Miracle-dz/UniFAR-FTUs huggingface dataset:
The matter distribution in z ~ 0.5 redshift clusters of galaxies. II : The link between dark and visible matter

We present an optical analysis of a sample of 11 clusters built from the EXCPRES sample of X-ray selected clusters at intermediate redshift (z ~ 0.5). With a careful selection of the background galaxies we provide the mass maps reconstructed from the weak lensing by the clusters. We compare them with the light distribution traced by the early-type galaxies selected along the red sequence for each cluster. The strong correlations between dark matter and galaxy distributions are confirmed, although some discrepancies arise, mostly for merging or perturbed clusters. The average M/L ratio of the clusters is found to be: M/L_r = 160 +/- 60 in solar units (with no evolutionary correction), in excellent agreement with similar previous studies. No strong evolutionary effects are identified even if the small sample size reduces the significance of the result. We also provide a individual analysis of each cluster in the sample with a comparison between the dark matter, the galaxies and the gas distributions. Some of the clusters are studied for the first time in the optical.
Network Intrusion Detection Method Based on Multi-Scale CNN in Internet of Things

Network intrusion detection is a powerful means to identify and analyze the state of the Internet of things. For the reliability requirements of the Internet of things, an intrusion detection analysis method of the Internet of things based on a deep network model is proposed. First, based on the Inception network architecture as the backbone network, this method constructs a multi-scale convolutional neural network (M-CNN) intrusion detection analysis network model. The long-term and short-term memory network models are introduced into M-CNN to enhance the local feature extraction ability of the model. At the same time, batch normalization and global average pooling layers are introduced to make the data distribution of each layer uniform, reduce the model training time, reduce the model calculation gradient, and further improve the efficiency of the network. The simulation experiment takes the KDDcup99 data set as an example, and the results show that the M-CNN intrusion detection model can achieve better results. The precision P r e and recall R e of the detection model are 93.90% and 93.59%, respectively.
THE MOST EFFECTIVE ENGLISH TEACHING METHODS IN RURAL SCHOOLS

Effective teaching methods in many contexts are still a concern when it comes to teaching English as a foreign language in Indonesia. It relates to a lack of English proficiency. Even after six years of formal language learning, students can still not acquire productive English abilities such as speaking and writing. This study's main objective is to find the English teachers' perspectives concerning the most effective teaching methods in rural schools throughout four districts, Malaka, Kupang, Timor Tengah Utara, and Timor Tengah Selatan. The mixed-method was administered through a questionnaire, data collected from 26 English teachers at Senior High School who met the criteria. In addition, eight respondents were interviewed to learn how to apply effective methods. The most effective methods of teaching English in rural areas include Suggestopedia, Audio-Lingual Method, Communicative Language Teaching, and Task-Based Language Teaching.
UNDERSTANDING THE X-RAY FLARING FROM η CARINAE

We quantify the rapid variations in X-ray brightness (“flares”) from the extremely massive colliding wind binary η Carinae seen during the past three orbital cycles by the Rossi X-ray Timing Explorer. The observed flares tend to be shorter in duration and more frequent as periastron is approached, although the largest ones tend to be roughly constant in strength at all phases. Plausible scenarios include (1) the largest of multi-scale stochastic wind clumps from the Luminous Blue Variable (LBV) component entering and compressing the hard X-ray-emitting wind–wind collision (WWC) zone, (2) large-scale corotating interacting regions in the LBV wind sweeping across the WWC zone, or (3) instabilities intrinsic to the WWC zone. The first one appears to be the most consistent with the observations, requiring homologously expanding clumps as they propagate outward in the LBV wind and a turbulence-like power-law distribution of clumps, decreasing in number toward larger sizes, as seen in Wolf–Rayet winds.
Power Quality Improvement in a Solar PV Assisted Microgrid Using Upgraded ANN-Based Controller

This paper proposes the design of a controller using the artificial neural network (ANN) for a solar photovoltaic (PV)-fed cascaded multilevel inverter (CMLI) to enhance the power quality. The objective of this presented ANN controller is to obtain a maximum output voltage with no filter components. This paper also investigates and eliminates the voltage harmonics that occurred in a solar-fed cascaded 3-stage inverter using various techniques such as pulse width modulation (PWM), digital logic control (DLC), fuzzy logic controller (FLC), and ANN, and the results are compared. Based on the results, the proposed ANN-based controller efficiently reduces harmonics and improves the power quality. This is achieved by solving the harmonic equations and thereby changing the switching angles of each semiconductor to a minimum value. The ANN is trained by a dataset consisting of varying input voltage and switching angles. The simulation was performed using MATLAB/Simulink for different types of controllers like PWM, DLC, FLC, and ANN for the 3-stage inverter. The simulated results are compared with the results obtained from a 3 kWp photovoltaic plant connected to the CMLI. Finally, on the basis of performance analysis, it was confirmed that the ANN-based controller effectively eliminates harmonics and improves the power quality.
Glaucoma Diagnosis Based on Retinal Fundus Image: A Review

Glaucoma is one of the most dangerous eye diseases. It occurs as a result of an imbalance in the drainage and flow of the retinal fluid. Consequently, intraocular pressure is generated, which is a significant risk factor for glaucoma. Intraocular pressure causes progressive damage to the optic nerve head, thus leading to vision loss in the advanced stages. Glaucoma does not give any signs of disease in the early stages, so it is called "the Silent Thief of Sight". Therefore, early diagnosis and treatment of retinal eye disease is extremely important to prevent vision loss. Many articles aim to analyze fundus retinal images and diagnose glaucoma. This review can be used as a guideline to help diagnose glaucoma. It presents 63 articles related to the applications of fundus retinal analysis. Applications of the glaucomatous image classification are improving fundus images by locating and segmenting the optic disc, optic cup, fovea, and blood vessels. The study also presents datasets, metrics, and parameters that indicate the changes in retina structure and the steps and results for each paper.
Effect of Various Doses of Electron Beam Irradiation Treatment on the Quality Characteristics of Vacuum-Packed Dry Fermented Sausage during Refrigerated Storage

In this study, we investigated the effect of electron beam irradiation on the physicochemical, microbiological, and sensory attributes of dry fermented sausage during 8 weeks of refrigerated storage at 4°C. The five doses of e-beam irradiation applied were: 0 kGy (control) and 1, 2, 3, and 4 kGy. All the experimental treatments led to a significant decrease in pH values during the storage period of 60 days (P<0.05). The 2-kGy treatment caused a significant (P<0.05) decrease in pH value, bacterial growth (total plate count, Listeria monocytogenes, Salmonella Typhimurium, and Escherichia coli), and thiobarbituric acid-reactive substances values than other irradiated fermented sausage batches during the study. Irradiation did not affect the water activity value of the fermented sausage samples. For color characteristics, 3 kGy exhibited significantly lower (P<0.05) L* (lightness) values than other irradiation treatments. A similar trend of significantly lower (P<0.05) a* (redness) and b* (yellowness) values was observed in all irradiated treatments than in the control. All the treatments showed no significant differences (P>0.05) in scores in sensory attributes (color and sourness); however, fermented sausage irradiated with 3 kGy had the highest sensory characteristics (overall acceptability) at the end of the storage period. In conclusion, 1, 2, and 3 kGy irradiation treatments can be beneficial for inhibiting lipid oxidation, controlling microbial growth, and maintaining sensory attributes of fermented sausage during storage, thereby enhancing their food safety and shelf stability.
MODELING THE SYSTEM PARAMETERS OF 2M 1533+3759: A NEW LONGER PERIOD LOW-MASS ECLIPSING sdB+dM BINARY

We present new photometric and spectroscopic observations for 2M 1533+3759 (= NSVS 07826147), the seventh eclipsing subdwarf B star + M dwarf (sdB+dM) binary ever found. It has an orbital period of 0.16177042 days, or ∼3.88 hr, significantly longer than the 2.3–3.0 hr periods of the other known eclipsing sdB+dM systems. Spectroscopic analysis of the hot primary yields Teff = 29230 ± 125 K, log g = 5.58 ± 0.03, and log N(He)/N(H) = −2.37 ± 0.05. The sdB velocity amplitude is K1 = 71.1 ± 1.0 km s−1. The only detectable light contribution from the secondary is due to the surprisingly strong reflection effect, whose peak-to-peak BVRI amplitudes are 0.10, 0.13, 0.15, and 0.19 mag, respectively. Light-curve modeling produced several solutions corresponding to different values of the system mass ratio, q (M2/M1), but only one is consistent with a core helium burning star, q = 0.301. The orbital inclination is 86. °6. The sdB primary mass is M1 = 0.376 ± 0.055 M☉ and its radius is R1 = 0.166 ± 0.007 R☉. 2M 1533+3759 joins PG 0911+456 (and possibly also HS 2333+3927) in having an unusually low mass for an sdB star. SdB stars with masses significantly lower than the canonical value of 0.48 M☉, down to as low as 0.30 M☉, were theoretically predicted by Han et al., but observational evidence has only recently begun to confirm the existence of such stars. The existence of core helium burning stars with masses lower than 0.40–0.43 M☉ implies that at least some sdB progenitors have initial main-sequence masses of 1.8–2.0 M☉ or more, i.e., they are at least main-sequence A stars. The orbital separation in 2M 1533+3759 is a = 0.98 ± 0.04R☉. The secondary has M2 = 0.113 ± 0.017 M☉, R2 = 0.152 ± 0.005R☉, and K, consistent with a main-sequence M5 star. If 2M 1533+3759 becomes a cataclysmic variable (CV), its orbital period will be 1.6 hr, below the CV period gap.
SINGLE-DEGENERATE TYPE Ia SUPERNOVAE WITHOUT HYDROGEN CONTAMINATION

The lack of hydrogen in spectra of type Ia supernovae (SNe Ia) is often seen as troublesome for single-degenerate (SD) progenitor models. We argue that, since continued accretion of angular momentum can prevent explosion of the white dwarf, it may be natural for the donor stars in SD progenitors of SNe Ia to exhaust their envelopes and shrink rapidly before the explosion. This outcome seems most likely for SD SN Ia progenitors where mass transfer begins from a giant donor star and might extend to other SD systems. Not only is the amount of hydrogen left in such a system below the current detection limit, but the donor star is typically orders of magnitude smaller than its Roche lobe by the point when an SD SN Ia occurs, in which case attempts to observe collisions between SN shocks and giant donor stars seem unlikely to succeed. We consider the constraints on this model from the circumstellar structures seen in spectra of SN 2006X and suggest a novel explanation for the origin of this material.
Changes of Physical Activity and Ultra-Processed Food Consumption in College students during COVID-19 Pandemic: An Observational Study

The government has developed initiatives to restrictive activity during the COVID-19 pandemic, which have led to changes in lifestyle habits, especially those involving physical activity and food consumption. Changes of physical activity and ultra-processed foods consumption have occurred in several countries during the COVID-19 pandemic. The changing of lifestyle might affect obesity that 32.5% of the population (>18 years) in Samarinda, East Kalimantan, Indonesia are obese. Good eating behaviours in the early stages of life and adolescence can influence the current health status and the predisposition to non-communicable diseases in adulthood. Therefore, this cross-sectional study with 378 college students aimed to determine changes of physical activity and ultra-processed foods consumption in college students during restrictive activity in the COVID-19 pandemic. Data was collected using an online questionnaire for two months. Further, data was analyzed using Wilcoxon and chi-square test with 95% confidence level (α= 0.05). This study showed that the prevalence of normal nutritional status was 60.1%, inactive physical activity status was 89.4%, and the consumption level of ultra-low processed foods was 82.5%. Statistical tests obtained p-value differences in physical activity (p=<0.001) and differences in ultra-processed food consumption (p=0.034) before and after the restrictive activity in the COVID-19 pandemic. Additionally, mother's educational level (p=0.004) and the number of occupants in the house (p=0.001) significantly affected the consumption of ultra-processed foods.
A Search for Type Ia Supernova Progenitors: the Central Stars of the Planetary Nebulae NGC 2392 and NGC 6026

Abstract We use photoionization modeling to assess the binary nature of the central stars of NGC 2392 and NGC 6026. If they are close binaries, they are potential Type Ia supernovae (SNe Ia) progenitors if the total mass exceeds the Chandrasekhar limit. We show that the nucleus of NGC 2392 likely has a hot, massive (≃1 M⊙) white dwarf companion, and a total mass of ~1.6 M⊙, making it an especially interesting system. The binary mass in NGC 6026 is less, ~1.1 M⊙. Even though its orbital period is short, it is not considered to be an SNe~Ia progenitor.
Ship Target Detection in Optical Remote Sensing Images Based on Multiscale Feature Enhancement

Due to the multiscale characteristics of ship targets in ORSIs (optical remote sensing images), ship target detection in ORSIs based on depth learning is still facing great challenges. Aiming at the low accuracy of multiscale ship target detection in ORSIs, this paper proposes a ship target detection algorithm based on multiscale feature enhancement based on YOLO v4. Firstly, an improved mixed convolution is introduced into the IRes (inverted residual block) to form an MIRes (mixed inverted residual block). The MIRes are used to replace the Res (residual block) in the deep CSP module of the backbone network to enhance the multiscale feature extraction capability of the backbone network. Secondly, for different scale feature maps' perception fields, feature information, and the scale of the detected objects, the multiscale feature enhancement modules—SFEM (small scale feature enhancement module) and MFEM (middle scale feature enhancement module)—are proposed to enhance the feature information of the middle- and low-level feature maps, respectively, and then the enhanced feature maps are sent to the detection head for detection. Finally, experiments were implemented on the LEVIR-ship dataset and the NWPU VHR-10 dataset. The accuracy of the proposed algorithm in ship target detection reached 79.55% and 90.70%, respectively, which is improved by 3.25% and 3.56% compared with YOLO v4.
Safety-Aware Time-Optimal Motion Planning With Uncertain Human State Estimation

Human awareness in robot motion planning is crucial for seamless interaction with humans. Many existing techniques slow down, stop, or change the robot's trajectory locally to avoid collisions with humans. Although using the information on the human's state in the path planning phase could reduce future interference with the human's movements and make safety stops less frequent, such an approach is less widespread. This paper proposes a novel approach to embedding a human model in the robot's path planner. The method explicitly addresses the problem of minimizing the path execution time, including slowdowns and stops owed to the proximity of humans. For this purpose, it converts safety speed limits into configuration-space cost functions that drive the path's optimization. The costmap can be updated based on the observed or predicted state of the human. The method can handle deterministic and probabilistic representations of the human state and is independent of the prediction algorithm. Numerical and experimental results on an industrial collaborative cell demonstrate that the proposed approach consistently reduces the robot's execution time and avoids unnecessary safety speed reductions.
Combined analysis of KamLAND and Borexino neutrino signals from Th and U decays in the Earth's interior

E.L. thanks G. Fiorentini, A. Ianni and W.F. McDonough for many useful discussions about geoneutrino physics in the last few years. The work of G.L. F. , E.L. and A.M.R. is partly supported by the Italian Ministero dell’Istruzione, dell’Universita e della Ricerca (MIUR) through the Progetto di Rilevante Interesse Nazionale (PRIN) “Fisica Astroparticellare: Neutrino ed Universo Primordiale,” and partly by the Istituto Nazionale di Fisica Nucleare (INFN) through the research initiative “Fisica Astroparticellare FA51. ” The work of A.P. is supported by the Spanish Ministerio de Educacion y Ciencia (MEC) under the I3P program, by the Spanish Grants FPA2008-00319, CSD2009-00064, PROMETEO/2009/091, and by the European network UNILHC (PITN-GA-2009-237920).
Quantum Fisher information of entangled coherent states in the presence of photon loss

We investigate the performance of entangled coherent states for quantum-enhanced phase estimation. An exact analytical expression of quantum Fisher information is derived to show the role of photon losses on the ultimate phase sensitivity. We find a transition of the sensitivity from the Heisenberg scaling to the classical scaling due to quantum decoherence of the photon state. This quantum-classical transition is uniquely determined by the number of photons being lost, instead of the number of incident photons or the photon loss rate alone. Our results also reveal that a crossover of the sensitivity between the entangled coherent state and the NOON state can occur even for very small photon loss rate.
Distributed inference for two‐sample U‐statistics in massive data analysis

This paper considers distributed inference for two‐sample U‐statistics under the massive data setting. In order to reduce the computational complexity, this paper proposes distributed two‐sample U‐statistics and blockwise linear two‐sample U‐statistics. The blockwise linear two‐sample U‐statistic, which requires less communication cost, is more computationally efficient especially when the data are stored in different locations. The asymptotic properties of both types of distributed two‐sample U‐statistics are established. In addition, this paper proposes bootstrap algorithms to approximate the distributions of distributed two‐sample U‐statistics and blockwise linear two‐sample U‐statistics for both nondegenerate and degenerate cases. The distributed weighted bootstrap for the distributed two‐sample U‐statistic is new in the literature. The proposed bootstrap procedures are computationally efficient and are suitable for distributed computing platforms with theoretical guarantees. Extensive numerical studies illustrate that the proposed distributed approaches are feasible and effective.
Stochastic asymptotical synchronization of chaotic Markovian jumping fuzzy cellular neural networks with mixed delays and the Wiener process based on sampled-data control

We investigate the stochastic asymptotical synchronization of chaotic Markovian jumping fuzzy cellular neural networks (MJFCNNs) with discrete, unbounded distributed delays, and the Wiener process based on sampled-data control using the linear matrix inequality (LMI) approach. The Lyapunov—Krasovskii functional combined with the input delay approach as well as the free-weighting matrix approach is employed to derive several sufficient criteria in terms of LMIs to ensure that the delayed MJFCNNs with the Wiener process is stochastic asymptotical synchronous. Restrictions (e.g., time derivative is smaller than one) are removed to obtain a proposed sampled-data controller. Finally, a numerical example is provided to demonstrate the reliability of the derived results.
Interaction between an Isotropic Nanoparticle and Drifting Electrons in a Quantum Well

A hybrid system composed of an isotropic nanoparticle and a semiconductor heterostructure with a quantum well has been considered. The nanoparticle is supposed to be polarizable in an external electric field. A theoretical model of the hybrid system is substantiated and formulated. Exact solutions of the model equations are obtained. The frequencies of charge oscillations in the hybrid system and their damping owing to the dipole--plasmon interaction are found, the damping mechanism being similar to that of Landau damping. The space-time behavior of concentration perturbations in the two-dimensional electron gas is analyzed, and the polarization oscillations of a nanoparticle are studied. The induced polarization of a nanoparticle at nonzero electron drift velocities is found to have a complicated dynamics. In particular, the polarization vector circulates along elliptic trajectories for two of three frequency dispersion branches. If the electric current flows through the quantum well due to an applied electric field, the damping of oscillations in the hybrid system is replaced by their growth in time, which corresponds to the electric instability of the system. New phenomena in hybrid systems can be used to excite the emission of nanoparticles by an electric current and to electrically stimulate the emission in the terahertz spectral range.
WERE PROGENITORS OF LOCAL L* GALAXIES Lyα EMITTERS AT HIGH REDSHIFT?

The Lyα emission has been observed from galaxies over a redshift span z ∼ 0–8.6. However, the evolution of high-redshift Lyα emitters (LAEs), and the link between these populations and local galaxies, remains poorly understood. Here, we investigate the Lyα properties of progenitors of a local L* galaxy by combining cosmological hydrodynamic simulations with three-dimensional radiative transfer calculations using the new ART2 code. We find that the main progenitor (the most massive one) of a Milky-Way-like galaxy has a number of Lyα properties close to those of observed LAEs at z ∼ 2–6, but most of the fainter ones appear to fall below the detection limits of current surveys. The Lyα photon escape fraction depends sensitively on a number of physical properties of the galaxy, such as mass, star formation rate, and metallicity, as well as galaxy morphology and orientation. Moreover, we find that high-redshift LAEs show blueshifted Lyα line profiles characteristic of gas inflow, and that the Lyα emission by excitation cooling increases with redshift, and becomes dominant at z ≳ 6. Our results suggest that some observed LAEs at z ∼ 2–6 with luminosity of LLyα ∼ 1042–1043 erg s−1 may be similar to the main progenitor of the Milky Way at high redshift, and that they may evolve into present-day L* galaxies.