Miracle-dz/UniFAR-FTUs huggingface dataset:
Combination with Continual Learning Update Scheme for Power System Transient Stability Assessment

In recent years, the power system transient stability assessment (TSA) based on a data-driven method has been widely studied. However, the topology and modes of operation of power systems may change frequently due to the complex time-varying characteristics of power systems. which makes it difficult for prediction models trained on stationary distributed data to meet the requirements of online applications. When a new working situation scenario causes the prediction model accuracy not to meet the requirements, the model needs to be updated in real-time. With limited storage space, model capacity, and infinite new scenarios to be updated for learning, the model updates must be sustainable and scalable. Therefore, to address this problem, this paper introduces the continual learning Sliced Cramér Preservation (SCP) algorithm to perform update operations on the model. A deep residual shrinkage network (DRSN) is selected as a classifier to construct the TSA model of SCP-DRSN at the same time. With the SCP, the model can be extended and updated just by using the new scenarios data. The updated prediction model not only complements the prediction capability for new scenarios but also retains the prediction ability under old scenarios, which can avoid frequent updates of the model. The test results on a modified New England 10-machine 39-bus system and an IEEE 118-bus system show that the proposed method in this paper can effectively update and extend the prediction model under the condition of using only new scenarios data. The coverage of the updated model for new scenarios is improving.
Takhrij Hadith of the Law of Buying and Selling Transactions

This study aims to discuss the hadith about buying and selling. This research uses a qualitative approach by applying descriptive analytical method. The formal object of this research is the takhrij hadith within the scope of hadith science, while the material object of this research is the hadith about buying and selling. The results and discussion show the Hadith of Tirmidhi History No. 1052 concerning the sale and purchase of valid quality so that it is maqbul as the basis for the implementation of Islam in the implementation of buying and selling transactions. This study concludes that the hadith narrated by Tirmidhi No. 1052 has the qualifications maqbul ma'mul bih for the basis of the implementation of buying and selling transactions in Islam, where the seller must act honestly based on goodness and the perpetrators of buying and selling are prohibited from cheating. Hadith narrated by Tirmidhi No. 1052 concerning relevant buying and selling is used as the basis of Islamic law.
Homogeneous Condensation—Freezing Nucleation Rate Measurements for Small Water Droplets in an Expansion Cloud Chamber

Abstract Experimental data on ice nucleation, presented in an earlier paper, are analyzed to yield information about the homogeneous nucleation rate of ice from supercooled liquid and the heights of energy barriers to that nucleation. The experiment consisted of using an expansion cloud chamber to nucleate from the vapor a cloud of supercooled pure water drops and the observation of the fraction of drops which subsequently froze. The analysis employed standard classical homogeneous nucleation theory. The data are used to extract the first experimental measurement (albeit indirect) of the activation energy for the transfer of a water molecule across the liquid-ice interface at temperatures near −40°C. The results provide further evidence that the local liquid structure becomes more icelike as the temperature is lowered.
Design of Low-SAR and High On-Body Efficiency Tri-Band Smartwatch Antenna Utilizing the Theory of Characteristic Modes of Composite PEC-Lossy Dielectric Structures

A low specific absorption rate (SAR) and high on-body efficiency tri-band smartwatch antenna is designed utilizing the theory of characteristic modes (TCM) of composite perfect electric conductors and lossy dielectric structures. The antenna works in the GPS frequency band, WLAN 2.4 GHz/Bluetooth frequency band, and 5G frequency band. After analyzing the characteristic modes of the antenna and human body in the above three frequency bands, the characteristic modes with small modal coupling coefficients (MCCs) are selected and excited. Due to the small mutual coupling between the antenna and the human body, the proposed antenna has good performance on both SAR and on-body efficiency. Its measured 10 g average body SAR is lower than 1.3 W/kg. When it is placed 0 mm above the body, its on-body efficiency is 9.3%–9.88% in the GPS frequency band, 12%–14.2% in the WLAN 2.4 GHz/Bluetooth frequency band, and 17.3%–20.1% in the 5G frequency band.
Position Sensorless Control of Dual Three-Phase IPMSM Drives With High-Frequency Square-Wave Voltage Injection

Dual three-phase interior permanent-magnet synchronous motor (IPMSM) drives have received more attention by the merits of better fault-tolerant capability and lower torque ripples. To improve the reliability of the system against failures in position sensor, it is necessary to investigate the position estimation method for dual three-phase IPMSM drives. The high-frequency (HF) signals injection is utilized for position estimation in three-phase IPMSM drives during low-speed operation region. However, the torque ripples are inevitable owing to the mixing of fundamental and HF components in the same control space for three-phase IPMSM drives. In this article, the position sensorless control method has been proposed by injecting HF square-wave voltage in the harmonic subspace for the dual three-phase IPMSM drives. Since the harmonic subspace is decoupled from the torque subspace, the torque disturbance can be mitigated well with the proposed HF signal injection-based position sensorless method. Moreover, the digital filters in signal extraction and current feedback can be avoided and the signal separation process becomes easy with the proposed method. The experiments have been conducted to validate the performance of the proposed method.
Removal of Powerline Noise in Geophysical Datasets With a Scientific Machine-Learning Based Approach

The most common noise in geophysical data is probably interference from powerlines. This noise manifests itself as a sinusoidal signal oscillating at the fundamental 50 or 60 Hz frequency of the power grid and as harmonic components oscillating at integer multiples. Many different mitigation strategies, tailored for the specific geophysical method, have been developed to target powerline noise. One method that applies to fully sampled data is model-based subtraction, where a model of the powerline noise is fit to the noisy dataset and subsequently subtracted. In most cases, this leads to significant improvements in the signal-to-noise ratio. However, the determination of the powerline model parameters, in particular the fundamental powerline frequency, is computationally expensive, as it requires repeated solutions of a least-squares problem. We demonstrate that the powerline frequency can be directly predicted with a scientific machine-learning-based approach. We work on both time domain-induced polarization and surface nuclear magnetic resonance data. We use a different network for each method to trade-off prediction accuracy and prediction speed. In both cases, the prediction accuracy is fully on par with standard methods, and we obtain speed-ups by factors of 400 and 10 for the two types of data.
Early years autism and bilingualism: An interpretative phenomenological analysis of parent perceptions during lockdown

Aim This study explores how bilingual parents of autistic children made language decisions for their families, how the event of the SARS-CoV-2 pandemic and subsequent lockdown impacted the communication environment of their households, and whether these experiences affected their language habits. Method Semi-structured interviews were conducted with five bilingual parents of autistic children who lived through lockdown in France. Data were analysed using interpretative phenomenological analysis. Demographic and background information was collected using an adapted version of the Questionnaire for Parents of Bilingual Children. Results Participants reported conflicting advice given by a range of practitioners. Parents expressed differing beliefs about the impact of language choices on their children. Parents described active engagement with their children's home-learning as generally positive. Parents identified an increase in children's exposure to their first language during the lockdown. Parents reported an increase in children's overall communication abilities. Conclusion Parents believed that their children's positive communication development during lockdown was related to increased exposure to their first language(s), and direct involvement in their children's learning programs.
Numerical Simulation on Mean Flow past a Circular Cylinder Based on the Lattice Boltzmann Method

Lattice Boltzmann methods (LBM) have become an alternative to conventional computational fluid dynamics (CFD) methods for various systems. In this paper, flow field of mean flow past a circular cylinder was simulated based on the lattice Boltzmann method. The streamline of air past the cylinder illuminated that the fluid adhere on the boundary and doesn’t separate from the surface of cylinder when Re number less than 5. When Re number equal 40, flow separated to form a pair of recirculating eddies can be observed. With the Re number increasing, the trailing vortex length is growth accordingly. When Re number come up to 80, the trailing vortex begin to shed regularly. This result is consistent with the experiment data. Drag coefficient that fluid act on the surface of cylinder was calculated. The calculated results were same as the experiment data. Simulation indicate that LBM can simulate the vortex taking place and shedding effectively.
Snow porosity estimation using advanced synthetic aperture radar single look complex data analysis and its effects on backscattering coefficient

This paper discusses the methodology of Synthetic Aperture Radar (SAR) data analysis for studying snow porosity and its effect on electric property of snow. ENVISAT- Advanced Synthetic Aperture Radar (ASAR) single polarized, single look complex (SLC) data have been processed for backscattering coefficient image generation. Incidence angle image has been extracted from the ASAR header data using interpolation method. These images were multi-looked 5 times in azimuth and 1 time in range direction. ASAR Backscattering coefficient images have been calibrated. The estimation of snow porosity is optimal at different incidence angles. The effect of snow porosity on snow wetness, snow density and backscattering coefficient is studied in detail. The correlation coefficient between estimated and measured porosity is observed to be 0.88 and absolute error was 0.045.
Real-Time Identification of Rogue WiFi Connections in the Wild

WiFi connections are vulnerable to simulated attacks from rogue access points (APs) or devices whose SSID and/or MAC/IP address are the same as legitimate devices. This kind of attack is difficult to counter with traditional network security mechanisms. In this article, we propose a new security mechanism that uses environment-independent features extracted from channel state information (CSI) to detect and identify rogue WiFi devices or APs, and reject their connections. We find that due to the $I/Q$ imbalance and imperfect oscillator of each WiFi network card (NIC), the nonlinear phase error of different subcarriers will vary with the NIC. Through our experimental verification, this cross-subcarrier phase feature is invariant to the location and the environment. We deploy systems on two platforms that can extract constant phase errors from the constantly changing CSI in less than 1 s, which is at least $8 \times $ faster than that of the state-of-the-art solution. Extensive experiments on commercial routers and end devices in different scenarios show that based on the Industrial Platform Computer (IPC) platform, where only nonencrypted rogue connections can be detected, the detection accuracy rate reaches 96%, and the false alarm rate is less than 2%. Based on the ASUS router platform (a commercial WiFi router), WiFi channels and smart device types are not restricted, which greatly improved universality, and the accuracy of device connection detection can even reach more than 99%. We improve a device-type identification method based on the communication traffic features of the device when connected to WiFi. Experiments show that even if there are multiple similar devices from the same manufacturer, the accuracy of device-type detection exceeds 99%.
Damage spreading and ferromagnetic order in the three-dimensional ±J Edwards-Anderson spin glass model

Using information of the ground-state topology we show that the damage spreading technique unveils ferromagnetic order in the three-dimensional ±J Edwards-Anderson spin glass model. With spin-flipping dynamics damage spreads for temperatures larger than Tg, the glass transition temperature. With spin-orienting dynamics and for temperatures in Tg<T<Td, damage spreads over a finite region of the system, composed of finite clusters of ferromagnetic character. Td is the spin-orienting damage critical temperature, which is of the same order as the critical temperature of the ferromagnetic Ising model, Tc. The present results allow for an interpretation within a single framework of known —and sometimes puzzling— results, giving an intuitive picture for growing order in spin glasses.
On the Bimodal Radial Solute Transport in Dual‐Permeability Porous Media

Porous media usually exhibit distinct transport properties of a dual domain, which is attributed to layering, fracturing, or aggregation. In this study, a mobile‐mobile (MM) model of radial solute transport consisting of two advection‐dispersion equations (ADEs) is presented to describe the bimodal (or double‐peaked) breakthrough curves (BTCs) through two distinct pore domains consisting of interrelated fast‐flow and slow‐flow domains. Transport processes, including advection, dispersion, and first‐order mass transfer between the two domains, were considered in the model. Semi‐analytical solutions were derived using a Laplace transform, matrix diagonalization and numerical Laplace inversion method, and the solutions were verified against the existing analytical solution for the mobile‐immobile (MIM) model under the special case of zero velocity in the slow‐flow domain. In addition, Markov Chain Monte Carlo is applied to estimate the MM model parameters using the experimental data. The results indicate that a larger transfer coefficient between the fast‐flow and the slow‐flow domains resulted in a weaker bimodal phenomenon for concentration distribution curves, which was notably more apparent when there was a greater variation in pore flow velocities between the two domains. Also, the MM model can be used to investigate other types of abnormal transport features such as late arrival and early arrival. Finally, the ADE, MIM, and MM models were used to interpret the experimental data conducted by Fernàndez‐Garcia et al. (2004, http://doi.org.10.1029/2004wr003112), and it was found that the proposed MM model can explain the bimodal feature of BTCs while the ADE and MIM models fail to do so.
Global solutions for 3D nonlocal Gross-Pitaevskii equations with rough data

We study the Cauchy problem for the Gross-Pitaevskii equation with a nonlocal interaction potential of Hartree type in three space dimensions. If the potential is even and positive definite or a positive function and its Fourier transform decays sufficiently rapidly the problem is shown to be globally well-posed for large rough data which not necessarily have finite energy and also in a situation where the energy functional is not positive definite. The proof uses a suitable modification of the I-method.
Co-bath hot-batch dyeing of cotton fibers with dopamine and CI reactive red 239

Polydopamine polymerization is one of the simplest methods for the functional modification of material surfaces. Because of the high requirements for rubbing and washing color fastness of textile and clothes fabrics during taking, the polydopamine on the fabric surface is a porous, loose, and disordered structure that cannot meet the color fastness requirements. To solve the above problems, we use a hot pad-batch treatment process of dopamine and CI reactive red 239 dye (RR239) that induces the orderly polymerization and growth of dopamine to prepare smooth and orderly polydopamine-modified and dyed cotton fabrics. In this way, the fastness of color is satisfied, and the color of the polydopamine-modified fabric can be enriched. In this paper, we compared the effects of three modification processes on the surface morphology of fibers with cotton fabrics as substrates, investigated the results on the dyeing properties of cotton fibers in the co-presence of dopamine/RR239, explored the role of calcium (Ca2+) ions in the dyeing process, and the Fourier transform infrared and X-ray photoelectron spectrometer spectra of polydopamine-modified dyed cotton fibers were tested and the mechanism of cotton fiber modification and dyeing was elaborated. The results showed that the hot pad-batch dyeing process with the simultaneous presence of dopamine and reactive dyestuff could improve the polymerization and covalent cross-linking of dopamine, and increase the reaction of reactive dyestuff with fiber fixation. Due to the strong fabric extrusion, the polydopamine is an ordered and smooth structure, with excellent color fastness.
Association between the distribution of Capercaillies Tetrao urogallus and road and track densities at a landscape scale in a national park

ABSTRACT Capsule: The inherited pattern of roads and tracks, now primarily used by people for recreation in the Cairngorms National Park, was associated with a reduced presence of Capercaillie Tetrao urogallus signs in woodland. Aims: To examine if the distribution of Capercaillies in the Cairngorms National Park was associated with the density of roads and tracks that run through woods in the Park, having accounted for habitat variables that are known to affect the distribution of Capercaillies. Methods: In 2013, Capercaillie distribution, as assessed from signs of presence, and habitat variables in seven woods totalling 142 km2 within the Cairngorms National Park were assessed along regularly spaced transects. Numbers of people walking, on bicycles, and in vehicles were counted on selected tracks, and the density of roads and tracks (a measure of human use) in 0.25 km2 squares of woodland was obtained from maps. A logistic regression compared habitat variables and road and track densities in 0.25 km2 squares of woodland where signs of Capercaillie were or were not found. Results: Greater road and track densities were associated with reduced likelihood of finding Capercaillie signs in woodland squares, but the track effect was associated only with the two woods that had the highest levels of use by people. Conclusion: In response to the landscape-scale, correlative evidence of disturbance to Capercaillies, a reduction in track density (a current mean of 2.3 km per km2 of woodland) or modifying human usage of tracks are conservation management options. This presents a challenge for forest managers, public bodies, the tourism industry, and others who wish to promote visitor access to the countryside and also to protect rare and vulnerable wildlife.
Global Weak Solutions to Non-isothermal Nematic Liquid Crystals in 2D

In this paper, we prove the global existence of weak solutions to the non-isothermal nematic liquid crystal system on $\mathbb T^2$, based on a new approximate system which is different from the classical Ginzburg-Landau approximation. Local energy inequalities are employed to recover the estimates on the second order spacial derivatives of the director fields locally in time, which cannot be derived from the basic energy balance. It is shown that these weak solutions conserve the total energy and while the kinetic and potential energies transfer to the heat energy precisely. Furthermore, it is also established that these weak solutions have at most finite many singular times at which the energy concentration occurs, and as a result, the temperature must increase suddenly at each singular time on some part of $\mathbb T^2$.
Storing and Retrieving Information in a Layered Spin System

We introduce a neural network model with layered architecture and binary (spin) variables. Hebbian rules are used to define unidirectional couplings between spins of adjacent layers. A fast learning algorithm produces couplings that store a large number of random patterns, and efficiently recognizes noisy patterns. Performance of this network is compared with spin-glass type models of pattern recognition.
Hubble Space Telescope Absolute Spectrophotometry of Vega from the Far-Ultraviolet to the Infrared

The Space Telescope Imaging Spectrograph (STIS) has measured the absolute flux for Vega from 0.17–1.01 μm on the Hubble Space Telescope white dwarf (WD) flux scale. These data are saturated by up to a factor of 80 overexposure but retain linearity to a precision of 0.2% because the charge bleeds along the columns and is recovered during readout of the CCD. The signal-to-noise ratio per pixel exceeds 1000, and the resolution R is about 500. A V magnitude of 0.026 ± 0.008 is established for Vega, and the absolute flux level is 3.46 × 10-9 ergs cm-2 s-1 at 5556 Å. In the regions of Balmer and Paschen lines, the STIS equivalent widths differ from the pioneering work of Hayes in 1985 but do agree with predictions of a Kurucz model atmosphere, so that the STIS flux distribution is preferred to that of Hayes. Over the full wavelength range, the model atmosphere calculation shows excellent agreement with the STIS flux distribution and is used to extrapolate predicted fluxes into the IR region. However, the IR fluxes are 2% lower than the standard Vega model of Cohen. IUE data provide the extension of the measured STIS flux distribution from 0.17 down to 0.12 μm. The STIS relative flux calibration is based on model atmosphere calculations of pure hydrogen WDs, while the Hayes flux calibration is based on the physics of laboratory lamps and blackbody ovens. The agreement to 1% of these two independent methods for determining the relative stellar flux distributions suggests that both methods may be correct from 0.5–0.8 μm and adds confidence to claims that the fluxes relative to 5500 Å are determined to better than 4% by the pure hydrogen WD models from 0.12 to 3 μm.
TarGAN: CT to MRI Translation Using Private Unpaired Data Domain

The detection and treatment of cancer and other disorders depend on the use of magnetic resonance imaging (MRI) and computed tomography (CT) scans. Compared to CT scan, MRI scans provide sharper pictures. An MRI is preferable to an X-ray or CT scan when the doctor needs to observe the soft tissues. Besides, MRI scans of organs and soft tissues, such as damaged ligaments and herniated discs, can be more accurate than CT imaging. However, capturing MRI typically takes longer than CT. Furthermore, MRI is substantially more expensive than CT because it requires more sophisticated current equipment. As a result, it is challenging to gather MRI scans to help with the medical image segmentation training issue. To address the aforementioned issue, we suggest using a deep learning network (TarGAN) to reconstruct MRI from CT scans. These created MRI images can then be used to enrich training data for MRI images segmentation issues.