Miracle-dz/UniFAR-FTUs huggingface dataset:
The Finescale Structure of a West Texas Dryline

Abstract During spring and early summer, a surface confluence zone, often referred to as the dryline, forms in the midwestern United States between continental and maritime air masses. The dewpoint temperature across the dryline can vary in excess of 18°C in a distance of less than 10 km. The movement of the dryline varies diurnally with boundary layer growth over sloping terrain leading to an eastward apparent propagation of the dryline during the day and a westward advection or retrogression during the evening. In this study, we examine the finescale structure of a retrogressing, dryline using data taken by a Doppler lidar, a dual-channel radiometer, and serial rawinsonde ascents. While many previous studies were unable to accurately measure the vertical motions in the vicinity of the dryline, our lidar measurements suggest that the convergence at the dryline is intense with maximum vertical motions of ∼5 m s−1. The winds obtained from the Doppler lidar Measurements were combined with the equations of m.
Assessing Factors That Affect the Estimation of a Canopy’s Gap Fraction and Extinction Coefficient Using Discrete Airborne LiDAR Data

Gap fraction (<inline-formula> <tex-math notation="LaTeX">${p(\theta)}$ </tex-math></inline-formula>) and extinction coefficient (<inline-formula> <tex-math notation="LaTeX">$k$ </tex-math></inline-formula>) are critical variables to predict canopy structure parameters, such as the leaf area index (LAI). The discrete airborne LiDAR scanner (ALS) provides an entirely new method to estimate <inline-formula> <tex-math notation="LaTeX">${p(\theta)}$ </tex-math></inline-formula> and <inline-formula> <tex-math notation="LaTeX">$k$ </tex-math></inline-formula> of a canopy. However, it is widely recognized that estimating <inline-formula> <tex-math notation="LaTeX">${p(\theta)}$ </tex-math></inline-formula>, derived from the laser penetration index (LPI), and estimating <inline-formula> <tex-math notation="LaTeX">$k$ </tex-math></inline-formula>, are strongly influenced by the characteristics of the LiDAR sensor, observation geometry, and canopy properties. This study conducted a global sensitivity analysis to comprehensively assess the influences of factors deriving from the above three sources on <inline-formula> <tex-math notation="LaTeX">${p(\theta)}$ </tex-math></inline-formula> and <inline-formula> <tex-math notation="LaTeX">$k$ </tex-math></inline-formula>, using the point cloud data simulated by the computer simulation model. Also, the applicability of point cloud for estimating <inline-formula> <tex-math notation="LaTeX">${p(\theta)}$ </tex-math></inline-formula> and for estimating <inline-formula> <tex-math notation="LaTeX">$k$ </tex-math></inline-formula> using the normal vector reconstruction (NVR) method under different conditions was investigated. Results showed that the influence of explored factors on different LPIs of the canopy is dominated by some single factor, but the specific factors are LPI- and LAI-dependent. In contrast, the influences from explored factors on <inline-formula> <tex-math notation="LaTeX">$k$ </tex-math></inline-formula> showed an identical pattern across different support region sizes (SSRs) and leaf angular distribution types. The retrieved <inline-formula> <tex-math notation="LaTeX">$k$ </tex-math></inline-formula> was influenced by pulse density-related factors. The estimated <inline-formula> <tex-math notation="LaTeX">${p(\theta)}$ </tex-math></inline-formula> accuracy varied with the form of LPI and the range of LAI. The capability of successfully estimating <inline-formula> <tex-math notation="LaTeX">$k$ </tex-math></inline-formula> relied on the leaf angular distribution. The estimated <inline-formula> <tex-math notation="LaTeX">$k$ </tex-math></inline-formula> was influenced by the inherent target selection effect of LiDAR return, which requires further investigation.
Mathematical Analysis of Macroscopic Models for Slow Dense Granular Flow

In this dissertation we present analysis of macroscopic models for slow dense granular flow. Models are derived from plasticity theory with yield condition and flow rule. Corner stone equations are conservation of mass and conservation of momentum with special constitutive law. Such models are considered in the class of generalised Newtonian fluids, where viscosity depends on the pressure and modulo of the strain-rate tensor. We showed the hyperbolic nature for the evolutionary model in 1D and ill-posed behaviour for 2D and 3D. The steady state equations are always hyperbolic. In the 2D problem we derived a prototype nonlinear backward parabolic equation for the velocity and the similar equation for the shear-rate. Analysis of derived PDE showed the finite blow up time. Blow up time depends on the initial condition. Full 2D and antiplane 3D model were investigated numerically with finite element method. For 2D model we showed the presence of boundary layers. Antiplane 3D model was investigated with the Runge Kutta Discontinuous Galerkin method with mesh addoption. Numerical results confirmed that such a numerical method can be a good choice for the simulations of the slow dense granular flow.
Evolution of Raindrop Spectra. Part I: Solution to the Stochastic Collection/Breakup Equation Using the Method of Moments.

Abstract We present a solution to the stochastic collection/breakup equation (SCE/SBE) using our recently developed method of moments and the Low and List fragment distribution function. We prove that the collisional breakup equation conserves overall mass irrespective of the degree to which the fragment distribution function conserves mass for individual collisions. The method is compared with analytical solutions to the steady state collection/breakup equation, as well as with the breakup equation, for simple kernels. The proposed method produces better approximations to the analytical solutions for simple kernels, than those obtained using a single moment method. In writing the breakup terms, an approximation to the breakup kernel and fragment distribution function in discrete categories is used. This approach allows one to write the algorithm without prescribing the shape of the distribution function within the category. The approximation to the fragment distribution function in a discrete category is.
Comparison of Drop Size Distribution Measurements by Impact and Optical Disdrometers

Abstract Simultaneous observations made with optical- and impact-type disdrometers were analyzed to broaden knowledge of these instruments. These observations were designed to test how accurately they measure drop size distributions (DSDs). The instruments' use in determining radar rainfall relations such as that between reflectivity and rainfall rate also was analyzed. A unique set of instruments, including two video and one Joss–Waldvogel disdrometer along with eight tipping-bucket rain gauges, was operated within a small area of about 100 × 50 m2 during a 2-month-long field campaign in central Florida. The disdrometers were evaluated by comparing their rain totals with the rain gauges. Both disdrometers underestimated the rain totals, but the video disdrometers had higher readings, resulting in a better agreement with the gauges. The disdrometers underreported small- to medium-size drops, which most likely caused the underestimation of rain totals. However, more medium-size drops were measured by the v.
Objective Priors for Model Selection in One-Way Random Eects Models

It is broadly accepted that the Bayes factor is a key tool in model selection. Nevertheless, it is an important, dicult and still open question which priors should be used to develop objective (or default) Bayes factors. We consider this problem in the context of the one-way random eects model. Arguments based on concepts like orthogonality, matching predictive, and invariance are used to justify a specific form of the priors, in which the (proper) prior for the new parameter (using Jereys’ terminology) has to be determined. Two dierent proposals for this proper prior have been derived: the intrinsic priors and the divergence based priors, a recently proposed methodology. It will be seen that the divergence based priors produce consistent Bayes factors. The methods are illustrated on examples and compared with other proposals. Finally, the divergence based priors and the associated Bayes factor are derived for the unbalanced case.
A note on Woodrucondence intervals for quantiles

Woodru� (1952) proposed a simple condence interval for quantiles in complex surveys based upon inverting the usual condence intervals for the distribution function. In the moderate to extreme tail regions of the distribution function the usual condence interval performs poorly for moderate sample size. In this paper we demonstrate that despite this fact, the Woodruintervals based upon inverting these badly behaved intervals perform very well. We go on to explain this rather surprising fact. c 2001 Elsevier Science B.V. All rights reserved
THERMAL ANALYSIS OF CHARRING MATERIALS BASED ON PYROLYSIS INTERFACE MODEL

Charring thermal protection systems have been used to protect hypersonic vehicles from high heat loads. The pyrolysis of charring materials is a complicated physical and chemical phenomenon. Based on the pyrolysis interface model, a simulating approach for charring ablation has been designed in order to obtain one dimensional transient thermal behavior of homogeneous charring materials in reentry capsules. As the numerical results indicate, the pyrolysis rate and the surface temperature under a given heat flux rise abruptly in the beginning, then reach a plateau, but the temperature at the bottom rises very slowly to prevent the structural materials from being heated seriously. Pyrolysis mechanism can play an important role in thermal protection systems subjected to serious aerodynamic heat.
Single Image Dehazing via Fusion of Multilevel Attention Network for Vision-Based Measurement Applications

Nowadays, researchers use vision-based measurement tools to record, detect, and monitor an atmospheric phenomenon called haze. It impedes the proper functioning of many outdoor industrial systems, such as autonomous driving, surveillance, satellite imagery, and so on. Conventional visibility restoration methods cannot accurately recover image quality due to inaccurate estimations of haze thickness and the presence of color-cast effects. Deep neural networks are evolving due to their ability to directly dehaze images from hazy scenes. Therefore, a unique attention-based end-to-end dehazing network named oval-net has been proposed in this study to restore clear images from its counterpart without employing the atmospheric scattering model. The oval-net is an encoder–decoder architecture that uses spatial and channel attention at each stage to focus on dominant and significant information while avoiding the transmission of irrelevant information from the encoder to the decoder, allowing quicker convergence. The proposed approach outperforms seven state-of-the-art algorithms in quantitative and qualitative assessments of a variety of synthetic and real-world hazy images, proving its effectiveness for vision-based industrial systems.
EFFECTS OF FOOTWEAR VARIATIONS ON THREE-DIMENSIONAL KINEMATICS AND TIBIAL ACCELERATIONS OF SPECIFIC MOVEMENTS IN AMERICAN FOOTBALL

American football is associated with a high rate of non-contact chronic injuries. Players are able to select from both high and low cut footwear. The aim of the current investigation was to examine the influence of high and low cut American football specific footwear on tibial accelerations and three-dimensional (3D) kinematics during three sport specific movements. Twelve male American football players performed three movements, run, cut and vertical jump whilst wearing both low and high cut footwear. 3D kinematics of the lower extremities were measured using an eight-camera motion analysis system alongside tibial acceleration parameters which were obtained using a shank mounted accelerometer. Tibial acceleration and 3D kinematic differences between the different footwear were examined using either repeated measures or Friedman’s ANOVA. Tibial accelerations were significantly greater in the low cut footwear in comparison to the high cut footwear for the run and cut movements. In addition, peak ankle eversion and tibial internal rotation parameters were shown to be significantly greater in the low cut footwear in the running and cutting movement conditions. The current study indicates that the utilization of low cut American football footwear for training/performance may place American footballers at increased risk from chronic injuries.
Estimating Effective Leaf Area Index of Winter Wheat Based on UAV Point Cloud Data

Leaf area index (LAI) is a widely used plant biophysical parameter required for modelling plant photosynthesis and crop yield estimation. UAV remote sensing plays an increasingly important role in providing the data source needed for LAI extraction. This study proposed a UAV-derived 3-D point cloud-based method to automatically calculate crop-effective LAI (LAIe). In this method, the 3-D winter wheat point cloud data filtered out of bare ground points was projected onto a hemisphere, and then the gap fraction was calculated through the hemispherical image obtained by projecting the sphere onto a plane. A single-angle inversion method and a multi-angle inversion method were used, respectively, to calculate the LAIe through the gap fraction. The results show a good linear correlation between the calculated LAIe and the field LAIe measured by the digital hemispherical photography method. In particular, the multi-angle inversion method of stereographic projection achieved the highest accuracy, with an R2 of 0.63. The method presented in this paper performs well in LAIe estimation of the main leaf development stages of the winter wheat growth cycle. It offers an effective means for mapping crop LAIe without the need for reference data, which saves time and cost.
SOMMERFELD RADIATION CONDITION FOR INCOMPRESSIBLE VISCOUS FLOWS

This paper investigates the methods of determining the convective velocity of the Sommerfeld radiation condition for incompressible Navier-Stokes equations in primitive variables. The Sommerfeld radiation condition for incompressible flows is a one-dimensional convective equation and has been widely used for outflow boundary condition of spatial developing flows. The definition of its convective velocity is unclear and the selection of appropriate value for the convective velocity is a critical issue. Four decision methods of the convective velocity with finite difference method are considered: the mean velocity over the exit boundary, the arithmetic mean velocity of the maximum and the minimum velocities on the outflow boundary, the local instantaneous velocity, and the numerically evaluated convective velocity which is modified procedure of Orlanski's open boundary condition. These methods are applied to two test problems for comparison. The first case is two Lamb dipoles traveling in a slow uniform flow. The second case is a two-dimensional impulsively starting jet flow. The numerical evaluated convective velocity produces minimum distortion and deformation of a vortex and provides no reflection.
Background Noise Levels and Reverberation Times in Old and New Elementary School Classrooms

The adequacy of the acoustic environment of classrooms is an important factor in a child’s ability to listen and learn. Undesirable noise and reverberation can affect the achievement and educational performance of children, both those with normal and impaired hearing. The purpose of this study was to evaluate the acoustical conditions of old and new elementary school classrooms. Results were compared to the American National Standards Institute standard for acoustical characteristics of classrooms (ANSI S12.60-2002). Results indicated that neither new nor old classrooms for children with normal hearing were in compliance with the ANSI classroom background noise standard but all classrooms met the minimum reverberation criteria.
A CLASS OF SEMIPARAMETRIC ORDINARY RIDGE ESTIMATORS OF REGRESSION COEFFICIENTS

In this article, a class of easy-to-implement semiparametric ordinary ridge estimators of regression coefficients is introduced. Their properties are investigated and simulation results are provided to investigate their behaviors when the error variances are small and relatively large, respectively. The semiparametric estimators outperform the Hoerl, Kennard and Baldwin (1975) estimator in the sense that they give less risk (total mean squared error). An empirical application is also presented.
UKF-based adaptive variable structure observer for vehicle sideslip with dynamic correction

Knowing vehicle sideslip angle is important and useful in various vehicle active safety applications. However, equipment which could directly measure sideslip angle is usually too expensive for industrial applications, so a reliable, affordable sideslip angle observer is necessary. Model-based observer is affected by the model uncertainty, non-linearity and the road friction inaccuracy. Sensor-based observer might be easily affected by the sensor noise and the bias induced by the road micro-uneven. Thus, an unscented Kalman filter (UKF)-based adaptive variable structural observer with dynamic correction (AUKF) for vehicle body sideslip angle is brought forward in this study. First, an UKF observer with adaptive parameters is used to compensate the model uncertainty. Then, a sensor-based observer is applied to realise a variable structure observer to compensate the estimation error in the highly non-linear region. A pseudointegral method and a zero point reset method are adopted to dynamically correct the bias drift problem in the integral. Both simulations and real vehicle tests validated the proposed approach. The accurate vehicle sideslip angle is measured by a differential global positioning system. Results show that the proposed approach has better performance compared with traditional UKF method, and makes a good foundation for stability control.
Unraveling the Host Genetic Background Effect on Internal Organ Weight Influenced by Obesity and Diabetes Using Collaborative Cross Mice

Type 2 diabetes mellitus (T2DM) is a severe chronic epidemic that results from the body’s improper usage of the hormone insulin. Globally, 700 million people are expected to have received a diabetes diagnosis by 2045, according to the International Diabetes Federation (IDF). Cancer and macro- and microvascular illnesses are only a few immediate and long-term issues it could lead to. T2DM accelerates the effect of organ weights by triggering a hyperinflammatory response in the body’s organs, inhibiting tissue repair and resolving inflammation. Understanding how genetic variation translates into different clinical presentations may highlight the mechanisms through which dietary elements may initiate or accelerate inflammatory disease processes and suggest potential disease-prevention techniques. To address the host genetic background effect on the organ weight by utilizing the newly developed mouse model, the Collaborative Cross mice (CC). The study was conducted on 207 genetically different CC mice from 8 CC lines of both sexes. The experiment started with 8-week-old mice for 12 weeks. During this period, one group maintained a standard chow diet (CHD), while the other group maintained a high-fat diet (HFD). In addition, body weight was recorded bi-weekly, and at the end of the study, a glucose tolerance test, as well as tissue collection (liver, spleen, heart), were conducted. Our study observed a strong effect of HFD on blood glucose clearance among different CC lines. The HFD decreased the blood glucose clearance displayed by the significant Area Under Curve (AUC) values in both populations. In addition, variation in body weight changes among the different CC lines in response to HFD. The female liver weight significantly increased compared to males in the overall population when exposed to HFD. Moreover, males showed higher heritability values than females on the same diet. Regardless of the dietary challenge, the liver weight in the overall male population correlated positively with the final body weight. The liver weight results revealed that three different CC lines perform well under classification models. The regression results also varied among organs. Accordingly, the differences among these lines correspond to the genetic variance, and we suspect that some genetic factors invoke different body responses to HFD. Further investigations, such as quantitative trait loci (QTL) analysis and genomic studies, could find these genetic elements. These findings would prove critical factors for developing personalized medicine, as they could indicate future body responses to numerous situations early, thus preventing the development of complex diseases.
Functional connectome fingerprinting across the lifespan

Abstract Systematic changes have been observed in the functional architecture of the human brain with advancing age. However, functional connectivity (FC) is also a powerful feature to detect unique “connectome fingerprints,” allowing identification of individuals among their peers. Although fingerprinting has been robustly observed in samples of young adults, the reliability of this approach has not been demonstrated across the lifespan. We applied the fingerprinting framework to the Cambridge Centre for Ageing and Neuroscience cohort (n = 483 aged 18 to 89 years). We found that individuals are “fingerprintable” (i.e., identifiable) across independent functional MRI scans throughout the lifespan. We observed a U-shape distribution in the strength of “self-identifiability” (within-individual correlation across modalities), and “others-identifiability” (between-individual correlation across modalities), with a decrease from early adulthood into middle age, before improving in older age. FC edges contributing to self-identifiability were not restricted to specific brain networks and were different between individuals across the lifespan sample. Self-identifiability was additionally associated with regional brain volume. These findings indicate that individual participant-level identification is preserved across the lifespan despite the fact that its components are changing nonlinearly.
A Theoretical Study of Hydrogen Abstraction Reactions in Guanosine and Uridine

All practically possible hydrogen abstraction reactions for guanosine and uridine have been investigated through quantum chemical calculations of energy barriers and rate constants. This was done at the level of density functional theory (DFT) with the ωB97X-D functional and the 6-311++G(2df,2pd) Pople basis set. Transition state theory with the Eckart tunneling correction was used to calculate the rate constants. The results show that the reaction involving the hydrogen labelled C4’ in the ribofuranose part has the largest rate constant for guanosine with the value 5.097×1010 L mol−1s−1 and the largest for uridine with the value 1.62×1010 L mol−1s−1. Based on the results for these two nucleosides, there is a noticeable similarity between the rate constants in the ribofuranose part of the molecule, even though they are bound to two entirely different nucleobases.