Miracle-dz/UniFAR-FTUs huggingface dataset:
Nonlinear Innovations and Impulse Responses with Application to VAR Sensitivity

This paper introduces impulse response analysis for nonlinear processes based on the concept of nonlinear innovation. Our approach borrows from the traditional linear impulse response analysis in that we consider shocks to innovations of a process. It also extends the methods of nonlinear impulse response analysis proposed earlier in the literature, in that it eliminates the problem of serial correlation of error terms, allows to examine permanent shocks, i.e. shocks occurring repeatedly in time, and provides straightforward interpretation of transitory or symmetric shocks. In our approach, the impulse responses are represented by the joint distribution of the perturbed and unperturbed paths. The analysis can be applied to processes such as the popular GARCH, or ACD models, and can be used to study shock sensitivity of dynamic financial strategies. As an illustration, we show how impulse responses can determine the Value at Risk and the minimum capital requirement under a dynamic portfolio management.
Comparison of sporadic sodium layer characteristics observed at different time resolutions

Sporadic sodium (Na-s) layers, occurring in roughly the same height range as ionospheric sporadic-E layers, were first detected by lidar some 30 yr ago. Nas layers have a typical thickness of a few hundred meters to a few km, with peak atom concentrations several times that of the background layer. Despite a great deal of excellent work over the past decades, the source of Nas layers is still not altogether clear, partly as a result of our incomplete knowledge of Nas layer characteristics. In this paper we concentrate on some typical case studies chosen from the similar to 127 h of sporadic sodium layer observations made at a time resolution of 1.5 s at Yanqing (115.97 degrees E, 40.47 degrees N), Beijing, China. This is a much better time resolution than what has been employed in most earlier measurements. The results show that the Nas layer peak heights are dispersed at slightly different although adjacent heights. When averaged over several minutes, as has been the case with most earlier measurements, the height scatter results in an apparent layer thickness of a few km. We conclude, therefore, that these dispersed peaks at different but adjacent heights constitute the 5 min Nas layer. Similar to the observations of sporadic-E-ion (Es) layers and meteor rate, we observe quasi-periodic fluctuations on a timescale on the order of several minutes in the peak height and the peak density of sporadic layers, which is a universal feature but concealed by the lower temporal resolution previously adopted. Spatially localized multiple scatterers and multiple thin layers with similar apparent movement in Nas layers are also found. We discuss the possible formation mechanism by the direct deposition of large swarms of micrometeoroids and demonstrate a typical example of meteor trails evolving into a Nas layer, which suggests that this mechanism might indeed occur.
Galaxies - fractal dimensions, counts in cells, and correlations

The luminosity function for clusters of galaxies is determined theoretically, assuming that the many-body galaxy correlation functions are scale-invariant. It is shown that the luminosity function is a power law with an upper and lower cutoff, and that the fractal dimensions for cluster-rich and empty regions of the resulting galaxy distribution are different. The specific values of these fractal dimensions are not in agreement with those determined by Jones et al. (1988). 24 references.
An electromagnetic parameters extraction method for metamaterials based on phase unwrapping technique

Abstract A new method of extracting effective permittivity and permeability of metamaterials has been developed in this paper. Scattering parameters are used to represent effective wave impedance and refractive index of the metamaterials. Considering analytical continuation of effective refractive index of the metamaterials in the upper half of a complex angular frequency plane, a phase unwrapping technique has been implemented to solve branch ambiguity of the refractive index caused by complex inverse cosine function. An empirical formula to estimate the starting frequency in the phase unwrapping technique has been developed to improve the efficiency of the parameter retrieval procedure. Numerical results including five slabs of rods and split-ring resonators (SRRs) and a structure composed of two SRRs and four capacitively loaded strips are given to demonstrate good accuracy, high efficiency, and noise insensitivity of the proposed retrieval method.
A New Method for Extraction of the Scattering Mechanism of Randomly Rough Surfaces Using Eigenvector Based Decomposition Technique

Abstract In this article, a statistical approach to evaluate distributed targets in a forward scattering problem is presented. Due to electromagnetic scattering, the scattered fields of a plane wave impinging upon randomly rough surfaces are usually affected by several parameters. In the surface remote sensing, the roughness criteria, such as ks and kl, play an important role in the scattering process. Whereas in synthetic aperture radar applications these parameters are stochastic; the use of the deterministic techniques, such as target decomposition, cannot be useful by itself as a tool of analysis. In these investigations, a statistical approach, namely the maximum-likelihood estimator, is essentially required to evaluate the target parameters including random variables. The goal of this article is the estimation of the polarimetric signatures, such as the scattering mechanism α and the entropy H, via a novel approach including the combination of target decomposition and the maximum-likelihood estimator. To validate our work, synthetic aperture radar data sets provided by the European Space Agency are analyzed and compared with the simulation results. These evaluations show that these signatures are estimated with an acceptable accuracy by means of the proposed technique.
Bayesian quantile regression for longitudinal data models

In this paper, we discuss a fully Bayesian quantile inference using Markov Chain Monte Carlo (MCMC) method for longitudinal data models with random effects. Under the assumption of error term subject to asymmetric Laplace distribution, we establish a hierarchical Bayesian model and obtain the posterior distribution of unknown parameters at τ-th level. We overcome the current computational limitations using two approaches. One is the general MCMC technique with Metropolis–Hastings algorithm and another is the Gibbs sampling from the full conditional distribution. These two methods outperform the traditional frequentist methods under a wide array of simulated data models and are flexible enough to easily accommodate changes in the number of random effects and in their assumed distribution. We apply the Gibbs sampling method to analyse a mouse growth data and some different conclusions from those in the literatures are obtained.
Application of discriminant analysis to predict the class of degree for graduating students in a university system

In this Paper, discriminant analysis was used to predict the class of degree obtainable in a University system. The conditions for predictive discriminant analysis were obtained, and the analysis yielded a linear discriminant function which successfully classified or predicted 87.5 percent of the graduating students’ class of degrees. The function had a hit ratio of 88.2 percent when generalized, as a valid tool to classify fresh students of unknown group membership. It was also discovered that success in classifying or predicting fresh students of unknown group into classes of degree, was essentially similar to that of the historical sample. Key words: Discrimination, prediction, linear discriminant function, confusion matrix.
Simulation Study of an Extended Divertor Leg for Heat Control in the SlimCS DEMO Reactor

Power handling in the divertor is one of the most important issues for fusion tokamak reactor design. In this study, the effect of the divertor leg length on power handling in the SlimCS DEMO reactor is investigated for future divertor design. Simulation with the SONIC code suite shows enhancement of recycling in the outer divertor region due to effects of the long divertor leg and the deep V‐shaped corner. As a result, the ion and electron temperature at the outer divertor significantly decreases. In addition, the peak of the Ar impurity radiation, which is located close to the outer divertor target in the standard divertor geometry, moves upstream. The former effect decreases the heat load to the outer divertor due to ion conduction and convection, while the latter reduces the heat load due to the impurity radiation. The peak of the total heat load on the outer divertor decreases by about 30 % (© 2012 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)
1D and 2D systolic implementations for radial basis function networks

Shows that radial basis function networks can be efficiently implemented on 1D and 2D systolic arrays. The authors discuss such networks in the framework of probability density function approximation for classification problems. In fact, the most computation intensive parts of the classification process consist in calculating pattern distances. In the initialisation phase of the algorithm this involves calculating the mutual (intra-class) distance matrix. The classification of an input vector mainly involves the calculation of the distance vector between this input vector and all the learning set vectors. The proposed implementations are 2D systolic, 1D pipeline and 1D parallel. Practical implementation issues are discussed for the MANTRA machine (2D grid) and the SMART Neuro-computer (1D ring).
The perturbed test function method for viscosity solutions of nonlinear PDE

Synopsis The method of viscosity solutions for nonlinear partial differential equations (PDEs) justifies passages to limits by in effect using the maximum principle to convert to the corresponding limit problem for smooth test functions. We describe in this paper a “perturbed test function” device, which entails various modifications of the test functions by lower order correctors. Applications include homogenisation for quasilinear elliptic PDEs and approximation of quasilinear parabolic PDEs by systems of Hamilton-Jacobi equations.
Multi-Channel Nonlinearity Mitigation Using Machine Learning Algorithms

This paper investigates multi-channel machine learning (ML) techniques in the presence of receiver nonlinearities and noise, and compares the results with the single-channel receiver architecture. It is known that the multi-channel architecture relaxes the sampling speed requirement of analog to digital conversion and provides significant robustness to clock jitter and front-end noise due to the bandwidth-splitting property inherent in these receivers. However, when a high-voltage swing signal is used in a wireline communication link, the received signal suffers from third-order harmonic distortions and inter-modulation products caused by the nonlinearity profile of the analog front-end (AFE). To this end, this paper proposes the channel decision passing (CDP) algorithm in combination with nonlinear feedback cancellation as a low-complexity candidate for nonlinearity mitigation and compares the performance of this solution with other well-known ML algorithms. Simulation results show significant improvement in a multi-channel receiver architecture equipped with nonlinear feedback cancellation and CDP in comparison with its single-channel counterpart under practical nonlinearity profiles and noise conditions.
Object tracking algorithm based on improved CAMShift

For the problem of Mean Shift algorithm extracting the target color features easily affected by the background,this paper selects non-linear kernel density estimation to detect single moving object, then uses CAMShift method to track the detected target, combined with test results of nonlinear kernel density estimation to do adaptive update of target histogram. This article also gives solution of target occlusion problem. Experimental results show that the method which combines the foreground detection and CAMShift can achieve automatic tracking of moving target, as well as adaptive update of target histogram. The reliable performance of this algorithm can satisfy real-time requirement, and eliminate the effects of unstable scene illumination and object occlusion.
Synthesis of NVCL-NIPAM Hydrogels Using PEGDMA as a Chemical Crosslinker for Controlled Swelling Behaviours in Potential Shapeshifting Applications

Stimuli-responsive hydrogels have recently gained interest within shapeshifting applications due to their capabilities to expand in water and their altering swelling properties when triggered by stimuli, such as pH and heat. While conventional hydrogels lose their mechanical strength during swelling, most shapeshifting applications require materials to have mechanical strength within a satisfactory range to perform specified tasks. Thus, stronger hydrogels are needed for shapeshifting applications. Poly (N-isopropylacrylamide) (PNIPAm) and poly (N-vinyl caprolactam) (PNVCL) are the most popular thermosensitive hydrogels studied. Their close-to-physiological lower critical solution temperature (LCST) makes them superior candidates in biomedicine. In this study, copolymers made of NVCL and NIPAm and chemically crosslinked using poly (ethylene glycol) dimethacrylate (PEGDMA) were fabricated. Successful polymerisation was proven via Fourier transform infrared spectroscopy (FTIR). The effects of incorporating comonomer and crosslinker on the LCST were found minimal using cloud-point measurements, ultraviolet (UV) spectroscopy, and differential scanning calorimetry (DSC). Formulations that completed three cycles of thermo-reversing pulsatile swelling are demonstrated. Lastly, rheological analysis validated the mechanical strength of PNVCL, which was improved due to the incorporation of NIPAm and PEGDMA. This study showcases potential smart thermosensitive NVCL-based copolymers that can be applied in the biomedical shapeshifting area.
Artificial Neural Network Assisted Probabilistic and Geometric Shaping for Flexible Rate High-Speed PONs

In this paper, we employ artificial neural networks (ANNs) to optimize joint probabilistic shaping (PS) and geometric shaping (GS) for a realistic 50G IM/DD passive optical network (PON) link. Apart from being able to find a generalized mutual information (GMI)-maximizing modulation for channel conditions unseen at the training phase, the compatibility of the ANN training with Monte Carlo simulation also enables us to use a more complicated channel model that more closely resembles a real PON system where fiber dispersion, bandwidth limitation and digital signal processing (DSP) are present. The forward error correction (FEC) requirement that must be satisfied in an actual implementation is imposed on the learned modulation by including a normalized GMI (NGMI) penalty term in the loss function. The proposed scheme is demonstrated with simulations. Results show that the ANN can achieve similar performance compared to a case-by-case optimization while also being capable of generalizing to a wide range of received optical power (ROP) from −30 dBm to −18 dBm and/or a broad range of fiber distance from 0 km to 20 km. About 0.1-bits/symbol GMI improvement is attained compared to uniform modulation.
Tailored medication management intervention delivered by occupational therapists for older adults: A study protocol

Introduction: Medication management is an essential instrumental activity of daily living for older adults; however, 40–70% of older adults fail to take their medications correctly. Addressing medication management falls under the scope of occupational therapy, but there is a lack of evidence supporting occupational therapy interventions to improving medication management. This study’s primary aims are to examine the feasibility, acceptability, and preliminary efficacy of a Tailored Intervention for Medication Management delivered by occupational therapists to improve medication management. Method/Design: Single-blind, parallel-group randomized controlled equivalency trial, with two phases. Thirty community-dwelling older adults will be enrolled in this study. In Phase 1, participants in the treatment group will receive Tailored Intervention for Medication Management delivered remotely; those in the waitlist control will receive attention visits. In Phase 2, waitlist control participants will receive Tailored Intervention for Medication Management in person. The primary outcomes are feasibility and acceptability; secondary outcomes include preliminary efficacy of the intervention delivered by an occupational therapist remotely and in person. Additionally, the remote and in-person delivery methods will be compared to each other for equivalency. Discussion: Inability to manage medication and inappropriate polypharmacy are significant and prevalent problems that must be addressed so older adults can safely perform this essential instrumental activity of daily living. Trial Registration: ClinicalTrials.gov identifier NCT04717297.
Displacement Damage Equivalence of Neutron and Proton Radiations in Triple-Junction GaInP/GaAs/Ge Solar Cells

In this work, radiation effects in GaInP/GaAs/Ge triple junction solar cells irradiated by 3-, 5-, 10-, 60-, 100-MeV protons and 1-MeV equivalent neutrons are investigated. The external quantum efficiency (EQE), open-circuit voltage (<inline-formula> <tex-math notation="LaTeX">$V_{\mathrm {oc}}$ </tex-math></inline-formula>), maximum power (<inline-formula> <tex-math notation="LaTeX">$P_{\mathrm {max}}$ </tex-math></inline-formula>), and conversion efficiency (<inline-formula> <tex-math notation="LaTeX">$E_{\mathrm {ff}}$ </tex-math></inline-formula>) of solar cells are measured and compared. The Geant4 software is utilized to simulate non-ionizing energy loss (NIEL) with different particles. The physical mechanisms behind the different phenomena of device performance degradation due to neutron, low-energy proton, and high-energy proton irradiations at the same displacement damage dose (DDD) are analyzed. The proportion of primary knock-on atom (PKA) number produced by neutrons and low-energy protons is consistent with that of NIEL, but the proportion of PKA number produced by high-energy protons is not consistent with that of NIEL. The energy spectrum of PKA is investigated, and it is proposed that different energies and types of PKA may lead to different defect morphologies. The DDD method is used to determine the radiation damage equivalent between protons and neutrons, and the equivalent relationship between <inline-formula> <tex-math notation="LaTeX">$V_{\mathrm {oc}}$ </tex-math></inline-formula>, <inline-formula> <tex-math notation="LaTeX">$P_{\mathrm {max}}$ </tex-math></inline-formula>, and <inline-formula> <tex-math notation="LaTeX">$E_{\mathrm {ff}}$ </tex-math></inline-formula> is given. The results prove that the neutron source can be used as an alternative particle source for on-orbit solar cells to predict the performance degradation caused by protons.
Abrupt Changes in Atmospheric Circulation During the Medieval Climate Anomaly and Little Ice Age Recorded by Sr‐Nd Isotopes in the Siple Dome Ice Core, Antarctica

The Southern Hemisphere westerly winds (SWW) play a critical role in global climate, yet their behavior on decadal to centennial timescales, and the mechanisms driving these changes during the preindustrial era, remain poorly understood. We present a decadally resolved record of dust compositions using strontium and neodymium isotope ratios in mineral dust from the Siple Dome ice core, Antarctica, to explore the potential that abrupt changes in SWW behavior occurred over the past millennium. The record spans portions of the Medieval Climate Anomaly (MCA) and the Little Ice Age (LIA) intervals as defined in the Northern Hemisphere. We find evidence of an abrupt strengthening of atmospheric circulation during the MCA at ∼1125 CE (825 BP) that persisted for about 60 yr, indicating increased influence of Patagonia‐sourced dust. This occurs during an extended positive phase of Southern Annular Mode (SAM+)‐like conditions, characterized by high SWW velocities and a southerly shift of the main wind belt toward ∼60°S, suggesting that rapid changes in SWW strength could occur under the present SAM+ pattern. A second 20 yr long shift in dust compositions during the LIA at ∼1748 CE (200 BP) is coincident with higher dust delivery to Siple Dome, and may indicate increased dust emissions related to glacier activity in Patagonia. The new Siple Dome ice core data set demonstrates that Sr‐Nd isotopes can be used to trace shifts in atmospheric circulation on decadal timescales.
New experimental device for high-temperature normal spectral emissivity measurements of coatings

A new experimental device for normal spectral emissivity measurements of coatings in the infrared spectral range from 1.38 μm to 26 μm and in the temperature range from 550 K to 1250 K is presented. A Fourier transform infrared spectrometer (FTIR) is used for the detection of sample and blackbody spectral radiation. Sample heating is achieved by a fiber laser with a scanning head. Surface temperature is measured by two methods. The first method uses an infrared camera and a reference coating with known effective emissivity, the second method is based on the combination of Christiansen wavelength with contact and noncontact surface temperature measurement. Application of the method is shown on the example of a high-temperature high-emissivity coating. Experimental results obtained with this apparatus are compared with the results performed by a direct method of Laboratoire National d’Essais (LNE) in France. The differences in the spectra are analyzed.
Magnetic resonance of magnetite nanoparticles dispersed in mesoporous copolymer matrix

Magnetic resonance is used to investigate fine particles of magnetite (Fe/sub 3/O/sub 4/) synthesized as isolated nanoparticles (INP's) in a mesoporous styrene-divinylbenzene (Sty-DVB) copolymer template. The magnetite nanoparticles were obtained through alkaline precipitation of ferrous sulfate, at different iron (II) concentration (Q), in the sulfonated polymeric matrix. Analysis of the temperature (T) dependence of the resonance field (H/sub R/) and resonance linewidth (/spl Delta/H/sub R/) provide a useful way to estimate the average size of the magnetite nanoparticles. The data indicates that the nanoparticle average diameter (D) increases as Q increases, in accordance with the data reported previously.
Integrated Experimental and Numerical Analysis of an Atmospheric Pressure Reactive Air Plasma Jet Generated by Dielectric Barrier Discharge

The effects of applied voltage, pulse frequency, flow rate and permittivity of dielectric material on the concentration of O3 and NO2 in a Dielectric Barrier Discharge (DBD) air plasma jet are experimentally investigated for industrial applications. Furthermore, the production and decay processes of chemical species and also time dependent chemical species concentration field in a DBD discharge region are numerically analyzed by integrated chemical reaction model with thermofluid flow field. There is a reasonable agreement of O3 and NO2 concentration with experimental data.
Reversion of turbulent to laminar flow

It has been shown experimentally that quite large departures occur from the universal inner-law velocity distribution in the presence of severe favourable pressure gradients in turbulent boundary layers and that these departures are associated with the tendency for the turbulent boundary layer to revert to a laminar state. From the measurements a criterion for the onset of reverse transition has been deduced in terms of the mean shear-stress gradient in the wall region of the flow. Experiments in fully developed pipe and channel flows suggest that the proposed criterion may be quite generally applicable to all fully turbulent shear flows.