Miracle-dz/UniFAR-FTUs huggingface dataset:
HIGH D2O/HDO RATIO IN THE INNER REGIONS OF THE LOW-MASS PROTOSTAR NGC 1333 IRAS2A

Water plays a crucial role both in the interstellar medium and on Earth. To constrain its formation mechanisms and its evolution through the star formation process, the determination of the water deuterium fractionation ratios is particularly suitable. Previous studies derived HDO/H2O ratios in the warm inner regions of low-mass protostars. We here report a detection of the D2O 11, 0–10, 1 transition toward the low-mass protostar NGC 1333 IRAS2A with the Plateau de Bure interferometer: this represents the first interferometric detection of D2O—and only the second solar-type protostar for which this isotopologue is detected. Using the observations of the HDO 54, 2–63, 3 transition simultaneously detected and three other HDO lines previously observed, we show that the HDO line fluxes are well reproduced with a single excitation temperature of 218 ± 21 K and a source size of ∼0. ″5. The D2O/HDO ratio is ∼(1.2 ± 0.5) × 10−2, while the use of previous HO observations give an HDO/H2O ratio of ∼(1.7 ± 0.8) × 10−3, i.e., a factor of seven lower than the D2O/HDO ratio. These results contradict the predictions of current grain surface chemical models and indicate that either the surface deuteration processes are poorly understood or that both sublimation of grain mantles and water formation at high temperatures (≳230 K) take place in the inner regions of this source. In the second scenario, the thermal desorption of the grain mantles would explain the high D2O/HDO ratio, while water formation at high temperature would explain significant extra production of H2O leading to a decrease of the HDO/H2O ratio.
z-Weyl gravity in higher dimensions

We consider higher dimensional gravity in which the four dimensional spacetime and extra dimensions are not treated on an equal footing. The anisotropy is implemented in the ADM decomposition of higher dimensional metric by requiring the foliation preserving diffeomorphism invariance adapted to the extra dimensions, thus keeping the general covariance only for the four dimensional spacetime. The conformally invariant gravity can be constructed with an extra (Weyl) scalar field and a real parameter z which describes the degree of anisotropy of conformal transformation between the spacetime and extra dimensional metrics. In the zero mode effective 4D action, it reduces to four-dimensional scalar-tensor theory coupled with nonlinear sigma model described by extra dimensional metrics. There are no restrictions on the value of z at the classical level and possible applications to the cosmological constant problem with a specific choice of z are discussed.
Surface and bulk electronic structure of the strongly correlated system SmB 6 and implications for a topological Kondo insulator

Recent theoretical calculations and experimental results suggest that the strongly correlated material SmB6 may be a realization of a topological Kondo insulator. We have performed an angle-resolved photoemission spectroscopy study on SmB6 in order to elucidate elements of the electronic structure relevant to the possible occurrence of a topological Kondo insulator state. The obtained electronic structure in the whole three-dimensional momentum space reveals one electron-like 5d bulk band centered at the X point of the bulk Brillouin zone that is hybridized with strongly correlated f electrons, as well as the opening of a Kondo band gap (Delta(B) similar to 20 meV) at low temperature. In addition, we observe electron-like bands forming three Fermi surfaces at the center Gamma point and boundary (X) over bar point of the surface Brillouin zone. These bands are not expected from calculations of the bulk electronic structure, and their observed dispersion characteristics are consistent with surface states. Our results suggest that the unusual low-temperature transport behavior of SmB6 is likely to be related to the pronounced surface states sitting inside the band hybridization gap and/or the presence of a topological Kondo insulating state.
Selective Input Sparsity in Spiking Neural Networks for Pattern Classification

The concept of input sparsity in Spiking Neural Networks for pattern recognition is introduced and explored with the goals of reductions in network inference time and size, leading to lower resource requirements in hardware implementations. A method is proposed by which selective input sparsity can be inferred from the training set to reduce the size of the network before training and decrease the network inference time. This method also requires no additional pre-processing steps during the testing phase, making it an excellent candidate for edge applications. For a basic fully connected spiking neural network trained to solve the MNIST handwritten digits, selective input sparsity is applied and the network size is reduced by 58.16% and a 41.07% decrease in the network's inference time is observed without notable accuracy hinderance. In the case of the Fashion MNIST dataset, selective input sparsity reduced the network size by 55.99% and reduced the network's inference time by 59.05%.
A High-Speed Codec Architecture for Lagrange Coded Computing

The Lagrange Coded Computing (LCC), proposed recently by Yu et at. , is regarded as a promising solution for most distributed learning algorithms thanks to its good tradeoff between resiliency, security, and privacy over cloud servers. As a kind of coded computing, LCC also costs extra computations in a local computer for encoding and decoding, which contains many complex operations, such as the continued product operations and divisions. In this paper, we present an efficient high-speed LCC codec architecture based on the linear regression algorithm for the first time. By analyzing the formulas and evaluating the hardware resource, we select a set of optimal parameters and remove most of the complex operations by storing the precomputed coefficients. Besides, the proposed architecture is inherently scalable and can be fully utilized and reused for encoding and decoding. The experimental results on an FPGA show that a significant speedup is achieved compared with the prior art.
Analyzing Factors Influencing Intention to Use and Actual Use of Mobile Fintech Applications Free Interbank Money Transfer Flip Using UTAUT 2 Model with Trust and Perceived Security

Financial Technology is a financial innovation that is growing rapidly in recent years in line with technological developments that continue to advance and provide innovation for the banking sector, one of which is the type of Fintech Payment, such as free interbank money transfer applications, which in practice there are still many problems that make users reluctant to use the innovation. Then, the purpose of this study is to determine the factors that influence user intentions and the use of the Flip free interbank money transfer mobile application by adopting the Unified Theory of Acceptance and Use of Technology 2 (UTAUT 2) model and adding two variables, namely Trust and Perceived security. Research data were obtained from 402 users of the Flip free interbank money transfer mobile application in Indonesia through a questionnaire and analyzed using a Structural Equation Model (SEM) approach. Result of this study found that the most influential factors on the intention to use in order from the largest are Price Value, Trust, Performance Expectancy, Social Influence, and Effort Expectancy. While the most influential on its use in order from the largest are Habit, Trust, and Behavioral Intention. The Perceived Security variable was also confirmed to have an influence on Trust on the intention to use and also the use of the Flip free interbank money transfer mobile application. The findings of this study can provide theoretical contributions as well as practical implications for the development of Fintech applications.
Optimizing a Multispectral-Images-Based DL Model, Through Feature Selection, Pruning and Quantization

The inclusion of technology in agriculture is highly relevant given the increasing global demand for food and our growing population. This paper focuses on an application for the analysis of multispectral images of wheat fields, and how they could be used to predict yield in a way that is resource-efficient and time convenient. Thus, our main goal is to optimize a deep learning model already proposed in the literature, through feature selection, pruning, and quantization, to be efficient enough that it could be deployed on a computer with limited resources. The main results of this work show that the size of the model was reduced by almost 94%, its inference time was almost 73% faster compared to the original model, while reducing its performance by 19% (still better than what was found in literature). This could be an important step towards the deployment of edge intelligence for plant phenotyping.
Algorithm-Hardware Co-Optimization for Cost-Efficient ML-based ISP Accelerator

In this paper, we present an advanced algorithm-hardware co-optimization method for designing an efficient accelerator architecture for image signal processing (ISP) with deep neural networks (DNNs). Based on the systolic-array structure, for performing the target network model, we newly introduce two evaluation metrics, each of which is dedicated to fairly representing either the processing speed or the energy consumption. Then, the overall evaluation metric is defined to test each systolic array, finding the initial array configuration for the given number of total multipliers. From the initial array, several array-scaling methods are then presented to find the most cost-efficient array structure. In addition, the original ML model is adjusted to further enhance the overall efficiency with subtle quality drops of image outputs. Implementation results in 28nm CMOS technology show that the proposed co-optimization method successfully finds the cost-efficient systolic accelerator architecture for ISP applications, improving the energy efficiency by 51% compared to the straightforward array design.
Optimal Task Offloading and Resource Allocation for C-NOMA Heterogeneous Air-Ground Integrated Power Internet of Things Networks

By combining information communication technology with power grid, the smart grid-oriented Power Internet of Things (PIoT) has become a critical technology to guarantee the safe and reliable power grid operation and improve system energy efficiency. Nevertheless, PIoT devices have only limited communication and computing resources since they are mostly deployed in remote areas that may be out of service coverage of existing terrestrial 5G networks. To overcome the resource limitation, we leverage Air-Ground Integrated C-NOMA Heterogeneous PIoT Networks (PAGIC HetNets), and study the core challenges in PAGIC HetNets. As PIoT devices are normally powered by battery, we aim at minimizing the energy consumption of PIoT devices and thoroughly investigate the problem of task offloading and resource allocation with minimal energy consumption. This problem belongs to a mixed integer nonlinear programming (MINLP) with extra difficulty that the long-term queuing delay and short-term constraints are coupled. To tackle the difficulty, we use Lyapunov optimization to transform this hard problem into three subproblems. The first subproblem is task splitting and local computing resource assignment at the PAGIC user side, which we solve with the Lagrangian multiplier method. The second subproblem is queue-aware channel reusing, and matching theory is adopted to solve it. The third subproblem is optimizing the aerial server resource allocation, for which we propose a greedy-based solution. Numerical simulations demonstrate that our approach can obtain excellent performance in terms of energy consumption, spectrum efficiency, task backlog, and queuing delay with lower complexity compared with several benchmark methods.
BAYESIAN ANALYSIS OF TWO STELLAR POPULATIONS IN GALACTIC GLOBULAR CLUSTERS. II. NGC 5024, NGC 5272, AND NGC 6352

We use Cycle 21 Hubble Space Telescope (HST) observations and HST archival Advanced Camera for Surveys Treasury observations of Galactic Globular Clusters to find and characterize two stellar populations in NGC 5024 (M53), NGC 5272 (M3), and NGC 6352. For these three clusters, both single and double-population analyses are used to determine a best fit isochrone(s). We employ a sophisticated Bayesian analysis technique to simultaneously fit the cluster parameters (age, distance, absorption, and metallicity) that characterize each cluster. For the two-population analysis, unique population level helium values are also fit to each distinct population of the cluster and the relative proportions of the populations are determined. We find differences in helium ranging from ∼0.05 to 0.11 for these three clusters. Model grids with solar α-element abundances ([α/Fe] = 0.0) and enhanced α-elements ([α/Fe] = 0.4) are adopted.
A NEW DENSITY VARIANCE–MACH NUMBER RELATION FOR SUBSONIC AND SUPERSONIC ISOTHERMAL TURBULENCE

The probability density function of the gas density in subsonic and supersonic, isothermal, driven turbulence is analyzed using a systematic set of hydrodynamical grid simulations with resolutions of up to 10243 cells. We perform a series of numerical experiments with root-mean-square (rms) Mach number ranging from the nearly incompressible, subsonic () to the highly compressible, supersonic () regime. We study the influence of two extreme cases for the driving mechanism by applying a purely solenoidal (divergence-free) and a purely compressive (curl-free) forcing field to drive the turbulence. We find that our measurements fit the linear relation between the rms Mach number and the standard deviation (std. dev.) of the density distribution in a wide range of Mach numbers, where the proportionality constant depends on the type of forcing. In addition, we propose a new linear relation between the std. dev. of the density distribution σρ and that of the velocity in compressible modes, i.e., the compressible component of the rms Mach number, . In this relation the influence of the forcing is significantly reduced, suggesting a linear relation between σρ and , independent of the forcing, and ranging from the subsonic to the supersonic regime.
Empirical Fit to Inelastic Electron-Deuteron and Electron-Neutron Resonance Region Transverse Cross Sections

An empirical fit is described to measurements of inclusive inelastic electron-deuteron cross sections in the kinematic range of four-momentum transfer $$0 \le Q^2<10$$ GeV$^2$ and final state invariant mass $1.2<3$ GeV. The deuteron fit relies on a fit of the ratio $R_p$ of longitudinal to transverse cross sections for the proton, and the assumption $R_p=R_n$. The underlying fit parameters describe the average cross section for proton and neutron, with a plane-wave impulse approximation (PWIA) used to fit to the deuteron data. Pseudo-data from MAID 2007 were used to constrain the average nucleon cross sections for $W<1.2$ GeV. The mean deviation of data from the fit is 3\%, with less than 5\% of the data points deviating from the fit by more than 10\%.
Detection for Spectrum Sensing in CRN under Impact of Distributional Uncertainty of Noise and Interference

Since the advent of Cognitive Radio and exploitation of unused spectrum by secondary devices, spectrum has gained immense importance. In cognitive radio network setting, due to very low received signal to noise ratio (SNR), spectrum sensing has been a challenging task. Further, signal detection is obscured due to presence of accumulated interference for which the statistical distribution is unknown and has significant distributional uncertainty. Covariance based signal detection methods have been proposed by various authors and proved to be better than other methods due to its independence on SNR, accuracy, and medium algorithmic complexity. Some results from Random Matrix Theory (RMT) on modelling of covariance matrices can be used in signal detection. This paper presents an algorithm for detection of Chi-Square distributed independent random signals using Wishart matrix which model the covariance matrix. A centering matrix is employed to scale the sample covariance matrix with Wishart distribution. The signals under various fading environment are used to evaluate the performance of the proposed algorithm. Also, a DVBT-2K signal is used to evaluate the performance for more realistic conditions. Furthermore, quantification of distributional uncertainty of accumulated interference in DTV based CRN is calculated using differential entropy of pdf of the interference. The quantified uncertainty is used to calculate the new threshold for detection. As per our knowledge, it is observed in the proposed work that the Maximum-Minimum Eigenvalue (MME) based proposed algorithm performs better than other proposed schemes in terms of probability of detection and complexity.
EARLY AND EXTENDED HELIUM REIONIZATION OVER MORE THAN 600 MILLION YEARS OF COSMIC TIME

We measure the effective optical depth of He ii Lyα absorption at in 17 UV-transmitting quasars observed with UV spectrographs on the Hubble Space Telescope. The median values increase gradually from 1.95 at to at , but with a strong sightline-to-sightline variance. Many comoving Mpc regions of the intergalactic medium (IGM) remain transmissive ( ), and the gradual trend with redshift appears consistent with density evolution of a fully reionized IGM. These modest optical depths imply average He ii fractions of and He ii ionizing photon mean free paths of comoving Mpc at , thus requiring that a substantial volume of the helium in the universe was already doubly ionized at early times; this stands in conflict with current models of He ii reionization driven by luminous quasars. Along 10 sightlines we measure the coeval H i Lyα effective optical depths, allowing us to study the density dependence of at . We establish that the dependence of on increasing is significantly shallower than expected from simple models of an IGM reionized in He ii. This requires higher He ii photoionization rates in overdense regions or underdense regions being not in photoionization equilibrium. Moreover, there are very large fluctuations in at all which greatly exceed the expectations from these simple models. These data present a distinct challenge to scenarios of He ii reionization—an IGM where He ii appears to be predominantly ionized at , and with a radiation field strength that may be correlated with the density field, but exhibits large fluctuations at all densities.
Constraining neutrino properties with a Euclid-like galaxy cluster survey

We perform a forecast analysis on how well a Euclid-like photometric galaxy cluster survey will constrain the total neutrino mass and effective number of neutrino species. We base our analysis on the Monte Carlo Markov Chains technique by combining information from cluster number counts and cluster power spectrum. We find that combining cluster data with Cosmic Microwave Background (CMB) measurements from Planck improves by more than an order of magnitude the constraint on neutrino masses compared to each probe used independently. For the Lambda CDM+m(v) model the 2 sigma upper limit on total neutrino mass shifts from Sigma m(v) < 0.35eV using cluster data alone to Sigma m(v) < 0.031eV when combined with Planck data. When a non- standard scenario with N-eff (sic) 3.046 number of neutrino species is considered, we estimate an upper limit of N-eff < 3.14 (95%CL), while the bounds on neutrino mass are relaxed to Sigma m(v) < 0.040eV. This accuracy would be sufficient for a 2 sigma detection of neutrino mass even in the minimal normal hierarchy scenario (Sigma m(v) similar or equal to 0.05 eV). In addition to the extended Lambda CDM+ m(v) + N-eff model we also consider scenarios with a constant dark energy equation of state and a non-vanishing curvature. When these models are considered the error on Sigma m(v) is only slightly affected, while there is a larger impact of the order of similar to 15% and similar to 20% respectively on the 2 sigma error bar of N-eff with respect to the standard case. To assess the effect of an uncertain knowledge of the relation between cluster mass and optical richness, we also treat the Lambda CDM+ m(v) + N-eff case with free nuisance parameters, which parameterize the uncertainties on the cluster mass determination. Adopting the over-conservative assumption of no prior knowledge on the nuisance parameter the loss of information from cluster number counts leads to a large degradation of neutrino constraints. In particular, the upper bounds for Sigma m(v) are relaxed by a factor larger than two, Sigma m(v) < 0.083 eV (95%CL), hence compromising the possibility of detecting the total neutrino mass with good significance. We thus confirm the potential that a large optical/near-IR cluster survey, like that to be carried out by Euclid, could have in constraining neutrino properties, and we stress the importance of a robust measurement of masses, e.g. from weak lensing within the Euclid survey, in order to full exploit the cosmological information carried by such survey.
A multi-scale exploration of a massive young stellar object

Context. The rarity of young massive stars combined with the fact that they are often deeply embedded has limited the understanding of the formation of stars larger than 8 M⊙. Ground based mid-infrared (IR) interferometry is one way of securing the spatial resolution required to probe the circumstellar environments of massive young stellar objects (MYSOs). Given that the spatial-frequency coverage of such observations is often incomplete, direct-imaging can be supplementary to such a dataset. By consolidating these observations with modelling, the features of a massive protostellar environment can be constrained. Aims. This paper aims to detail the physical characteristics of the protostellar environment of the MYSO G305.20+0.21 at three size-scales by fitting one 2.5D radiative transfer model to three different types of observations simultaneously, providing an extensive view of the accreting regions of the MYSO. Methods. Interferometry, imaging and a multi-wavelength spectral energy distribution (SED) are combined to study G305.20+0.21. The high-resolution observations were obtained using the Very Large Telescope’s MIDI and VISIR instruments, producing visibilities in the N-band and near-diffraction-limited imaging in the Q-band respectively. By fitting simulated observables, derived from the radiative transfer model, to our observations the properties of the MYSO are constrained. Results. The VISIR image shows elongation at 100 mas scales and also displays a degree of asymmetry. From the simulated observables derived from the radiative transfer model output we find that a central protostar with a luminosity of ~5 × 104 L⊙ surrounded by a low-density bipolar cavity, a flared 1 M⊙ disk and an envelope is sufficient to fit all three types of observational data for G305.20+0.21. The weak silicate absorption feature within the SED requires low-density envelope cavities to be successfully fit and is an atypical characteristic in comparison to previously studied MYSOs. Conclusions. The fact that the presence of a dusty disk provides the best fit to the MIDI visibilities implies that this MYSO is following a scaled-up version of the low-mass star formation process. The low density, low extinction environment implies the object is a more evolved MYSO and this combined with large inner radius of the disk suggests that it could be an example of a transitional disk around an MYSO.