Miracle-dz/UniFAR-FTUs huggingface dataset:
A high-order WENO-based staggered Godunov-type scheme with constrained transport for force-free electrodynamics

The force-free (or low inertia) limit of magnetohydrodynamics (MHD) can be applied to many astrophysical objects, including black holes, neutron stars and accretion discs, where the electromagnetic field is so strong that the inertia and pressure of the plasma can be ignored. This is difficult to achieve with the standard MHD numerical methods because they still have to deal with plasma inertial terms even when these terms are much smaller than the electromagnetic terms. Under the force-free approximation, the plasma dynamics is entirely determined by the magnetic field. The plasma provides the currents and charge densities required by the dynamics of electromagnetic fields, but these currents carry no inertia. We present a high-order Godunov scheme to study such force-free electrodynamics. We have implemented weighted essentially non-oscillatory (WENO) spatial interpolations in our scheme. An exact Riemann solver is implemented, which requires spectral decomposition into characteristic waves. We advance the magnetic field with the constrained transport (CT) scheme to preserve the divergence-free condition to machine round-off error. We apply the third-order total variation diminishing (TVD) Runge-Kutta scheme for the temporal integration. The mapping from face-centred variables to volume-centred variables is carefully considered. Extensive testing are performed to demonstrate the ability of our scheme to address force-free electrodynamics correctly. We finally apply the scheme to study relativistic magnetically dominated tearing instabilities and neutron star magnetospheres.
Sparse neural network regression with variable selection

This paper reports on our study of a sparse neural network regression method based on a single hidden layer architecture and sparsity‐inducing penalties. To determine the size of network in a data‐adaptive way, we adopt the lasso and group lasso penalty functions to simultaneously induce sparsity at node and predictor levels. We also devise several techniques to improve performance of the neural network regression estimator. We adopt a B‐spline activation function with a compact support to identify local trends of data. In addition, we develop an algorithm based on node addition process, in which additional nodes come into the network as a complexity parameter decreases. At each value of the complexity parameter, the algorithm initializes the additional nodes along the direction that best captures the unexplained functional relationship between the response and predictors. The optimization step is conducted based on an efficient coordinate descent algorithm. Numerical studies based on simulated and real datasets illustrate that the combination of the aforementioned devices significantly improves the performance of the neural network estimator.
Colloidal Transport in Locally Periodic Evolving Porous Media - An Upscaling Exercise

We derive an upscaled model describing the aggregation and deposition of colloidal particles within a porous medium allowing for the possibility of local clogging of the pores. At the level of the pore scale, we extend an existing model for colloidal dynamics including the evolution of free interfaces separating colloidal particles deposited on solid boundaries (solid spheres) from the colloidal particles transported through the gaseous parts of the porous medium. As a result of deposition, the solid spheres grow reducing therefore the space available for transport in the gaseous phase. Upscaling procedures are applied and several classes of macroscopic models together with effective transport tensors are obtained, incorporating explicitly the local growth of the solid spheres. The resulting models are solved numerically and various simulations are presented. In particular, they are able to detect clogging regions, and therefore, can provide estimates on the storage capacity of the porous matrix.
Detecting the elusive blazar counter-jets

Detection of blazar pc scale counter-jets is difficult, but it can provide invaluable insight into the relativistic effects, radiative processes and the complex mechanisms of jet production, collimation and accelation in blazars. We build on recent populations models (optimized using the MOJAVE apparent velocity and redshift distributions) in order to derive the distribution of jet-to-counter-jet ratios and the flux densities of the counter-jet at different frequencies, in an effort to set minimum sensitivity limits required for existing and future telescope arrays in order to detect these elusive counter-jets. We find that: for the BL Lacs $5\%$ of their counter-jets have a flux-density higher than 100mJy, $15\%$ are higher than 10 mJy, and $32\%$ have higher flux-density than 1 mJy, whereas for the FSRQs $8\%$ have a flux-density higher than 10mJy, $17\%$ are higher than 1 mJy, and $32\%$ are higher than 0.1 mJy (at 15 GHz). Future telescopes like the SKA and newly operating like e-MERLIN and JVLA may detect up to $99\%$ of the BL Lac and $77\%$ of the FSRQ counter-jets. Sources with both low apparent velocity and a low Doppler factor make prime candidates for counter-jet detection. Combining our findings with literature values we have identified five such counter-jet detection candidates. Finally, we discuss possible effects beyond relativistic deboosting that may complicate the detection of counter-jets and that need to be accounted for in the interpretation of detections.
MXenes: Advances in the synthesis and application in supercapacitors and batteries

MXenes, the newest family member of the two-dimensional materials have been widely investigated for different applications, particularly in the energy storage realm. With regard to this, MXene precursors have attained widespread attention for the application in electrochemical energy storage devices especially supercapacitors and batteries. This review has comprehensively studied various synthesis strategies adopted for MXenes including the top-down and bottom-up approaches. The shift to renewable energy alternatives have focused on the electrochemical choices such as supercapacitors and batteries, the most common and relevant ones. Thus the application of MXenes and its composite in supercapacitors as electrodes have been analyzed along with its detailed mechanism and electrochemical performance. Several battery chemistries including lithium-ion, sodium-ion and other battery systems utilizing MXenes have also been discussed here. Thus the existing strategies, advancements, and drawbacks regarding the inclusivity of MXenes in the electrochemical energy systems of supercapacitors and batteries are reviewed in this article. Graphical abstract
A Risk-Based Framework for Power System Modeling to Improve Resilience to Extreme Events

The extent of the damage to Puerto Rico from Hurricane Maria in September 2017 led to outages in electricity service that persisted for months. Power system operators attempting to restore critical facilities faced challenges on almost every front, from supply chain interruptions to the inaccessibility of key assets. After a disaster of this magnitude, it is critical, but challenging, to prioritize how limited resources are directed toward rebuilding and fortifying the electric power system. To inform these decisions, the U.S. Department of Energy funded efforts investigating methodologies to identify critical vulnerabilities to the Puerto Rican power system, and to provide data-driven recommendations on how to harden and operate the system for greater resilience. This work presents the Risk-based Contingency Analysis Tool (RCAT), a framework developed as a part of that resilience initiative. The framework can qualitatively and quantitatively describe the most critical system vulnerabilities with an understanding of both likelihood of occurrence and impact. It evaluates the effectiveness of candidate remediation strategies in reducing overall risk to the system from future hurricane events. This paper will describe RCAT, with an emphasis on how different modeling capabilities have been integrated along with probabilistic methods and analytical metrics to better describe risk.
Dimensional reduction and its breakdown in the three-dimensional long-range random-field Ising model

We investigate dimensional reduction, the property that the critical behavior of a system in the presence of quenched disorder in dimension $d$ is the same as that of its pure counterpart in $d\ensuremath{-}2$, and its breakdown in the case of the random-field Ising model in which both the interactions and the correlations of the disorder are long ranged, i.e., power-law decaying. To some extent the power-law exponents play the role of spatial dimension in a short-range model, which allows us to probe the theoretically predicted existence of a nontrivial critical value separating a region where dimensional reduction holds from one where it is broken, while still considering the physical dimension $d=3$. By extending our recently developed approach based on a nonperturbative functional renormalization group combined with a supersymmetric formalism, we find that such a critical value indeed exists, provided one chooses a specific relation between the decay exponents of the interactions and of the disorder correlations. This transition from dimensional reduction to its breakdown should therefore be observable in simulations and numerical analyses, if not experimentally.
The Effect of the Aesthetically Mobile Interfaces on Students’ Learning Experience for Primary Education

Mobile devices such as mobile phones are becoming more important to school students today. This is due to the COVID-19 pandemic, mostly traditional face-to-face learning has shifted to online learning such as learning via a mobile platform. Mobile learning also known as m-learning, is defined as learning in numerous situations through social and content interaction utilizing personal electronic devices. M-learning applications not only need to have efficient functions, but it also has to attract students to learn by providing an attractive interface. An aesthetic of a mobile interface is essential since it could influence the user's learning experiences, but vice versa for non-aesthetic interfaces. User experience (UX) encompasses an extensive range of outcomes of the user-device interaction, including cognitions, attitudes, beliefs, behaviour, behavioural intentions, and affect. However, this study focuses on UX in terms of learnability, satisfaction, and efficiency since most previous studies were not explicitly focused on examining these three (3) UX components. Thus, this study aims to investigate the effect of aesthetically mobile interfaces on the learnability, satisfaction, and efficiency of primary school students, specifically, for Kelas Al-Quran and Fardu Ain (KAFA) students. This study found that aesthetically mobile interfaces significantly affected students’ learning experiences regarding learnability, satisfaction, and efficiency. In conclusion, the findings of this study could serve as guidelines for future research in the field of mobile interface design. © 2022, International Journal of Advanced Computer Science and Applications. All Rights Reserved. All Rights Reserved.
The stellar and dark matter distributions in elliptical galaxies from the ensemble of strong gravitational lenses

We derive the average mass profile of elliptical galaxies from the ensemble of 161 strong gravitational lens systems selected from several surveys, assuming that the mass profile scales with the stellar mass and effective radius of each lensing galaxy. The total mass profile is well fitted by a power-law \rho(r) \propto r^\gamma with best-fit slope \gamma = -2.11+/-0.05. The decomposition of the total mass profile into stellar and dark matter distributions is difficult due to a fundamental degeneracy between the stellar initial mass function (IMF) and the dark matter fraction f_DM. We demonstrate that this IMF-f_DM degeneracy can be broken by adding direct stellar mass fraction measurements by quasar microlensing observations. Our best-fit model prefers the Salpeter IMF over the Chabrier IMF, and a smaller central dark matter fraction than that predicted by adiabatic contraction models.
Constrained optimal consensus in multi-agent systems with single- and double-integrator dynamics

ABSTRACT This paper fully studies distributed optimal consensus problem in undirected dynamical networks. We consider a group of networked agents that are supposed to rendezvous at the optimal point of a collective convex objective function. Each agent has no knowledge about the global objective function and only has access to its own local objective function, which is a portion of the global one, and states information of agents within its neighbourhood set. In this setup, all agents coordinate with their neighbours to seek the consensus point that minimises the network's global objective function. In the current paper, we consider agents with single-integrator and double-integrator dynamics. Further, it is supposed that agents' movements are limited by some convex inequality constraints. In order to find the optimal consensus point under the described scenario, we combine the interior-point optimisation algorithm with a consensus protocol and propose a distributed control law. The associated convergence analysis based on Lyapunov stability analysis is provided.
Starobinsky-like inflationary models as avatars of no-scale supergravity

Models of cosmological inflation resembling the Starobinsky R+R2 model emerge naturally among the effective potentials derived from no-scale SU(N,1)/SU(N) × U(1) supergravity when N > 1. We display several examples in the SU(2,1)/SU(2) × U(1) case, in which the inflaton may be identified with either a modulus field or a matter field. We discuss how the modulus field may be stabilized in models in which a matter field plays the role of the inflaton. We also discuss models that generalize the Starobinsky model but display different relations between the tilt in the spectrum of scalar density perturbations, ns, the tensor-to-scalar ratio, r, and the number of e-folds, N*. Finally, we discuss how such models can be probed by present and future CMB experiments.
Research on distributed competition big data hierarchical storage method based on Ceph architecture

In the face of intensive data access requests, the current big data storage methods have the problem of poor concurrent read-write performance. Based on Ceph architecture, a distributed big data hierarchical storage method is designed to realize the robust storage service of data files. According to the frequency and popularity of the access object, the cold data with low frequency is eliminated, and the access cache pool or back-end storage pool is selected. Standardize the I/O performance, load and capacity values in the OSD set, calculate the comprehensive weight, and determine the priority of node access. The entire Ceph architecture balances the data distribution. When highly concurrent data access operations occur, a random number is selected to execute the read service of the storage node to ensure the interconnection communication in different clusters. The test results show that the write and read time of the hierarchical storage method based on Ceph architecture is greatly reduced, and good results are achieved in terms of cache hit rate, which can effectively manage and store competitive big data.
The black hole and cosmological solutions in IR modified Hořava gravity

Recently Ho? ava proposed a renormalizable gravity theory in four dimensions which reduces to Einstein gravity with a non-vanishing cosmological constant in IR but with improved UV behaviors. Here, I study an IR modification which breaks ``softly'' the detailed balance condition in Ho? ava model and allows the asymptotically flat limit as well. I obtain the black hole and cosmological solutions for ``arbitrary'' cosmological constant that represent the analogs of the standard Schwarzschild-(A)dS solutions which can be asymptotically (A)dS as well as flat and I discuss their thermodynamical properties. I also obtain solutions for FRW metric with an arbitrary cosmological constant. I study its implication to the dark energy and find that it seems to be consistent with current observational data.
Evolution of Cell Wall Polymers in Tip-Growing Land Plant Gametophytes: Composition, Distribution, Functional Aspects and Their Remodeling

During evolution of land plants, the first colonizing species presented leafy-dominant gametophytes, found in non-vascular plants (bryophytes). Today, bryophytes include liverworts, mosses, and hornworts. In the first seedless vascular plants (lycophytes), the sporophytic stage of life started to be predominant. In the seed producing plants, gymnosperms and angiosperms , the gametophytic stage is restricted to reproduction. In mosses and ferns, the haploid spores germinate and form a protonema, which develops into a leafy gametophyte producing rhizoids for anchorage, water and nutrient uptakes. The basal gymnosperms (cycads and Ginkgo) reproduce by zooidogamy. Their pollen grains develop a multi-branched pollen tube that penetrates the nucellus and releases flagellated sperm cells that swim to the egg cell. The pollen grain of other gymnosperms (conifers and gnetophytes) as well as angiosperms germinates and produces a pollen tube that directly delivers the sperm cells to the ovule (siphonogamy). These different gametophytes, which are short or long-lived structures, share a common tip-growing mode of cell expansion. Tip-growth requires a massive cell wall deposition to promote cell elongation, but also a tight spatial and temporal control of the cell wall remodeling in order to modulate the mechanical properties of the cell wall. The growth rate of these cells is very variable depending on the structure and the species, ranging from very slow (protonemata, rhizoids, and some gymnosperm pollen tubes), to a slow to fast-growth in other gymnosperms and angiosperms. In addition, the structural diversity of the female counterparts in angiosperms (dry, semi-dry vs wet stigmas, short vs long, solid vs hollow styles) will impact the speed and efficiency of sperm delivery. As the evolution and diversity of the cell wall polysaccharides accompanied the diversification of cell wall structural proteins and remodeling enzymes, this review focuses on our current knowledge on the biochemistry, the distribution and remodeling of the main cell wall polymers (including cellulose, hemicelluloses, pectins, callose, arabinogalactan-proteins and extensins), during the tip-expansion of gametophytes from bryophytes, pteridophytes (lycophytes and monilophytes), gymnosperms and the monocot and eudicot angiosperms.
ASTROSAT: Some Key Science Prospects

ASTROSAT is an astronomy satellite designed for simultaneous multi-wavelength studies in the Optical/UV and a broad X-ray energy range. With four X-ray instruments and a pair of UV-Optical telescopes, ASTROSAT will provide unprecedented opportunity for simultaneous multi-wavelength observations, which is of immense value in study of highly variable sources, especially X-ray binaries and active galactic nuclei. The Large Area X-ray Proportional Counters (LAXPC) of ASTROSAT, which has the largest effective area in the hard X-ray band compared to all previous X-ray missions, will enable high time resolution X-ray measurements in the 2–80 keV band with moderate energy resolution. Here we give a brief summary of the payload characteristics of ASTROSAT and discuss some of the main science topics that will be addressed with the LAXPC, and with simultaneous observations with the UVIT telescopes, with particular emphasis on X-ray binaries and compact objects. The possibility of aiding gravitational wave experiments is also briefly mentioned.
Geometry equilibration of crystalline defects in quantum and atomistic descriptions

We develop a rigorous framework for modeling the geometry equilibration of crystalline defects. We formulate the equilibration of crystal defects as a variational problem on a discrete energy space and establish qualitatively sharp far-field decay estimates for the equilibrium configuration. This work extends [V. Ehrlacher, C. Ortner and A. Shapeev, Analysis of boundary conditions for crystal defect atomistic simulations, Arch. Ration. Mech. Anal. 222 (2016) 1217–1268] by admitting infinite-range interaction which in particular includes some quantum chemistry based interatomic interactions.
CDT - an Entropic Theory of Quantum Gravity

In these lectures we describe how a theory of quantum gravity may be constructed in terms of a lattice formulation based on so-called causal dynamical triangulations (CDT). We discuss how the continuum limit can be obtained and how to define and measure diffeomorphism-invariant correlators. In four dimensions, which has our main interest, the lattice theory has an infrared limit which can be identified with de Sitter spacetime. We explain why this infrared property of the quantum spacetime is nontrivial and due to "entropic" effects encoded in the nonperturbative path integral measure. This makes the appearance of the de Sitter universe an example of true emergence of classicality from microscopic quantum laws. We also discuss nontrivial aspects of the UV behaviour, and show how to investigate quantum fluctuations around the emergent background geometry. Finally, we consider the connection to the asymptotic safety scenario, and derive from it a new, conjectured scaling relation in CDT quantum gravity.
Ion acceleration in the ‘dragging field’ of a light-pressure-driven piston

We propose a new acceleration scheme by employing the enormous electric potential behind a light-pressure-driven piston, namely ‘dragging field acceleration’. When a thin foil driven by light pressure of an ultra-intense laser pulse propagates in underdense background plasma, it serves as a shock-like piston, trapping and reflecting background protons to ultra-high energies. Unlike in shock wave acceleration, the piston velocity is not limited by the Mach number and can be highly relativistic. Background protons can be trapped and reflected forward by the ‘dragging field’ potential attached to a piston, which is not employed in light-pressure acceleration. Our one-dimensional particle-in-cell simulations and analytical model both show that proton energies of several tens to hundreds of GeV can be obtained. The injection conditions are investigated. Generation of mono-energetic tens-of-GeV proton bunch in two-dimensional geometry are discussed. Finally, the scheme is demonstrated with a three-dimensional simulation, where the effect of radiation reaction is included.