health indices (HIs) for degradation assessment are constructed by extracting feature information from the collected data, which significantly influences the prognosis result. Conventional HI construction methods rely heavily on expert knowledge and also have limited capacity for learning health information from the raw data from roller bearings. Furthermore, outlier regions often occur in HIs developed by those methods, and these can easily result in false alarms. To address these problems, a novel HI construction method based on a deep multilayer perceptron (MLP) convolution neural network (DMLPCNN) model, which also considers outlier regions, is proposed in this paper. In the proposed model, a 1-D MLP convolution block, consisting of a convolution layer and a micronetwork, is applied to learn features directly from the vibrational data. The learned features are then mapped into an HI using a global average pooling layer and a logistic regression layer. Finally, an outlier region correction method, based on sliding thresholds, is proposed to detect and remove outliers in the HI. The outlier region correction method is able to enhance the interpretability of the constructed HI. The effectiveness of the proposed method is verified using whole-life data sets of 17 bearings. Experimental results demonstrate that the proposed method outperforms conventional methods.
Inductance Calculation of Interior Permanent Magnet Machines Considering Asymmetrical Saturation of the Bridge

The bridge of the interior permanent magnet (IPM) machine can reduce the leakage of the machine, which makes the utilization rate of the permanent magnet (PM) improved. However, the asymmetric saturation in the bridges will cause the asymmetry distribution of the magnetic potential on the rotor surface, which will bring challenges to the accurate calculation of inductances. Excited by the armature current at different initial phase angles, the flux distributions in the bridges are analyzed. Meanwhile, the reason why the asymmetric saturation exists in the bridges is revealed theoretically. Based on the above analysis, the rotor magnetic potential (RMP) model for an IPM machine with the bridges is established and used to calculate the armature reaction magnetic field and inductances of the IPM machine. In this paper, the RMP distribution in the bridges is obtained by considering asymmetric saturation, so the RMP model can reflect the rotor surface magnetic potential distribution more accurately, which is evident from the adjacent degree between the calculation results and the finite-element analysis (FEA) ones.