Miracle-dz/UniFAR-FTUs huggingface dataset:
Spectrum of sprite halos

[1] Spectra of sprite halos in the spectral ranges 200–500 nm and 640–1065 nm are calculated for different spectral resolutions (between 2 nm and 10 nm), rotational temperatures (220 K and 1000 K) and observation altitudes corresponding to mountain (3 km and 4.3 km), airplane (14 km), balloon (35 km) and space observation platforms. We have calculated the non-equilibrium vibrational distribution functions (VDF) of different excited electronic states of molecular nitrogen (N2) associated to sprite halo optical emissions in the ultraviolet (UV), due to the N2 Lyman-Birge-Hopfield (LBH) and Vegard-Kaplan (VK) band systems, and near UV, visible and near infrared (NIR) due to the first (1PG) and second positive (2PG) bands of N2. Comparison of synthetic sprite halo spectra with the single sprite halo spectrum existing to date shows reasonable agreement after the observed sprite halo spectra was corrected for instrument sensitivity response. Calculated VDFs of the N2(B3Πg) and N2(C3Πu) states of sprite halos show that the blue and NIR emissions produced through strong N2-1PG (B3Πg → A3Σu+) and N2-2PG (C3Πu → B3Πg) transitions are generally similar to those of known sprite spectral emission patterns, but differences may be observable at some vibrational levels. The calculated sprite halo spectra can be used as a predictive tool for the expected spectral emissions of sprite halos in different possible scenarios.
GAUSSIAN INFERENCE IN AR(1) TIME SERIES WITH OR WITHOUT A UNIT ROOT

This paper introduces a simple first-difference-based approach to estimation and inference for the AR(1) model. The estimates have virtually no finite-sample bias and are not sensitive to initial conditions, and the approach has the unusual advantage that a Gaussian central limit theory applies and is continuous as the autoregressive coefficient passes through unity with a uniform $\sqrt{n}$ rate of convergence. En route, a useful central limit theorem (CLT) for sample covariances of linear processes is given, following Phillips and Solo (1992, Annals of Statistics, 20, 971–1001). The approach also has useful extensions to dynamic panels.
Altered hemodynamic oscillations of resting-state networks in mesial temporal lobe epilepsy

Mesial-temporal lobe epilepsy (mTLE), a neurological disorder characterized by abnormal synchronous discharges in a large cell population, affects the hemodynamic activities of functional networks remote from the epileptogenic zone and causes widespread deficits in brain functions. Although a number of resting-state fMRI studies have found altered spatial patterns in the canonical resting-state networks (RSNs) in patients with mTLE, including the default mode network (DMN), dorsal lateral attention network (DAN), auditory network (AUN), somatosensory network (SMN) and visual network (VIN), none of these studies has addressed the question whether the frequencies of hemodynamic oscillations in these RSNs were altered. In the present study, we have proposed a network-based temporal clustering analysis (TCA) method to characterize the resting hemodynamic activity of a large-scale functional network. First, the RSNs were identified in healthy controls as well in the left mTLE patients using independent component analysis (ICA). Then, a time course representing the hemodynamic activity of each RSN was extracted by counting the number of the voxels that were activated simultaneously at each time point within the network. Finally, the power spectral density (PSD) of the time course was estimated. Our results have demonstrated significant differences in the frequency profiles of the SMN, VIN and left DAN between the patients and controls: the peaks of these spectra shifted toward a lower frequency in the patients, while more power was distributed over higher frequency bands in the healthy controls. However, no significant difference has been found in the AUN, DMN and right DAN. These features might serve as biomarkers to differentiate the patients from controls.
Nearby Spiral Globular Cluster Systems. I. Luminosity Functions

We compare the near-infrared (JHK) globular cluster luminosity functions (GCLFs) of the Milky Way, M31, and the Sculptor Group spiral galaxies. We obtained near-infrared photometry with the Persson's Auxiliary Nasmyth Infrared Camera on the Baade Telescope for 38 objects (mostly globular cluster candidates) in the Sculptor Group. We also have near-infrared photometry from the Two Micron All Sky Survey (2MASS)-6X database for 360 M31 globular cluster candidates and aperture photometry for 96 Milky Way globular cluster candidates from the 2MASS All-Sky and Second Incremental Release databases. The M31 6X GCLFs peak at absolute reddening-corrected magnitudes of M = -9.18, M = -9.73, and M = -9.98. The mean brightness of the Milky Way objects is consistent with that of M31 after accounting for incompleteness. The average Sculptor absolute magnitudes (correcting for relative distance from the literature and foreground reddening) are M = -9.18, M = -9.70, and M = -9.80. NGC 300 alone has absolute foreground-dereddened magnitudes M = -8.87, M = -9.39, and M = -9.46 using the newest Gieren et al. distance. This implies either that the NGC 300 GCLF may be intrinsically fainter than that of the larger galaxy M31 or that NGC 300 may be slightly farther away than previously thought. Straightforward application of our M31 GCLF results as a calibrator gives NGC 300 distance moduli of 26.68 ± 0.14 using J, 26.71 ± 0.14 using H, and 26.89 ± 0.14 using K.
Convective Dynamos with Penetration, Rotation, and Shear

We investigate the dynamo properties of Boussinesq, penetrative convection in the presence of rotation and large-scale velocity shear flows. Several numerical experiments are conducted in a local Cartesian computational domain in which the relative stability of the lower stable layer, the rotation rate, the supercriticality of the convection, and the strength of the imposed shear flow are varied. Once a statistically steady hydrodynamic state is achieved for any set of parameters, a weak seed magnetic field is added and the subsequent dynamo evolution is followed. In all cases studied, the weak seed field is initially amplified exponentially and then eventually saturates in a stationary magnetohydrodynamic (MHD) state. Even in the presence of penetration, rotation, and shear, the field is predominantly small-scale. We analyze the reasons for this and make suggestions as to possible further mechanisms that may lead to large-scale field generation.
Comparison of bias removal algorithms in track-to-track association

This paper compares the performance of several algorithms for estimating relative sensor biases when two sets of sensor tracks from two sensor systems are to be fused to form system tracks. The primary focus of this paper is the algorithms' performance, particularly in terms of the mean-square estimation error criterion. The efficiency of the algorithms is not our focus for this study. We are especially interested in three estimation algorithms: (1) the joint track-association/ relative-bias-estimation maximum a posteriori (MAP) probability-density/probability-mass function algorithm; (2) the marginal MAP probability density estimation algorithm; and (3) the minimum-variance (MV) estimation algorithm. Those algorithms rely on the capability of generating and evaluating multiple significant track-to-track association hypotheses, which may be obtained by any of the recently developed k-best bipartite data assignment algorithms. Several other algorithms that have been considered in the past will also be discussed.
On the accuracy and reliability of different fluid models of the direct current glow discharge

We developed and tested 2D “extended fluid model” of a dc glow discharge using COMSOL MULTIPHYSICS software and implemented two different approaches. First, assembling the model from COMSOL’s general form pde’s and, second, using COMSOL’s built-in Plasma Module. The discharge models are based on the fluid description of ions and excited neutral species and use drift-diffusion approximation for the particle fluxes. The electron transport as well as the rates of electron-induced plasma-chemical reactions are calculated using the Boltzmann equation for the EEDF and corresponding collision cross-sections. The self-consistent electric field is calculated from the Poisson equation. Basic discharge plasma properties such as current-voltage characteristics and electron and ion spatial density distributions as well as electron temperature and electric field profiles were studied. While the solutions obtained by two different COMSOL models are essentially identical, the discrepancy between COMSOL and CFD-ACE+ model.
Finding of Rigid Punch Shape and Optimal Contact Pressure Distribution#

The problem of contact pressure optimization is formulated for the case of rigid punch interacted with elastic medium. Coupling of the punch penetration and action of external loads at the outside regions is taken into account. The shape of the punch is considered as an unknown design variable. The minimized integral functional characterizes the discrepancy between the actual contact pressure and the required pressure distribution. The problem is studied under condition that the total forces and moments applied to the punch and the loads acted at the outside regions are given. It is shown that the considered optimization problem can be split and transformed to two successively solved problems. Optimal shapes are found analytically for the punches having rectangular contact domains.
The Behavior of Synoptic-Scale Errors in the Eta Model

Abstract A previous study of the mean spatial bias errors associated with operational forecast models motivated an examination of the mechanisms responsible for these biases. One hypothesis for the cause of these errors is that mobile synoptic-scale phenomena are partially responsible. This paper explores this hypothesis using 24-h forecasts from the operational Eta Model and an experimental version of the Eta run with Kain–Fritsch convection (EtaKF). For a sample of 44 well-defined upper-level short-wave troughs arriving on the west coast of the United States, 70% were underforecast (as measured by the 500-hPa geopotential height), a likely result of being undersampled by the observational network. For a different sample of 45 troughs that could be tracked easily across the country, consecutive model runs showed that the height errors associated with 44% of the troughs generally decreased in time, 11% increased in time, 18% had relatively steady errors, 2% were uninitialized entering the West Coast, and .
Whistlers observed by Voyager 1: Detection of lightning on Jupiter

During the Voyager 1 encounter with Jupiter a number of discrete signals were identified in the wideband plasma wave data with characteristics similar to whistlers generated by lightning. In this paper we show that the calculated whistler-mode travel times from Jupiter to the spacecraft are in good agreement with the measured dispersion characteristics, thereby confirming that the signals are caused by lightning on Jupiter and substantiating the Voyager 1 photographic evidence for lightning on Jupiter. A quantitative estimate of the north-south thickness of the Io plasma torus is also obtained from the measured whistler dispersion.
Plasma 0-Dimer as a Marker for Postoperative Deep Venous Thrombosis A Study after Total Hip or Knee Arthroplasty

Summary Plasma levels of D-dimer have been found useful as a marker of deep venous thrombosis in those patients in. whom thrombosis is sus pected, but their usefulness in postoperative screening is less clear. We have investigated the relationship of D-dimer to deep venous throm bosis in 90 patients after total hip and knee arthroplasty. From the first postoperative day the D-dimer levels were found to be highly significantly raised in patients with deep venous thrombosis. A combined result over the first six postoperative days in excess of 1200 ng/ml correlated with thrombosis with a specificity of 100%, sensitivity of 45%, positive predictive value of 60%, and negative predictive value of 100%. However, individual estimations were not discriminatory.
Investigation and Validation of Wind Turbine Wake Models

This article discusses the application of widely used, state of the art, wake models, focusing on the Ainslie [1], Katic [2] and Larsen [3] models, breaking these down and explaining the individual, integral components. Models used to predict the turbulence intensity within the wake are also explained. Measured data are subsequently used to validate these wake and turbulence models, showing acceptable results for the prediction of velocity deficit within the wake, wake width and wake shape. Results also highlight the validity of the analysed turbulence models. The paper describes the problems encountered when using measured data to validate wake models and concludes by outlining subsequent work which could be carried out to further validate these models.
A Bayesian Approach for Nonlinear Structural Equation Models With Dichotomous Variables Using Logit and Probit Links

Analysis of ordered binary and unordered binary data has received considerable attention in social and psychological research. This article introduces a Bayesian approach, which has several nice features in practical applications, for analyzing nonlinear structural equation models with dichotomous data. We demonstrate how to use the software WinBUGS and R2WinBUGS to obtain Bayesian estimates of the unknown parameters, estimates of latent variables, and the Deviance Information Criterion for model comparison. An illustrative example with an artificial data set is provided. Finally, simulation studies are conducted, not only to reveal the empirical performance of the Bayesian approach, but also to show that incorrectly treating binary data as ordinal, and vice versa, would produce misleading results.
Early Identification and Intervention in Pediatric Obsessive-Compulsive Disorder

Obsessive-compulsive disorder (OCD) is a psychiatric disorder characterized by persistent thoughts with subsequent repetitive behaviors. Interventions that are effective for adult OCD cannot simply be generalized to pediatric OCD, since OCD in children and adolescents usually has a different clinical presentation, etiology and course from adult OCD. Delayed and inadequate treatment is associated with a worse prognosis, making the need for early identification and intervention in pediatric OCD very urgent. In this paper, we reflected on the current constraints that make early interventions for pediatric OCD unpromoted and reviewed the approaches with potential application for early identification and early intervention in pediatric OCD, categorized by three-level prevention stages corresponding to a clinical staging model. Since the etiology of pediatric OCD is still unclear, primary prevention is most lacking, and early interventions for pediatric OCD are currently focused on the secondary prevention stage, which aims to prevent the conversion of obsessive-compulsive symptoms into full-blown OCD; tertiary prevention mostly focuses on the alleviation of mild to moderate OCD, while interventions for co-morbidities are still in their infancy. We closed by considering the important research questions on this topic.
Quantile estimation for a selected normal population

Suppose independent random sampls are drawn from k normal populations with unknown and possibly different means and variances. The pupulatioon. corresponding to the largest sample mean is selected as the best population. We consider estimation of quantiles of the selected population when the loss function is taken to he the squared error. Admissibility and inadmissibility of a natural estimator for the quantile is investigated in certain subclasses of linear and affine equivariant estimators.
Symmetric Squares, Spherical Designs, and Lattice Minima

1 Part of this work was done while the third author was visiting the Institute for Experimental Mathematics, University of Essen, Germany. It is a pleasure to thank the IEM for its generous hospitality and support. The authors are grateful to Professors J. G. Thompson and B. H. Gross for helpful discussions, and to Dr. G. Nebe for some computer calculation. They are also grateful to the referee for helpful comments on the paper.
Femtosecond Laser-Assisted Cataract Surgery versus Conventional Phacoemulsification Surgery: Clinical Outcomes with EDOF IOLs

In this study, we evaluate and compare the outcomes of conventional phacoemulsification cataract surgery (CPS) and femtosecond laser-assisted cataract surgery (FLACS) with the implantation of an extended depth of field (EDOF) intraocular lens (IOL). A prospective, consecutive cohort study was conducted. Patients were given the option to choose FLACS or CPS and were implanted with an EDOF IOL. Refractive data, visual acuity data, ocular aberration measured with a wavefront aberrometer, and optical quality measured with an optical quality analysis system II were collected at one month postoperatively. A total of 92 eyes of 64 patients were enrolled in this study; 35 eyes of 26 patients were treated with FLACS, whereas 57 eyes of 38 patients were treated with CPS. Uncorrected visual acuity at far, intermediate, and near distance and best-spectacle-corrected visual acuity were not statistically significantly different between the groups (all p > 0.05), nor were the mean cylinder and mean spherical equivalent refraction (both p > 0.05). The FLACS group had a lower ocular trefoil than the CPS group (p = 0.033), and there was no significant difference between the two groups considering other aberration parameters, whether ocular or internal (all p > 0.05). Optical-quality-related parameters showed also no significant difference between the two groups (all p > 0.05). In conclusion, there was no significant difference between FLACS and CPS with implantation of EDOF IOLs in postoperative ocular parameters, refractive outcomes, ocular aberration, optical quality, and aberration parameters, except a lower ocular trefoil in the FLACS group. In terms of these indicators, FLACS does not provide an additional clinical benefit for patients over CPS.
An Empirical Study Of Factors Influencing Hotel Customers' Online Booking Intention

Given the increasing amount of people who book hotels online, it is important for those in the industry to know which factors influence hotel customers’ online booking intention. Consequently, the aim of this study is to investigate the factors that influence the customer’s intention to book a hotel online, these factors are: ease of use, social influence, perceived risk, and positive eWOM. A self- administered questionnaire was used to gather data and measure respondents’ perceptions, and a total of 214 students at University Utara Malaysia completed the survey. This study used a multiple regression analysis to test the hypotheses. The results showed that social influence has a high positive significant influence on customer's intention to book a hotel online, followed by ease of use and positive eWOM. It was also found that perceived risk has a negative significant influence on the intention to book a hotel online. Based on the results, implications are presented for practitioners.
Allied intelligence reports on wartime German penicillin research and production

La production industrielle de la penicilline pendant la seconde guerre mondiale fut l'une des grandes reussites de la science et de la technologie anglo-americaine. Dans le meme temps, la tentative de production en masse de la penicilline par les allemands echoua. L'article reunit des documents provenant des deux agences de renseignements americaine et anglaise concernant cet echec et s'attache a presenter un historique de l'evolution de la production a grande echelle de la penicilline tout en discutant de la recherche scientifique allemande pendant la guerre.
Boosting the Initial Coulomb Efficiency of Sisal Fiber-Derived Carbon Anode for Sodium Ion Batteries by Microstructure Controlling

As anode material for sodium ion batteries (SIBs), biomass-derived hard carbon has attracted a great deal of attention from researchers because of its renewable nature and low cost. However, its application is greatly limited due to its low initial Coulomb efficiency (ICE). In this work, we employed a simple two-step method to prepare three different structures of hard carbon materials from sisal fibers and explored the structural effects on the ICE. It was determined that the obtained carbon material, with hollow and tubular structure (TSFC), exhibits the best electrochemical performance, with a high ICE of 76.7%, possessing a large layer spacing, a moderate specific surface area, and a hierarchical porous structure. In order to better understand the sodium storage behavior in this special structural material, exhaustive testing was performed. Combining the experimental and theoretical results, an “adsorption-intercalation” model for the sodium storage mechanism of the TSFC is proposed.
Towards a practicable Bayesian nonparametric density estimator

SUMMARY Nonparametric density estimators smooth the empirical distribution function and are sensitive to the choice of smoothing parameters. This paper develops an hierarchical Bayes formulation for the smoothing problem. The prior distribution for the density function is the logistic normal process, which is a logistic transform of a Gaussian process. The covariance of the Gaussian process is a smoothing kernel and has parameters that control the degree of smoothness. The likelihood function for the smoothing parameters and their posterior density are computed from an approximation of the joint moments of the logistic normal process. The marginal predictive density mixes the conditional predictive density given the smoothing parameters with their posterior distribution. This hierarchical Bayes analysis provides a fully automated, data-dependent method for smoothing and selects the amount of smoothing that is coherent with its prior specification. A Bayesian approach to nonparametric problems is to construct a probability distribution on the relevant space of distribution functions and to update this distribution as observations become available. Families of prior distributions must not only have stochastic properties that can adequately model prior information, but also must provide tractable models. The Dirichlet process (Ferguson, 1973) has been quite successful on both counts. However, it is not directly applicable to absolutely continuous distributions because the posterior probability of the space of absolutely continuous distributions is zero. Lo (1984) convolves the Dirichlet process with a smoothing kernel to model a density function. The computational complexity of the posterior mean increases exponentially with the sample size. An alternative to the Dirichlet model is provided by the logistic normal process