Miracle-dz/UniFAR-FTUs huggingface dataset:
Structured Beamforming Based on Orbital Angular Momentum Mode-Group

The structured beams, which can manipulate arbitrary intensity and phase of electromagnetic rays, are significant in communication and sensing. The vortex electromagnetic wave carrying orbital angular momentum (OAM) exhibits the phase distribution of the helical wavefront, which can be viewed as a complete set of eigenmodes for electromagnetic waves. It provides a flexible beamforming method to achieve the azimuthal pattern diversity by the spatial superposition of multiple specific OAM modes. We have proposed a novel form of OAM wave with a two-dimensional structure called plane spiral OAM (PS-OAM), which is conducive to overlapping different modes. Based on this, the PS-OAM mode-group can be employed to modify the spatial beam structure and form structured electromagnetic beams. This kind of beam not only retains the inherent vorticity and orthogonality of the OAM waves but also tackles the difficulties in applications stemming from the singularity-caused dark zone and beam divergence of conventional OAM waves. In this paper, the construction and manipulation of the structured beams are investigated, and the properties are analyzed. The potential applications in multiple-input multiple-output (MIMO) communication, orthogonal multiplexing communication, and spatial field digital modulation (SFDM) communication are envisioned.
Prospect and scope of artificial neural network in livestock farming: a review

ABSTRACT Early prediction of livestock productivity in any livestock enterprise provides valuable information to adopt strategic farm management for economic and profitable livestock production. Therefore, researchers developed and implemented different mathematical tools to establish the accuracy of prediction. However, due to the complexity of data sets and high-order non-linearity among the individuals concerning different production traits, the accuracy of forecasting livestock productivity is a tedious job. With this context, the artificial neural network (ANN), a machine learning program, gained popularity in the field of animal science due to its robust and effective handling of the complexity of a large datasets. The present review aims to discuss the potential utility of artificial neural networks in the different fields of livestock farming for improving livestock productivity as well as for the efficient farm management practices for economic and sustainable livestock production.
BIOINFORMATIC ANALYSIS AND PURIFICATION OF GLUTATHIONE TRANSFERASE (GST) from Pseudomonas sp. UW4

The study aimed at identifying and purifying cytosolic glutathione transferase isoforms expressed in Pseudomonas sp. UW4. Search at UniProt (https://www.uniprot.org/uniprot/), has indicated that there were 20 genes encoding putative glutathione transferases for the microorganism. The molecular weights of the isoforms ranged from 17.6 to 34.06 kDa. SDS-polyacrylamide gel electrophoresis revealed that the GST purified using Sulfobromophthalein-glutathione (BSP) affinity column, resolved into a single band with a low molecular weight (MW) of 16 kDa with the pI value of 6.0. Purified GST was reactive towards ethacrynic acid, 1-chloro-2,4-dinitrobenzene, cumene hydroxide, and hydrogen peroxide, but no detectable activity with Trans-2-octenal, hepta-2,4-dienal and Trans-4-phenyl-3-butene-2-one. This has proven that putative GST possessed peroxidase activity and proposed to be similar to PputUW4_00801 (putative glutathione S-transferase) of Pseudomonas sp. UW4 according to its estimated molecular weight and the pI values obtained experimentally.
Distillability and partial transposition in bipartite systems

Institut fu¨r Theoretische Physik, Universit¨at Hannover, D-30167 Hannover, Germany(February 1, 2008)We study the distillability of a certain class of bipartitedensity operators which can be obtained via depolarizationstarting from an arbitrary one. Our results suggest that non-positivity of the partial transpose of a density operator is nota suﬃcient condition for distillability, when the dimension ofboth subsystems is higher than two.03. 67. -a, 03.65. Bz, 03.65. Ca, 03.65. HkI. INTRODUCTION
Atomic transport in dense multicomponent metallic liquids

Pd 4 3 Ni 1 0 Cu 2 7 P 2 0 has been investigated in its equilibrium liquid state with incoherent, inelastic neutron scattering. As compared to simple liquids, liquid Pd 4 3 Ni 1 0 Cu 2 7 P 2 0 is characterized by a dense packing with a packing fraction above 0.5. The intermediate scattering function exhibits a fast relaxation process that precedes structural relaxation. Structural relaxation obeys a time-temperature superposition that extends over a temperature range of 540 K. The mode-coupling theory of the liquid to glass transition [mode-coupling theory (MCT)] gives a consistent description of the dynamics that governs the mass transport in liquid Pd-Ni-Cu-P alloys. MCT scaling laws extrapolate to a critical temperature T c at about 20% below the liquidus temperature. Diffusivities derived from the mean relaxation times compare well with Co diffusivities from recent tracer diffusion measurements and diffusivities calculated from viscosity via the Stokes-Einstein relation. In contrast to simple metallic liquids, the atomic transport in dense, liquid Pd 4 3 Ni 1 0 Cu 2 7 P 2 0 is characterized by a drastic slowing down of dynamics on cooling and a q - 2 dependence of the mean relaxation times at intermediate q as a result of a highly collective transport mechanism. At temperatures as high as 2T c diffusion in liquid Pd 4 3 Ni 1 0 Cu 2 7 P 2 0 is as fast as that in simple liquids at the melting point. However, the difference in the underlying atomic transport mechanism indicates that the diffusion mechanism in liquids is not controlled by the value of the diffusivity but rather by that of the packing fraction.
Probing topological superconductors with emergent gravity

We study the interplay of three phenomena that occur in 2+1 dimensional $p$-wave superconductors. The first is emergent gravity, where interacting fermions behave effectively as fermions interacting with a form of gravity, which is described by the superconducting order parameter. The second is topological superconductivity, the existence of nontrivial topological phases, characterized by a Chern number, of the effectively free fermions in the emergent gravitational background. The third is the spontaneous breaking of $U(1)$ symmetry, which is the statement that the number of effectively free fermions is not conserved. We show that an energy-momentum response of the fermions to the emergent gravitational background reveals their topological phase. This response is encoded in a gravitational Chern-Simons (gCS) term and is intimately related to the existence of chiral Majorana fermions on domain walls between different topological phases, via energy-momentum conservation, or gravitational anomaly inflow. Thus emergent gravity is a natural probe for topological phases of superconductors, and provides a physical interpretation for the boundary gravitational anomaly and bulk gCS term in this context. The spontaneous breaking of $U(1)$ symmetry introduces additional bulk responses, encoded in a gravitational pseudo Chern-Simons term. Although not topological in nature, these responses carry surprising similarities to the topological responses encoded in the gCS term.
Compact Programmable True Random Number Generator Based on Spin Torque Nano-Oscillator

True Random Number Generator (TRNG) is the key component for stochastic computation. It can also act as the Probabilistic Bit (P-Bit) which is the core device for Ising Computer. In previous study, we have proposed a novel programmable TRNG based on Spin Torque Nano-Oscillator (STNO). With this TRNG constructed with STNO, a time division multiplexing Ising computer is designed to work under the Incremental Coupling Rule. However, the programmable TRNG is still lack of a corporeal hardware implementation. In this work, a SPICE model for STNO which can accurately describe the frequency, resistance as well as noise spectrum is provided first. And then, a compact optimized Schmitt trigger circuit with 14 nm FinFET technology is proposed to construct the programmable TRNG. Finally, the performance of the compact programmable TRNG circuit is evaluated and discussed.
Low redshift observational constraints on tachyon models of dark energy

The background evolution of an accelerated, dark energy dominated universe is aptly described by non-canonical tachyon scalar field models. The accelerated expansion of the universe is determined by the choice of a suitable scalar field potential; in the case of a tachyon field, a `runaway' potential. In the absence of a fundamental theory, dark energy properties are studied in a phenomenological approach. This includes determining the model parameters using observations and to probe the allowed deviation from the cosmological constant model. In this paper, we present constraints on tachyon scalar field parameters from low redshift data for two different scalar field potentials. These scalar field potentials have been crucial in tachyon dark energy studies. The datasets considered in this paper include the supernova type Ia data, independent measurements of the Hubble parameter and the Baryon Acoustic Oscillation data. In this paper, we present constraints on tachyon field parameters using these observations and their combination. A combination of the datasets indicates that those model parameters are preferred which emulate the cosmological constant model. The initial value of the scalar field, in the unit of the Hubble constant, is bounded from below and does not require fine-tuning at larger values.
Valuing the Changes in Herbicide Risks Resulting from Adoption of Roundup Ready Soybeans by U.S. Farmers: An Empirical Analysis of Revealed Value Estimates

A revealed-preference approach is proposed for the evaluation of the impact of changed patterns of herbicide use on RR soybeans. The results indicate that farmers consider herbicide safety in their herbicide choices and associate positive values with safety improvements. The aggregate welfare impact of reduced risk for the U.S. soybean farmers was estimated to be $90.3 million in 2001.
Comparing the 'D.V' Lottery with the Point System: Costs, Benefits and a Superior Alternative

The diversity visa lottery popularly known as the D.V lottery is a U.S relatively new immigration policy that was shrouded with a lot of controversy at its inception in 1995. The main stated objective of this policy is to increase diversity in the U.S. However, from the policy inception, immigration specialists seriously doubted the claimed objective. They strongly believe that the congressional sponsors of the visa lottery adopted the diversity mantra as a cover for a program that was actually designed to satisfy other objectives. Whether or not this claim is true is yet unanswered objectively and would be probably had to verify. In this paper, we review in details the D.V immigration policy program considering qualitatively its potential costs and benefits to the US. We then highlight in details the pros and cons of the most commonly suggested alternative to this program, the point systems. Then using simple cost/ benefit techniques, we attempt to estimate the fiscal benefit or burden of each program under certain conditions and assumptions. Finally, we propose an alternative policy that would achieve the diversity objective and dominates both policy programs for the U.S in terms of net fiscal benefit.
Black Hole Formation and Explosion from Rapidly Rotating Very Massive Stars

We explore the formation process of a black hole (BH) through the pair-instability collapse of a rotating Population III very massive star in axisymmetric numerical relativity. As the initial condition, we employ a progenitor star that is obtained by evolving a rapidly rotating zero-age main-sequence star with mass 320 M⊙ until it reaches a pair-instability region. We find that for such a rapidly rotating model, a fraction of the mass, ∼10 M⊙, forms a torus surrounding the remnant BH of mass ∼130 M⊙, and an outflow is driven by a hydrodynamical effect. We also perform simulations, artificially reducing the initial angular velocity of the progenitor star, and find that only a small or no torus is formed and no outflow is driven. We discuss the possible evolution scenario of the remnant torus for the rapidly rotating model by considering the viscous and recombination effects and show that if an energy of ∼1052 erg is injected from the torus to the envelope, the luminosity and timescale of the explosion could be of the orders of 1043 erg s−1 and years, respectively. We also point out the possibility for observing gravitational waves associated with the BH formation for the rapidly rotating model by ground-based gravitational-wave detectors.
A Self-Supervised Method for Infrared and Visible Image Fusion

Infrared and visible image fusion (IVIF) plays important roles in many applications. Since there is no ground-truth, the fusion performance measurement is a difficult but important problem for the task. Previous unsupervised deep learning based fusion methods depend on a hand-crafted loss function to define the distance between the fused image and two types of source images, which still cannot well preserve the vital information in the fused images. To address these issues, we propose an image fusion performance measurement between the fused image and the decomposition of the fused image. A novel self-supervised network for infrared and visible image fusion is designed to preserve the vital information of source images by narrowing the distance between the source images and the decomposed ones. Extensive experimental results demonstrate that our proposed measurement has the ability in improving the performance of backbone network in both subjective and objective evaluations.
Comparison of the optoelectronic BTS Smart system and IMU-based MyoMotion system for the assessment of gait variables.

PURPOSE Although inertial measurement unit (IMU)-based systems have been validated against optoelectronic systems for recording joint kinematics, the accuracy of each system must be evaluated, and measurements from different systems cannot be easily compared. Therefore, this study compared the joint angles recorded using the IMU-based MyoMotion system and the optoelectronic BTS Smart-DX 700 system during Nordic walking. METHODS The study subject, a long-time Nordic walking instructor, was assigned to walk 12 m/trial (14 trials with 5 sampled gait cycles) at a velocity preferred for Nordic walking. The trials were simultaneously recorded by both systems. The instantaneous lower (ankle, knee, hip) and upper (shoulder, elbow, wrist) limb joint angles were recorded. RESULTS The joint angles from MyoMotion were significantly larger or smaller (depending on the joint and plane) than those from BTS. CONCLUSIONS Joint angles measured by MyoMotion are not interchangeable with values from BTS, and IMU-recorded values should be interpreted carefully. However, MyoMotion can still provide information about intra-individual changes based on the joint angle profiles, e.g., following Nordic walking training.
High-energy neutrino flare from cloud-jet interaction in the blazar PKS 0502+049

Following the detection of a $\sim$300 TeV neutrino potentially associated with the flaring blazar TXS 0506+056, an excess of neutrinos around its position in 2014-2015 was revealed by IceCube. However, its contemporaneous quiescence in $\gamma$-rays is challenging to interpret consistently. Meanwhile, the blazar PKS 0502+049, positioned within the neutrino localization uncertainties, was seen to be flaring in $\gamma$-rays. We show that dense, line-emitting gas clouds that interact with its jet and induce cosmic ray acceleration and hadronuclear interaction can plausibly explain the 2014-2015 neutrino flare.
Determinants Driving the Student’s Decision Making to Opt Institution for Higher Education in India: An Exploratory Factor Analysis

This study intends to build up a thorough understanding of the determinants that largely influence student’s decision-making to opt institution for higher education empirically from the Indian perspective. It also attempts to develop the rank of importance of the determinants influencing their institution selection decision. Prior research has various constructs that influence the design of the student’s career path, but this is the first time, “uncertainty” a new construct has been introduced which made this study relevant. The factor analysis was conducted to analyze the data of 558 students of Delhi NCR, India, and identified seven determinants namely Holistic institutional environment, Conformity influence, Human intelligence, Institutional prominence, Geographic characteristics, Student residential life, and Financial viability that impact student’s decision-making to opt institution for higher education. The findings of the study can guide educational institutions by empowering them to set objectives to draw the interest of students to pursue higher studies.
Evolution of Short-Range Optical Wireless Communications

The optical wireless communication (OWC) technology explores the broad unregulated optical spectrum to provide high-speed wireless communications, and the visible, ultraviolet and near-infrared wavelength ranges all have been investigated. Compared with the conventional radio frequency (RF) band, the spectrum in OWC systems is much less congested and the interference is much lower. The OWC technology also provides enhanced physical layer security due to the natural confinement of optical beams that makes it difficult to intercept the transmitted signal. Hence, the OWC technology has been widely studied and considered as a promising candidate in future beyond-5G communications. The OWC technology has been considered for both long-range and short-range applications, and in this paper we will introduce the fundamentals and recent developments of short-range OWC systems. In particular, we will focus on the key short-range OWC applications in indoor personal or local area communications, underwater wireless communications, wireless data center networks, and vehicular communications. We will also introduce some recent widely studied advanced techniques to boost the performance of short-range OWC systems, including the spatial domain diversity, multiplexing and modulation principles to improve the system robustness and data rate, and the machine learning algorithms and hardware accelerators to suppress both linear and nonlinear effects to improve OWC signal quality and bit-error-rate performance.
Fast high-fidelity entangling gates for spin qubits in Si double quantum dots

Implementing high-fidelity two-qubit gates in single-electron spin qubits in silicon double quantum dots is still a major challenge. In this work, we employ analytical methods to design control pulses that generate high-fidelity entangling gates for quantum computers based on this platform. Using realistic parameters, we present simple control pulses that generate CNOT, CPHASE, and CZ gates with average fidelities greater than 99.99% and gate times as short as 45 ns. Moreover, using the local invariants of the system's evolution operator, we show that a simple square pulse generates a CNOT gate in less than 27 ns and with a fidelity greater than 99.99%. Last, we use the same analytical methods to generate two-qubit gates locally equivalent to $\sqrt{CNOT}$ and $\sqrt{CZ}$ that are used to implement simple two-piece pulse sequences that produce high-fidelity CNOT and CZ gates in the presence of low-frequency noise.
PSR J1906+0746: From relativistic spin-precession to beam modeling

Abstract Shortly after the discovery of PSR J1906+0746, some hints of profile variations were already interpreted as first signs of relativistic spin-precession occuring. Using observations from the Nançay, Arecibo and Green Bank Radio Observatories, we report here the measurement of pulse profile and polarimetric variations. Using the Rotating Vector Model, we show that PSR J1906+0746 is likely to be an orthogonal rotator (α ≃ 80°). Fitting our polarimetric data to a precession model, we determined the geometry of the pulsar and found a wide misalignment angle (δ = 89−44+85 deg, 95% C.L.), although the uncertainty is large. Assuming this geometry, we constructed the beam maps of both magnetic poles.
A multivariate analysis of annual earnings forecasts generated from quarterly forecasts of financial

The Financial Accounting Standards Board [1977] recently emphasized the importance of forecasted accounting earnings in the formulation of investment decisions. Empirical investigations into various aspects of the investment decision process, such as cost of capital, firm valuation, and the relationship between earnings and stock prices, have utilized forecasted accounting earnings extensively as a measure of earnings expectations. Thus, both policy boards and empirical research support the importance of forecasted accounting earnings. Current sources of these forecasts which are widely available are univariate time-series models and financial analysts. In the future, another may be management forecasts, if the SEC and FASB should desire to make those more widely available. Analysts' and managements' forecasts may be characterized as representing comprehensive models, in that input to these models can incorporate numerous variables both endogenous and exogenous to the firm. In contrast, the univariate timeseries models incorporate a single variable, past earnings. Both comprehensive and univariate models have advantages and disadvantages. Currently, a major question is the value of a comprehensive model relative to a univariate model. Another question is whether a univariate model should be identified individually for each firm or if a generally identified or premier model would provide forecasts that are
Robust coupled tensor decomposition and feature extraction for multimodal medical data

Abstract High-dimensional and multimodal data to describe various aspects of a patient’s clinical condition have become increasingly abundant in the medical field across a variety of domains. For example, in neuroimaging applications, electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) can be collected simultaneously (i.e., EEG-fMRI) to provide high spatial and temporal resolution of a patient’s brain function. Additionally, in telemonitoring applications, a smartphone can be used to record various aspects of a patient’s condition using its built-in microphone, accelerometer, touch screen, etc. Coupled CANDECOMP/PARAFAC decomposition (CCPD) is a powerful approach to simultaneously extract common structures and features from multiple tensors and can be applied to these high-dimensional, multi-modal data. However, the existing CCPD models are inadequate to handle outliers, which are highly present in both applications. For EEG-fMRI, outliers are common due to fluctuations in the electromagnetic field resulting from interference between the EEG electrodes and the fMRI machine. For telemonitoring, outliers can result from patients not properly following instructions while performing smartphone-guided exercises at home. This motivates us to propose a robust CCPD (RCCPD) method for robust feature extraction. The proposed method utilizes the Alternating Direction Method of Multipliers (ADMM) to minimize an objective function that simultaneously decomposes a pair of coupled tensors and isolates outliers. We compare the proposed RCCPD method with the classical CP decomposition, the coupled matrix-tensor/tensor-tensor factorization (CMTF/CTTF), and the tensor robust CP decomposition (TRCPD). Experiments on both synthetic and real-world data demonstrate that the proposed RCCPD effectively handles outliers and outperforms the benchmarks in terms of accuracy.