Miracle-dz/UniFAR-FTUs huggingface dataset:
A novel model of gestational diabetes: Acute high fat high sugar diet results in insulin resistance and beta cell dysfunction during pregnancy in mice

Gestational diabetes mellitus (GDM) affects 7–18% of all pregnancies. Despite its high prevalence, there is no widely accepted animal model. To address this, we recently developed a mouse model of GDM. The goal of this work was to further characterize this animal model by assessing insulin resistance and beta cell function. Mice were randomly assigned to either control (CD) or high fat, high sugar (HFHS) diet and mated 1 week later. At day 0 (day of mating) mice were fasted and intraperitoneal insulin tolerance tests (ipITT) were performed. Mice were then euthanized and pancreata were collected for histological analysis. Euglycemic hyperinsulinemic clamp experiments were performed on day 13.5 of pregnancy to assess insulin resistance. Beta cell function was assessed by glucose stimulated insulin secretion (GSIS) assay performed on day 0, 13.5 and 17.5 of pregnancy. At day 0, insulin tolerance and beta cell numbers were not different. At day 13.5, glucose infusion and disposal rates were significantly decreased (p<0.05) in Pregnant (P) HFHS animals (p<0.05) suggesting development of insulin resistance in P HFHS dams. Placental and fetal glucose uptake was significantly increased (p<0.01) in P HFHS dams at day 13.5 of pregnancy and by day 17.5 of pregnancy fetal weights were increased (p<0.05) in P HFHS dams compared to P CD dams. Basal and secreted insulin levels were increased in HFHS fed females at day 0, however at day 13.5 and 17.5 GSIS was decreased (p<0.05) in P HFHS dams. In conclusion, this animal model results in insulin resistance and beta cell dysfunction by mid-pregnancy further validating its relevance in studying the pathophysiology GDM.
Empirically Constrained Color-Temperature Relations. I. BV(RI)C

This investigation presents a set of transformations to Johnson B-V, Cousins V-R, and Cousins V-I, as well as bolometric corrections to V, for [Fe/H] = -3, -2, -1, -0.5, 0.0, and +0.3 and, in each case, values of log g from -0.5 to 5.0 for 3000 K ≤ Teff ≤ 5500 K and from 2.0 to 5.0 for 6000 K ≤ Teff ≤ 40,000 K. These transformations employ the predictions from Kurucz model atmospheres at high temperatures (Teff ≥ 8000 K) and from MARCS model atmospheres at intermediate temperatures (from 7000 K down to a temperature in the range 4000 K ≤ Teff ≤ 5500 K, depending on [Fe/H], where adjustments to satisfy observational constraints become necessary). Thus, theoretical color-Teff relations are used exclusively down to a minimum temperature that is cooler than the temperatures of turnoff stars in open and globular star clusters. To better represent the color transformations obeyed by cool stars (down to 3000 K), corrections to the synthetic transformations have been determined from a careful consideration of observations for a few globular clusters (M92, M68, and 47 Tucanae), the color-magnitude diagrams (CMDs) of several open clusters (M67, the Pleiades, the Hyades, and NGC 6791), the CMDs and mass-luminosity diagram for solar neighborhood stars having good distance measurements from Hipparcos, empirical (B-V)-Teff and (V-K)-Teff relations, and color-color diagrams for field giants. The semiempirical color transformations that have been produced as a result of our analysis are also compared with several others that have been published in recent years: some of the deficiencies of the latter are revealed.
An Improved Method of Training Overcomplete Dictionary Pair

Training overcomplete dictionary pair is a critical step of the mainstream superresolution methods. For the high time complexity and susceptible to corruption characteristics of training dictionary, an improved method based on lifting wavelet transform and robust principal component analysis is reported. The high-frequency components of example images are estimated through wavelet coefficients of 3-tier lifting wavelet transform decomposition. Sparse coefficients are similar in multiframe images. Accordingly, the inexact augmented Lagrange multiplier method is employed to achieve robust principal component analysis in the process of imposing global constraints. Experiments reveal that the new algorithm not only reduces the time complexity preserving the clarity but also improves the robustness for the corrupted example images.
Transducer-Shadow Effects on Turbulence Spectra Measured by Sonic Anemometers

Abstract We show that the horizontal turbulent velocity components measured by the common sonic anemometer array can suffer attenuation and crosstalk as a result of the flow blockage caused by the acoustic transducer assemblies. Using an analytical model of this “transducer-shadow effect”, flow-blockage data from test arrays, and a simple linear model of the fluctuating response, we show the nature of the distortion in the measured velocity spectra. We suggest that rather than correct for the shadow effect, which ran be quite significant for horizontal velocity spectra and stress cospectra, it would be preferable to minimize it through design. There is encouraging evidence that the Kaijo-Denki transducer design produces much less shadow effect than the conventional (right circular cylinder) shape.
Sodium‐ion pickup observed above the magnetopause during MESSENGER's first Mercury flyby: Constraints on neutral exospheric models

Single‐particle tracings of sodium pickup ions launched upstream of Mercury's magnetopause are used to investigate the access of these ions to the magnetosphere and set limits on the distribution of neutral sodium about the planet during the first MESSENGER flyby. The transport of pickup ions is modeled using flow velocity and magnetic fields from a three‐dimensional magnetohydrodynamic simulation. Extensive penetration of pickup ions into the magnetosphere is found in the post‐noon and dusk local time sectors due to the northward interplanetary magnetic field at the time of MESSENGER's first flyby. It is concluded that: (1) pickup of magnetosheath photoions may be an important source of hot planetary ions within the magnetosphere; and (2) the sodium ions in the magnetosheath observed by MESSENGER must originate from an extended neutral exosphere due to ion sputtering and/or to a partially escaping distribution generated by photon‐stimulated desorption with yields modified by regolith trapping.
Supervised linear dimensionality reduction with robust margins for object recognition

Linear Dimensionality Reduction (LDR) techniques have been increasingly important in computer vision and pattern recognition since they permit a relatively simple mapping of data onto a lower dimensional subspace, leading to simple and computationally efficient classification strategies. Recently, many linear discriminant methods have been developed in order to reduce the dimensionality of visual data and to enhance the discrimination between different groups or classes. Many existing linear embedding techniques relied on the use of local margins in order to get a good discrimination performance. However, dealing with outliers and within-class diversity has not been addressed by margin-based embedding method. In this paper, we explored the use of different margin-based linear embedding methods. More precisely, we propose to use the concepts of Median miss and Median hit for building robust margin-based criteria. Based on such margins, we seek the projection directions (linear embedding) such that the sum of local margins is maximized. Our proposed approach has been applied to the problem of appearance-based face recognition. Experiments performed on four public face databases show that the proposed approach can give better generalization performance than the classic Average Neighborhood Margin Maximization (ANMM). Moreover, thanks to the use of robust margins, the proposed method down-grades gracefully when label outliers contaminate the training data set. In particular, we show that the concept of Median hit was crucial in order to get robust performance in the presence of outliers.
Efficient solution of a Toeplitz-plus-Hankel coefficient matrix system of equations

There are well-known fast algorithms, such as the Levinson recursion, for solving linear equations with a Toeplitz (or Hankel) coefficient matrix. This paper extends the saving obtained by the Levinson recursion for inversion of a Toeplitz matrix to problems involving the inversion of matrices which are the sum of Toeplitz and Hankel matrices.
A scanning surface plasmon resonance sensor based on the phase shift algorithm

A novel surface plasmon resonance setup is introduced in this paper. By applying a galvo scanner to modulate the incident beam, the interference noise caused by the coherent light source and mismatching optical interfaces can be reduced significantly and a wide measurement range can be acquired meanwhile. In order to calculate the tiny shift of the resonance angle, a new algorithm called the phase shift algorithm based on discrete Fourier transform is proposed. The method measures the angle shift by detecting the signal phase shift in the frequency domain. According to the simulation and experimental results, this method has better resolution, good immunity of light source drift and fast computation speed. The experimental results demonstrate that a resolution of 1.8 × 10−6 RIU (3 standard derivations) is finally acquired with a measurement range from 1.33 to 1.385. It suggests a good potential value in small molecule interaction detection.
Plasma Edge Turbulence

Model mode-coupling equations for the resistive drift-wave instability are derived and numerically solved to study the properties of turbulence near a plasma edge. The wave-number spectrum of the turbulence is found to exhibit an inverse cascade to form an iso- tropic, two-dimensional Kolmogorov spectrum, k/sup -3/, in the large--wave-number regime. The turbulence has a broad frequency spectrum with a large saturation level and produces Bohm-type particle diffusion.
An on-line fiber drawing tension and diameter measurement device

A noncontact online drawing tension meter is described. This meter measures both the drawing tension and fiber diameter during the fiber drawing process. Experimental results show that this meter functions satisfactorily in all aspects of testing. The knowledge of online drawing tension not only helps in the manufacture of fibers with low surface tensile stress, but it also gives information about furnace temperature change and the viscosity of the glass at the neck-down region. >
A Nonparametric Version of the Bartlett-Nanda-Pillai Multivariate Test. Asymptotics, Approximations, and Applications

SYNOPTIC ABSTRACT We consider a nonparametric version of the Bartlett-Nanda-Pillai multivariate test that has been introduced in Bathke and Harrar (2008) in the asymptotic context of a large number of treatments and small sample sizes per treatment (large a, small n). The test is based on separate rankings for the different variables. Here, we derive its asymptotic distribution for large ni and small a. Also, two small sample approximations are presented, and their performance is investigated in a simulation study. In the presence of outliers, the proposed nonparametric version shows far superior power than the parametric Bartlett-Nanda-Pillai test. Similar to the parametric case, there is no clear ordering when comparing the nonparametric versions of Bartlett-Nanda-Pillai, Lawley-Hotelling, and ANOVA type test. We show how to apply the test in practice, using SAS. The application is demonstrated with two different data sets conforming to the two different asymptotic frameworks, large a and large ni respectively.
Pulsations in the atmosphere of the rapidly oscillating star 33 Lib

In 2009, the rapidly oscillating peculiar A-type (roAp) star 33 Lib was the target of an intense observing campaign, combining ground-based spectroscopy with space photometry obtained with the Microvariability and Oscillation of STars (MOST) satellite. We collected 780 spectra using the Echelle Spectro Polarimetric Device for the Observation of Stars (ESPaDOnS) spectrograph attached at the 3.6-m Canada–France–Hawaii Telescope and 374 spectra with the Fibre-fed Echelle Spectrograph attached at the 2.56-m Nordic Optical Telescope to perform time-resolved spectroscopy of 33 Lib. In addition, we used 111 Ultraviolet and Visual Echelle Spectrograph (UVES) spectra (2004) from the European Southern Observatory archive to check mode stability. Frequency analysis of the new radial velocity (RV) measurements confirms the previously reported frequency pattern (two frequencies and the first harmonic of the main one) and reveals an additional frequency at 1.991 mHz. The new frequency solution perfectly reproduces the RV variations from the 2004 and 2009 observational sets, providing strong support for p mode stability in this roAp star over at least 5 years.
The New Millennium separated spacecraft interferometer

Spaceborne optical interferometry has been identified as a critical technology for many of NASA’s 21st century science visions. Included in the visions are interferometers that can probe the origins of stars and galaxies, and can ultimately study Earth-like planets around nearby stars. To accomplish this feat, separation of an interferometer’s small collecting apertures by large baselines are required-hundreds of meters up to thousands of kilometers. Thus the large separations require multiple spacecraft formation flying. Furthermore, optical pathlengths over these distances must be controlled to the nanometer level. This level of control demands tightly coupled spacecraft controls, active optics, metrology, and starlight detection technologies. To date, these technologies have been demonstrated only in ground applications with baselines of order of a hundred meters; space operation will require a significant capability enhancement. This paper describes the New Millennium separated spacecraft optical inte.
Ultrafast carrier dynamics in pentacene, functionalized pentacene, tetracene, and rubrene single crystals

We measure the transient photoconductivity in pentacene, functionalized pentacene, tetracene, and rubrene single crystals using optical pump-terahertz probe techniques. In all of the samples studied, we observe subpicosecond charge photogeneration and a peak photoconductive response that increases as the temperature decreases from 297 down to 20K, indicative of bandlike transport. Similar decay dynamics are observed at room temperature, but at low temperatures the decay dynamics measured in pentacene, rubrene, and tetracene crystals are much faster than those observed in functionalized pentacene crystals, revealing different charge trapping properties.
Adaptive-weight iterative algorithm for flat-top laser beam shaping

An adaptive-weight fast-Fourier-transform-based iterative algorithm is proposed for far-field flat-top beam shaping. This algorithm inherits the projection optimization idea from the Gerchberg-Saxton algorithm, but the far-field amplitude for inverse fast Fourier transform is adaptively modified by using a novel optimized adaptive-weight strategy. First, the application of this method to square flat-top intensity-profile beam shaping is discussed as an example. The pure-phase distribution simulated by 100 iterations of this method concentrates 93.89% of the incident laser energy into the desired region and the root mean square error (RMSE) of the tailored flat-top intensity profile is 0.0094. Less than 20 iterations of this method concentrate more than 90% of the incident laser energy into the desired region and the RMSE of the tailored flat-top intensity profile is under 0.05. Then, the applicability of the method to designing the phase distributions for variable-shape or variable-diameter flat-top beam shaping is demonstrated.
Fractional order adaptive controller for stabilised systems via high-gain feedback

Controllers based on fractional order calculus are gaining more and more interests from the control community. This type of controllers may involve fractional integration, fractional differentiation and/or fractional systems in their structure or implementation. They have been introduced in the control applications in a continuous effort to enhance the system control quality performances and robustness. In this study, a new scheme of fractional order adaptive controller via high-gain output feedback for a class of linear, time-invariant, minimum phase and single input-single output systems of relative degree one is proposed. The basic idea of the new design is a further modification in the adaptive proportional control law by the introduction of a fractional integration besides of the regular one of the squared output of the system in the adaptation gain of the control strategy. An analytical stability proof of the feedback control system is presented. The control quality enhancement of the proposed control scheme compared with the classical one has been presented through the simulation results of an illustrative example.
PARTIAL EIGENSTRUCTURE ASSIGNMENT FOR THE QUADRATIC PENCIL

Abstract It is shown in this paper that, by the appropriate choice of gain and input influence matrices, certain eigenpairs of a vibrating system may be assigned while the other eigenpairs remain unchanged. The system under consideration is modelled by a set of second order differential equations and the assignment is carried by multi-input state feedback control. The solution may be of particular interest in the stabilization and control of flexible structures using smart materials, where only a small part of the eigenstructure is to be reassigned and the rest is required to remain unchanged. The method presented is illustrated with a numerical example.
Resource Management in Cloud and Cloud-influenced Technologies for Internet of Things Applications

The trend of adopting Internet of Things (IoT) in healthcare, smart cities, Industry 4.0, and so on is increasing by means of cloud computing, which provides on-demand storage and computation facilities over the Internet. To meet specific requirements of IoT applications, the cloud has also shifted its service offering platform to its next-generation models, such as fog, mist, and dew computing. As a result, the cloud and IoT have become part and parcel of smart applications that play significant roles in improving the quality of human life. In addition to the inherent advantages of advanced cloud models, to improve the performance of IoT applications further, it is essential to understand how the resources in the cloud and cloud-influenced platforms are managed to support various phases in the end-to-end IoT deployment. Considering this importance, in this article, we provide a brief description, a systematic review, and possible research directions on every aspect of resource management tasks, such as workload modeling, resource provisioning, workload scheduling, resource allocation, load balancing, energy management, and resource heterogeneity in such advanced platforms, from a cloud perspective. The primary objective of this article is to help early researchers gain insight into the underlying concepts of resource management tasks in the cloud for IoT applications.
EMN: An Edge Mask based Network for Building Detection from Remote Sensing Images

Building detection from remote sensing images plays an important role in applications such as urban management and city planning. In recent years, deep learning basic building detection methods have become popular, and many sophisticated methods are proposed with expectation of replacing tedious human labeling process. However, complex backgrounds and diverse building appearance impose great challenges to the building detection. Automatic and accurate building detection methods are on demand in the community. Considering that buildings have distinct edge features, which enables them to be well distinguished from complex backgrounds, this paper proposes an edge mask-based enhancement network (EMN) for boosting Faster R-CNN. Our experiments show that the proposed method demonstrates its effectiveness.
Detection of Malicious Web Requests Using Neural Networks with Multi Granularity Features

Web attacks have long been a serious threat to network security. At present, malicious web requests are flooding in the network environment. Traditional detection methods need expert rules or a large number of Feature Engineering, and are not good at detecting new malicious requests. In order to overcome the above problems, we propose a neural network based on deep learning and multi granularity feature fusion to detect malicious web requests. Specifically, we use multi-layer CNN to extract the requests character level features, and use BiLSTM based on attention mechanism to extract word level features. Then the two granularity features are fused to construct a more accurate feature representation of web requests. Finally, the web requests are classified by a linear classifier to identify malicious. The experimental results show that compared with the existing methods, this method has significant advantages.
Electromagnetic scattering for multilayered sphere: Recursive algorithms

We have proposed more stable and accurate recursing equations and a computing procedure to calculate scattering coefficients for a multilayered sphere. The procedure involves three logarithmic derivatives of Ricatti-Bessel functions ψn′(z)/ ψn(z), χn′(z)/ χn(z), and ξn ′(z)/ξn (z), as well as the ratio ψn(z)/χn(z). The asymptotic behavior, stability, and accuracy of the procedure and scattering coefficients an and bn are discussed for any complex refractive indices. This procedure can be used for large and small inhomogeneous spherical particles.
Parallel Minimum Cuts in O(m log2n) Work and Low Depth

We present a randomized O(m łog^2 n) work, O(polylog n) depth parallel algorithm for minimum cut. This algorithm matches the work bounds of a recent sequential algorithm by Gawrychowski, Mozes, and Weimann [ICALP'20], and improves on the previously best parallel algorithm by Geissmann and Gianinazzi [SPAA'18], which performs O(m łog^4 n) work in O(polylog n) depth. Our algorithm makes use of three components that might be of independent interest. Firstly, we design a parallel data structure that efficiently supports batched mixed queries and updates on trees. It generalizes and improves the work bounds of a previous data structure of Geissmann and Gianinazzi and is work efficient with respect to the best sequential algorithm. Secondly, we design a parallel algorithm for approximate minimum cut that improves on previous results by Karger and Motwani. We use this algorithm to give a work-efficient procedure to produce a tree packing, as in Karger's sequential algorithm for minimum cuts. Lastly, we design an efficient parallel algorithm for solving the minimum 2-respecting cut problem.
Imaging of rotational Brownian motion of biomolecules in living cells using fluorescence depolarization microscopy

Two-dimensional fluorescence depolarization measurement was achieved by a fluorescence microscope equipped with polarizing devices and an image intensified CCD camera. Anisotropy images were acquired using living cells stained with a membrane specific binding dye. It was found that the bound dye is spatially distinguishable from the free dye which does not bind to the membrane of a cell, due to the difference in rotational Brownian motion. In addition, we succeeded in obtaining fluorescence depolarization images by means of time- resolved measurement and two-photon excitation measurement. Two-photon excitation images showed a superior signal-to-noise ratio compared to one-photon excitation images. Fluorescence depolarization imaging will therefore prove a powerful tool for studying molecular functions in cells.