Miracle-dz/UniFAR-FTUs huggingface dataset:
Direction-of-Arrival Estimation Based on DNN for Closely Spaced Signals

The performance of the traditional direction-of-arrival (DOA) estimation algorithms would deteriorate seriously for closely spaced sources, especially at low SNR. To tackle the accurate DOA estimation for closely spaced sources, the article proposes a new algorithm based on a deep neural network (DNN). The DNN is designed to learn the mapping relationship between signals and their DOAs. In the training process, different low SNR samples will be used to train the neural network. With such a form, the DNN would enhance the robustness of DOA estimation under harsh environments. Simulation results demonstrate that the proposed algorithm outperforms the existing algorithms under challenging scenarios, especially for closely spaced sources at low signal-to-noise ratio (SNR).
Control of texture in image halftoning

In image halftoning, texture is one of the important parameters that has a major effect on image reproduction as well as perception. We propose a halftoning algorithm based on a numerical texture metric and on the threshold accepting algorithm, which provides control of the occurrence of specific textures in the halftoned image. To conserve the image information a simultaneous control of the graytone rendition is implemented. Moreover, additional parameters may be added to control further image characteristics. The algorithm permits control of textures composed of symmetric as well as asymmetric texels and a weighted balance among the different control parameters.
On the piston and sloshing modes in moonpools

So-called ‘moonpools’ are vertical openings through the deck and hull of ships or barges, used for marine and offshore operations, such as pipe laying or recovery of divers. In the present study rectangular moonpools of large horizontal dimensions are considered. The natural modes of oscillation of the inner free surfaces are determined, under the assumption of infinite water depth and infinite length and beam of the barges that contain the moonpools. The problem is treated in two and three dimensions, via linearized potential flow theory. Results are given for the natural frequencies and the associated shapes of the free surface, for wide ranges of the geometric parameters. Simple quasi-analytical approximations are derived that yield the natural frequencies. The most striking result is that the natural frequencies of the longitudinal sloshing modes increase without bounds when both the draught and the width decrease to zero, the length of the moonpool being kept constant. As a corollary the problem of waves travelling in a channel through a rigid ice sheet is addressed and their dispersion equation is derived. The same behaviour is obtained: the waves travel increasingly faster as both the draught and the width of the channel are reduced.
Design of Dielectric Resonant Antenna (DRA) Array for 77GHz Automotive Radar Application

A novel antenna design is proposed for 77GHz Millimeter- Wave angular radar applications. The proposed radar antenna consists of 14 longitudinal radiating slot elements and the same number of rectangular resonators fold above, a single-layer substrate integrated waveguide (SIW) feeding structure. To further improve the broad matching and gain characteristics, another coupled feeding structure is applied to the transition between rectangular waveguide (RWG) and SIW feeding network. Through simulation optimization, the antenna has $S_{11}< -10\text{dB}$ in the frequency band of $75.8\text{GHz}\sim 77.8\text{GHz}$, the peak gain of the antenna array is 13.6dB, sidelobe level (SLL) is −14.5 dB in the azimuth plane and the maximum half-power beamwidth (HPBW) is $100.3{}^{\circ}$.
Magnitude of the truncation error in sampling expansions of band-limited signals

Bounds are established for the truncation error in the sampling theorem for signals with radian bandwidth πW, W > 0. The assumptions are either differenfiability conditions upon the Fourier transform of the signal or on the rate of decay of the first derivative of the signal itself. Finally, our theorems are applied to two new examples, worked out in detail.
Fine Beam Tracking Using Spatio–Temporal Interpolation in Wireless Power Transfer Systems

The use of transmit beamforming in a radio-frequency wireless power transfer (WPT) system can improve the energy transmission efficiency by concentrating the transmit power in the angle of departure (AoD). Optimal beamforming requires information regarding the AoD or the channel between the transmitter and receiver. A previously proposed WPT system continually estimates the optimal AoD using custom-designed pilot signals, which are known as beam-steered pilot signals and are transmitted periodically at every frame. Herein, we propose a spatio–temporal interpolation technique to improve the accuracy of beam tracking for such a WPT system. Specifically, thin-plate spline interpolation is adopted in the space domain to overcome the limited angular resolution of the beam-steered pilot signals in a three-dimensional channel. In the time domain, polynomial interpolation is performed to track the changing AoD during consecutive frames. Numerical results show that the proposed technique can improve the WPT efficiency as well as the mean square error performance of the beamforming weight vector.
The growth of a mixing layer in a laminar channel

The effect of the wall-normal diffusion on the spanwise spreading of a steady passive scalar interface is computed for a laminar channel in which the Péclét number, $\Pe$, is high but the velocity profile is parabolic. Two regimes are found according to whether the dimensionless streamwise coordinate $\tilde{x}$ is smaller or larger than $\Pe$. In both cases the mixing layer spreads as $\tilde{x}^{1/2}$ to the lowest approximation in $\Pe^{-1}$, although with different numerical coefficients. When $\tilde{x},{\ll}\,\Pe$ there is a faster growth of order $\tilde{x}^{1/3}$ that is restricted to boundary layers near the wall. The intermediate region between those two limits is universal, and is computed numerically. Quantitative results are given that should be useful to experimentally measure diffusion coefficients. The results are easily generalizable to other velocity profiles.
A 64-QAM 94-GHz GaAs Transceiver with 18 dBm Output Power for High Data-Rate Communication

This paper presents a 90–96 GHz GaAs transceiver chip with printed on-board low-loss microstrip line to waveguide transition. By introducing power enhancing technique in the design of the double-balanced passive tripler of the LO multiplier chain, the impedance matching of the tripler is improved. Benefiting from the introduced high-pass matching network in the LO chain, the out-of-band unwanted harmonics suppression are improved to be over 70 dBc within the entire bandwidth, which makes the system have better spectral purity to support high-order modulation. The transmitter chip achieves a measured maximum output power of 18 dBm at 90 GHz and delivers a Psat of 17.4 to 18 dBm from 90 to 96 GHz. The receiver chip achieves a noise figure better than 5.1 dB. In the system wireless data transmission measurement, the transmitter and receiver chips are connected to horn antennas through the designed low-loss microstrip line to waveguide transition structure. The measured TX-to-RX EVM in 400 MHz 64QAM 5G NR signal is 4.86% at a 1 m distance. Compared to other state-of-arts that support high order modulation and to the best of the authors' knowledge, the transmitter's output power is the highest in the 94 GHz band.
Inducing Performance of Commercial Surgical Robots in Space

Pre-existing surgical robotic systems are sold with electronics (sensors and controllers) that can prove difficult to retroactively improve when newly developed methods are proposed. Improvements must be somehow “imposed” upon the original robotic systems. What options are available for imposing performance from pre-existing, common systems and how do the options compare? Optimization often assumes idealized systems leading to open-loop results (lacking feedback from sensors), and this manuscript investigates utility of prefiltering, such other modern methods applied to non-idealized systems, including fusion of noisy sensors and so-called “fictional forces” associated with measurement of displacements in rotating reference frames. A dozen modern approaches are compared as the main contribution of this work. Four methods are idealized cases establishing a valid theoretical comparative benchmark. Subsequently, eight modern methods are compared against the theoretical benchmark and against the pre-existing robotic systems. The two best performing methods included one modern application of a classical approach (velocity control) and one modern approach derived using Pontryagin’s methods of systems theory, including Hamiltonian minimization, adjoint equations, and terminal transversality of the endpoint Lagrangian. The key novelty presented is the best performing method called prefiltered open-loop optimal + transport decoupling, achieving 1–3 percent attitude tracking performance of the robotic instrument with a two percent reduced computational burden and without increased costs (effort).
An Updated Overview on the Role of Small Molecules and Natural Compounds in the “Young Science” of Rejuvenation

Aging is a gradual process that occurs over time which leads to a progressive decline of cells and tissues. Telomere shortening, genetic instability, epigenetic alteration, and the accumulation of misfolded proteins represent the main hallmarks that cause perturbed cellular functions; this occurs in conjunction with the progression of the so-called “aging clocks”. Rejuvenation aims to influence the natural evolution of such aging clocks and to enhance regenerative capacity, thus overcoming the limitations of common anti-aging interventions. Current rejuvenation processes are based on heterochronic parabiosis, cell damage dilution through asymmetrical cell division, the excretion of extracellular vesicles, the modulation of genetic instability involving G-quadruplexes and DNA methylation, and cell reprogramming using Yamanaka factors and the actions of antioxidant species. In this context, we reviewed the most recent contributions that report on small molecules acting as senotherapeutics; these molecules act by promoting one or more of the abovementioned processes. Candidate drugs and natural compounds that are being studied as potential rejuvenation therapies act by interfering with CDGSH iron-sulfur domain 2 (CISD2) expression, G-quadruplex structures, DNA methylation, and mitochondrial decay. Moreover, direct and indirect antioxidants have been reported to counteract or revert aging through a combination of mixed mechanisms.
CARMENES. V: non-cryogenic solutions for YJH-band NIR instruments

Currently, every single instrument using NIR detectors is cooled down to cryogenic temperatures to minimize the thermal flux emitted by a warm instrument. Cryogenization, meaning reaching very low operating temperatures, is a must when the K band is needed for the science case. This results in more complex and more expensive instruments. However, science cases that do not benefit from observing in the K band, like the detection of exoplanets around M dwarfs through the radial velocity technique, can make use of non-cryogenic instruments. The CARMENES instrument is implementing a cooling system which could allow such a solution. It is being built by a consortium of eleven Spanish and German institutions and will conduct an exoplanet survey around M dwarfs. Its concept includes two spectrographs, one equipped with a CCD for the range 550-950 nm, and one with HgCdTe detectors for the range from 950-1700 nm, covering therefore the YJH bands. In this contribution, different possibilities are studied to reach the final cooling solution to be used in CARMENES, all of them demonstrated to be feasible, within the requirements of the SNR requested by the science case.
On boundary kernels for distribution function estimation

The use of second order boundary kernels for distribution function estimation was recently addressed in the literature (C. Tenreiro, 2013, Boundary kernels for distribution function estimation, REVSTAT-Statistical Journal, 11, 169-190). In this note we return to the subject by considering an enlarged class of boundary kernels that shows it self to be especially performing when the classical kernel distribution function estimator suffers from severe boundary problems.
Contactless Stethoscope Enabled by Radar Technology

Contactless vital sign measurement technologies have the potential to greatly improve patient experiences and practitioner safety while creating the opportunity for comfortable continuous monitoring. We introduce a contactless alternative for measuring human heart sounds. We leverage millimeter wave frequency-modulated continuous wave radar and multi-input multi-output beamforming techniques to capture fine skin vibrations that result from the cardiac movements that cause heart sounds. We discuss contact-based heart sound measurement techniques and directly compare the radar heart sound technique with these contact-based approaches. We present experimental cases to test the strengths and limitations of both the contact-based measurement techniques and the contactless radar measurement. We demonstrate that the radar measurement technique is a viable and potentially superior method for capturing human heart sounds in many practical settings.
Weeds: An Insidious Enemy or a Tool to Boost Mycorrhization in Cropping Systems?

Weeds have always been considered an insidious enemy, capable of reducing crop production. Conversely, the agroecological vision attributes a key role to the spontaneous flora in promoting plant diversity and belowground interactions, which may improve the ecological performance of agroecosystems. We summarized the literature on the weeds’ arbuscular–mycorrhizae (AM) interaction and we analyzed evidence on the: (i) AM suppressive/selective effect on weed communities; (ii) effect of weeds on AM colonization, and (iii) positive role of AM-supporting weeds on forming shared mycorrhizal hyphal connections in agroecosystems. While some authors conceptualized AM as a weed control tool, others underlined their selective effect on weed communities. Recent studies suggest that AM-host weeds can participate in the development of a common mycorrhizal mycelial network (MMN) among different plants species. Nevertheless, direct evidence of the actual exchange of nutrients and C between coexisting plants through MMN in agroecosystems is missing. Although the effect of agricultural practices on plant community-AM interactions are complex, more conservative farming management seems to foster AM populations. Future studies should focus on: (i) field studies, (ii) weed communities and their traits, rather than on the most abundant species, and (iii) the use of advanced analytical techniques, able to monitor MMN development and functionality.
Finite Sampling Properties of the Point Estimates and Confidence Intervals of the RMSEA

A key advantage of the root mean square error of approximation (RMSEA) is that under certain assumptions, the sample estimate has a known sampling distribution that allows for the computation of confidence intervals. However, little is known about the finite sampling behaviors of this measure under violations of these ideal asymptotic conditions. This information is critical for developing optimal criteria for using the RMSEA to evaluate model fit in practice. Using data generated from a computer simulation study, the authors empirically tested a set of theoretically generated research hypotheses about the sampling characteristics of the RMSEA under conditions commonly encountered in applied social science research. The results suggest that both the sample estimates and confidence intervals are accurate for sample sizes of n = 200 and higher, but caution is warranted in the use of these measures at smaller sample sizes, at least for the types of models considered here.
A comparison between the Local Ensemble Transform Kalman Filter and the Ensemble Square Root Filter for the assimilation of radar data in convective‐scale models

Two ensemble data assimilation methods are used to assimilate Doppler radar observations into a convection‐allowing model. The analyses and subsequent forecasts from the two systems are compared. The Local Ensemble Transform Kalman Filter (LETKF) simultaneously assimilates all observations that can impact the model state at a given location. It is compared to the Ensemble Square Root Filter (EnSRF), which assimilates observations sequentially and has commonly been used for convective‐scale Doppler radar data assimilation. While the filters should behave the same for ideal systems, a comparison between the serial and simultaneous filters has not previously been explored at the convective scale where significant nonlinear effects are present. Observing System Simulation Experiments (OSSEs) are first used to compare the assimilation systems for the analysis and forecast of a supercell thunderstorm. Both the EnSRF and LETKF produce reasonable analyses from the Doppler velocity and reflectivity observations of the true supercell. Small improvements in analysis errors and system noise from the LETKF simultaneous update do not significantly impact the subsequent forecasts. This result is consistent across a range of localization length‐scales and is independent of the manner in which localization is applied. Tests comparing the EnSRF and LETKF for a real‐data case also have small differences. The magnitudes of these differences are similar to those that arise from the sampling variability associated with a finite ensemble. Overall, the results suggest the EnSRF and LETKF approaches are equally capable methods for radar data assimilation at convective scales.
The Effect of low temperature on DC and RF characteristics of GaAs pHEMT

In this paper, the characteristics of domestic GaAs pHEMT device in cryogenic temperature region are measured and analyzed. From 250K to 77K, the DC performance is improved a lot, the saturation current increases by 20%, and the pinch-off voltage increases slightly. Besides, the RF performance is improved significantly. The gate resistance decreases to 40% as the temperature decreases, the characteristic frequency increases from about 32GHz to over 42GHz, and the highest oscillation frequency increases from about 100GHz to over 120GHz.
TiO2 anatase nanolayer on TiN thin film exhibiting high-speed bipolar resistive switching

The surface oxidized layer of a TiN barrier metal thin film grown on a Pt electrode was used as a resistive switching material. The fabricated memory cell shows bipolar resistive switching on a nanosecond order. A TiO2 anatase layer of about 2.5nm thick on TiN thin film was characterized by high-resolution scanning transmission electron microscopy. The results suggested that the high-speed resistive change was derived from the Mott transition in the TiO2 anatase nanolayer, and the obtained results could relate to the formation of filament paths previously reported in binary transition metal oxide thin films exhibiting resistive switching.
Physical Activity Recognition Based on Deep Learning Using Photoplethysmography and Wearable Inertial Sensors

Human activity recognition (HAR) extensively uses wearable inertial sensors since this data source provides the most information for non-visual datasets’ time series. HAR research has advanced significantly in recent years due to the proliferation of wearable devices with sensors. To improve recognition performance, HAR researchers have extensively investigated other sources of biosignals, such as a photoplethysmograph (PPG), for this task. PPG sensors measure the rate at which blood flows through the body, and this rate is regulated by the heart’s pumping action, which constantly occurs throughout the body. Even though detecting body movement and gestures was not initially the primary purpose of PPG signals, we propose an innovative method for extracting relevant features from the PPG signal and use deep learning (DL) to predict physical activities. To accomplish the purpose of our study, we developed a deep residual network referred to as PPG-NeXt, designed based on convolutional operation, shortcut connections, and aggregated multi-branch transformation to efficiently identify different types of daily life activities from the raw PPG signal. The proposed model achieved more than 90% prediction F1-score from experimental results using only PPG data on the three benchmark datasets. Moreover, our results indicate that combining PPG and acceleration signals can enhance activity recognition. Although, both biosignals—electrocardiography (ECG) and PPG—can differentiate between stationary activities (such as sitting) and non-stationary activities (such as cycling and walking) with a level of success that is considered sufficient. Overall, our results propose that combining features from the ECG signal can be helpful in situations where pure tri-axial acceleration (3D-ACC) models have trouble differentiating between activities with relative motion (e.g., walking, stair climbing) but significant differences in their heart rate signatures.
Novel Insights into the Role of the Antioxidants in Prostate Pathology

To date, it is known that antioxidants protect cells from damage caused by oxidative stress and associated with pathological conditions. Several studies have established that inflammation is a state that anticipates the neoplastic transformation of the prostate. Although many experimental and clinical data have indicated the efficacy of antioxidants in preventing this form of cancer, the discrepant results, especially from recent large-scale randomized clinical trials, make it difficult to establish a real role for antioxidants in prostate tumor. Despite these concerns, clinical efficacy and safety data show that some antioxidants still hold promise for prostate cancer chemoprevention. Although more studies are needed, in this review, we briefly describe the most common antioxidants that have shown benefits in preclinical and clinical settings, focusing our attention on synthesizing the advances made so far in prostate cancer chemoprevention using antioxidants as interesting molecules for the challenges of future therapies.
A 2-18-GHz, Ultra-Wideband and Cylindrically Conformal Phased Array Using Tightly Coupled Dipole Element with Low Profile and Low SCS

In this paper, an ultra-wideband, cylindrically conformal phased array antenna with a ultra-wide impedance bandwidth (2-18-GHz) is proposed. This array is composed of the tightly coupled dipole elements. It has an array profile lower than 0. 06λlow, where λlow is the wavelength at the lowest in-band frequency (2 GHz). Low scattering cross section (SCS) characteristic within the operating bands is also achieved. The integrated capacitance component is added into the Marchand balun for improving the bandwidth and reducing the profile height. Then, a multi-layer meta-surface (MS) structure is added to improve the wide-scanning impedance matching inside ±60° volume. By adding the slots on the multi-layer MS, the inverting phase response (0°/180°) for the cross-polarized incident wave is achieved, so that the ultra-wideband SCS reduction is obtained. To certify the correction of this design, a prototype array is built and measured.