Miracle-dz/UniFAR-FTUs huggingface dataset:
An Efficient Algorithm for a Class of Large-Scale Support Vector Machines Exploiting Hidden Sparsity

Support vector machines (SVMs) are successful supervised learning models that analyze data for classification and regression. Previous work has demonstrated the superiority of the SVMs in dealing with the high dimensional, low sample size problems. However, the increase of the sample size brings great challenges to accurately and efficiently solve the large-scale SVMs, especially for the nonlinear kernel SVMs, which may lead to huge computational costs and unaffordable storage burden. In this paper, we propose a highly efficient sparse semismooth Newton (SsN) based augmented Lagrangian (AL) method for solving a class of large-scale SVMs that can be formulated as a convex quadratic programming problem with a linear equality constraint and a simple box constraint. The asymptotic superlinear convergence rate of both the primal and the dual iteration sequences generated by the AL method is guaranteed due to the piecewise linear-quadratic structure of the problem. Furthermore, we reveal the close connection between the number of support vectors and the sparse structure of the generalized Jacobian for the inner subproblem of the AL method. By exploiting this hidden sparsity, the inner subproblem can be solved by the SsN method efficiently and accurately, which greatly reduces the storage burden and computational costs. In particular, for the nonlinear kernel SVMs, since the sparse structure may not manifest in the early iterations of the AL method, we solve a linear kernel SVM approximated by the random Fourier features method to produce a good initial point, and then transfer to solve the original problem. Numerical experiments demonstrate that the proposed algorithm outperforms the current state-of-the-art solvers for the large-scale SVMs.
Strongly Bipolar Inner Ejecta of the Normal Type IIP Supernova ASASSN-16at

We report distinctly double-peaked Hα and Hβ emission lines in the late-time, nebular-phase spectra (≳200 days) of the otherwise normal at early phases (≲100 days) type IIP supernova ASASSN-16at (SN 2016X). Such distinctly double-peaked nebular Balmer lines have never been observed for a type II SN. The nebular-phase Balmer emission is driven by the radioactive 56Co decay, so the observed line profile bifurcation suggests a strong bipolarity in the 56Ni distribution or in the line-forming region of the inner ejecta. The strongly bifurcated blueshifted and redshifted peaks are separated by ∼3 × 103 km s−1 and are roughly symmetrically positioned with respect to the host-galaxy rest frame, implying that the inner ejecta are composed of two almost-detached blobs. The red peak progressively weakens relative to the blue peak, and disappears in the 740 days spectrum. One possible reason for the line-ratio evolution is increasing differential extinction from continuous formation of dust within the envelope, which is also supported by the near-infrared flux excess that develops after ∼100 days.
Accretion-driven gravitational radiation from nonrotating compact objects: Infalling quadrupolar shells

This paper reports results from numerical simulations of the gravitational radiation emitted from non--rotating compact objects(both neutron stars and Schwarzschild black holes) as a result of the accretion of matter. A hybrid procedure is adopted: we evolve, in axisymmetry, the linearized equations describing metric and fluid perturbations, coupled with a nonlinear hydrodynamics code that calculates the motion of the accreting matter. The initial matter distribution is shaped in the form of extended quadrupolar shells of dust or perfect fluid. Self--gravity and radiation reaction effects of the accreting fluid are neglected. This idealized setup is used to understand the qualitative features appearing in the energy spectrum of the gravitational wave emission from compact stars or black holes, subject to accretion processes involving extended objects. A comparison for the case of point--like particles falling radially onto black holes is also provided. Our results show that, when the central object is a black hole, the spectrum is far from having only one clear, monochromatic peak at the frequency of the fundamental quasi-normal mode, but it shows a complex pattern, with interference fringes produced by the interaction between the infalling matter and the underlying perturbed spacetime: most of the energy is emitted at frequencies lower than that of the fundamental mode of the black hole. Similar results are obtained for extended shells accreting onto neutron stars, but in this case the stellar fundamental mode is clearly excited. Our analysis shows that the gravitational wave signal driven by accretion is influenced more by the details and dynamics of the process, than by the quasi--normal mode structure of the central object.
A New Series Variable Flux Memory Machine with Wide Flux Regulation Range

In conventional series hybrid magnet variable flux memory machine (SHM-VFMMs), LCF PMs are reversely protected by high corrective force (HCF) PMs, which inevitably limits the flux regulation range. To address this issue, a new SHM-VFMM with spatially separated LCF and HCF PMs is proposed. The flux regulation ranges of the conventional and proposed machines are investigated and compared by using the magnetic circuit method to reveal the wide flux regulation range mechanism of the proposed machine. Moreover, the basic electromagnetic characteristics of the two machines are compared to verify the feasibility and superiority of the proposed configuration. More relevant research will be presented in the full paper.
On resummation of the irregular conformal block

We discuss the resummation procedure of the superpotential in 4d $\mathcal{N}=2$ SYM theory without matter from the point of view of 2d Liouville conformal field theory, utilizing the AGT correspondence. We identify contributions of different descendants of the intermediate state, defining a conformal block in CFT, to the superpotential and answer the question, which descendants are responsible for the appearance of the branch cuts in the superpotential.
Using Artificial Intelligence for COVID-19 Detection in Blood Exams: A Comparative Analysis

COVID-19 is an infectious disease that was declared a pandemic by the World Health Organization (WHO) in early March 2020. Since its early development, it has challenged health systems around the world. Although more than 12 billion vaccines have been administered, at the time of writing, it has more than 623 million confirmed cases and more than 6 million deaths reported to the WHO. These numbers continue to grow, soliciting further research efforts to reduce the impacts of such a pandemic. In particular, artificial intelligence techniques have shown great potential in supporting the early diagnosis, detection, and monitoring of COVID-19 infections from disparate data sources. In this work, we aim to make a contribution to this field by analyzing a high-dimensional dataset containing blood sample data from over forty thousand individuals recognized as infected or not with COVID-19. Encompassing a wide range of methods, including traditional machine learning algorithms, dimensionality reduction techniques, and deep learning strategies, our analysis investigates the performance of different classification models, showing that accurate detection of blood infections can be obtained. In particular, an F-score of 84% was achieved by the artificial neural network model we designed for this task, with a rate of 87% correct predictions on the positive class. Furthermore, our study shows that the dimensionality of the original data, i.e. the number of features involved, can be significantly reduced to gain efficiency without compromising the final prediction performance. These results pave the way for further research in this field, confirming that artificial intelligence techniques may play an important role in supporting medical decision-making.
Comparison of Prior Setting Methods for Multilevel Model Effect Estimation Based on Small Sample Imbalanced Nested Data in Bayesian Framework

In the fields of education and psychology, nested data with small samples and imbalances are very common. Bauer et al. (2008) first proposed adjusting the traditional multilevel model to analyze the small sample imbalanced nested data (SSIND). In terms of parameter estimation, the Bayesian method shows the possibility of providing unbiased estimation when the sample size is small. This study proposes that the Bayesian method should be used to analyze the SSIND. This study explores the performance of different treatment effects and nesting effects estimation methods in the multilevel model based on the Bayesian method that performs well in the case of small samples, to provide an appropriate and scientific method reference for the subsequent analysis of the model. Two prior setting methods are compared for multilevel model effect estimation based on a small sample of imbalanced nested data in the Bayesian framework. Two prior setting methods are gamma prior setting method and uniform prior setting method. The research results show that when the treatment condition ICC is small (0.05), the bias and RMSE values of the parameter estimation by the gamma prior setting method are larger and the performance is unstable, while the bias and RMSE values of the parameter estimation by the uniform prior setting method are smaller and the performance is relatively stable, so the uniform prior setting method is recommended; when the treatment condition ICC is large (0.15), the bias and RMSE values of the parameter estimation by the uniform prior setting method are larger and the performance is unstable, while the bias and RMSE values of the parameter estimation by the gamma prior setting method are smaller and the performance is relatively stable, so the gamma prior setting method is recommended; when the treatment condition ICC is between 0.05 and 0.15, both prior setting methods have similar effects. Furthermore, when the number of treatment groups is small (8), the gamma prior setting method is recommended; when the number of treatment groups is large (16), the uniform prior setting method is recommended; when the number of treatment groups is between 8 and 16, both prior setting methods have similar effects. Summarily, when we choose which prior setting method to use for the SSIND, we must consider the interaction between the ICC and the number of treatment groups.
Research on the phenolic profile, antiradical and anti-inflammatory activity of a thick hydroalcoholic feverfew (Tanacetum parthenium L.) herb extract

The aim – to study the phenolic complex of a thick hydroalcoholic extract of the feverfew (Tanacetum parthenium (L.) herb (FTHAE), its antiradical activity and anti-inflammatory properties in a model of carrageenan and histamine oedema. Materials and methods. The studied extract was obtained from the Tanacetum parthenium herb, collected in Sumy and Poltava regions of Ukraine during the period of mass flowering (June-August): degree of grinding of raw materials 2.0-3.0 mm, extraction temperature - 25 °C, extractant – 70 % ethanol, raw material/extractant ratio – 1:12, infusion time – 12 hours, multiplicity of extractions – 3. HPLC and spectrophotometric methods were used to determine the composition and amount of phenolic compounds of FTHAE. HPLC analysis was performed using a “Waters e2695 Alliance system” (Waters, Milford, MA, USA) with a photodiode array detector “Waters 2998” according to the HPLC–PDA method for phenolic compounds. The scavenging of ABTSA radical cation evaluated the radical scavenging activity. In addition, the anti-inflammatory properties of FTHAE were studied on carrageenan and histamine paw oedema in rats. Anti-inflammatory activity (AIA) was evaluated as the ability to reduce oedema compared to the control pathology. FTHAE was used at a dose of 50 mg/kg. The results. The content of the sum of hydroxycinnamic acids in the obtained extract was determined by spectrophotometry, which was 13.92±0.02 % and the content of the sum of flavonoids – 5.16±0.03 %. The content of 12 compounds with a total amount of 72432.09µg/g was identified and determined by HPLC. The dominant compounds were hydroxycinnamic acids, namely 3,4-dicaffeoylquinic, 4,5-dicaffeoylquinic and сhlorogenic acids. The antiradical activity of the extract was 620.19±4. 53µmol/g. On the model of carrageenan oedema, the maximum effect of oedema suppression was 71.0-73.2 %. In the model of histamine oedema, the anti-inflammatory effect of the extract was 57.8; 51.8; and 49.1 % for 30 minutes, 1 and 1.5 hours of oedema, respectively. The severity of the anti-inflammatory activity of the extract during the first hour is not inferior to the diclofenac sodium, quercetin and loratadine. Conclusions. Due to the HPLC method, 12 compounds were determined to cause antiradical activity, among which chlorogenic acid and rutin were identified. The studied extract has a pronounced anti-inflammatory effect, which is due to the antiradical properties of the extract and its inhibitory effect on inflammatory mediators
Is quantum mechanics creationism, and not science?

I revisit the reply of Bohr to Einstein. Bohr's implication that there are no causes in atomic scale systems is, as a closer analysis reveals, not in line with the Copenhagen interpretation since it would contain a statement about reality. What Bohr should have written is that there are no causes in mathematics, which is universally acknowledged. The law of causality requires physical effects to be due to physical causes. For this reason any theoretical model which replaces physical causes by mathematical objects is creationism, that is, it creates physical objects out of mathematical elements. I show that this is the case for most of quantum mechanics.
The Unified Approach for the Best Choice Problem Applied to Alternative-Choice Selection Problems

The objective of this paper is to show that the so-called unified approach to stopping problems with unknown cardinality introduced in Bruss (1984) proves to be efficient for solving other types of best-choice problems. We show that what we will call the alternative-choice stopping problem, which will be exemplified right away in Section 1, can be seen as a "two-sided" Secretary problem. This problem is instigated by a former problem of R. R. Weber (Cambridge University). Our approach yields for unknown cardinality the sharp lower bound $1/2$ for the probability of success. This problem is, at the same time, a special case of a model more generally based on $k \ge 2$ linearly ordered subsets. We shall also give the solution for such problems for k independent streams of arrivals. Our approach is elementary and self-contained.
Lower regularity solutions of non-homogeneous boundary value problems of the sixth order Boussinesq equation in a quarter plane

In this article, we study an initial-boundary-value problem of the sixth order Boussinesq equation on a half line with nonhomogeneous boundary conditions: \[ u_{tt}-u_{xx}+\beta u_{xxxx}-u_{xxxxxx}+(u^2)_{xx}=0,\quad x>0\mbox{, }t>0,\] \[u(x,0)=\varphi (x), u_t(x,0)=\psi ''(x),\] \[ u(0,t)=h_1(t), u_{xx}(0,t)=h_2(t), u_{xxxx}(0,t)=h_3(t),\] where $\beta=\pm1$. It is shown that the problem is locally well-posed in $H^s(\mathbb{R}^+)$ for $-\frac12<s\leq 0$ with initial condition $(\varphi,\psi)\in H^s(\mathbb{R}^+)\times H^{s-1}(\mathbb{R}^+)$ and boundary condition $(h_1,h_2,h_3) $ in the product space $H^{\frac{s+1}{3}}(\mathbb{R}^+)\times H^{\frac{s-1}{3}}(\mathbb{R}^+)\times H^{\frac{s-3}{3}}(\mathbb{R}^+)$.
Energy-conserving finite-β electromagnetic drift-fluid equations

Nonlinear energy-conserving drift-fluid equations that are suitable to describe self-consistent finite-β low-frequency electromagnetic (drift-Alfven) turbulent fluctuations in a nonuniform, anisotropic, magnetized plasma are derived from a variational principle. The variational principle is based on a drift-fluid Lagrangian that contains linear and nonlinear E×B velocities derived directly from the corresponding single-particle finite-β gyrocenter Hamiltonian (in the zero-Larmor-radius limit). Covariant electromagnetic effects introduce a magnetic generalization to the standard ion polarization density as well as introduce a new ion magnetization current, which appear in finite-β gyrokinetic theory [T. S. Hahm, W. W. Lee, and A. J. Brizard, Phys. Fluids 31, 1940 (1988)] but are both missing from existing gyrofluid and drift-fluid Poisson–Ampere equations. An exact energy conservation law is also derived directly from the drift-fluid Lagrangian by application of the Noether method.
Field equations and particle motion in covariant emergent gravity

We derive the full set of field equations based on Hossenfelder's recent covariant formulation of the emergent gravity model, along with perturbative and exact solutions. The exact solution describes a static, spherically-symmetric spacetime with a non-trivial vector field which plays the role of dark matter under the emergent gravity paradigm. Equations of motion of relativistic test masses are derived and are shown to reduce to Modified Newtonian Dynamics with additional relativistic corrections. It is also shown that the presence of the vector field gives an additional positive contribution to the bending angle in the deflection of light.
Global Regularity for Gravity Unstable Muskat Bubbles

In this paper, we study the dynamics of fluids in porous media governed by Darcy’s law: the Muskat problem. We consider the setting of two immiscible fluids of different densities and viscosities under the influence of gravity in which one fluid is completely surrounded by the other. This setting is gravity unstable because along a portion of the interface, the denser fluid must be above the other. Surprisingly, even without capillarity, the circle-shaped bubble is a steady state solution moving with vertical constant velocity determined by the density jump between the fluids. Taking advantage of our discovery of this steady state, we are able to prove global in time existence and uniqueness of dynamic bubbles of nearly circular shapes under the influence of surface tension. We prove this global existence result for low regularity initial data. Moreover, we prove that these solutions are instantly analytic and decay exponentially fast in time to the circle.
Black holes have more states than those giving the Bekenstein-Hawking entropy: a simple argument

It is often assumed that the maximum number of independent states a black hole may contain is $N_{BH}=e^{S_{BH}}$, where $S_{BH}=A/4$ is the Bekenstein-Hawking entropy and $A$ the horizon area in Planck units. I present a simple and straightforward argument showing that the number of states that can be distinguished by local observers inside the hole must be greater than this number.
The DEEP2 Galaxy Redshift Survey: Spectral Classification of Galaxies at z ∼ 1

We present a principal component analysis (PCA)-based spectral classification, η, for the first 5600 galaxies observed in the DEEP2 Redshift Survey. This parameter provides a very pronounced separation between absorption- and emission-dominated galaxy spectra—corresponding to passively evolving and actively star-forming galaxies in the survey, respectively. In addition it is shown that, despite the high resolution of the observed spectra, this parameter alone can be used to quite accurately reconstruct any given galaxy spectrum, suggesting there are not many "degrees of freedom" in the observed spectra of this galaxy population. It is argued that this form of classification, η, will be particularly valuable in making future comparisons between high- and low-redshift galaxy surveys for which very large spectroscopic samples are now readily available, particularly when used in conjunction with high-resolution spectral synthesis models, which will be made public in the near future. We also discuss the relative advantages of this approach to distant galaxy classification compared to other methods such as colors and morphologies. Finally, we compare the classification derived here with that adopted for the 2dF Galaxy Redshift Survey and in so doing show that the two systems are very similar. This will be particularly useful in subsequent analyses when making comparisons between results from each of these surveys to study evolution in the galaxy populations and large-scale structure.
Interleukin-33 Derived from Endometriotic Lesions Promotes Fibrogenesis through Inducing the Production of Profibrotic Cytokines by Regulatory T Cells

In endometriosis, it has been widely believed that the local immunological milieu is Th2-skewed. Regulatory T cells (Tregs) promote fibrogenesis of endometriosis through the transforming growth factor β1 (TGF-β1) and platelet-derived growth factor (PDGF) signaling pathways. We aimed to explore whether Tregs in endometriotic lesions acquire increased production of effector cytokines under the influence of lesion-derived interleukin (IL)-33. We extracted lymphocytes from normal endometrium and ovarian endometrioma to evaluate the expression of IL-4, IL-13, interferon-γ (IFN-γ), TGF-β1, and the IL-33 receptor (ST2) by Tregs from these tissues. Colocalization of IL-33 and FOXP3 in normal endometrium and ovarian endometrioma was evaluated by immunofluorescence. Tregs and endometriotic stromal cells were co-cultured and treated with anti-IL-33 antibody, and the cytokines produced by Tregs were analyzed by flow cytometry and enzyme-linked immunosorbent assay (ELISA). Tregs in ovarian endometrioma produced significant amounts of IL-4, IL-13, TGF-β1, and ST2. Colocalization of IL-33 and FOXP3 was detected in ovarian endometrioma. IL-33 from endometriotic stromal cells caused the differentiation of lesional Tregs into type 2 T helper (Th2)-like cells, along with increased production of TGF-β1 by Tregs. Thus, Tregs and endometriotic lesions engage active crosstalk through IL-33 to promote fibrogenesis in endometriosis, and, as such, this finding opens up new avenues to identify novel therapeutic targets for endometriosis.
The multiplicative property characterizes $\ell_p$ and $L_p$ norms

We show that $\ell_p$ norms are characterized as the unique norms which are both invariant under coordinate permutation and multiplicative with respect to tensor products. Similarly, the $L_p$ norms are the unique rearrangement-invariant norms on a probability space such that $\|X Y\|=\|X\|\cdot\|Y\|$ for every pair $X,Y$ of independent random variables. Our proof relies on Cram\'er's large deviation theorem.
Evaluating the friction of rotary joints in molecular machines

A computationally-efficient method for evaluating friction in molecular rotary bearings is presented. This method estimates drag from fluctuations in molecular dynamics simulations via the fluctuation–dissipation theorem. This is effective even for simulation times short compared to a bearing's energy damping time and for rotation speeds comparable to or below typical thermal values. We apply this method to two molecular rotary bearings of similar size at 300 K: previously studied nested (9,9)/(14,14) double-walled carbon nanotubes and a hypothetical rotary joint consisting of single acetylenic bonds in a rigid diamondoid housing. The acetylenic joint has a rotational frictional drag coefficient of 2 × 10−35 kg m2 s−1. The friction for the nested nanotubes is 120 times larger, comparable to values reported by previous studies. This fluctuation-based method could evaluate dissipation in a variety of molecular systems with similarly rigid and symmetric bearings.