Miracle-dz/UniFAR-FTUs huggingface dataset:
Public knowledge and practice of sore throat management among visitors of primary care clinic in Riyadh, Saudi Arabia

Sore throat is a common symptom of in􀅫lammation of the pharynx and tonsils, and it’s a common health burden worldwide. The etiology in 85% of the time is a viral infection, which is a self-limiting disease. The other 15% of sore throat causes could be bacterial, fungal, smoking, intubation and yelling. Several studies were conducted regarding the management of pharyngitis and acute respiratory infections, whichshowedahighrateofantibioticusageinaninjudiciousmanner. Thisisacross-sectionalstudy,which tookplace in the primary careclinic in King Khalid UniversityHospital. A conveniencesample wasselected from the primary care clinic where data were collected via self-administered questionnaires. The research investigators designed the questionnaires and they were handed in 2014 in the time period between January 19 and January 27 where 320 questionnaires were handed. Data were collected from subjects who 􀅫it the inclusion criteria, which included adult outpatients (18 or above) who experienced sore throat in the pastyear. Detailsonthedatathatwerecollectedinclude: demographicvariables, clinicalpresentation, risk factors and mode of management. Data were analyzed using SPSS. The data collection procedure yielded 276 respondents; 44 participants were excluded for not being eligible or not fully 􀅫illing the questionnaire. 52.2% of whom were females and 47.8% were males and only 6.9% of the total respondents chose the appropriate management which is analgesics. The age of respondents held no signi􀅫icance to the choice of managementbut genderexhibitedsigni􀅫icance asthe majorityof participantswhochose theinappropriate management were males constituting 16.4% of the total. In addition, educational level as a demographic factor held signi􀅫icance as well in which respondents carrying bachelor’s degrees formed a percentage of 14.3% of people who chose antibiotics while respondents carrying a high school degree chose analgesics establishing 2.9%. The participants were asked if they follow any guidelines when managing their sore throat and 79.4% denied following guidelines. Also, we recommend similar research to be done on a bigger scale, with a bigger sample size and in different regions to know more about knowledge, attitude and practiceofabiggerportionofthesociety. Moreover,furtherresearchisrecommendedregardingphysicians and pharmacists prescribing antibiotics in an inappropriate fashion as well as supplying them with clear guidelines about the appropriate management of patients complaining of sore throat. © 2017 The Author(s). Published by TAF Publishing.
ON THE SUB-SUPERSOLUTION APPROACH FOR DIRICHLET PROBLEM DRIVEN BY (p(x), q(x))-LAPLACIAN OPERATOR WITH CONVECTION TERM

The method of sub and super-solution is applied to obtain existence and location of solutions to a quasilinear elliptic problem with variable exponent and Dirichlet boundary conditions involving a nonlinear term f depending on solution and on its gradient. Under a suitable growth condition on the convection term f , the existence of at least one solution satisfying a priori estimate is obtained.
Compact Dupin hypersurfaces

A hypersurface M in R is said to be Dupin if along each curvature surface, the corresponding principal curvature is constant. A Dupin hypersurface is said to be proper Dupin if the number of distinct principal curvatures is constant on M , i.e., each continuous principal curvature function has constant multiplicity on M . These conditions are preserved by stereographic projection, so this theory is essentially the same for hypersurfaces in R or S. The theory of compact proper Dupin hypersurfaces in S is closely related to the theory of isoparametric hypersurfaces in S, and many important results in this field concern relations between these two classes of hypersurfaces. This problem was formulated in 1985 in a conjecture of Cecil and Ryan [17, p. 184], which states that every compact, connected proper Dupin hypersurface M ⊂ S is equivalent to an isoparametric hypersurface in S by a Lie sphere transformation. This paper gives a survey of progress on this conjecture and related developments. 1 Dupin hypersurfaces This paper is a survey of the main results in the theory of compact, proper Dupin hypersurfaces in Euclidean space R, which began with the study of the cyclides of Dupin in R in a book by Dupin [25] in 1822. This theory is closely related to the well-known theory of isoparametric hypersurfaces in S, i.e., hypersurfaces with constant principal curvatures in S, introduced by E. Cartan [2]–[5] and developed by many mathematicians (see [7], [23], [65], [18, pp. 85–184] for surveys).
Positron Effects on Polarized Images and Spectra from Jet and Accretion Flow Models of M87* and Sgr A*

We study the effects of including a nonzero positron-to-electron fraction in emitting plasma on the polarized spectral energy distributions and submillimeter images of jet and accretion flow models for near-horizon emission from M87* and Sgr A*. For M87*, we consider a semi-analytic fit to the force-free plasma regions of a general relativistic magnetohydrodynamic jet simulation, which we populate with power-law leptons with a constant electron-to-magnetic pressure ratio. For Sgr A*, we consider a standard self-similar radiatively inefficient accretion flow where the emission is predominantly from thermal leptons with a small fraction in a power-law tail. In both models, we fix the positron-to-electron ratio throughout the emission region. We generate polarized images and spectra from our models using the general relativistic ray tracing and radiative transfer from GRTRANS. We find that a substantial positron fraction reduces the circular polarization fraction at IR and higher frequencies. However, in submillimeter images, higher positron fractions increase polarization fractions due to strong effects of Faraday conversion. We find an M87* jet model that best matches the available broadband total intensity, and 230 GHz polarization data is a sub-equipartition, with positron fraction of ≃10%. We show that jet models with significant positron fractions do not satisfy the polarimetric constraints at 230 GHz from the Event Horizon Telescope (EHT). Sgr A* models show similar trends in their polarization fractions with increasing pair fraction. Both models suggest that resolved, polarized EHT images are useful to constrain the presence of pairs at 230 GHz emitting regions of M87* and Sgr A*.
Neural networks behave as hash encoders: An empirical study

The input space of a neural network with ReLU-like activations is partitioned into multiple linear regions, each corresponding to a specific activation pattern of the included ReLU-like activations. We demonstrate that this partition exhibits the following encoding properties across a variety of deep learning models: (1) {\it determinism}: almost every linear region contains at most one training example. We can therefore represent almost every training example by a unique activation pattern, which is parameterized by a {\it neural code}; and (2) {\it categorization}: according to the neural code, simple algorithms, such as $K$-Means, $K$-NN, and logistic regression, can achieve fairly good performance on both training and test data. These encoding properties surprisingly suggest that {\it normal neural networks well-trained for classification behave as hash encoders without any extra efforts. } In addition, the encoding properties exhibit variability in different scenarios. {Further experiments demonstrate that {\it model size}, {\it training time}, {\it training sample size}, {\it regularization}, and {\it label noise} contribute in shaping the encoding properties, while the impacts of the first three are dominant. } We then define an {\it activation hash phase chart} to represent the space expanded by {model size}, training time, training sample size, and the encoding properties, which is divided into three canonical regions: {\it under-expressive regime}, {\it critically-expressive regime}, and {\it sufficiently-expressive regime}. The source code package is available at \url{https://github.com/LeavesLei/activation-code}.
Single collective excitation of an atomic array trapped along a waveguide: A study of cooperative emission for different atomic chain configurations

Ordered atomic arrays trapped in the vicinity of nanoscale waveguides offer original light-matter interfaces, with applications to quantum information and quantum non-linear optics. Here, we study the decay dynamics of a single collective atomic excitation coupled to a waveguide in different configurations. The atoms are arranged as a linear array and only a segment of them is excited to a superradiant mode and emits light into the waveguide. Additional atomic chains placed on one or both sides play a passive role, either reflecting or absorbing this emission. We show that when varying the geometry, such a one-dimensional atomic system could be able to redirect the emitted light, to directionally reduce or enhance it, and in some cases to localize it in a cavity formed by the atomic mirrors bounding the system.
The $\mathcal{F}$-family of covariance functions: A Mat\'ern analogue for modeling random fields on spheres

The Matérn family of isotropic covariance functions has been central to the theoretical development and application of statistical models for geospatial data. For global data defined over the whole sphere representing planet Earth, the natural distance between any two locations is the great circle distance. In this setting, the Matérn family of covariance functions has a restriction on the smoothness parameter, making it an unappealing choice to model smooth data. Finding a suitable analogue for modelling data on the sphere is still an open problem. This paper proposes a new family of isotropic covariance functions for random fields defined over the sphere. The proposed family has a parameter that indexes the mean square differentiability of the corresponding Gaussian field, and allows for any admissible range of fractal dimension. Our simulation study mimics the fixed domain asymptotic setting, which is the most natural regime for sampling on a closed and bounded set. As expected, our results support the analogous results (under the same asymptotic scheme) for planar processes that not all parameters can be estimated consistently. We apply the proposed model to a dataset of precipitable water content over a large portion of the Earth, and show that the model gives more precise predictions of the underlying process at unsampled locations than does the Matérn model using chordal distances.
Uniform resonance free regions for convex cocompact hyperbolic surfaces and expanders

Let X = Γ\H be a convex cocompact hyperbolic surface, let Xn = Γn\H 2 be a family of finite regular covers of X, and let Gn be the associated family of Cayley graphs of the covering groups Gn = Γ/Γn with respect to the set of Schottky generators of X. We prove that if the graphs Gn form a family of two-sided expanders, then the surfaces Xn have a uniform resonance-free strip. This is the analogue for convex cocompact hyperbolic surfaces of the results of Brooks [10], Burger [11, 12], and Bourgain–Gamburd–Sarnak [6]. Moreover, this result generalizes the work on convex cocompact congruence covers by Oh–Winter [32] and Bourgain–Kontorovich–Magee [20].
A General Method for Generating Discrete Orthogonal Matrices

Discrete orthogonal matrices have applications in information coding and cryptography. It is often challenging to generate discrete orthogonal matrices. A common approach widely in use is to discretize continuous orthogonal functions that have been discovered. The need of such continuous functions is restrictive. Polynomials, as the simplest class of continuous functions, are widely studied for their orthogonality, to serve the purpose of generating orthogonal matrices. However, beginning with continuous orthogonal polynomials still takes much work. To overcome this complexity while improving the efficiency and flexibility, we present a general method for generating orthogonal matrices directly through the construction of certain even and odd polynomials from a set of distinct positive values, bypassing the need of continuous orthogonal functions. We present a constructive proof by induction that not only asserts the existence of such polynomials, but also tells how to iteratively construct them. Besides the derivation of the method as simple as a few nested loops, we discuss two well-known discrete transforms, the Discrete Cosine Transform and the Discrete Tchebichef Transform, about how they can be achieved using our method with the specific values, and how to embed them into the transform module of video coding. By the same token, we also give the examples for generating new orthogonal matrices from arbitrarily chosen values. The demonstrative experiments indicate that our method is not only simpler to implement, but also more efficient and flexible. It can generate orthogonal matrices of larger sizes, compared with those existing methods.
Modeling of Drying of Food Materials with Thickness of Several Centimeters by the Reaction Engineering Approach (REA)

Food materials are highly perishable. Drying is necessary to restrict biological and chemical activity to extend shelf life. A good drying model is useful for design of a better dryer, evaluation of dryer performance, prediction of product quality, and optimization. The reaction engineering approach (REA) is a simple-lumped parameter model revealed to be accurate and robust to model drying of various thin layers or small objects. Modeling drying behavior of different sizes is essential for a good drying model, yet it is still very challenging, even for a traditional diffusion-based model, which requires several sets of experiments to generate the diffusivity function. The REA is implemented in this study, for the first time, to model drying of rather thick samples of food materials. An approximate spatial distribution of sample temperature is introduced and combined with the REA to model drying kinetics. Results have indicated that the REA can model both moisture content and temperature profiles. The accuracy and effectiveness of the REA to model drying of thick samples of food materials are revealed in this study. This has extended the application of REA substantially. The application of the REA is currently not restricted for thin layesr or small objects but also for thick samples.
On the Origin of Hard X-Ray Emissions from the Behind-the-limb Flare on 2014 September 1

The origin of hard X-rays and γ-rays emitted from the solar atmosphere during occulted solar flares is still debated. The hard X-ray emissions could come from flaring loop tops rising above the limb or coronal mass ejection shock waves, two by-products of energetic solar storms. For the shock scenario to work, accelerated particles must be released on magnetic field lines rooted on the visible disk and precipitate. We present a new Monte Carlo code that computes particle acceleration at shocks propagating along large coronal magnetic loops. A first implementation of the model is carried out for the 2014 September 1 event, and the modeled electron spectra are compared with those inferred from Fermi Gamma-ray Burst Monitor (GBM) measurements. When particle diffusion processes are invoked, our model can reproduce the hard electron spectra measured by GBM nearly 10 minutes after the estimated on-disk hard X-rays appear to have ceased from the flare site.
Constraints on stellar rotation from the evolution of Sr and Ba in the Galactic halo

Recent studies show that the chemical evolution of Sr and Ba in the Galaxy can be explained if different production sites, hosting r- and s-processes, are taken into account. However, the question of unambiguously identifying these sites is still unsolved. Massive stars are shown to play an important role in the production of s-material if rotation is considered. In this work, we study in detail the contribution of rotating massive stars to the production of Sr and Ba, in order to explain their chemical evolution, but also to constrain the rotational behaviour of massive stars. A stochastic chemical evolution model was employed to reproduce the enrichment of the Galactic halo. We developed new methods for model-data comparison which help to objectively compare the stochastic results to the observations. We employed these methods to estimate the value of free parameters which describe the rotation of massive stars, assumed to be dependent on the stellar metallicity. We constrain the parameters using the observations for Sr and Ba. Employing these parameters for rotating massive stars in our stochastic model, we are able to correctly reproduce the chemical evolution of Sr and Ba, but also Y, Zr, and La. The data supports a decrease of both the mean rotational velocities and their dispersion with increasing metallicity. Our results show that a metallicity-dependent rotation is a necessary assumption to explain the s-process in massive stars. Our novel methods of model-data comparison represent a promising tool for future galactic chemical evolution studies.
Superconducting microstrip single-photon detector with system detection efficiency over 90% at 1550  nm

Generally, a superconducting nanowire single-photon detector (SNSPD) is composed of wires with a typical width of ~100 nm. Recent studies have found that superconducting stripes with a micrometer-scale width can also detect single photons. Compared with the SNSPD, the superconducting microstrip single-photon detector (SMSPD) has smaller kinetic inductance, higher working current, and lower requirement in fabrication accuracy, providing potential applications in the development of ultra-large active area detectors. However, the study on SMSPD is still in its infancy, and the realization of its high-performance and practical use remains an opening question. This study demonstrates a NbN SMSPD with a saturated system detection efficiency (SDE) of ~92.2% at a dark count rate of ~200 cps, a polarization sensitivity of ~1.03, and a timing jitter of ~48 ps, at the telecom wavelength of 1550 nm when coupled with a single mode fiber and operated at 0.84 K. Furthermore, the detector's SDE is over 70% when operated at a 2.1-K closed-cycle cryocooler.
Towards Practical Adam: Non-Convexity, Convergence Theory, and Mini-Batch Acceleration

Adam is one of the most influential adaptive stochastic algorithms for training deep neural networks, which has been pointed out to be divergent even in the simple convex setting via a few simple counterexamples. Many attempts, such as decreasing an adaptive learning rate, adopting a big batch size, incorporating a temporal decorrelation technique, seeking an analogous surrogate, \textit{etc.}, have been tried to promote Adam-type algorithms to converge. In contrast with existing approaches, we introduce an alternative easy-to-check sufficient condition, which merely depends on the parameters of the base learning rate and combinations of historical second-order moments, to guarantee the global convergence of generic Adam for solving large-scale non-convex stochastic optimization. This observation, coupled with this sufficient condition, gives much deeper interpretations on the divergence of Adam. On the other hand, in practice, mini-Adam and distributed-Adam are widely used without any theoretical guarantee. We further give an analysis on how the batch size or the number of nodes in the distributed system affects the convergence of Adam, which theoretically shows that mini-batch and distributed Adam can be linearly accelerated by using a larger mini-batch size or a larger number of nodes.At last, we apply the generic Adam and mini-batch Adam with the sufficient condition for solving the counterexample and training several neural networks on various real-world datasets. Experimental results are exactly in accord with our theoretical analysis.
Speaker Activity Driven Neural Speech Extraction

Target speech extraction, which extracts the speech of a target speaker in a mixture given auxiliary speaker clues, has recently received increased interest. Various clues have been investigated such as pre-recorded enrollment utterances, direction information, or video of the target speaker. In this paper, we explore the use of speaker activity information as an auxiliary clue for single-channel neural network-based speech extraction. We propose a speaker activity driven speech extraction neural network (ADEnet) and show that it can achieve performance levels competitive with enrollment-based approaches, without the need for pre-recordings. We further demonstrate the potential of the proposed approach for processing meeting-like recordings, where the speaker activity is obtained from a diarization system. We show that this simple yet practical approach can successfully extract speakers after diarization, which results in improved ASR performance, especially in high overlapping conditions, with a relative word error rate reduction of up to 25%.
Pandemic spread in communities via random graphs

Working in the multi-type Galton–Watson branching-process framework we analyse the spread of a pandemic via a general multi-type random contact graph. Our model consists of several communities, and takes, as input, parameters that outline the contacts between individuals in distinct communities. Given these parameters, we determine whether there will be an outbreak and if yes, we calculate the size of the giant-connected-component of the graph, thereby, determining the fraction of the population of each type that would be infected before it ends. We show that the pandemic spread has a natural evolution direction given by the Perron–Frobenius eigenvector of a matrix whose entries encode the average number of individuals of one type expected to be infected by an individual of another type. The corresponding eigenvalue is the basic reproduction number of the pandemic. We perform numerical simulations that compare homogeneous and heterogeneous spread graphs and quantify the difference between them. We elaborate on the difference between herd immunity and the end of the pandemic and the effect of countermeasures on the fraction of infected population.
Agglomerative Hierarchical Clustering for Selecting Valid Instrumental Variables

We propose a procedure, which combines hierarchical clustering with a test of overidentifying restrictions for selecting valid instrumental variables (IV) from a large set of IVs. Some of these may be invalid in that they fail the exclusion restriction. We show that if the largest group of IVs is valid, our method achieves oracle properties. Unlike existing techniques, our work deals with multiple endogenous regressors, weak instruments, heterogeneous effects and near validity. In simulations our procedure outperforms the Hard Thresholding and the Confidence Interval method. The method is applied to estimating the effect of immigration on wages and the return to education.
A comparative study of scoring systems by simulations

We study the trade-off between two risks for scoring rules used in sports competitions containing multiple contests: (1) the threat of early clinch when the title is clinched before the last contest(s) of the competition take place; and (2) the danger of winning the competition without finishing first in any contest. Four historical points scoring systems of the Formula One World Championship are compared with the family of geometric scoring rules. The current scheme seems to be a reasonable compromise close to the Pareto frontier. Our results contribute to the issue of choosing an optimal set of point values.