Miracle-dz/UniFAR-FTUs huggingface dataset:
Quantum-correlated twin-atom laser from a Bose-Hubbard system

We propose and evaluate a method to construct a quantum-correlated twin-atom laser using a pumped and damped Bose-Hubbard in-line trimer which can operate in a stationary regime. With pumping via a source condensate filling the middle well and damping using either an electron beam or optical means at the two end wells, we show that bipartite quantum correlations build up between the ends of the chain and that these can be measured either in situ or in the outcoupled beams. While nothing similar to our system has yet been achieved experimentally, recent advances mean that it should be practically realizable in the near future.
Plant disease identification using Deep Learning: A review

The paper reviews various classification techniques exclusively used for plant disease identification. Early stage plant disease identification is extremely important as that can adversely affect both quality and quantity of crops in agriculture. For identification of plant diseases, different approaches like image processing, machine learning, artificial neural networks, and deep learning are in use. This review focusses on an in-depth analysis on recently emerging deep learning-based methods starting from machine learning techniques. The paper highlights the crop diseases they focus on, the models employed, sources of data used and overall performance according to the performance metrics employed by each paper for plant disease identification. Review findings indicate that Deep Learning provides the highest accuracy, outperforming existing commonly used disease identification techniques and the main factors that affect the performance of deep learning-based tools. This paper is an attempt to document all such approaches for increasing performance accuracy and minimizing response time in the identification of plant diseases. The authors also present the attempts for disease diagnosis in Indian conditions using real dataset.
N-Beats as an EHG Signal Forecasting Method for Labour Prediction in Full Term Pregnancy

The early prediction of onset labour is critical for avoiding the risk of death due to pregnancy delay. Low-income countries often struggle to deliver timely service to pregnant women due to a lack of infrastructure and healthcare facilities, resulting in pregnancy complications and, eventually, death. In this regard, several artificial-intelligence-based methods have been proposed based on the detection of contractions using electrohysterogram (EHG) signals. However, the forecasting of pregnancy contractions based on real-time EHG signals is a challenging task. This study proposes a novel model based on neural basis expansion analysis for interpretable time series (N-BEATS) which predicts labour based on EHG forecasting and contraction classification over a given time horizon. The publicly available TPEHG database of Physiobank was exploited in order to train and test the model, where signals from full-term pregnant women and signals recorded after 26 weeks of gestation were collected. For these signals, the 30 most commonly used classification parameters in the literature were calculated, and principal component analysis (PCA) was utilized to select the 15 most representative parameters (all the domains combined). The results show that neural basis expansion analysis for interpretable time series (N-BEATS) forecasting can forecast EHG signals through training after few iterations. Similarly, the forecasting signal’s duration is determined by the length of the recordings. We then deployed XG-Boost, which achieved the classification accuracy of 99 percent, outperforming the state-of-the-art approaches using a number of classification features greater than or equal to 15.
Exploring the shape of the γ-ray spectrum around the “π0-bump”

The “pion-decay” bump is a distinct signature of the differential energy spectrum of γ-rays between 100 MeV and 1 GeV produced in hadronic interactions of accelerated particles (cosmic rays) with the ambient gas. We use recent parametrisations of relevant cross-sections to study the formation of the “pion-decay” bump. The γ-ray spectrum below the maximum of this spectral feature can be distorted because of contributions of additional radiation components, in particular, due to the bremsstrahlung of secondary electrons and positrons, the products of decays of π±-mesons, accompanying the π0-production. At energies below 100 MeV, a non-negligible fraction of γ-ray flux could originate from interactions of sub-relativistic heavy ions. We study the impact of these radiation channels on the formation of the overall γ-ray spectrum based on a time-dependent treatment of evolution of energy distributions of the primary and secondary particles in the γ-ray production region.
Correlated Fermions in a One-Dimensional Quasiperiodic Potential

We study analytically one-dimensional interacting spinless fermions in a Fibonacci potential. We show that the effects of the quasiperiodic modulation are intermediate between those of a commensurate potential and a disordered one. The system exhibits a metal-insulator transition whose position depends both on the strength of the correlations and on the position of the Fermi level. Consequently, the conductivity displays a power law like size and frequency behaviour characterized by a non trivial exponent.
Unified parametric ICA algorithm for hybrid sources and its stability analysis

Independent component analysis (ICA) refers to extract independent signals from their linear mixtures without assuming prior knowledge of their mixing coefficients. The purpose of this paper is to develop a novel unified parametric ICA algorithm, which enable to separate hybrid source signals including symmetric and asymmetric sources with a self-adaptive score functions. It is derived from the parameterized asymmetric generalized Gaussian density (AGGD) model. The parameters of the score function in the algorithm can be chosen adaptively by estimating the high order statistics of the observed signals online. Stability analysis of the proposed AGGD-ICA learning algorithm is also discussed. Compared with conventional ICA algorithm, the method can separate a wide range of source signals using only one unified density model. Simulations confirm the effectiveness and performance of the proposed algorithm.
Prediction of COVID-19 Spreading using LSTM Recurrent Neural Networks in Southeast Asia

The world has come to a standstill due to the coronavirus. The number of confrmed cases and the number of deaths are increasing day by day. Now accurate and real-time predictions are very important. Currently, a lot of work is being done on the spread prediction of coronavirus. If we can predict the number of corona patients in a country in advance, then it will be benefcial for the government of that country to take action in advance. In this paper, we experiment with Bangladesh and India data using the deep learning method. We have used LSTM (LONG SHORT-TERM MEMORY) neural network which is a type of recurrent neural network. The LSTM method can work very well even with very little data. Since we do not currently have much data on covid19, LSTM neural networks may be a suitable model. We have got very good prediction results using this method even with very little data. The prediction of various parameters (number of confrmed cases per day, number of deaths per day, number of total confrmed cases, and number of total deaths). We also calculate MAPE, MAE, and RMSE values and compare them among different models. Our modeloutperforms others’ models. We think this research will be a benefcial tool for administrators and health offcials. GUB JOURNAL OF SCIENCE AND ENGINEERING, Vol 8, Dec 2021 P 1-6
Molecular-dynamics simulations of lead clusters

Molecular dynamics simulations of nanometer-sized lead clusters have been performed using the Lim, Ong and Ercolessi glue potential (Surf. Sci. {\bf 269/270}, 1109 (1992)). The binding energies of clusters forming crystalline (fcc), decahedron and icosahedron structures are compared, showing that fcc cuboctahedra are the most energetically favoured of these polyhedral model structures. However, simulations of the freezing of liquid droplets produced a characteristic form of ``shaved'' icosahedron, in which atoms are absent at the edges and apexes of the polyhedron. This arrangement is energetically favoured for 600-4000 atom clusters. Larger clusters favour crystalline structures. Indeed, simulated freezing of a 6525-atom liquid droplet produced an imperfect fcc Wulff particle, containing a number of parallel stacking faults. The effects of temperature on the preferred structure of crystalline clusters below the melting point have been considered. The implications of these results for the interpretation of experimental data is discussed.
Characterization and Bioactive Potential of Carotenoid Lutein from Gordonia rubripertncta GH-1 Isolated from Traditional Pixian Douban

The characterization and bioactive properties of carotenoid produced by Gordonia rubripertincta GH-1 originating from Pixian Douban (PXDB), the Chinese traditional condiment, was investigated. The produced and purified yellow pigment was characterized by ultraviolet-visible spectroscopy (UV-Vis), Fourier transformed infrared (FTIR), nuclear magnetic resonance (NMR), and high-resolution mass spectrometry (HRMS), and was identified as carotenoid lutein. Additionally, the bioactive activity of lutein from G. rubripertincta GH-1 was evaluated by measuring the free radical scavenging capacity in vitro and feeding zebrafish lutein through aqueous solution. The results showed that the carotenoid lutein had strong antioxidant capacity and a protective effect on zebrafish eye cells, which could inhibit the apoptosis of eye cells in a concentration dependent manner. The results suggested that carotenoid lutein from G. rubripertincta GH-1 could be utilized as a potential source of natural antioxidants or functional additives for food/pharmaceutical industries.
Exploring Millennials’ Motives in Media Class Preferences: Advertising Implications

Millennials have become a preoccupation for marketers, especially as they enter their peak earning and spending life stages. This exploratory study represents a touchstone to the motivations, beliefs, feelings, and behaviors members of the millennial cohort, those born between 1980-2000, exhibited toward three major media classes (print, broadcast, and Internet). Forty-one millennials participated in a series of synchronous online focus groups administered through a learning management system (LMS), or focus group chats (FGCs) for short. This study compares millennials’ views toward traditional media (namely, television and newspapers) against the Internet with an emphasis on perceived advantages and disadvantages of each medium, especially as they relate to millennials’ media class preferences. Support for the participants’ suppositions and expressions of their motives, behaviors, and opinions came by way of their verbatim answers to questions posed by the online focus group moderator. The findings suggest that millennials’ media class choices are influenced by convenience, access availability, time shift issues, and preferences. The participants showed discernable control anxiety about new Internet connected devices (ICDs) and media content sources.
Electron acceleration by colliding laser beams in plasmas

All-optical controlled injection and acceleration of electrons in a laser wakefield has recently been achieved [1]. Injection was made using a second counterpropagating laser pulse with the same polarization as the main pulse . In this scheme, the interference pattern formed during the collision between the pulses pre-accelerates electrons that are then trapped in the wakefield. Numerical simulations of this process performed with a new Particle-in-Cell code are presented here. The results show the nature of the injection mechanism and explain some striking features found experimentally, such as the dependence of beam energy with the collision position and the reduction of the charge at high energies. Simulations reproduce well the main features of the experimental observations. The field of laser-plasma wakefield acceleration has known a fast development over the past few years. In this approach, particles are accelerated in the relativistic plasma wave excited by an intense laser propagating in a underdense plasma. Electric fields in the wake can reach some hundreds of GeV/m instead of the tens of MeV/m attainable in conventional RF accelerators, opening the door to a new generation of compact particle accelerators. Up to now, a single laser beam was responsible for the injection and subsequent acceleration of the electrons [2, 3, 4, 5]. Very recently, the external injection of electrons in the wakefield using a second laser beam has been demonstrated [1]. Electron beams obtained in this manner are quasi-monoenergetic, tuneable and stable. The idea of using a second laser to inject the electrons was proposed years ago [6], and further developed in the scheme implemented in the experiments [7]. In this version, two counterpropagating laser pulses with the same wavelength �0 and polarization are used. The first pulse (the pump pulse), with normalized amplitude a0 > 1, creates a wakefield. The second pulse (the injection pulse), with normalized amplitude a1 < 1, collides with the pump pulse. During the collision, a laser beatwave pattern with phase velocity vbw ≈ 0 is formed [7]. The scale of the beatwave pattern is �0/2, therefore the ponderomotive force of the beatwave Fbw ∝ 2a0a1/�0
Effects of Weak Lensing on the Topology of Cosmic Microwave Background Maps

We investigate the non-Gaussian signatures in cosmic microwave background maps induced by the intervening large-scale structure through weak lensing. In order to measure the deviation from the Gaussian behavior of the intrinsic temperature anisotropies, we use a family of three morphological descriptors, the so-called Minkowski functionals. We show analytically how these quantities depend on the temperature threshold and compare the results to numerical experiments including the instrumental effects of Planck. Minkowski functionals can directly measure the statistical properties of the displacement field and hence provide useful constraints on large-scale structure formation in the past.
The evolving far-IR galaxy luminosity function and dust-obscured star-formation rate density out to z~5

We present a new measurement of the evolving galaxy far-IR luminosity function (LF) extending out to redshifts z~5, with resulting implications for the level of dust-obscured star-formation density in the young Universe. To achieve this we have exploited recent advances in sub-mm/mm imaging with SCUBA-2 on the James Clerk Maxwell Telescope (JCMT) and the Atacama Large Millimeter/Submillimeter Array (ALMA), which together provide unconfused imaging with sufficient dynamic range to provide meaningful coverage of the luminosity-redshift plane out to z>4. Our results support previous indications that the faint-end slope of the far-IR LF is sufficiently flat that comoving luminosity-density is dominated by bright objects (~L*). However, we find that the number-density/luminosity of such sources at high redshifts has been severely over-estimated by studies that have attempted to push the highly-confused Herschel SPIRE surveys beyond z~2. Consequently we confirm recent reports that cosmic star-formation density is dominated by UV-visible star formation at z>4. Using both direct (1/Vmax) and maximum likelihood determinations of the LF, we find that its high-redshift evolution is well characterized by continued positive luminosity evolution coupled with negative density evolution (with increasing redshift). This explains why bright sub-mm sources continue to be found at z>5, even though their integrated contribution to cosmic star-formation density at such early times is very small. The evolution of the far-IR galaxy LF thus appears similar in form to that already established for active galactic nuclei, possibly reflecting a similar dependence on the growth of galaxy mass.
A Bayesian Approach to the Linear Model with Unequal Variances

Estimation procedures are proposed for the means and variances of several normal distributions. They are valid in cases where the parameters of different distributions may be unequal but are thought a priori to be related in certain ways. A log-linear model is assumed for the variances, together with a linear model for the means. Some general Bayesian results are obtained, and some special cases are discussed including the important situation where parameters of different distributions are a priori exchangeable. The posterior estimates then adjust the standard estimates, by shrinking them towards central values based on collateral information. A numerical example concerns the simultaneous estimation of the variances of the observed breaking strengths of six fabrics.
The Orthographic Ambiguity of the Arabic Graphic System: Evidence from a Case of Central Agraphia Affecting the Two Routes of Spelling

The Arabic writing system includes ambiguities that create difficulties in spelling. These ambiguities relate mainly to the long vowels, some phoneme-grapheme conversions, lexical particularities, and the connectivity of letters. In this article, the first to specifically explore acquired spelling impairments in an Arabic-speaking individual, we report the case of CHS, who presented with agraphia following a stroke. Initial testing indicated substantial impairment of CHS's spelling abilities in the form of mixed agraphia. The experimental study was specifically designed to explore the influence of the orthographic ambiguity of the Arabic graphemic system on CHS's spelling performance. The results revealed that CHS had substantial difficulties with orthographic ambiguity and tended to omit ambiguous graphemes. Some of the errors she produced suggested reliance on the sublexical route of spelling, while others rather reflected the adoption of the lexical-semantic route. These findings from a case involving a non-Western, non-Indo-European language contribute to discussions of theoretical models of spelling. They show that CHS's pattern of impairment is consistent with the summation hypothesis, according to which the lexical-semantic and the sublexical routes interactively contribute to spelling.
Kinematics and Mass Profile of AWM 7

We have measured 492 redshifts (311 new) in the direction of the poor cluster AWM 7 and have identified 179 cluster members (73 new). We use two independent methods to derive a self-consistent mass profile, under the assumptions that the absorption-line galaxies are virialized and that they trace an underlying Navarro, Frenk, & White (NFW) dark matter profile: (1) we fit such an NFW profile to the radial distribution of galaxy positions and to the velocity dispersion profile; (2) we apply the virial mass estimator to the cluster. With these assumptions, the two independent mass estimates agree to ∼15% within 1.7 h-1 Mpc, the radial extent of our data; we find an enclosed mass ∼(3 ± 0.5) × 1014 h-1 M⊙. The largest potential source of systematic error is the inclusion of young emission-line galaxies in the mass estimate. We investigate the behavior of the surface term correction to the virial mass estimator under several assumptions about the velocity anisotropy profile, still within the context of the NFW model, and remark on the sensitivity of derived mass profiles to outliers. We find that one must have data out to a large radius in order to determine the mass robustly, and that the surface term correction is unreliable at small radii.
Data-driven linear time advance operators for the acceleration of plasma physics simulation

We demonstrate the application of data-driven linear operator construction for time advance with a goal of accelerating plasma physics simulation. We apply dynamic mode decomposition (DMD) to data produced by the nonlinear SOLPS-ITER (Scrape-off Layer Plasma Simulator - International Thermonuclear Experimental Reactor) plasma boundary code suite in order to estimate a series of linear operators and monitor their predictive accuracy via online error analysis. We find that this approach defines when these dynamics can be represented by a sequence of approximate linear operators and is essential for providing consistent projections when compared to an unconstrained application. For linear diffusion and advection–diffusion fluid test problems, we construct and apply operators within explicit and implicit time advance schemes, demonstrating that stability can be robustly guaranteed in each case. We further investigate the use of the linear time advance operators within several integration methods including forward Euler, backward Euler, and the matrix exponential. The application of this method to simulation data from SOLPS-ITER, with varying levels of Markov chain Monte Carlo numerical noise, shows that constrained DMD operators yield a capability to identify, extract, and integrate a (slow) subset of the present timescales. Example applications show that for projected speedup factors of [Formula: see text], and [Formula: see text], a mean relative error of 3%, 5%, and 8% and maximum relative error less than 20% are achievable, which appears acceptable for typical SOLPS-ITER steady-state simulations.
Resolving the Composite Fe Kα Emission Line in the Galactic Black Hole Cygnus X-1 with Chandra

We observed the Galactic black hole Cyg X-1 with the Chandra High Energy Transmission Grating Spectrometer for 30 ks on 2001 January 4. The source was in an intermediate state, with a flux that was approximately twice that commonly observed in its persistent low/hard state. Our best-fit model for the X-ray spectrum includes narrow Gaussian emission line (E = 6.415 ± 0.007 keV, FWHM= 80 eV, W = 16 eV) and broad-line (E = 5.82 keV, FWHM= 1.9 keV, W = 140 eV) components, and a smeared edge at 7.3 ± 0.2 keV (τ ~ 1.0). The broad-line profile is not as strongly skewed as those observed in some Seyfert galaxies. We interpret these features in terms of an accretion disk with irradiation of the inner disk producing a broad Fe Kα emission line and edge, and irradiation of the outer disk producing a narrow Fe Kα emission line. The broad line is likely shaped predominantly by Doppler shifts and gravitational effects, and to a lesser degree by Compton scattering due to reflection. We discuss the underlying continuum X-ray spectrum and these line features in the context of diagnosing the accretion flow geometry in Cyg X-1 and other Galactic black holes.
An electroholographic colour reconstruction by time division switching of reference lights

In this paper, we report an electroholographic reconstruction method for a colour three-dimensional (3D) object, using the time division switching of reference lights. We use a reflective liquid crystal display (LCD) panel with a high refresh rate as a spatial light modulator. A colour 3D object is divided into red, green and blue components, from which we compute three computer-generated holograms (CGHs). The LCD panel displays the CGHs in sequence at a refresh rate of about 100 Hz. The LCD panel also outputs synchronized signals, indicating that one of the CGHs is currently displayed on the LCD panel. Red, green and blue light emitting diodes (LEDs), as used for reference lights, are switched by the synchronized signals. As a result of the afterimage effect on human eyes, we can clearly observe a coloured 3D object.