Miracle-dz/UniFAR-FTUs huggingface dataset:
Stellar populations in star clusters

Stellar populations contain the most important information about star cluster formation and evolution. Until several decades ago, star clusters were believed to be ideal laboratories for studies of simple stellar populations (SSPs). However, discoveries of multiple stellar populations in Galactic globular clusters have expanded our view on stellar populations in star clusters. They have simultaneously generated a number of controversies, particularly as to whether young star clusters may have the same origin as old globular clusters. In addition, extensive studies have revealed that the SSP scenario does not seem to hold for some intermediate-age and young star clusters either, thus making the origin of multiple stellar populations in star clusters even more complicated. Stellar population anomalies in numerous star clusters are well-documented, implying that the notion of star clusters as true SSPs faces serious challenges. In this review, we focus on stellar populations in massive clusters with different ages. We present the history and progress of research in this active field, as well as some of the most recent improvements, including observational results and scenarios that have been proposed to explain the observations. Although our current ability to determine the origin of multiple stellar populations in star clusters is unsatisfactory, we propose a number of promising projects that may contribute to a significantly improved understanding of this subject.
Transport Properties and Diamagnetism of Dirac Electrons in Bismuth

Bismuth crystal is known for its remarkable properties resulting from particular electronic states, e. g. , the Shubnikov-de Haas effect and the de Haas-van Alphen effect. Above all, the large diamagnetism of bismuth had been a long-standing puzzle soon after the establishment of quantum mechanics, which had been resolved eventually in 1970 based on the effective Hamiltonian derived by Wolff as due to the interband effects of a magnetic field in the presence of a large spin-orbit interaction. This Hamiltonian is essentially the same as the Dirac Hamiltonian, but with spatial anisotropy and an effective velocity much smaller than the light velocity. This paper reviews recent progress in the theoretical understanding of transport and optical properties, such as the weak-field Hall effect together with the spin Hall effect, and ac conductivity, of a system described by the Wolff Hamiltonian and its isotropic version with a special interest of exploring possible relationship with orbital magnetism. It is shown that there exist a fundamental relationship between spin Hall conductivity and orbital susceptibility in the insulating state on one hand, and the possibility of fully spin-polarized electric current in magneto-optics. Experimental tests of these interesting features have been proposed.
ULTRADEEP KS IMAGING IN THE GOODS-N

We present an ultradeep KS-band image that covers 0.5 × 0.5 deg2 centered on the Great Observatories Origins Deep Survey-North (GOODS-N). The image reaches a 5σ depth of in the GOODS-N region, which is as deep as the GOODS-N Spitzer Infrared Array Camera (IRAC) 3.6 μm image. We present a new method of constructing IRAC catalogs that uses the higher spatial resolution KS image and catalog as priors and iteratively subtracts fluxes from the IRAC images to estimate the IRAC fluxes. Our iterative method is different from the χ2 approach adopted by other groups. We verified our results using data taken in two different epochs of observations, as well as by comparing our colors with the colors of stars and with the colors derived from model spectral energy distributions of galaxies at various redshifts. We make available to the community our WIRCam KS-band image and catalog (94,951 objects in 0.25 deg2), the Interactive Data Language pipeline used for reducing the WIRCam images, and our IRAC 3.6–8.0 μm catalog (16,950 objects in 0.06 deg2 at 3.6 μm). With this improved KS and IRAC catalog and a large spectroscopic sample from our previous work, we study the color–magnitude and color–color diagrams of galaxies. We compare the effectiveness of using KS and IRAC colors to select active galactic nuclei and galaxies at various redshifts. We also study a color selection of z = 0.65–1.2 galaxies using the KS, 3.6 μm, and 4.5 μm bands.
Thermal stability of a weakly magnetized rotating plasma

The thermal stability of a weakly magnetized, rotating, stratified, optically thin plasma is studied by means of linear-perturbation analysis. We derive dispersion relations and criteria for stability against axisymmetric perturbations that generalize previous results on either non-rotating or unmagnetized fluids. The implications for the hot atmospheres of galaxies and galaxy clusters are discussed.
Community detection in the sparse hypergraph stochastic block model

We consider the community detection problem in sparse random hypergraphs. Angelini et al. in [6] conjectured the existence of a sharp threshold on model parameters for community detection in sparse hypergraphs generated by a hypergraph stochastic block model. We solve the positive part of the conjecture for the case of two blocks: above the threshold, there is a spectral algorithm which asymptotically almost surely constructs a partition of the hypergraph correlated with the true partition. Our method is a generalization to random hypergraphs of the method developed by Massoulié (2014) for sparse random graphs.
Effect of long‐term organic and mineral fertilization strategies on rhizosphere microbiota assemblage and performance of lettuce

Summary Long‐term agricultural fertilization strategies gradually change soil properties including the associated microbial communities. Cultivated crops recruit beneficial microbes from the surrounding soil environment via root exudates. In this study, we aimed to investigate the effects of long‐term fertilization strategies across field sites on the rhizosphere prokaryotic (Bacteria and Archaea) community composition and plant performance. We conducted growth chamber experiments with lettuce (Lactuca sativa L.) cultivated in soils from two long‐term field experiments, each of which compared organic versus mineral fertilization strategies. 16S rRNA gene amplicon sequencing revealed the assemblage of a rhizosphere core microbiota shared in all lettuce plants across soils, going beyond differences in community composition depending on field site and fertilization strategies. The enhanced expression of several plant genes with roles in oxidative and biotic stress signalling pathways in lettuce grown in soils with organic indicates an induced physiological status in plants. Lettuce plants grown in soils with different fertilization histories were visibly free of stress symptoms and achieved comparable biomass. This suggests a positive aboveground plant response to belowground plant–microbe interactions in the rhizosphere. Besides effects of fertilization strategy and field site, our results demonstrate the crucial role of the plant in driving rhizosphere microbiota assemblage.
Spin-orbit coupling in periodically driven optical lattices

We propose a method for the emulation of artificial spin orbit coupling in a system of ultracold, neutral atoms trapped in a tight-binding lattice. This scheme does not involve near-resonant laser fields, avoiding the heating processes connected to the spontaneous emission of photons. In our case, the necessary spin dependent tunnel matrix elements are generated by a rapid, spin dependent, periodic force, which can be described in the framework of an effective, time averaged Hamiltonian. An additional radio frequency coupling between the spin states leads to a mixing of the spin bands.
Malaria in Senegal: Recent and Future Changes Based on Bias-Corrected CMIP6 Simulations

Malaria is a constant reminder of the climate change impacts on health. Many studies have investigated the influence of climatic parameters on aspects of malaria transmission. Climate conditions can modulate malaria transmission through increased temperature, which reduces the duration of the parasite’s reproductive cycle inside the mosquito. The rainfall intensity and frequency modulate the mosquito population’s development intensity. In this study, the Liverpool Malaria Model (LMM) was used to simulate the spatiotemporal variation of malaria incidence in Senegal. The simulations were based on the WATCH Forcing Data applied to ERA-Interim data (WFDEI) used as a point of reference, and the biased-corrected CMIP6 model data, separating historical simulations and future projections for three Shared Socio-economic Pathways scenarios (SSP126, SSP245, and SSP585). Our results highlight a strong increase in temperatures, especially within eastern Senegal under the SSP245 but more notably for the SSP585 scenario. The ability of the LMM model to simulate the seasonality of malaria incidence was assessed for the historical simulations. The model revealed a period of high malaria transmission between September and November with a maximum reached in October, and malaria results for historical and future trends revealed how malaria transmission will change. Results indicate a decrease in malaria incidence in certain regions of the country for the far future and the extreme scenario. This study is important for the planning, prioritization, and implementation of malaria control activities in Senegal.
CORRELATION FUNCTIONS OF MULTISITE INTERACTION SPIN-S MODELS ON THE BETHE-LIKE LATTICES

Multisite interaction spin-S models in an external magnetic field are studied recursively on the Bethe-like lattices. The transfer-matrix method is extended to calculate exactly the two-spin correlation functions. The exact expressions for the correlation length and magnetic susceptibility are derived for spin-1/2 models. The singularity of the correlation length with critical index ν = 1 and the proportionality of magnetic susceptibility to correlation length in the second order phase transition region of spin-1/2 ferromagnetic models on the Bethe-like lattices are established analytically.
Evaluation of parameterisation approaches for estimating soil hydraulic parameters with HYDRUS-1D in the groundnut basin of Senegal

ABSTRACT Soil hydraulic parameters (SHPs) required as inputs for numerical models are scarce in Sahelian regions. Instead, they are estimated using pedotransfer functions (PTFs), but their ability to simulate soil water dynamics has not been evaluated. This study aims to parameterize SHPs with seven different PTFs and inverse modelling to examine their ability to simulate water fluxes in Senegal’s Groundnut basin. We used four years of field measurements of soil water content (SWC) and actual evapotranspiration (ETa) under pearl millet and groundnut crop rotation for model evaluation. Inverse modelling for SWC (root mean square error [RMSE] ≤ 0.015 cm3 cm−3) and ETa (RMSE ≤ 0.62 mm d−1) yielded the best model performance compared to PTFs (0.024–0.175 cm3 cm−3 and 0.68–0.96 mm d−1, respectively). Where field measurements are lacking for inverse estimation, three of the seven tested PTFs yielded good modelling results and could be used as a parsimonious approach for cultivated Sahelian soils.
ON THE CONSISTENCY OF NEUTRON-STAR RADIUS MEASUREMENTS FROM THERMONUCLEAR BURSTS

The radius of neutron stars can in principle be measured via the normalization of a blackbody fitted to the X-ray spectrum during thermonuclear (type-I) X-ray bursts, although few previous studies have addressed the reliability of such measurements. Here we examine the apparent radius in a homogeneous sample of long, mixed H/He bursts from the low-mass X-ray binaries GS 1826−24 and KS 1731−26. The measured blackbody normalization (proportional to the emitting area) in these bursts is constant over a period of up to 60 s in the burst tail, even though the flux (blackbody temperature) decreased by a factor of 60%–75% (30%–40%). The typical rms variation in the mean normalization from burst to burst was 3%–5%, although a variation of 17% was found between bursts observed from GS 1826−24 in two epochs. A comparison of the time-resolved spectroscopic measurements during bursts from the two epochs shows that the normalization evolves consistently through the burst rise and peak, but subsequently increases further in the earlier epoch bursts. The elevated normalization values may arise from a change in the anisotropy of the burst emission or alternatively variations in the spectral correction factor, fc, of order 10%. Since burst samples observed from systems other than GS 1826−24 are more heterogeneous, we expect that systematic uncertainties of at least 10% are likely to apply generally to measurements of neutron-star radii, unless the effects described here can be corrected for.
Artificial Intelligence for Automated Plant Species Identification: A Review

—Plants are very important for life on Earth. There is a wide variety of plant species and their number increases each year. The plants identification using conventional keys is complex, takes time and it is frustrating for non-experts because of the use of specific botanical terms/techniques. This creates a difficult obstacle to overcome for novices interested in acquiring knowledge about species, which is very important to develop any environmental study, like climate change anticipation models for example. Today, there is an increasing interest in automating the species identification process. The availability and omnipresence of relevant technologies, such as digital cameras, mobile devices, pattern recognition and artificial intelligence techniques in general, have allowed the idea of automated species identification to become a reality. In this paper, we present a review of automated plant identification over all significant available studies in literature. The main result of this synthesis is that the performance of advanced deep learning models, despite the presence of several challenges, is becoming close to the most advanced human expertise.
A Survey of Network Automation for Industrial Internet-of-Things Toward Industry 5.0

Network automation has been bred by the deployment of 5G based Industrial Internet-of-Things (IIoT) in Industry 4.0, and further approaching pervasive AI and human-robot-interaction/-collaboration toward 6G based Industry 5.0. Hitherto, to the best of the authors knowledge, research efforts are still required to provide a comprehensive review of the state-of-the-art network automation technologies for IIoT in 5G based Industry 4.0 and summary of challenges for next-generation network automation regarding the stricter network requirements of 6G based Industry 5.0. Therefore, in this article, we conduct a comprehensive overview of the state-of-the-art network automation technologies, standardizations, and corresponding impact on IIoT of Industry 4.0. We also forecast the next-generation network automation development toward 6G based Industry 5.0. This article provides blueprint of the next-generation network automation, meanwhile conducting comprehensive overview of the SoA network automation technologies in Industry 4.0, which gains high referable value for the researchers in the relative domain.
Glass and jamming transition of simple liquids: static and dynamic theory

We study the glass and jamming transition of finite-dimensional models of simple liquids: hard- spheres, harmonic spheres and more generally bounded pair potentials that modelize frictionless spheres in interaction. At finite temperature, we study their glassy dynamics via field-theoretic methods by resorting to a mapping towards an effective quantum mechanical evolution, and show that such an approach resolves several technical problems encountered with previous attempts. We then study the static, mean-field version of their glass transition via replica theory, and set up an expansion in terms of the corresponding static order parameter. Thanks to this expansion, we are able to make a direct and exact comparison between historical Mode-Coupling results and replica theory. Finally we study these models at zero temperature within the hypotheses of the random-first-order-transition theory, and are able to derive a quantitative mean-field theory of the jamming transition. The theoretic methods of field theory and liquid theory used in this work are presented in a mostly self-contained, and hopefully pedagogical, way. This manuscript is a corrected version of my PhD thesis, defended in June, 29th, under the advisorship of Fr\'ed\'eric van Wijland, and also contains the result of collaborations with Ludovic Berthier and Francesco Zamponi. The PhD work was funded by a CFM-JP Aguilar grant, and conducted in the Laboratory MSC at Universit\'e Denis Diderot--Paris 7, France.
FEEDBACK IN LUMINOUS OBSCURED QUASARS

We use spatially resolved long-slit spectroscopy from Magellan to investigate the extent, kinematics, and ionization structure in the narrow-line regions of 15 luminous, obscured quasars with z < 0.5. Increasing the dynamic range in luminosity by an order of magnitude, as well as improving the depth of existing observations by a similar factor, we revisit relations between narrow-line region size and the luminosity and linewidth of the narrow emission lines. We find a slope of 0.22 ± 0.04 for the power-law relationship between size and luminosity, suggesting that the nebulae are limited by availability of gas to ionize at these luminosities. In fact, we find that the active galactic nucleus is effectively ionizing the interstellar medium over the full extent of the host galaxy. Broad (∼300–1000 km s−1) linewidths across the galaxies reveal that the gas is kinematically disturbed. Furthermore, the rotation curves and velocity dispersions of the ionized gas remain constant out to large distances, in striking contrast to normal and starburst galaxies. We argue that the gas in the entire host galaxy is significantly disturbed by the central active galactic nucleus. While only ∼107–108 M☉ worth of gas are directly observed to be leaving the host galaxies at or above their escape velocities, these estimates are likely lower limits because of the biases in both mass and outflow velocity measurements and may in fact be in accord with expectations of recent feedback models. Additionally, we report the discovery of two dual obscured quasars, one of which is blowing a large-scale (∼10 kpc) bubble of ionized gas into the intergalactic medium.
Chemistry in Disks. IV. Benchmarking gas-grain chemical models with surface reactions

Abridged: We detail and benchmark two sophisticated chemical models developed by the Heidelberg and Bordeaux astrochemistry groups. The main goal of this study is to elaborate on a few well-described tests for state-of-the-art astrochemical codes covering a range of physical conditions and chemical processes, in particular those aimed at constraining current and future interferometric observations of protoplanetary disks. We consider three physical models: a cold molecular cloud core, a hot core, and an outer region of a T Tauri disk. Our chemical network (for both models) is based on the original gas-phase osu_03_2008 ratefile and includes gas-grain interactions and a set of surface reactions for the H-, O-, C-, S-, and N-bearing molecules. The benchmarking is performed with the increasing complexity of the considered processes: (1) the pure gas-phase chemistry, (2) the gas-phase chemistry with accretion and desorption, and (3) the full gas-grain model with surface reactions. Using atomic initial abundances with heavily depleted metals and hydrogen in its molecular form, the chemical evolution is modeled within 10^9 years. The time-dependent abundances calculated with the two chemical models are essentially the same for all considered physical cases and for all species, including the most complex polyatomic ions and organic molecules. This result however required a lot of efforts to make all necessary details consistent through the model runs, e.g. definition of the gas particle density, density of grain surface sites, the strength and shape of the UV radiation field, etc. The reference models and the benchmark setup, along with the two chemical codes and resulting time-dependent abundances are made publicly available in the Internet: this http URL
Airport Capacity Prediction With Multisource Features: A Temporal Deep Learning Approach

Accurate airport capacity estimation is crucial for the secure and orderly operation of the aviation system. However, such estimation is a non-trivial task as capacity depends on various meteorological and operational features. The complex coupling characteristics among these multi-source features have proved to be challenging for most of the traditional regression models. Recently, enhanced by its excellent ability to mine nonlinear relationships, the machine learning methods trigger widely applications. However, due to the imbalance of features scatter and the neglect of temporal dependences in aviation systems, existing machine learning methods for airport capacity prediction still have room for improvement. In light of these, this paper presents a novel airport capacity prediction method based on the multi-channel fusion Transformer model (MF-Transformer). Besides the commonly used aviation features, we unprecedentedly harness the power of the high-dimensional meteorological feature for accurate prediction. As to the model, we construct a multi-channel feature fusion structure, which includes a three-channel network for multi-source features extraction and an attention-based feature fusion module between channels. In each channel, the Transformer-based model is utilized to capture the temporal dependences of features. We conduct experiments on the capacity prediction tasks of the Beijing Capital International Airport which is the largest airport in China and verify that the proposed MF-Transformer outperforms benchmarks under different prediction horizons.
The ROSAT Brightest Cluster Sample — I. The compilation of the sample and the cluster log N—log S distribution

We present a 90 per cent flux-complete sample of the 201 X-ray-brightest clusters of galaxies in the northern hemisphere (δ ≥ 0°), at high Galactic latitudes (|b| ≥ 20°), with measured redshifts z ≤ 0.3 and fluxes higher than 4.4 × 10−12 erg cm−2 s−1 in the 0.1–2.4 keV band. The sample, called the ROSAT Brightest Cluster Sample (BCS), is selected from ROSAT All-Sky Survey data and is the largest X-ray-selected cluster sample compiled to date. In addition to Abell clusters, which form the bulk of the sample, the BCS also contains the X-ray-brightest Zwicky clusters and other clusters selected from their X-ray properties alone. Effort has been made to ensure the highest possible completeness of the sample and the smallest possible contamination by non-cluster X-ray sources. X-ray fluxes are computed using an algorithm tailored for the detection and characterization of X-ray emission from galaxy clusters. These fluxes are accurate to better than 15 per cent (mean 1σ error). We find the cumulative log N–log S distribution of clusters to follow a power law κSα with α = 1.31+0.06−0.03 (errors are the 10th and 90th percentiles) down to fluxes of 2 × 10−12 erg cm−2 s−1, i.e. considerably below the BCS flux limit. Although our best-fitting slope disagrees formally with the canonical value of −1.5 for a Euclidean distribution, the BCS log N–log S distribution is consistent with a non-evolving cluster population if cosmological effects are taken into account. Our sample will allow us to examine large-scale structure in the northern hemisphere, determine the spatial cluster–cluster correlation function, investigate correlations between the X-ray and optical properties of the clusters, establish the X-ray luminosity function for galaxy clusters, and discuss the implications of the results for cluster evolution.