Miracle-dz/UniFAR-FTUs huggingface dataset:
Rate Splitting Multiple Access for Sum-Rate Maximization in IRS Aided Uplink Communications

In this paper, an intelligent reflecting surface (IRS) aided uplink (UL) rate-splitting multiple access (RSMA) system is investigated for dead-zone users where the direct link between the users and the base station (BS) is unavailable and the UL transmission is carried out only through IRS. In the considered RSMA system, a message of each user is split into several sub-messages and each part contributes to the rate of that user and depending upon split proportions BS decodes them using appropriate decoding order. The problem of sum-rate maximization is formulated to jointly design the optimal power allocation at each UL user, passive beamforming at the IRS under optimal decoding order of sub-messages. Due to non-convexity and discrete non-linear programming of the formulated problem, the original problem is intractable and hence, we decouple the problem into different sub-problems in which the problems of power allocation and passive beamforming are alternatively solved under using successive convex approximation and Riemaniann conjugate gradient algorithms, respectively. Moreover, the decoding order strategy is analytically derived which confirm that the optimal decoding order strategy depend upon decreasing order of channel gain of users and increasing order of split proportions of sub-messages. Later, the unified solution based on block-coordinate descent (BCD) algorithm is proposed. Simulation results validate that the proposed decoding order scheme attains performance closer to the optimal solution with low computational complexity. Moreover, the proposed IRS aided RMSA system outperforms the system with non-orthogonal multiple access (NOMA) and orthogonal multiple access (OMA) schemes in terms of achievable sum-rate throughput.
LEVERAGING 3D-HST GRISM REDSHIFTS TO QUANTIFY PHOTOMETRIC REDSHIFT PERFORMANCE

We present a study of photometric redshift accuracy in the 3D-HST photometric catalogs, using 3D-HST grism redshifts to quantify and dissect trends in redshift accuracy for galaxies brighter than JHIR > 24 with an unprecedented and representative high-redshift galaxy sample. We find an average scatter of 0.0197 ± 0.0003(1 + z) in the Skelton et al. photometric redshifts. Photometric redshift accuracy decreases with magnitude and redshift, but does not vary monotonically with color or stellar mass. The 1σ scatter lies between 0.01 and 0.03 (1 + z) for galaxies of all masses and colors below z < 2.5 (for JHIR < 24), with the exception of a population of very red (U − V > 2), dusty star-forming galaxies for which the scatter increases to ∼0.1 (1 + z). We find that photometric redshifts depend significantly on galaxy size; the largest galaxies at fixed magnitude have photo-zs with up to ∼30% more scatter and ∼5 times the outlier rate. Although the overall photometric redshift accuracy for quiescent galaxies is better than that for star-forming galaxies, scatter depends more strongly on magnitude and redshift than on galaxy type. We verify these trends using the redshift distributions of close pairs and extend the analysis to fainter objects, where photometric redshift errors further increase to ∼0.046 (1 + z) at . We demonstrate that photometric redshift accuracy is strongly filter dependent and quantify the contribution of multiple filter combinations. We evaluate the widths of redshift probability distribution functions and find that error estimates are underestimated by a factor of ∼1.1–1.6, but that uniformly broadening the distribution does not adequately account for fitting outliers. Finally, we suggest possible applications of these data in planning for current and future surveys and simulate photometric redshift performance in the Large Synoptic Survey Telescope, Dark Energy Survey (DES), and combined DES and Vista Hemisphere surveys.
MPR-GAN: A Novel Neural Rendering Framework for MLS Point Cloud With Deep Generative Learning

Efficient point cloud visualization is indispensable for practical applications. In the context of point cloud visualization, 3-D rendering can be viewed as the kernel that transforms 3-D points into a 2-D scene image. Compared with traditional point-based rendering (PBR), neural image-based rendering (NIBR) has gradually emerged as a feasible solution for point cloud rendering. To efficiently render sparse and colorless mobile laser scanning (MLS) point cloud, we propose a novel neural rendering framework based on deep generative learning, named MLS point cloud rendering with generative adversarial network (MPR-GAN). In this framework, perspective projection with intrinsic parameter scaling and cumulative distribution normalization is first utilized to transform the 3-D point cloud into a compact 2-D image; a conditional generative adversarial network (CGAN)-based rendering model is then proposed to generate a photorealistic scene image from the projected 2-D image. In this CGAN model, the asymmetric encoder–decoder generator can implement inpainting and true colorization using context feature capturing and edge information perception; a multiscale discriminator is built to guarantee the model output with global consistency and local details. Moreover, a hybrid loss function is designed to improve the visual quality of the generated images with similarity constraints from both the content and the structure. Two public MLS point cloud datasets are selected and employed to carry out extensive evaluation using MPR-GAN and other baseline frameworks. The experimental results demonstrate that MPR-GAN achieves the state-of-the-art rendering performance in terms of peak signal-to-noise ratio (PSNR) and structural similarity (SSIM). Furthermore, the efficiency analysis shows that MPR-GAN can support real-time rendering, achieving end-to-end rendering from raw points.
Perfecting Reform in Latin America: What Role for the State?

COMPETITION POLICY, DEREGULATION, AND MODERNIZATION IN LATIN AMERICA. Edited by Moises Nairn and Joseph Tulchin. (Boulder, Colo.: Lynne Rienner, 1999. Pp. 293. $55.00 cloth.) GROWTH, EMPLOYMENT, AND EQUITY: THE IMPACT OF THE ECONOMIC REFORMS IN LATIN AMERICA AND THE CARIBBEAN. By Barbara Stallings and Wilson Peres. (Washington, D.C.: ECLAC and the Brookings Institution, 2000. Pp. 252. $22.95 cloth.) THE IMPACT OF PRIVATIZATION IN THE AMERICAS. Edited by Melissa H. Birch and Jerry Haar. (Coral Gables, Fla.: North-South Center Press, 2000. Pp. 256. $26.95 paper.) THE POLITICS OF TELECOMMUNICATIONS IN MEXICO: PRIVATIZATION AND STATE-LABOR RELATIONS, 1982-1995. By Judith Clifton. (New York: St. Martin's, 2000. Pp. 277. $69.95 cloth.) PRIVATIZATION SOUTH AMERICAN STYLE. By Luigi Manzetti. (New York: Oxford University Press, 1999. Pp. 373. $74.00 cloth.) REFORMING THE REFORMS IN LATIN AMERICA: MACROECONOMICS, TRADE, FINANCE. By Ricardo Ffrench-Davis. (New York: St. Martin's, 2000. Pp. 232. $65.00 cloth.) REGULATORY POLICY IN LATIN AMERICA: POST-PRiVATIZATION REALITIES. Edited by Luigi Manzetti. (Coral Gables, Fla.: North-South Center Press, 2000. Pp. 301. $55.00 cloth.)
FFT Analysis and Motion Classification of EMG Signals

Bu çalışmada EMG sinyallerinin frekans analizi yapılarak elde edilen veriler ile hareket sınıflandırması yapmak amaçlanmıştır. Üç kanaldan toplanan EMG sinyalleri uygun pencerelere ayrılarak her bir pencereye” hilbert “ zarflama yöntemi uygulanmış ve FFT katsayıları hesaplanmıştır. Kaydedilen EMG sinyallerinin frekans spektrumları incelenmiştir. Bu katsayıları ile bir sınıflandırma algoritmasında kullanmak amacıyla her bir pencerenin ağırlıklı frekans bileşeni hesaplanmıştır. Elde edilen veriler YSA (Yapay sinir Ağları) algoritmasının eğitilmesi amacıyla kullanılmış ve bu işlem EMG sinyallerinin sınıflandırılması amacıyla kullanılmıştır. Sınıflandırma işlemi sonucunda özellikle aynı kas gruplarındaki kasılma kuvvetleri ile birbirinden ayırt edilebilen hareketlerin yalnızca frekans domeninde değil zaman domeninde de incelenmesi gerektiği sonucuna varılmıştır.
Modelling the shapes of the largest gravitationally bound objects

We combine the physics of the ellipsoidal collapse model with the excursion set theory to study the shapes of dark matter haloes. In particular, we develop an analytic approximation to the non-linear evolution that is more accurate than the Zeldovich approximation; we introduce a planar representation of halo axial ratios, which allows a concise and intuitive description of the dynamics of collapsing regions and allows one to relate the final shape of a halo to its initial shape; we provide simple physical explanations for some empirical fitting formulae obtained from numerical studies. Comparison with simulations is challenging, as there is no agreement about how to define a non-spherical gravitationally bound object. Nevertheless, we find that our model matches the conditional minor-to-intermediate axial ratio distribution rather well, although it disagrees with the numerical results in reproducing the minor-to-major axial ratio distribution. In particular, the mass dependence of the minor-to-major axis distribution appears to be the opposite to what is found in many previous numerical studies, where low-mass haloes are preferentially more spherical than high-mass haloes. In our model, the high-mass haloes are predicted to be more spherical, consistent with results based on a more recent and elaborate halo finding algorithm, and with observations of the mass dependence of the shapes of early-type galaxies. We suggest that some of the disagreement with some previous numerical studies may be alleviated if we consider only isolated haloes.
Competition between the Superconducting Proximity Effect and Coulomb Interactions in a Graphene Andreev Interferometer

We have investigated transport through graphene Andreev interferometers exhibiting reentrance of the superconducting proximity effect. We observed a crossover in the Andreev conductance oscillations as a function of gate voltage ($V_{BG}$). At high $V_{BG}$ the energy-dependent oscillation amplitude exhibits a scaling predicted for non-interacting electrons, which breaks down at low $V_{BG}$. The phenomenon is a manifestation of electron-electron interactions, whose main effect is to shorten the single-particle phase coherence time $\tau_\phi$. These results indicate that graphene provides a useful experimental platform to investigate the competition between superconducting proximity effect and interactions.
First Demonstration of Ferroelectric Tunnel Thin-Film Transistor Nonvolatile Memory With Polycrystalline-Silicon Channel and HfZrO Gate Dielectric

In this work, the nonvolatile memory constructed on the tunnel thin-film transistors (tunnel-TFTs) using polycrystalline-silicon channel featuring ferroelectric HfZrOx layer is demonstrated for the first time. When the pulse voltages of program (PG) and erase (ER) are, respectively, 3.5 and −2 V with the pulsewidth of $1 ~\mu \text{s}$ , the threshold voltage modulation amount of the ferroelectric tunnel-TFT can reach −0.524 and 0.496 V, respectively. In addition, the endurance behaviors of the ferroelectric tunnel-TFT exhibit a strong PG/ER pulsewidth dependence. The wake-up effect of the ferroelectric layer becomes more pronounced as increasing the PG/ER pulsewidth. Moreover, the increase of the PG/ER pulsewidth also causes the ferroelectric tunnel-TFT to be subjected to the electrical dynamic stress effect, leading to the degradation of the subthreshold swing (SS) and the electron trapping effect. When the pulsewidth is 100 ns, the endurance is mainly dominated by the fatigue effect of the ferroelectric layer and the degradation of the SS. When the pulsewidth increases to $1 ~\mu \text{s}$ , the endurance is mainly dominated by the electron trapping effect of the ferroelectric layer in addition to the fatigue effect. The retention of the ferroelectric tunnel-TFT exhibits stable behavior at 50 °C. Consequently, the ferroelectric tunnel-TFT exhibits sufficient electrical performance and can be integrated with display panels and various sensor systems on smart wearable devices for edge computing applications.
Bearing Fault Diagnosis Method Based on Complementary Feature Extraction and Fusion of Multisensor Data

Bearing is the key component of rotating machinery, so the fault diagnosis of bearing is important to improve the reliability of equipment operation. In recent years, the feature fusion method has been extensively explored in the fault diagnosis of bearings. However, the complementary fault features from multisensor data are difficult to be fully extracted, which will lead to the failure of achieving the expected diagnostic accuracy. This article proposes a multitask network for bearing fault diagnosis. The multihead attention is improved by 1-D convolutional neural network (CNN) to extract the deep features of multisensor data. The task of feature source discrimination allows the extracted features to contain complementary fault information as much as possible. Based on the complementary fault features, the accuracy of the fault category classification task can be greatly improved. To verify the effectiveness of the proposed method, the experiments are conducted on Paderborn bearing data set. The results show that the accuracy of the proposed method is greatly improved, which is much higher than the other methods.
Machine learning based asymptotic homogenization and localization: Predictions of key local behaviors of multiscale configurations bearing microstructural varieties

In this article, a general framework is devised for reliable predictions over the local behaviors, such as the failure strength and stress intensity factor, of multiscale configurations bearing microstructural varieties. Methodologically, a mutually complementing use of asymptotic analysis and machine learning is addressed. On using asymptotic analysis, we manage to identify several key but implicit interrelationships, which link the local quantities of our interest with other onsite mean‐field quantities. Then these identified interrelationships are represented by neural networks in an offline stage, where the training data are also generated based on the formulation devised through asymptotic analysis. Then for the upcoming online simulation, those desired local behaviors can be quickly captured without resolving the microstructural configurations. Numerical examples are presented showing that for relatively complex multiscale configurations, the predicting error here can be theoretically controlled at a satisfactory level.
Research on Underwater Sound Source Localization Based on NLM-EEMD and FCM-Generalized Quadratic Correlation

The accuracy of underwater sound source localization depends on the preprocessing effect of signal denoising and delay estimation performance. In order to meet the needs of high-precision underwater positioning, this article studies a time delay estimation method based on nonlocal mean-enforced mean empirical mode decomposition (NLM-EEMD) autocorrelation denoising preprocessing and fuzzy C-means clustering (FCM)-generalized quadratic for underwater sound source localization technology. The theories such as NLM, EEMD, FCM, and generalized quadratic correlation delay estimation are studied in detail, and the speech signal of the test library in the TIMIT standard library is selected for simulation analysis, which verifies the correctness of the delay estimation method. Experiments were carried out in a larger outdoor pool. The analysis results show that the NLM-EEMD adaptive denoising method effectively reduces noise interference and improves the quality of EEMD decomposition and the FCM-generalized quadratic correlation method increases the correlation between two signals. The time delay estimation accuracy is improved, and the positioning accuracy is 48.66% higher than that of the direct generalized cross-correlation method.
Vertical transport of subwavelength localized surface electromagnetic modes

Transport of subwavelength electromagnetic (EM) energy has been achieved through near‐field coupling of highly confined surface EM modes supported by plasmonic nanoparticles, in a configuration usually on a two‐dimensional (2D) substrate. Vertical transport of similar modes along the third dimension, on the other hand, can bring more flexibility in designs of functional photonic devices, but this phenomenon has not been observed in reality. In this paper, designer (or spoof) surface plasmon resonators (‘plasmonic meta‐atoms’) are stacked in the direction vertical to their individual planes in demonstrating vertical transport of subwavelength localized surface EM modes. The dispersion relation of this vertical transport is determined from coupled‐mode theory and is verified with a near‐field transmission spectrum and field mapping with a microwave near‐field scanning stage. This work extends the near‐field coupled resonator optical waveguide (CROW) theory into the vertical direction, and may find applications in novel three‐dimensional slow‐light structures, filters, and photonic circuits.
A Rare Case of Bilateral Orbital Metastases From Rectal Adenocarcinoma

Colorectal carcinoma is among the commonest malignancies in the World. However, metastases from rectal carcinomas to the orbit are extremely rare. Only a few such cases have been reported in the literature till date. We report a case of adenocarcinoma of the rectum in a 27-year-old male with bilateral orbital metastases who is currently undergoing palliative radiotherapy. Our aim is to highlight the role of imaging in the diagnosis and management of orbital metastatic disease.
Approximate boundary conditions for electromagnetic fields in electrodmagnetics

The results of an analytical review of literature sources on the use of approximate boundary conditions for electromagnetic fields of impedance type in solving boundary value problems of electromagnetism for more than 80 recent years are presented. During this period, the impedance approach was generalized to various electrodynamic problems, in which its use made it possible to significantly expand the limits of mathematical modeling, which adequately considers the physical properties of real boundary surfaces. More than eighty years have passed since the publication of approximate boundary conditions for electromagnetic fields. The meaning and value of these conditions lies in the fact that they allow solving diffraction problems about fields outside well-conducting bodies without considering the fields inside them, which greatly simplifies the solution. Since then, numerous publications have been devoted to the application of impedance boundary conditions, the main of which (according to the authors) are presented in this paper. Particular attention is paid to the characteristics of electrically thin impedance vibrators and film-type surface structures as a personal contribution of the authors to the theory of impedance boundary conditions in electromagnetism. The subject of research in this article is the analysis of the limits and conditions for the correct application of impedance boundary conditions. The goal is to systematize the results of using the concept of approximate impedance boundary conditions for electromagnetic fields in problems of electrodynamics based on an analytical review of literature sources. The following results were obtained. The types of metal-dielectric structures are presented, for which methods of theoretical determination of the values of surface impedances for film-type structures are currently known, which are the most promising for creating technological control elements on their basis in centimeter and millimeter wavelength devices. Conclusions. The materials of this paper do not pretend to be a complete reference book covering all the results and aspects of the development of the concept of approximate impedance type boundary conditions in problems of electromagnetism over the past decades. Simultaneously, the authors hope that the information presented in this paper will be useful to specialists in the field of theoretical and applied electrodynamics, as well as graduate students, young scientists and students who are just mastering radiophysics and radio engineering specialties.
Relativistic Spectra of Hot Black-Hole Winds

We examine hybrid thermal-nonthermal synchrotron spectra from a spherically symmetric, optically-thin wind, taking into account the relativistic effect. In relativistic flow from the central object, due to the relativistic beaming effect, the observed spectra often shift towards high frequency and high intensity directions. In optically thin outflows, however, we find that the intensity of the observed spectra decreases compared with that of the emitted ones, although the peak frequency shifts towards the high-frequency direction. This is because in the optically thin outflows we can see the far-side flows that go away from the observer. We thus carefully consider optically thin relativistic flows around a black hole, such as Sgr A � .
Investigation of plasmid-mediated quinolone resistance genes in carbapenem resistant Enterobacterales

Fluoroquinolones, are effective agents both against gram-positive and gram-negative bacteria. Quinolones show bactericidal effect as a result of inhibition of DNA gyrase and topoisomerase IV enzymes. Main quinolo resistance mechanisms are chromosomal mutations in these enzymes and decreased intracellular accumulation due to efflux pumps or decreased membrane uptake. Recently a new quinolone resistance mechanism mediated by plasmids has been defined. These plasmids carry genes called as qnr. Qnr genes do not cause quinolone resistance but they cause decreased quinolone susceptibility and lead to higher minimum inhibitory concentrations. Currently there are qnrA, qnrB, qnrC, qnrD and qnrS genes. This study was aimed to investigate the presence of plasmid-mediated quinolone resistance determinants in carbapenem resistant Enterobacterales isolates. A total 154 carbapenem resistant Enterobacterales isolates were included in the study. Presence of qnrA, qnrB, qnrC, qnrD and qnrS genes were investigated by multiplex polymerase chain reaction (PCR) method. The results of the PCR amplification revealed that qnrA was detected in two isolates (E6, E85) (1.29%), qnrB was detected in 12 isolates (8.4%) (E32, E43, E46, E61, E62, E84, E94, E149, E 166, E167, E177, E179) and qnrS was detected in six isolates (E15, E25, E57, E63, E70, E80) (4.54%). And one isolate (E9) was both positive for qnrB and qnrS. QnrC and qnrD were not detected in any isolates. Transferable quinolone resistance due to the dissemination of qnr genes may have important impacts in terms of infection control and treatment problems. Survey of plasmid mediated quinolone resistance will help to determine the size of the issue and guide the measures that should be taken to avoid escalation of resistance and dissemination problem.
Voltage Correlation-Based Principal Component Analysis Method for Short Circuit Fault Diagnosis of Series Battery Pack

This article concerns the issue of data-driven fault diagnosis for series lithium-ion battery pack. A voltage correlation-based statistical analysis method is proposed. First, the voltage of each cell within the battery pack is measured independently, and the correlation coefficient (CC) between the voltages of adjacent cells is calculated. Then, all the CC signals under normal conditions are used to train a principal component analysis model, on the basis of which synthetic statistic and kernel density estimation-based thresholds are designed for simultaneously monitoring all the measured CC signals at each sampling instant. Once a fault is detected, an accumulative relative contribution plot algorithm is immediately used to isolate which CC signal has a problem and locate the faulty cell through a cross-positioning strategy. The experimental results on a realistic test platform for series battery pack show that the new method provides accurate and reliable assessments for different fault specifics, and it performs better than the state-of-the-art CC methods in terms of parallel processing capability, sensitivity to weak short circuit faults, and robustness to window width.