Miracle-dz/UniFAR-FTUs huggingface dataset:
Cascaded metasurfaces for complete phase and polarization control

A metasurface lens that focuses light and controls its polarization at a wavelength of 2 μm is presented. This lens demonstrates high transmission and complete phase control within a subwavelength thickness at near-infrared frequencies. By cascading four patterned sheets, the efficiency is dramatically improved over more common single sheet designs. In addition, by utilizing anisotropic sheets, arbitrary birefringence can be achieved. A planar lens that both focuses light and converts its polarization from linear to circular is analyzed.
Efficient design of rotary traveling wave oscillator array via geometric programming

This paper presents an efficient method for globally optimizing and automating component sizing for rotary traveling wave oscillator arrays. The lumped equivalent model of transmission lines loaded by inverter pairs is evaluated and posynomial functions for oscillation frequency, power dissipation, phase noise, etc. are formulated using transmission line theory. The resulting design problem can be posed as a geometric programming problem, which can be efficiently solved with a convex optimization solver. The proposed method can compute the global optima more efficiently than the traditional iterative scheme and various design problems can be solved with the same circuit model. The globally optimal trade-off curves between competing objectives are also computed to carry out robust designs and quickly explore the design space.
Real-time pole and probe assessment of orientational processes in electro-optic polymers

The electro‐optic properties of polymer films are measured by an original technique whereby a periodic sequence of poling and probing steps permits alternation of the application of orientation and dephasing potentials. Relaxation dynamics of the electro‐optic coefficient of Red–Acid–Magly crosslinkable polymer films is studied as a function of the temperature of the samples. The time constant of the decay τ as measured at several temperatures is found to follow a Vogel–Fulcher–Tamann—Hesse dependence, for temperatures above glass transition. Poling the samples in the presence of a pulsed electric field leads to a r33 electro‐optic coefficient as high as 6 pm/V.
General gauge mediation in five dimensions

We use the ''general gauge mediation'' (GGM) formalism to describe a five-dimensional setup with an S{sup 1}/Z{sub 2} orbifold. We first consider a model independent supersymmetry breaking hidden sector on one boundary and generic chiral matter on another. Using the definition of GGM, the effects of the hidden sector are contained in a set of global symmetry current correlator functions and is mediated through the bulk. We find the gaugino, sfermion and hyperscalar mass formulas for minimal and generalized messengers in different regimes of a large, small and intermediate extra dimension. Then we use the five-dimensional GGM formalism to construct a model in which an SU(5) Intriligator, Seiberg and Shih (ISS) model is located on the hidden boundary. We weakly gauge a global symmetry of the ISS model and associate it with the bulk vector superfield. Compared to four-dimensional GGM, there is a natural way to adjust the gaugino versus sfermion mass ratio by a factor (Ml){sup 2}, where M is a characteristic mass scale of the supersymmetry breaking sector and l is the length of the extra dimension.
LIGO sensing system performance

The optical sensing subsystem of a LIGO interferometer is described. The system includes two complex interferometric sensing schemes to control test masses in length and alignment. The length sensing system is currently employed on all LIGO interferometers to lock coupled cavities on resonance. Auto-alignment is to be accomplished by a wavefront-sensing scheme which automatically corrects for angular fluctuations of the test masses. Improvements in lock stability and duration are noted when the wavefront auto-alignment system is employed. Preliminary results from the commissioning of the 2 km detector in Washington are shown.
Tribochemical wear of single crystal aluminum in NaCl solution studied by atomic force microscopy

We report a systematic study of chemically enhanced wear of single crystal aluminum surfaces in aqueous solutions using an environmentally equipped atomic force microscope (AFM). The experiments were conducted by using a standard Si3N4 AFM tip to apply a localized force on a polished, single crystal aluminum (110) surface. Most measurements were performed in 0.5 M NaCl solution. We show the effect of applied force, number of scans, chemical solution, and temperature on the chemical−mechanical wear of aluminum on the nanometer scale. Aggressive chemical environments significantly enhance the wear of aluminum relative to scanning in dry air. Quantitative measurements show that the wear volume increases in proportion to the square root of force and the number of scans (or time). Arrhenius plots of wear volume versus temperature are consistent with an activation energy of 31 kJ/mol for scanning in 0.5 M NaCl. The wear of the AFM tip and the aluminum substrate is explained in terms of the synergistic surface c.
Edge preserving regularization for the PDE-based piecewise smooth Mumford–Shah algorithm

Abstract This paper presents an improved algorithm for the partial differential equation (PDE)-based piecewise smooth Mumford–Shah approach, in which we integrate Mumford–Shah segmentation with the anisotropic diffusion, leading to better edge preserving regularization. Considering that the energy function in the piecewise smooth Mumford–Shah functional is non-convex, evolution of the curve does not completely depend on the global properties of the image, and some local information also affects the segmentation result. Based on this idea, the anisotropic diffusion is integrated into it to enhance boundaries and denoising, and the edges (high gradient points) are smoothed at the isophote direction. Consequently, the problems such as low convergence rate and boundary leakage can be solved. Compared with previous works, since the smoothing operation is calculated only within the narrowband domain around the evolving curve, it is not expensive computationally. The proposed algorithm has been implemented and tested by several cases, and promising results are obtained.
Dynamic spatial Bayesian models for radioactivity deposition

Dynamic spatial Bayesian (DSB) models are proposed for the analytical modelling of radioactivity deposition after a nuclear accident. The proposed models are extensions of the multi‐variate time‐series dynamic linear models of West and Harrison (1997) to Markov random field processes. They combine the outputs from a long‐range atmospheric dispersal model with measured data (and prior information) to provide improved deposition prediction in space and time. Two versions of a Gaussian DSB model were applied to the radioactivity deposition in Bavaria over a 15 days period during the Chernobyl nuclear accident. One version had fixed functional forms for its spatial variances and covariances while the other allowed those to adapt and ‘learn’ from data in the conjugate Bayesian paradigm. There were two main sources of information for radioactivity deposition in our application: radioactivity measurements at a sparse set of 13 monitoring stations, and the numerical deposition evaluation of the atmospheric dispersal K‐model for the points of a 64 × 64 regular grid. We have analysed the temporal predictions (one‐step‐ahead forecasting) of those DSB models to show that the dispersal K‐model tended in general to underestimate the deposition levels at all times while the DSB models corrected for that although with different degrees of adjustment.
Characterization of the electron distribution function in an electron-cyclotron driven toroidal plasma

The local properties of the electron energy distribution function are investigated in the electron-cyclotron wave driven toroidal device TORPEX (Fasoli et al 2006 Phys. Plasmas 13 055902). The electron energy distribution function is measured by means of a time-resolved electrostatic energy analyser. The measurements indicate that electrons are accelerated to different energies at the electron-cyclotron and upper-hybrid resonances. Electrons from the upper-hybrid resonance have higher energies and can be described by a secondary maxwellian energy distribution function. The electron energy distribution function is found to be invariant with respect to experimental parameters such as the neutral gas pressure, the magnetic field configuration and the injected microwave power. The implications for a correct modelling of the particle source term for TORPEX plasmas are discussed.
Experimental Evaluation of Display Field Communication Based on Machine Learning and Modem Design

Display field communication (DFC) is a frequency-domain unobtrusive display-to-camera (D2C) communication, in which an electronic display serves as a transmitter and a camera serves as a receiver. In this paper, we propose a machine learning-based DFC scheme and evaluate its performance in a lab test scenario. First of all, we adopt the Discrete Cosine Transform (DCT) to transform a spatial-domain image into its spectral-domain equivalent. To reduce the computational complexity during the data-embedding process, addition allocation and subtraction data retrieval techniques are used. Moreover, channel coding is applied to overcome the data error caused by the optical wireless channel. In particular, robust turbo coding is used for error detection and correction. Afterward, we perform the experiments to validate the performance of the proposed system. After capturing the displayed image with a camera, data restoration is done using a deep learning technique. Extensive real-world experiments were performed considering various geometric distortions, noise, and different standard input images. As a result, we found that by increasing the transmit display image size (upsampling), the overall error rate can be reduced. In addition, real-world noise analysis is performed and it is notified that the actual noise is dominant in the low-frequency region of an image. The experimental results confirm the robust performance of the proposed DFC scheme and show that an error-free performance can be achieved up to a distance of 1m in the given lab test environment setting.
BeppoSAX observations in the 2–100 keV band of the nearby Seyfert galaxies: an atlas of spectra

An atlas of high energy ($E\geq2$ keV) spectra of nearby ($z\leq0.1$) Seyfert galaxies observed with ${\it BeppoSAX}$ is presented. The data have been analyzed in an homogeneous way. The final sample contains ${\it BeppoSAX}$ MECS+PDS (LECS data were not used here) pointings of 113 objects. No useful X-ray data were present for eight targets. The catalog of X-ray spectra contains data for 43 type-I Seyfert (including Seyfert 1.0, 1.2, and 1.5) and for 62 type-II objects (including Seyfert 1.8, 1.9, and 2.0). A total of 163 X-ray spectra (84 for type-I and 79 for type-II objects) were analyzed, since some sources were observed several times. 81 sources were detected at high energy (above 10 keV) by the PDS: 39 are Seyfert I and 42 are Seyfert II. The broadband X-ray spectra covering the ~2–100 keV band are 130 in total. In a forthcoming paper, the statistical analysis of these data will be presented.
Separating quasars from stars by support vector machines

Based on survey databases from different bands, we firstly employed random forest approach for feature selection and feature weighting, and investigated support vector machines (SVMs) to classify quasars from stars. Two sets of data were used, one from SDSS, USNO-B1.0 and FIRST (short for FIRST sample), and another from SDSS, USNO-B1.0 and ROSAT (short for ROSAT sample). The classification results with different data were compared. Moreover the SVM performance with different features was presented. The experimental result showed that the accuracy with FIRST sample was superior to that with ROSAT sample, in addition, when compared to the result with original features, the performance using selected features improved and that using weighted features decreased. Therefore we consider that while SVMs is applied for classification, feature selection is necessary since this not only improves the performance, but also reduces the dimensionalities. The good performance of SVMs indicates that SVMs is an effective method to preselect quasar candidates from multiwavelength data.
UHURU CATALOG OF X-RAY SOURCES.

A catalog of X-ray sources observed with the Uhuru satellite is presented. About 70 days of data have been analyzed for this catalog resulting in 125 sources. Approximately two-thirds of the sources are located within plus or minus 20 deg of the galactic plane. Some of the sources at higher galactic latitudes are identified with known extragalactic objects. Most of the strong sources near the galactic plane are found to be variable.
Fault‐tolerant control of linear multivariable controllers using iterative feedback tuning

This paper introduces the iterative feedback tuning (IFT) into a Youla parameterization scheme for fault‐tolerant control. By off‐line IFT‐experiments of tuning Youla parameters, the proposed algorithm deals with a number of conditional failures that are described by the dual Youla parameter. The main contribution of this paper is to show how Youla scheme‐based IFT can be constructed for multivariable linear time‐invariant systems. Particular attention is given to the issue of the structure of the Youla parameter (filter), in which both finite impulse response and infinite impulse response filters are presented and compared. As an illustration, the method is applied to a simulation model of a continuous stirred tank heater system. Copyright © 2014 John Wiley & Sons, Ltd.
An Immune Intrusion Detection Model Based on One-Class Classification Technology

An intrusion detection model based on biological immune principle and one-class classification technology is proposed. The one-class classification technology named support vector domain description (SVDD) is applied to the proposed model. Simple multi-dimension feature vectors of network packets are mapped into high dimension feature space. The description models of the antibody and the self set are constructed. The evolution process of antibodies is described with math language. The theoretical analysis shows that the proposed model can detect network attack effectively, and unknown network attacks can be detected.
FFT‐based bounds on the permeability of complex microstructures

A numerical scheme for the computation of the permeability of complex microstructures is presented. As a darcean counterpart of the FFT‐based scheme in elasticity, the method is designed to be directly coupled with 3D imaging techniques of porous samples, without meshing or definition of an equivalent pore network. The method relies on the variational principle of Hashin and Shtrikman, which ensures a rigorous upper bound status to the estimated permeabilities and provides an energetically consistent rule for heterogeneous voxels comprising both the solid and fluid phases. Copyright © 2014 John Wiley & Sons, Ltd.
Multiturn flux transformers for rf SQUID magnetometers

This work showed experimentally how the planar multiturn input coil of a flux transformer could be integrated with a coplanar resonator while still permitting one to couple radio frequency (rf) signals to an rf SQUID. A new layout of a multiturn flux transformer with one pickup loop and two input coils, one single turn and one multiturn, has been fabricated on (001) substrates and evaluated. A planar double-hole washer SQUID was inductively coupled to the two separate input coils via a flip chip configuration. With this layout the best magnetometer showed magnetic field white noise of at 77 K in a magnetically shielded surrounding.
Autoregressive conditional heteroscedasticity in daily temperature measurements

It is argued that the predictability of meteorological variables is not constant but shows regular variations. This is shown for the daily mean summer and winter temperatures at De Bilt, The Netherlands, over the last 30 years. To capture this feature, a generalized autoregressive conditional heteroscedastic (GARCH) model is proposed. In this model, the conditional variance of an observation depends linearly on the conditional variances of the previous observations and on the previous prediction errors. Here a GARCH(1,1) model is used for both the conditional variance and the conditional standard deviation, in conjunction with an AR(2) model for the mean, and conditionally normal errors. It is shown that these heteroscedastic models outperform their homoscedastic versions, and that the model which updates the conditional standard deviation is preferred.
Transmitting Vibration of Artificial Ossicle

A three dimensional finite e lement model of human middle ear is established, numerical analysis for ossicle structure is carried out. The optimal material, shape and size are obtained for partial artificial replacement. It is concluded that physical parameters are determined by elastic modulus-when the elastic modulus becomes larger, the artificial replacement behaves better, therefore, the hearing resume is consolidated. Key word: Ossicle; Vibration; Frequency; Numerical Simulation; Artificial Replacement
Scientific Charge-Coupled Devices

The charge-coupled device dominates an ever-increasing variety of scientific imaging and spectroscopy applications. Recent experience indicates, however, that the full potential of CCD performance lies well beyond that realized in devices currently available. Test data suggest that major improvements are feasible in spectral response, charge collection, charge transfer, and readout noise. These properties, their measurement in existing CCDs, and their potential for future improvement are discussed in this paper.
On the anisotropy of the cosmological background matter and radiation distribution. II - The radiation anisotropy in models with negative spatial curvature

The expected microwave background anisotropy has been calculated on bothlarge and small angular scales for various models with . cap omega. /sub 0/ = 0.1, including all effects of spatial curvature. Both adiabatic and isothermal fluctuations have been considered, with power spectrum Vertical Bar delta/sub m/(k)/sup 2/ proportional k/sup n/ initially. The adiabatic models can probably be ruled out on the basis of their large correlation length, but if only the microwave anisotropy is considered, models with n> or approx. =3 are acceptable. The microwave anisotropy is below current upper limits for all values of n considered with isothermal initial conditions.
Semi-Rigid Registration of 3D Points

In this paper, we proposed a method for semi-rigid changed 3D point clouds registration. We first segment the point clouds into individual segments and then the alignment energy costs of each segment are calculated. The rough initial transformation is estimated by minimizing the energy cost using integer programming. The final registration results are obtained by rigid alignments of separated corresponded segments. Experimental result with simulated point clouds demonstrate that the concept of semi-rigid registration works well.
High-pressure band structure and structural stability of EuTe

Band-structure calculations were carried out to study the pressure-induced structural transitions and structural stability of the magnetic compound, EuTe. The first-principle tight-binding linear muffin-tin orbital method within the local-density approximation (LDA) was used to obtain the electronic structure and total energies both at ambient as well as at high pressures. The magnetic phase stability was determined from the total-energy calculations within the atomic-sphere approximation for both nonmagnetic and magnetic phases. It is found that the magnetic phase is more stable than the nonmagnetic phase. The pure theoretical calculations further indicate that there is a phase transition from NaCl $(B1)$ type to CsCl $(B2)$ type structure at around 9.89 GPa, which is comparable to the experimentally observed value of 11.0 GPa. Furthermore, the bulk modulus and magnetic moments were also estimated, which were found to be in agreement with earlier experimental results.
SGORNN: C OMBINING S CALAR G ATES AND O R - THOGONAL C ONSTRAINTS IN R ECURRENT N ET -

Recurrent Neural Network (RNN) models have been applied in different domains, producing high accuracies on time-dependent data. However, RNNs have long suffered from exploding gradients during training, mainly due to their recurrent process. In this context, we propose a variant of the scalar gated FastRNN architecture, called Scalar Gated Orthogonal Recurrent Neural Networks (SGORNN). SGORNN utilizes orthogonal linear transformations at the recurrent step. In our experiments, SGORNN forms its recurrent weights through a strategy inspired by Volume Preserving RNNs (VPRNN), though our architecture allows the use of any orthogonal constraint mechanism. We present a simple constraint on the scalar gates of SGORNN, which is easily enforced at training time to provide a theoretical generalization ability for SGORNN similar to that of FastRNN. Next, we provide bounds on the gradients of SGORNN, to show the impossibility of (exponentially) exploding gradients. Our experimental results on the addition problem confirm that our combination of orthogonal and scalar gated RNNs are able to outperform both predecessor models on long sequences using only a single RNN cell, and outperforms LSTM. We further evaluate SGORNN on the HAR-2 classification task, where it improves upon the accuracy of FastRNN, VPRNN, and LSTM using far fewer parameters than FastRNN or LSTM. Finally, we evaluate SGORNN on the Penn Treebank word-level language modelling task, where it again outperforms its predecessor architectures and shows comparable performance to LSTM using far less parameters. Overall, this architecture shows higher representation capacity than VPRNN, suffers from less overfitting than the other two models in our experiments, benefits from a decrease in parameter count, and alleviates exploding gradients when compared with FastRNN on the addition problem.
Accuracy of RIPASA and Lintula Scores in Diagnosing Acute Appendicitis Using Surgical Findings as the Gold Standard

Background: Appendicitis is an inflammation of the vermiform appendix's inner lining that spreads to its other sections. Appendectomy is still the standard way to cure appendicitis. The diagnosis of acute appendicitis is still clinical and supported by a raised neutrophilic count and imaging studies; moreover, scoring systems, such as the Raja Isteri Pengiran Anak Saleha Appendicitis (RIPASA) and Lintula scores, help the clinicians in the diagnosis. The main objective of this study was to establish the diagnostic accuracy of RIPASA and Lintula scores for acute appendicitis using surgical findings as the gold standard, in an Asian population. Methods: This was a retrospective cohort study conducted at the Department of Surgery, Mayo Hospital, Lahore, and Department of Surgery, Services Hospital, Lahore. This study was conducted from January 2020 to January 2022, for the duration of two years. A total of 120 patients were enrolled after meeting the inclusion criteria, and demographic data were obtained. Lintula and RIPASA scores were recorded, and patients were classified as positive or negative based on histopathological findings. IBM SPSS Statistics, version 26 (IBM Corp., Armonk, NY) was used to evaluate all of the gathered data. Results: The average age of the patients in this study was 37.39±14.36 years, with a male-to-female ratio of 1.14:1. Taking surgical finding as the gold standard, RIPASA scoring had a diagnosis accuracy of 91.67% while the Lintula score had a diagnostic accuracy of 79.17%. Conclusion: While both the RIPASA and the Lintula scoring systems were accurate, the RIPASA scoring system outperformed the Lintula scoring system when surgical findings were used as the gold standard.