Miracle-dz/UniFAR-FTUs huggingface dataset:
Semisimple Lie superalgebras which are not the direct sums of simple Lie superalgebras

Any finite-dimensional semisimple Lie algebra (LA) is known to be realised as a direct sum of simple LA. The situation is somewhat more complicates in the Lie superalgebra (LSA) case. A theorem of Kac states how to build all the semisimple LSA. The goal of this paper is to give some explicit examples arising from this theorem, such illustrations perhaps being better understood by physicists rather than an abstract statement; and to show the relevance of the Neveu-Schwarz and Raman superalgebras when generalising the theorem to the infinite case.
Numerical Solution of Ordinary and Partial Differential Equations by Means of Equivalent Circuits

Numerical methods are developed to solve certain types of linear and nonlinear partial differential equations to any desired degree of accuracy with the aid of equivalent electrical networks. The methods of solution of ordinary differential equations, both linear and nonlinear, follow as special cases. Three types of problems are considered:1. Initial‐value problems. If the field quantities are known along a surface, the networks may be solved by a straight‐forward step‐by‐step calculation. The networks may also be looked upon as supplying a ``schedule'' of operations that can be put on a digital calculating machine.For time‐varying problems new types of networks are developed in which time appears as an extra spatial variable. Examples of new networks for the elastic field and for the general nonlinear wave equation are given. Sample calculations and theoretical checks of a transient heat flow problem and of an ordinary differential equation are also included.2. Boundary‐value problems. Four methods of s.
Linear magnetoresistance of potassium

Measurements of the linear magnetoresistance effect in pure potassium were made using two independent methods. Four-terminal measurements on straight narrow samples showed transverse and longitudinal effects of the same magnitude. An induced torque method was then used on large good single crystals. In these the magnetoresistance was of the same order of magnitude as in the narrow samples and it was isotropic. The presence of the linear variation of resistivity with field in this case of a probeless method, where no obvious boundary value problems occur, adds to the existing evidence that the effect is not a result of sample shape or contact configuration.
Extreme Hamiltonian circuits. Resolution of the convex-even case

Remark. The collinear case (odd or even) is a special case of Theorem III [2, p. 181]. Proof of the Theorem. Case I. Suppose no three points of 2 are collinear. A line segment DE with endpoints in 2 is said to be of type Lk (1 =A = «), if D and E are the endpoints of a polygonal subarc of B having k edges. For the cases where 2« is equal to 2 or 4, the Theorem is obviously true. Thus, in all that follows we assume 6 = 2«. Let A= [Pi • • • P2n] denote any polygon having the points of 2 as vertices and having at least one edge P¿Pf+i (subscripts reduced modulo 2«) of type Lk with 1 _&_« — 2. It will be shown that, in this case, it is possible to construct a polygon longer than A. The vertices Ri and Pi+1 define the following partition of B : PiWP2W {Rit Pi+1}, where Bi is the component of B— {P„ P»+i} containing exactly k — 1 points of 2. We first show that there are at least three edges of A having both vertices in P2 (only two of these edges will be used in
Broadband Brillouin slow light based on multifrequency phase modulation in optical fibers

We theoretically analyze and experimentally demonstrate broadband Brillouin slow light using multiple equal-amplitude spectral lines generated by multifrequency phase modulation. The theoretical analysis shows that 4n−1 equal-amplitude spectral lines can be obtained if the modulation signal comprises the fundamental frequency and the odd harmonic waves, where n denotes the number of frequency components in the modulation signal. In experiment, 7 and 11 equal-amplitude spectral lines are obtained and Brillouin bandwidths of 340 and 570 MHz are gained, respectively. The experimental results also indicate that the slope of the broadening factor for the delayed signal decreases in the case of broad and flattened Brillouin gain spectrum.
Linear Preservers of D-majorization

An even signed permutation matrix is a matrix that contains precisely one 1 or − 1 in each row and each column and all other entries equal to zero with the property that the number of − 1s is even. In this paper, using even signed permutation matrices, the concept of D-majorization is introduced. Then, the linear preservers of D-majorization on R n and M n , m are characterized
Helical antenna for exciting azimuthally asymmetric Alfvén waves

A new coupler for exciting azimuthally asymmetric Alfven waves has been experimentally investigated. The coupler, which consists of four symmetrical helical straps wound around the vacuum vessel, is driven by a four‐phase rf source. Waves excited by the coupler vary azimuthally as exp(jmϑ), where m can be chosen to be either +1 or −1. The coupler exhibits a strong propagation directionality and is capable of launching waves whose wavelengths differ considerably from its own. Loading measurements indicate an equivalent coil impedance, with a plasma load, of 1.2–3.9 Ω, which depends on the excitation frequency and the sign of m. The m=−1 wave was observed to propagate above and below ωci and was identified as the fast wave. The m=+1 wave was observed only below ωci as the slow wave. No m=+1 fast wave or m=−1 slow wave was observed.
Rheology of a suspension of long plates in a Poiseuille flow

An analytical study of a suspension of long solid plates in a plane Poiseuille geometry is presented. The flow rate, the dissipation, and the apparent viscosity η (≡η0Q0/Q, η0 is the fluid viscosity, and Q0 and Q the flow rates with and without particle, for a given pressure drop) are determined as a function of the underlying structure. For a single particle, it is found that both dissipation and flow rate are maximal, for a given pressure drop, when the particle is at the center, while η is minimal. We provide analytical results for these quantities for a set of N particles distributed in an arbitrary fashion in the channel. This is exploited for a periodic distribution of N particles. The dissipation is found to be quasi-linear as a function of the wavelength of the structure and is a nontrivial nonlinear function of the volume fraction.
A nonparametric test for proving noninferiority in clinical trials with ordered categorical data

We consider the problem of proving noninferiority when the comparison is based on ordered categorical data. We apply a rank test based on the Wilcoxon–Mann–Whitney effect where the asymptotic variance is estimated consistently under the alternative and a small‐sample approximation is given. We give the associated 100(1−α)% confidence interval and propose a formula for sample size determination. Finally, we illustrate the procedure and possible choices of the noninferiority margin using data from a clinical trial. Copyright © 2003 John Wiley & Sons, Ltd.
Periodic traveling compression regions during quiet geomagnetic conditions and their association with ground Pi2

Recently, Keiling et al. (2006) showed that periodic (~90 s) traveling compression regions (TCRs) during a substorm had properties of Pi2 pulsations, prompting them to call this type of periodic TCRs "lobe Pi2". It was further shown that time-delayed ground Pi2 had the same period as the lobe Pi2 located at 16 R E , and it was concluded that both were remotely driven by periodic, pulsed reconnection in the magnetotail. In the study reported here, we give further evidence for this association by reporting additional periodic TCR events (lobe Pi2s) at 18 R E all of which occurred in succession during a geomagnetically very quiet, non-substorm period. Each quiet-time periodic TCR event occurred during an interval of small H -bay-like ground disturbance ( H bays were superposed by Pi2s. These ground Pi2s are compared to the TCRs in the tail lobe (Cluster) and both magnetic pulsations and flow variations at 9 R E inside the plasma sheet (Geotail). The main results of this study are: (1) Further evidence is given that periodic TCRs in the tail lobe at distances of 18 R E and ground Pi2 are related phenomena. In particular, it is shown that both had the same periodicity and occurred simultaneously (allowing for propagation time delays) strongly suggesting that both had the same periodic source. Since the TCRs were propagating Earthward, this source was located in the outer magnetosphere beyond 18 R E . (2) The connection of periodic TCRs and ground Pi2 also exists during very quiet geomagnetic conditions with PBIs present in addition to the previous result (Keiling et al., 2006) which showed this connection during substorms. (3) Combining (1) and (2), we conclude that the frequency of PBI-associated Pi2 is controlled in the outer magnetosphere as opposed to the inner magnetosphere. We propose that this mechanism is pulsed reconnection based on previous results which combined modeled results and observations of substorm-related periodic TCRs and ground Pi2. (4) We show that TCRs with small compression ratios (ΔB/B 1% (which are more commonly studied). (5) Finally, it is noted that both quiet time and substorm-related periodic TCRs had remarkably similar periods in spite of the drastically different geomagnetic conditions prevailing during the events which poses the important question of what causes this periodicity under these different conditions.
Carrier relaxation through two-electron process during photoconduction in highly UV sensitive quasi-one-dimensional ZnO nanowires

We have investigated the carrier relaxation process during photoconduction in quasi-one-dimensional (Q1D) ZnO nanowires (NWs) of diameters 29–36nm on different substrates using photocurrent transient measurements. Ultraviolet (UV) sensitive NWs show around three to four orders of change in the photo-to-dark current ratio. Under steady UV illumination, the photocarrier relaxation occurs through two-electron process—carrier loss due to the trapping by the surface states and recombination at the deep defect states. The results demonstrate that the carrier relaxation during photoconduction in Q1D NWs of diameter comparable to the Debye length is also dominated by the surface states.We have investigated the carrier relaxation process during photoconduction in quasi-one-dimensional (Q1D) ZnO nanowires (NWs) of diameters 29–36nm on different substrates using photocurrent transient measurements. Ultraviolet (UV) sensitive NWs show around three to four orders of change in the photo-to-dark current ratio. Under steady UV illumination, the photocarrier relaxation occurs through two-electron process—carrier loss due to the trapping by the surface states and recombination at the deep defect states. The results demonstrate that the carrier relaxation during photoconduction in Q1D NWs of diameter comparable to the Debye length is also dominated by the surface states.
Neural Network Analysis Based on Data Parallelism

With the development of Internet technology, many image data emerge on the Internet, and deep learning algorithms can extract abstract features from these data for image classification by using multi-layer nonlinear transformation. Therefore, deep learning algorithm has become a research hotspot in image processing. Aiming at the complex semantic features of images, an efficient deep learning algorithm has essential research significance for extracting and analyzing the semantic information about images quickly and effectively. This paper mainly explores the application of deep learning in image classification. Three neural models, LeNet, VGG, and ResNet are selected to test CIFAR10, and their training duration and accuracy are compared. Secondly, this paper further explores the impact of trying three neural network models on different graphics cards on their performance, and further researches and learns the application of these models. Finally, this paper tests the data parallelism solution of PyTorch, and the results and problems of the three models in this process are analyzed.
The effectiveness of different machine learning algorithms in classifying pulsar stars and the impact of data preparation

With massive improvements in technology, astronomers have been uncovering impressive findings of the mysteries of the universe. At the same time, new technology is able to do more and more of the tasks usually given to people, especially when it comes to handling big pieces of data. As such, more jobs are being replaced by machines in the modern industrial age, which may very well include the jobs of astronomers. To investigate the potential of machine learning in astronomy and its effect on the livelihoods of astronomers, this paper aims to demonstrate the capabilities of machine learning algorithms in completing tasks usually done by astronomers, which in this case the identifying pulsar stars. Astronomers study these stars extensively to learn about extreme states of matter and explore different solar systems. This paper introduces various classification algorithms to perform the task of identifying pulsar stars from data of radio wave emissions in the universe. Two distinct methods of dealing with missing values were also used. Once the algorithms were applied to the dataset, the results were recorded and analyzed, mainly focusing on the accuracy of each model. From the results, all the models yielded accuracies above 90%. In addition, the models performed better on average with data preparation using the drop method compared to the average value method. These results provide extensive evidence that machine learning can perform certain tasks commonly performed by astronomers themselves. At the moment they cannot replace astronomers, but in the future, it has a possibility.
Research on parking guidance system based on computer vision

The rapid pace of urbanization has made the urban parking problem more and more important, and various regions have introduced corresponding policies and measures to solve the parking problem, such as building large parking plants, introducing intelligent systems, etc. However, the number of parking spaces in large parking plants is large, the spatial distribution is complex, and it is difficult to find parking spaces. It is very important to improve parking efficiency through intelligent parking guidance and management. The parking space recognition system based on image recognition technology of computer vision can obtain real-time parking space utilization. The vehicle guidance system based on the generalized shortest path can guide incoming vehicles, reduce the time for vehicles to wait and find parking spaces. As the core module of the parking intelligent management system, the intelligent parking space recognition system and vehicle guidance system can significantly improve the parking efficiency.
A 128-channel time-to-digital converter based on the 24-phase shift-clock sampling method for RPC

The Resistive Plate Chamber (RPC) are widely used in high energy physics (HEP) experiments. In recent years, new designs and application scenarios of RPCs abound, and an advanced time-to-digital converter (TDC) system is in demand. The TDC implemented in the field-programmable gate array (FPGA) is widely used in HEP experiments with changeable conditions as a flexible time measurement method. This article presents a multi-phase shift-clock sampling FPGA-based TDC with 128 channels. The TDC module is implemented in a Xilinx Kintex-7 FPGA. The sampling clock period (2.22 ns) is subdivided into 24 phases to achieve finer time resolution. The TDC performance measurements show that the root-mean-square (RMS) time resolution of the TDC module in the time interval measurement is 45.3 ∼ 57.7 ps, and the integral nonlinearity (INL) is smaller than 0.2368 least significant bit (LSB). In addition, some target designs are made to adapt to the application scenarios. This article also shows measurement results acquired from an RPC by this TDC. This TDC was used to measure the RPC efficiency plateau and the TOT of the RPC readout signal.
Dynamics of Holes in Antiferromagnetic State

Dynamics of holes in the antiferromagnetic state on the square lattice is studied. The dispersion curves, density of states and eigenfunctions of holes are calculated by using the t - J and t - t '- J models. It is found that the hole moves in the antiferromagnetic state being accompanied by spin distortion around it. The dispersion curves consist of almost continuous band and the low energy band splitting from it. The low energy band is caused by a motion of holes mediated by the quantum spin fluctuations and is rather sensitive to the sign and magnitude of the second near-neighbor hopping integral t '. The spectra of the optical conductivity and the Raman scattering due to two spin excitations around holes are calculated and compared with the experimental results. It is shown that spectra in the mid-infrared region appear in both the optical conductivity and Raman scattering.
Monocular Depth Estimation Network Based on Swin Transformer

Estimating depth from a single image is challenging because a single 2D image may correspond to many different 3D scenes with the same depth. While most deep learning based depth prediction methods extract depth features using small convolutional kernels with small receptive fields, which results in deformed depth edges and inaccurate depth values of distant objects in the depth estimation results. Aiming at this problem, we propose a depth estimation network based on Swin Transformer and the encoder-decoder structure. We construct the encoder using the Swin Transformer network, which can encode long-range spatial dependency and extract features on various scales and across different channels. The decoder of the proposed network is in charge of fusing the features from the encoder by the operations of interpolation, concatenation, and convolution. Experiments on KITTI and NYUv2 datasets show that our proposed network can get more accurate depth edges and depth values than the state-of-the-art methods.
Research on non-time-series data filling methods based on feature evaluation

With the rapid development of the information age, a large amount of data is used in popular research areas such as data mining. Missing data has a very serious impact on both the process and the result of data mining, and it is important to find out how to fill the missing values accurately and efficiently. In this paper, we propose a method to optimally fill the missing values based on the backpropagation of evaluation functions for non-time-series data. Based on both the target value error and its own error after filling, four classical filling methods, namely mean, interpolation, model prediction, and K-nearest neighbor, are considered for selection. Finally, single-model padding and multi-model weighted padding schemes are compared, and the results show that the padding method with the highest fitness value is selected to work best for data with different degrees of missingness in different datasets.
Statistical Learning Based Wireless Channel Parameter Estimation for Power Internet of Things

With the rapid increase in the number of sensors in Power Internet of Things (PIOT), the data volume surges and efficient communications are needed. Precise estimation of delay spread is critical to improve the communication performance. In this paper, we propose a statistical learning (SL) based root mean square delay spread (RMSDS) estimation method, which consists of offline training and online estimation. During the offline training process, the instantaneous delay spread (IDS) for each data frame is firstly computed based on the known pilots. The acquired IDS is a random variable and its statistical parameter is related to the actual RMSDS, which is preset and known during offline training. Then, the functional relationship between the statistical parameter and the preset RMSDS is acquired through the SL algorithm. The acquired functional relationship can be used in the online estimation process to accurately estimate the RMSDS. Simulation results indicate that the proposed method can accurately estimate the RMSDS and greatly improve the bit error rate performance.
First results from the Faint Object Camera - SN 1987A

The first images of SN 1987A taken on day 1278 after outburst with the Faint Object Camera on board the Hubble Space Telescope are presented. The supernova is well detected and resolved spatially in three broadband ultraviolet exposures spanning the 1500-3800 A range and in a narrow-band image centered on the forbidden O III 5007 line. Simple uniform disk fits to the profiles of SN 1987A yield an average angular diameter of 170 + or - 30 mas, corresponding to an average expansion velocity of 6000 km/s. The derived broadband ultraviolet fluxes, when corrected for interstellar absorption, indicate a blue ultraviolet spectrum corresponding to a color temperature near 13,000 K. 24 refs.
What determines the lateral bonding speed in silicon wafer bonding

In silicon wafer bonding, the initial contact area spreads laterally with a typical speed on the order of 10 mm/s. We observed that this lateral bonding speed increases with decreasing ambient pressure, and is independent of the distance of the contact front to the rim of the wafers and independent of wafer thickness. From these results, we conclude that the lateral bonding speed is mainly determined by pressing the ambient gas out between the two wafers from a very localized area close to the propagating bonding front.
Reducing Cross-Cultural Comparability Bias Obtained with Measurement Invariance Analysis by Means of Anchoring Vignettes in Heterogeneous Refugee Samples

Background: Configural, metric, and scalar measurement invariance have been indicators of bias-free statistical cross-group comparisons, although they are difficult to verify in the data. Low comparability of translated questionnaires or the different use of response formats by respondents might lead to rejection of measurement invariance and point to comparability bias in studies that use different languages. Anchoring vignettes have been proposed as a method to control for the different use of response formats by respondents (RC-DIF) as implemented by means of rating scales. We evaluate the question whether the comparability bias obtained by means of measurement invariance analysis can be reduced by means of anchoring vignettes or by considering socio-demographic heterogeneity as an alternative approach. Methods: We use the Health System Responsiveness (HSR) questionnaire in English and Arabic in a refugee population. We collected survey data in English (n = 183) and Arabic (n=121) in a random sample of refugees in the third largest German federal state. We conducted multiple-sample Confirmatory Factor Analyses (MGCFA) to analyse measurement invariance and compared the results when 1) using rescaled data on the basis of anchoring vignettes (non-parametric approach), 2) including information on DIF from the analyses with anchoring vignettes as covariates (parametric approach) and 3) including socio-demographic covariates. Results: For the HSR, every level of measurement invariance between Arabic and English questionnaires was rejected. Implementing rescaling on the basis of anchoring vignettes provided superior results over the initial MGCFA analysis, since configural, metric and scalar invariance could not be rejected. When using solely socio-demographic covariates, scalar measurement invariance could not be rejected, but configural and metric invariance had to be rejected. Conclusions: Surveys may consider anchoring vignettes as a method to obtain more satisfactory results of measurement invariance analyses; however, socio-demographic information cannot be included in the models as a standalone method. More research on the efficient implementation of anchoring vignettes and further development of methods to incorporate them when modelling measurement invariance is needed.