Miracle-dz/UniFAR-FTUs huggingface dataset:
Modelling the dusty universe - II. The clustering of submillimetre-selected galaxies

We combine the GALFORM semi-analytical model of galaxy formation, which predicts the star formation and merger histories of galaxies, the GRASIL spectrophotometric code, which calculates the spectral energy distributions of galaxies self-consistently, including reprocessing of radiation by dust, and artificial neural networks to investigate the clustering properties of galaxies selected by their emission at submillimetre (submm) wavelengths [submm galaxies (SMGs)]. We use the Millennium Simulation to predict the spatial and angular distribution of SMGs. At redshift z = 2, we find that these galaxies are strongly clustered, with a comoving correlation length of r(0) = 5.6 +/- 0.9 h(-1) Mpc for galaxies with 850-mu m flux densities brighter than 5 mJy, in agreement with observations. We predict that at higher redshifts, these galaxies trace denser and increasingly rarer regions of the universe. We present the predicted dependence of the clustering on luminosity, submm colour and halo and stellar masses. Interestingly, we predict tight relations between the correlation length and the halo and stellar masses, independent of submm luminosity.
Ethnobotanical Survey of Medicinal Plants Used in the Treatment of COVID-19 and Related Respiratory Infections in Ogbomosho South and North Local Government Areas, Oyo State, Nigeria

Coronavirus disease 2019 (COVID-19) has extensively spread worldwide with high mortality. Besides vaccination, the United States Food and Drug Administration approved only one oral medication as a treatment. Medicinal plants with antiviral and immunomodulatory properties could be explored as complementary treatments for COVID-19. Ogbomosho is home to such plants traditionally used to treat infectious diseases in Nigeria, making it relevant in complementary medicine. An ethnobotanical survey of medicinal plants used to treat COVID-19 and related ailments, including cough and flu in Ogbomosho South and North Local Government Areas, Nigeria, was conducted using a semi-structured questionnaire. Information was obtained from 56 participants, consisting of different groups of individuals with native knowledge of medicinal plants, and ethnobotanical indices, including the frequency of citation (FC), relative frequency of citation (RFC), and fidelity level (FL) were computed. Twenty-six medicinal plants (17 families) were used to treat COVID-19, 31 (20 families) for cough, and 29 (19 families) for flu. The most cited plant was Zingiber officinale (FC = 10; RFC = 0.18; FL = 18%) for treating COVID-19, Citrus limon (FC = 13; RFC = 0.23; FL = 23%) for cough, and Zingiber officinale (FC = 9; RFC = 0.16; FL = 16%) for flu. Leaves were the most used plant part for treating COVID-19 and flu, while the bark was the most used for cough. Trees and herbs were the most cited plant growth forms. The herbal remedies were mostly prepared by decoction and infusion and were mainly administered orally. Further research should be conducted on the identified species for the scientific validation of their antiviral and immunomodulatory efficacies and safety for use.
The Impact of Gender Differences and Two Event-Frames in English News Reports on Chinese Non-native English Learners' Emotions to Climate Change

: News organizations increasingly use event-frames to convey the urgency of climate change; yet, little is known about how different event-frames in English news reports affect Chinese Non-native English learners’ emotions to climate change with taking gender differences into consideration. Taking some English news reports on climate change from China Daily as corpus, this study analyses how using different event-frames to communicate messages about climate change to Chinese non-native English readers. Meanwhile, this study experimentally examines how event-frames of the news reports (i.e., on climate impacts, actions) influence Chinese non-native English learners’ emotions, as well as whether the effects depend on gender differences. Results showed that both different event-frames and gender differences have significant influence on Chinese non-native English learners’ emotions. News reports on climate impacts can elicit more fear and more anger for Chinese non-native English learners but less hope compared to news reports on climate actions. As for Chinese non-native English learners, emotion at “fear” and “hope” level has no significant gender differences, while emotion at “anger” level has significant gender differences. Moreover, event-frames and gender differences have a disordinal interaction effect.
Kinetic aspects of the ion current layer in a reconnection outflow exhaust

Kinetic aspects of the ion current layer at the center of a reconnection outflow exhaust near the X-type region are investigated by a two-dimensional particle-in-cell (PIC) simulation. The layer consists of magnetized electrons and unmagnetized ions that carry a perpendicular electric current. The ion fluid appears to be nonideal, sub-Alfvenic, and nondissipative. The ion velocity distribution functions contain multiple populations, such as global Speiser ions, local Speiser ions, and trapped ions. The particle motion of the local Speiser ions in an appropriately rotated coordinate system explains the ion fluid properties very well. The trapped ions are the first demonstration of the regular orbits in the chaotic particle dynamics [Chen and Palmadesso, J. Geophys. Res. 91, 1499 (1986)] in self-consistent PIC simulations. They would be observational signatures in the ion current layer near reconnection sites.
GLOBAL PROPERTIES OF NEUTRAL HYDROGEN IN COMPACT GROUPS

Compact groups of galaxies provide a unique environment to study the evolution of galaxies amid frequent gravitational encounters. These nearby groups have conditions similar to those in the earlier universe when galaxies were assembled and give us the opportunity to witness hierarchical formation in progress. To understand how the compact group environment affects galaxy evolution, we examine the gas and dust in these groups. We present new single-dish GBT neutral hydrogen (H i) observations of 30 compact groups and define a new way to quantify the group H i content as the H i-to-stellar mass ratio of the group as a whole. We compare the H i content with mid-IR indicators of star formation and optical [g − r] color to search for correlations between group gas content and star formation activity of individual group members. Quiescent galaxies tend to live in H i-poor groups, and galaxies with active star formation are more commonly found in H i-rich groups. Intriguingly, we also find “rogue” galaxies whose star formation does not correlate with group H i content. In particular, we identify three galaxies (NGC 2968 in RSCG 34, KUG 1131+202A in RSCG 42, and NGC 4613 in RSCG 64) whose mid-IR activity is discrepant with the H i. We speculate that this mismatch between mid-IR activity and H i content is a consequence of strong interactions in this environment that can strip H i from galaxies and abruptly affect star formation. Ultimately, characterizing how and on what timescales the gas is processed in compact groups will help us understand the interstellar medium in complex, dense environments similar to the earlier universe.
A Simple Computational Model for Particle Resuspension Behind a Normal Moving Shock

The simulation of particle resuspension from a surface due to shock passage and subsequent piston flow presents a means to analyze the postshock conditions of an environment, such as after a “dirty” bomb is detonated. This computational model is based on the “Rock’n Roll” models of particle detachment by Reeks, Reed, and Hall. The attractive forces used in the model are based on measurements by Truman et al. (2011). The simplifying assumptions of this model are: the simulation is two-dimensional, the particles are perfect spheres of identical size and are arranged in a hexagonal pattern in a bed of specified length and height. Each particle is categorized as being in one of five situations with respect to surrounding particles. These situations are used to model the forces and moments acting on the particles for resuspension. A random particle arrangement was generated within MATLAB, as well as a visual display of the particle layout as the shock wave passes over the particles. The model employs a turbulent velocity profile acquired from a STAR-CCM+ simulation with randomly-varying attractive forces between particles. Particle rolling and the dynamics of resuspending particles are computed during the passage of the shock and its following piston flow. A variety of multi-particle interactions was observed. Particles “zippered off” along the v direction of the flow. Mountains and canyons were eroded away due to either strongly-attracted or weakly-attracted particles. After the shock passes over the particle bed, predictions reveal that all particles are detached above a certain height due to high velocity piston flow. The simulation also predicts the percentage of particles resuspended when exposed to the shock.
Miniature X-Ray Solar Spectrometer: A Science-Oriented, University 3U CubeSat

The miniature x-ray solar spectrometer is a three-unit CubeSat developed at the Laboratory for Atmospheric and Space Physics at the University of Colorado, Boulder. Over 40 students contributed to the project with professional mentorship and technical contributions from professors in the Aerospace Engineering Sciences Department at University of Colorado, Boulder and from Laboratory for Atmospheric and Space Physics scientists and engineers. The scientific objective of the miniature x-ray solar spectrometer is to study processes in the dynamic sun, from quiet sun to solar flares, and to further understand how these changes in the sun influence the Earth’s atmosphere by providing unique spectral measurements of solar soft x rays. The enabling technology providing the advanced solar soft x-ray spectral measurements is the Amptek X123, a commercial off-the-shelf silicon drift detector. The Amptek X123 has a low mass (∼324 g after modification), modest power consumption (∼2.50 W), and small volume (6.86×9.9.
Bypass transition to turbulence and research Desiderata

Bypass transitions are seldom mentioned in texts or meetings on instability and transition to wall turbulence. The nature of a number of bypass transitions is illustrated by example. Until this characteristics is truly understood predicting transition on the basis of theory or statistically inadequate correlations (as they all are) entails risks that should be considered in justifying any design involving transition. A historical overview of bypass transition identified on blunt bodies is given.
Six Easy Pieces: Essentials of Physics Explained by Its Most Brilliant Teacher

Introduction by Paul Davies Atoms In Motion Introduction Matter Is Made From Atoms Atomic Processes Chemical Reactions Basic Physics Introduction Physics Before Quantum Physics Nuclei and Particles The Relation Of Physics To Other Sciences Introduction Chemistry Biology Astronomy Geology Psychology How Did It Get That Way? Conservation Of Energy What Is Energy? Gravitational Potential Energy Kinetic Energy Other Forms of Energy The Theory Of Gravitation Planetary Motions Keplers Laws Development of Dynamics Newtons Law of Gravitation Universal Gravitation Cavendishs Experiment What Is Gravity? Gravity and Relativity Quantum Behavior Atomic Mechanics An Experiment with Bullets An Experiment with Waves An Experiment with Electrons The Interface of Electron Waves Watching the Electrons First Principles of Quantum Mechanics The Uncertainty Principle.
THE UNREASONABLE WEAKNESS OF R-PROCESS COSMIC RAYS IN THE NEUTRON-STAR-MERGER NUCLEOSYNTHESIS SCENARIO

We reach the robust conclusion that, by combining the observed cosmic rays of r-process elements with the fact that the velocity of the neutron-star-merger ejecta is much higher than that of the supernova ejecta, either (1) the reverse shock in the neutron-star-merger ejecta is a very inefficient accelerator that converts less than 0.003% of the ejecta kinetic energy to the cosmic-ray energy or (2) the neutron star merger is not the origin of the Galactic r-process elements. We also find that the acceleration efficiency should be less than 0.1% for the reverse shock of the supernova ejecta with observed cosmic rays lighter than the iron.
Compatibility of neutrino DIS data and its impact on nuclear parton distribution functions

In global analyses of nuclear parton distribution functions (nPDFs), neutrino deep-inelastic scattering (DIS) data have been argued to exhibit tensions with the data from charged-lepton DIS. Using the nCTEQ framework, we investigate these possible tensions both internally and with the data sets used in our recent nPDF analysis nCTEQ15WZSIH. We take into account nuclear eﬀects in the calculation of the deuteron structure function F D 2 using the CJ15 analysis. The resulting nPDF ﬁt, nCTEQ15WZSIHdeut, serves as the basis for our comparison with inclusive neutrino DIS and charm dimuon production data. Using χ 2 hypothesis testing, we conﬁrm evidence of tensions with these data and study the impact of the proton PDF baseline as well as the treatment of data correlation and normalization uncertainties. We identify the experimental data and kinematic regions that generate the tensions and present several possible approaches how a consistent global analysis with neutrino data can be performed. We show that the tension can be relieved using a kinematic cut at low x ( x > 0 . 1 ) and also investigate a possibility of managing the tensions by using uncorrelated systematic errors. Finally, we present a diﬀerent approach identifying a subset of neutrino data which leads to a consistent global analysis without any additional cuts. Understanding these tensions between the neutrino and charged-lepton DIS data is important not only for a better ﬂavor separation in global analyses of nuclear and proton PDFs, but also for neutrino physics and for searches for physics beyond the Standard Model.
An Improved Image Denoising Approach Using Optimized Variance-Stabilizing Transformations

Image denoising plays a very important process in image processing. Many researchers would study about the various noise removal approaches used for fluorescence images. The fluorescence images mainly contain Poisson noise. The process of denoising is the image is gaussianized first then the resulting image is given as an input to the OWT SURELET to remove the Gaussian white noise. The OWT SURELET is one of the conventional denoising algorithms used to remove the noises. Then to attain an exact signal an inverse transform is applied to the denoised signal. Difficulties may arise to choose the inverse transformation for fluorescence images because the bias error may occur if the non linear forward transform is applied. To overcome these difficulties a study is made on the proposed Anscombe transformation and OWT-SURELET suitable for fluorescence images. The proposed OWT-SURELET is compared with BLS_GSM strategy and the results are discussed. Experimental result shows that the proposed system is more efficient than the existing system, the results are tested using ISNR changes with the denoising algorithms and the inverse transforms.
Roadmap for selected key measurements of LHCb

Six of the key physics measurements that will be made by the LHCb experiment, concerning CP asymmetries and rare B decays, are discussed in detail. The "road map" towards the precision measurements is presented, including the use of control channels and other techniques to understand the performance of the detector with the first data from the LHC.
Multi-Objective Resource Scheduling for IoT Systems Using Reinforcement Learning

IoT embedded systems have multiple objectives that need to be maximized simultaneously. These objectives conflict with each other due to limited resources and tradeoffs that need to be made. This requires multi-objective optimization (MOO) and multiple Pareto-optimal solutions are possible. In such a case, tradeoffs are made w.r. t. a user-defined preference. This work presents a general Multi-objective Reinforcement Learning (MORL) framework for MOO of IoT embedded systems. This framework comprises a general Multi-objective Markov Decision Process (MOMDP) formulation and two novel low-compute MORL algorithms. The algorithms learn policies to tradeoff between multiple objectives using a single preference parameter. We take the energy scheduling problem in general Energy Harvesting Wireless Sensor Nodes (EHWSNs) as a case example in which a sensor node is required to maximize its sensing rate, and transmission performance as well as ensure long-term uninterrupted operation within a very tight energy budget. We simulate single-task and dual-task EHWSN systems to evaluate our framework. The results demonstrate that our MORL algorithms can learn better policies at lower learning costs and successfully tradeoff between multiple objectives at runtime.
The Interrelationship between Road Pricing Acceptability and Self-Driving Vehicle Adoption: Insights from Four Countries

Driverless vehicles (i.e., autonomous and shared autonomous vehicles) are associated with many advantages for the transportation market. However, they may also increase the traveled miles on roads due to improved accessibility, thus aggravating congestion. Road pricing (RP) is a possible solution for mitigating traffic-related problems like congestion. Despite its benefits, RP is usually resented by the public, which may hinder its introduction. This study investigates the factors that may influence RP acceptability in the era of driverless vehicles and driverless vehicle adoption in the presence of RP. For this purpose, a survey was distributed in Hungary, Jordan, Ukraine, and Brazil. The study applied factor analysis, multiple linear regression, and multinomial logit modeling to examine RP acceptability and driverless vehicle adoption. All examined factors have a significant impact on mode choice. For instance, respondents willing to share their trips with others due to the application of RP, opted for shared autonomous vehicles, while those who enjoy driving were less likely to choose autonomous vehicles. In terms of RP acceptability, the respondents who were environmentally conscious in their trip planning showed more acceptance of RP. This study shows the significant impacts of the investigated factors on RP acceptability and driverless vehicle adoption.
Assessing the Antifungal Activities of Buchholzia coriacea on Dermatophytes Isolated from Horses in Katsina State, Nigeria

Dermatophytes are filamentous fungi that affect both human and animal skin, hair, and nails. There is a public health issue with it. In order to ascertain the effects of the methanolic extracts of Buccholzia coriacea on the isolates and the sensitivity level of the isolates to common antifungal drugs, this study was developed to explore the prevalence of Dermatophytes from clinical cases in horses. Samples were initially cultivated on Sabouraud dextrose agar, and then on Potato dextrose agar (secondary culture). Twelve (12%) of the sixty (60) clinical samples that were obtained were positive for Dermatophytes. T. rubrum (1), T. verrucosum (3), T. equinum (3), M. audounii (2), and M. gypseum (3) were the species recognized. At concentrations between 125 and 250 mg/ml, the methanolic extract of Buccholzia coriacea demonstrated antifungal effects on every isolate with values for the minimum inhibitory concentration (MIC) and minimum fungicidal concentration (MFC). The isolates' susceptibility to six popular antifungal medications was assessed. The isolates were well inhibited by Ketoconazole and Terbinafine, but none of them were susceptible to Amphotericin B. This study was able to show that Buccholzia coriacea's methanolic extract has antifungal properties. Additionally, two Dermatophytes species (Trichophyton and Microsporum) from Katsina state, Nigeria, were able to be isolated for this study.
Physical Inactivity and Sedentarism during and after Admission with Community-Acquired Pneumonia and the Risk of Readmission and Mortality: A Prospective Cohort Study

Background: Bed rest with limited physical activity is common during admission. The aim was to determine the association between daily step count and physical activity levels during and after admission with community-acquired pneumonia (CAP) and the risk of readmission and mortality. Methods: A prospective cohort study of 166 patients admitted with CAP. Step count and physical activity were assessed with accelerometers during and after admission and were categorised as sedentary, light, or moderate-vigorous physical activity. Linear regression was used to assess the association between step count and length of stay. Logistic regression was used to assess the association between step count, physical activity level, and risk of readmission and mortality. Results: Patients admitted with CAP were sedentary, light physically active, and moderate-to-vigorous physically active 96.4%, 2.6%, and 0.9% of their time, respectively, with 1356 steps/d. For every 500-step increase in daily step count on day 1, the length of stay was reduced by 6.6%. For every 500-step increase in daily step count during admission, in-hospital and 30-day mortality was reduced. Increased light and moderate-to-vigorous physical activity during admission were associated with reduced risk of in-hospital and 30-day mortality. After discharge, patients increased their daily step count to 2654 steps/d and spent more time performing light and moderate-to-vigorous physical activity. For every 500-step increase in daily step count after discharge, the risk of readmission was reduced. Higher moderate-to-vigorous physical activity after discharge was associated with a reduced risk of readmission. Conclusions: Increased physical activity during admission was associated with a reduced length of stay and risk of mortality, whereas increased physical activity after discharge was associated with a reduced risk of readmission in patients with CAP. Interventions focusing on increasing physical activity levels should be prioritised to improve the prognosis of patients admitted with CAP.
ASVspoof 2019: Future Horizons in Spoofed and Fake Audio Detection

ASVspoof, now in its third edition, is a series of community-led challenges which promote the development of countermeasures to protect automatic speaker verification (ASV) from the threat of spoofing. Advances in the 2019 edition include: (i) a consideration of both logical access (LA) and physical access (PA) scenarios and the three major forms of spoofing attack, namely synthetic, converted and replayed speech; (ii) spoofing attacks generated with state-of-the-art neural acoustic and waveform models; (iii) an improved, controlled simulation of replay attacks; (iv) use of the tandem detection cost function (t-DCF) that reflects the impact of both spoofing and countermeasures upon ASV reliability. Even if ASV remains the core focus, in retaining the equal error rate (EER) as a secondary metric, ASYspoof also embraces the growing importance of fake audio detection. ASVspoof 2019 attracted the participation of 63 research teams, with more than half of these reporting systems that improve upon the performance of two baseline spoofing countermeasures. This paper describes the 2019 database, protocols and challenge results. It also outlines major findings which demonstrate the real progress made in protecting against the threat of spoofing and fake audio.