Miracle-dz/UniFAR-FTUs huggingface dataset:
An Efficient Shear Deformation Beam Theory Based on Neutral Surface Position for Bending and Free Vibration of Functionally Graded Beams#

In this article, an efficient shear deformation beam theory based on neutral surface position is developed for bending and frees vibration analysis of functionally graded beams. The theory accounts for hyperbolic distribution of the transverse shear strains and satisfies the zero traction boundary conditions on the surfaces of the beam without using shear correction factors. The neutral surface position for a functionally graded beam in which its material properties vary in the thickness direction is determined. Based on the present higher order shear deformation beam theory and the neutral surface concept, the equations of motion are derived from Hamilton's principle. The accuracy of the present solutions is verified by comparing the obtained results with the existing solutions. It can be concluded that the present theory is not only accurate but also simple in predicting the bending and vibration behavior of functionally graded beams.
Generalization Analysis for Contrastive Representation Learning

Recently, contrastive learning has found impressive success in advancing the state of the art in solving various machine learning tasks. However, the existing generalization analysis is very limited or even not meaningful. In particular, the existing generalization error bounds depend linearly on the number $k$ of negative examples while it was widely shown in practice that choosing a large $k$ is necessary to guarantee good generalization of contrastive learning in downstream tasks. In this paper, we establish novel generalization bounds for contrastive learning which do not depend on $k$, up to logarithmic terms. Our analysis uses structural results on empirical covering numbers and Rademacher complexities to exploit the Lipschitz continuity of loss functions. For self-bounding Lipschitz loss functions, we further improve our results by developing optimistic bounds which imply fast rates in a low noise condition. We apply our results to learning with both linear representation and nonlinear representation by deep neural networks, for both of which we derive Rademacher complexity bounds to get improved generalization bounds.
The characteristic rupture height of the mediating air film beneath an impacting drop on atomically smooth mica

Before a droplet can contact a surface during impact, it must first displace the air beneath it. Over a wide range of impact velocities, the air is compressed into a thin film, slowing the progress of the liquid toward the surface. Below a critical impact velocity, the air film remains intact; the droplet rebounds off of the air film without making contact. Above this critical impact velocity, the droplet always makes contact. The initiation of contact formation occurs via a topological transition, whereby the initially connected gas domain is ruptured, and a liquid capillary bridge forms, binding the droplet to the surface. Here we probe this transition in detail around the critical impact velocity using calibrated total internal reflection (TIR) microscopy to monitor the air film profile at high speed during the impact process. Two air film rupture modalities are observed: nucleated contacts, which are isolated and don't correspond to the global minimum air film thickness, and spontaneous contacts, that occur always on a ring centered upon the impact axis where the air film reaches its global minimum. Our measurements show that for impact velocities exceeding the critical velocity for contact initiation, the air film ruptures at a nearly identical height h min ~ 20 nm, for two fluids - silicone oil and a water glycerol mixture. The height and time duration of the air film prior to contact, analyzed for over 180 droplet impact experiments, are consistent with a linear instability driven by van der Waals forces. Impact events of water solution droplets show different statistics for contact nucleation than the silicon oil; nevertheless, a critical impact velocity above which contact always occurs is identified for both liquids.
Strong Depletion of 13C in CO Induced by Photolysis of CO2 in the Martian Atmosphere, Calculated by a Photochemical Model

The isotopic signature of atmospheric carbon offers a unique tracer for the history of the Martian atmosphere and the origin of organic matter on Mars. The photolysis of CO2 is known to induce strong isotopic fractionation of the carbon between CO2 and CO. However, its effects on the carbon isotopic compositions in the Martian atmosphere remain uncertain. Here, we develop a 1D photochemical model to consider the isotopic fractionation via photolysis of CO2, to estimate the vertical profiles of the carbon isotopic compositions of CO and CO2 in the Martian atmosphere. We find that CO is depleted in 13C compared with CO2 at each altitude, due to the fractionation via CO2 photolysis: the minimum value of the δ 13C in CO is about −170‰ under the standard eddy diffusion setting. This result supports the hypothesis that fractionated atmospheric CO is responsible for the production of the 13C-depleted organic carbon in the Martian sediments detected by the Curiosity Rover, through the conversion of CO into organic materials and their deposition on the surface. The photolysis and transport-induced fractionation of CO that we report here leads to a ∼15% decrease in the amount of inferred atmospheric loss when combined with the present-day fractionation of the atmosphere and previous studies of carbon escape to space. The fractionated isotopic composition of CO in the Martian atmosphere may be observed by ExoMars Trace Gas Orbiter and ground-based telescopes, and the escaping ion species produced by the fractionated carbon-bearing species may be detected by the Martian Moons eXploration mission in the future.
A Note on Estimating the Jöreskog-Yang Model for Latent Variable Interaction Using LISREL 8.3

Kenny and Judd (1984) developed a latent variable interaction model for observed variables centered around their population means. They estimated the model by using a covariance matrix calculated from sample-mean-centered variables and products of these variables. Subsequently,Jöreskog and Yang (1996) identified the need to include intercepts for the measurement and structural equations and estimated the model by using a covariance matrix calculated from noncentered observed variables and products of these variables, and means of the observed variables and the products of noncentered variables. Evidence is presented that the Jöreskog-Yang procedure for estimating the Kenny-Judd interaction model is subject to severe convergence problems when implemented in LISREL8.3 and means for the indicators of the latent exogenous variables are nonzero. An alternative procedure is presented that solves the convergence problem and provides consistent estimators of the parameters.
Rank-Based Causal Discovery for Post-Nonlinear Models

Learning causal relationships from empirical observations is a central task in scientific research. A common method is to employ structural causal models that postulate noisy functional relations among a set of interacting variables. To ensure unique identifiability of causal directions, researchers consider restricted subclasses of structural causal models. Post-nonlinear (PNL) causal models constitute one of the most flexible options for such restricted subclasses, containing in particular the popular additive noise models as a further subclass. However, learning PNL models is not well studied beyond the bivariate case. The existing methods learn non-linear functional relations by minimizing residual dependencies and subsequently test independence from residuals to determine causal orientations. However, these methods can be prone to overfitting and, thus, difficult to tune appropriately in practice. As an alternative, we propose a new approach for PNL causal discovery that uses rank-based methods to estimate the functional parameters. This new approach exploits natural invariances of PNL models and disentangles the estimation of the non-linear functions from the independence tests used to find causal orientations. We prove consistency of our method and validate our results in numerical experiments.
Spatial Bias for Attention-free Non-local Neural Networks

In this paper, we introduce the spatial bias to learn global knowledge without self-attention in convolutional neural networks. Owing to the limited receptive field, conventional convolutional neural networks suffer from learning long-range dependencies. Non-local neural networks have struggled to learn global knowledge, but unavoidably have too heavy a network design due to the self-attention operation. Therefore, we propose a fast and lightweight spatial bias that efficiently encodes global knowledge without self-attention on convolutional neural networks. Spatial bias is stacked on the feature map and convolved together to adjust the spatial structure of the convolutional features. Therefore, we learn the global knowledge on the convolution layer directly with very few additional resources. Our method is very fast and lightweight due to the attention-free non-local method while improving the performance of neural networks considerably. Compared to non-local neural networks, the spatial bias use about 10 times fewer parameters while achieving comparable performance with 1.6 ~ 3.3 times more throughput on a very little budget. Furthermore, the spatial bias can be used with conventional non-local neural networks to further improve the performance of the backbone model. We show that the spatial bias achieves competitive performance that improves the classification accuracy by +0.79% and +1.5% on ImageNet-1K and cifar100 datasets. Additionally, we validate our method on the MS-COCO and ADE20K datasets for downstream tasks involving object detection and semantic segmentation.
A New Incremental Fit Index for General Structural Equation Models

Assessing overall model fit is an important problem in general structural equation models. One of the most widely used fit measures is Bentler and Bonett's (1980) normed index. This article has three purposes: (1) to propose a new incremental fit measure that provides an adjustment to the normed index for sample size and degrees of freedom, (2) to explain the relation between this new fit measure and the other ones, and (3) to illustrate its properties with an empirical example and a Monte Carlo simulation. The simulation suggests that the mean of the sampling distribution of the new fit measure stays at about one for different sample sizes whereas that for the normed fit index increases with N. In addition, the standard deviation of the new measure is relatively low compared to some other measures (e.g., Tucker and Lewis's (1973) and Bentler and Bonett's (1980) nonnormed index). The empirical example suggests that the new fit measure is relatively stable for the same model in different samples. In sum, it appears that the new incremental measure is a useful complement to the existing fit measures.
Uniformly Conservative Exploration in Reinforcement Learning

A key challenge to deploying reinforcement learning in practice is avoiding excessive (harmful) exploration in individual episodes. We propose a natural constraint on exploration -- \textit{uniformly} outperforming a conservative policy (adaptively estimated from all data observed thus far), up to a per-episode exploration budget. We design a novel algorithm that uses a UCB reinforcement learning policy for exploration, but overrides it as needed to satisfy our exploration constraint with high probability. Importantly, to ensure unbiased exploration across the state space, our algorithm adaptively determines when to explore. We prove that our approach remains conservative while minimizing regret in the tabular setting. We experimentally validate our results on a sepsis treatment task and an HIV treatment task, demonstrating that our algorithm can learn while ensuring good performance compared to the baseline policy for every patient; the latter task also demonstrates that our approach extends to continuous state spaces via deep reinforcement learning.
Effect of space-charge limited emission on measurements of plasma potential using emissive probes

Effects of space-charge limitation have been considered for an analytical estimation of plasma potential with use of emissive probes, taking account of a correct expression of emission current under space-charge limited condition. The analytical results are obtained for the floating potential method of emissive probe and for the differential emissive probe method, both without and with an oscillating ac potential. In the case of the floating potential method, the operating condition is discussed for different plasma parameters at several probe temperatures. These results indicate that the floating potential of the emissive probe gives us the plasma potential to an accuracy of the order of the plasma electron temperature Te/e for a strong probe emission. In the case of the differential emissive probe method, the relations among space-charge effects, the ratio of thermoelectron emission current to plasma electron collection current, the plasma electron temperature, the probe temperature, and the amplitude o.
Axisymmetric annular curtain stability

A temporal stability analysis was carried out to investigate the stability of an axially moving viscous annular liquid jet subject to axisymmetric disturbances in surrounding co-flowing viscous gas media. We investigated in this study the effects of inertia, surface tension, the gas-to-liquid density ratio, the inner-to-outer radius ratio and the gas-to-liquid viscosity ratio on the stability of the jet. With an increase in inertia, the growth rate of the unstable disturbances is found to increase. The dominant (or most unstable) wavenumber decreases with increasing Reynolds number for larger values of the gas-to-liquid viscosity ratio. However, an opposite tendency for the most unstable wavenumber is predicted for small viscosity ratio in the same inertia range. The surrounding gas density, in the presence of viscosity, always reduces the growth rate, hence stabilizing the flow. There exists a critical value of the density ratio above which the flow becomes stable for very small viscosity ratio, whereas for large viscosity ratio, no stable flow appears in the same range of the density ratio. The curvature has a significant destabilizing effect on the thin annular jet, whereas for a relatively thick jet, the maximum growth rate decreases as the inner radius increases, irrespective of the surrounding gas viscosity. The degree of instability increases with Weber number for a relatively large viscosity ratio. In contrast, for small viscosity ratio, the growth rate exhibits a dramatic dependence on the surface tension. There is a small Weber number range, which depends on the viscosity ratio, where the flow is stable. The viscosity ratio always stabilizes the flow. However, the dominant wavenumber increases with increasing viscosity ratio. The range of unstable wavenumbers is affected only by the curvature effect.
Novel results on fluence dependence and annealing behavior of oxygenated and non-oxygenated silicon detectors

This work presents the latest results on electrical properties degradation of silicon radiation detectors manufactured at the Institut de Microelectronica de Barcelona (IMB-CNM) subjected to proton irradiation at CERN, Switzerland, for high-energy physics (HEP) applications. The evolution of full depletion voltage and leakage current with fluence as well as their annealing behavior with time were studied. The results obtained extend the previous understanding of the role played by technology and oxygenated material in hardening silicon radiation detectors.
TIME-SERIES ENSEMBLE PHOTOMETRY OF SX PHOENICIS STARS. II. AE URSAE MAJORIS

We have examined the short period, double-mode variable star AE Ursae Majoris. Using time series ensemble photometry we have determined six new times of maximum light. We also applied a Fourier decomposition to the data to determine the component frequencies of the light curve. Using our data, along with archival data, we find that the period of AE UMa is continually decreasing at a rate of -1.14x 10-10 d d-1 . However, from the Fourier decomposition we find that the period ratio P1/P0 has remained constant at 0.773. We also find that AE UMa is incorrectly classified as a SX Phoenicis star.
The multiplication formulas for the Apostol–Bernoulli and Apostol–Euler polynomials of higher order

This article obtains the multiplication formulas for the Apostol–Bernoulli and Apostol–Euler polynomials of higher order and deduces some explicit recursive formulas. The λ-multiple power sum and λ-multiple alternating sum that are clearly evaluated associated with the Apostol–Bernoulli and Apostol–Euler polynomials of higher order, respectively, are also introduced. Some earlier results of Carlitz and Howard can be deduced.
INVOLUTIONS ON KNOT GROUPS AND VARIETIES OF REPRESENTATIONS IN A LIE GROUP

We prove the existence of a rationalisation of a classical or high-dimensional knot group Π which admits an involution if the Alexander polynomials of the knot are reciprocal. Using the group and its involution, we study the local structure, in the neighbourhood of an abelian representation, of the space of representation of the knot group Π in a a Lie group. We apply these results to the groups of classical prime knots up to 10 crossings.
Rainfall Regime of a Mountainous Mediterranean Region: Statistical Analysis at Short Time Steps

AbstractThis paper presents an analysis of the rainfall regime of a Mediterranean mountainous region of southeastern France. The rainfall regime is studied on temporal scales from hourly to yearly using daily and hourly rain gauge data of 43 and 16 years, respectively. The domain is 200 × 200 km2 with spatial resolution of hourly and daily rain gauges of about 8 and 5 km, respectively. On average, yearly rainfall increases from about 0.5 m yr−1 in the large river plain close to the Mediterranean Sea to up to 2 m yr−1 over the surrounding mountain ridges. The seasonal distribution is also uneven: one-third of the cumulative rainfall occurs during the autumn season and one-fourth during the spring. At finer time scales, rainfall is studied in terms of rain–no-rain intermittency and nonzero intensity. The monthly intermittency (proportion of dry days per month) and the daily intermittency (proportion of dry hours per day) is fairly well correlated with the relief. The higher the rain gauges are, the lower th.
Aerodynamic droplet atomization model (ADAM)

Abstract The present work studies low viscosity twin-fluid atomization experimentally and analytically to characterize and predict the droplet size distribution of the spray. The study is based on experiments conducted using commercially available twin-fluid nozzles with water as the liquid. Shadowgraph images were used to visualize the near-nozzle flow while the droplet size distribution was measured in the far field using a Malvern Spraytec. To analytically model the atomization of the spray, the authors’ recent works on aerodynamic droplet breakup, which describe the formation and breakup of ligament and bag structures by multiple mechanisms, are extended to provide an analytical prediction of the droplet size distribution of the spray that is validated against the present experiments. The present model is developed to be a good physical representation of the spray behaviour at practical operating conditions. A Python implementation of the model has been deposited in a GitHub repository to accompany this work.
Home range and activity patterns of the Critically Endangered endemic pygmy raccoon of Cozumel Island, México

Individuals from island and continental mammal populations have shown a number of differences in their behavioral ecology. We predicted that, like other island carnivores exhibiting dwarfism, the pygmy raccoon (Procyon pygmaeus), a Critically Endangered carnivore endemic to Cozumel Island, México, would show differences in its home ranges and activity patterns when compared to its mainland counterpart, the racoon, P. lotor. We radio-tracked 11 individuals (six males, five females) from February to July 2017 and used location data derived from triangulation to estimate the home range size, diel activity patterns, and distances traveled of pygmy raccoons. Individuals showed an average home range size between 96.9 ± 18.8 ha (95% minimum convex polygon) and 123.3 ± 31.2 ha (95% fixed kernel). Home ranges of males (109.4–142.8 ha) were larger than those of females (81.8–99.9 ha). Average home ranges were in the lower extreme of those reported for continental raccoons. Activity patterns of pygmy raccoons generally begin at sunset and continue up to 04:00 with rare activity peaks during the day; there were no significant differences in activity patterns between sexes. Data on spatial needs of individuals, and differences between sexes or insular versus continental populations have implications for conservation planning and management. Individuos de especies insulares muestran diferencias en su ecología del comportamiento con respecto a sus especies hermanas continentales. Presumimos que el mapache pigmeo (Procyon pygmaeus), un carnívoro Críticamente Amenazado endémico de Isla Cozumel, México, mostraría, al igual que otros carnívoros insulares que presentan enanismo, diferencias en sus áreas de acción y patrones de actividad con respecto a su homólogo continental. Seguimos a 11 individuos (seis machos, cinco hembras) marcados con radiocollares desde febrero hasta julio 2017, y utilizamos los datos de posición derivados por triangulación para estimar el tamaño de sus áreas de acción, patrones diarios de actividad y distancias recorridas por los mapaches pigmeos. Los individuos mostraron un tamaño promedio del área de acción de 96.9 ± 18.8 ha (polígono convexo mínimo al 95%) y de 123.31 ± 31.20 ha (método de Kernel fijo al 95%); las áreas de acción de los machos (109.4–142.8 ha) fueron más grandes que la de las hembras (81.86–99.9 ha). El promedio del área de acción se encontró en el extremo inferior del promedio de las áreas de acción documentadas en mapaches continentales. El patrón de actividad de los mapaches pigmeos generalmente empieza al anochecer y sigue hasta las 04:00 horas, con raros aumentos en actividad diurna y diferencias no significativas entre sexos. La información sobre los requerimientos espaciales de los individuos, las diferencias entre sexos o con individuos de la contraparte continental tiene implicaciones relevantes para la planificación de la conservación y el manejo de la especie.