Miracle-dz/UniFAR-FTUs huggingface dataset:
Computing In-Place FFTs with SIMD Lane Slicing

We present an approach for implementing in-place FFTs on cores fitted with SIMD units and non-temporal load-store units. Loading the input samples with SIMD instructions decimates them in time across the SIMD lanes. A classic FFT implementation is extended to operate on SIMD data rather than scalar data and computes the sub-transforms concurrently. This enables efficient exploitation of the SIMD arithmetic and memory access instructions while involving little SIMD lane shuffling. A last FFT stage then recombines in-place the sub-transforms results to produce the output. We illustrate this approach on a Cooley- Tukey radix-4 decimated-in-frequency FFT implementation, which also integrates the two inner loop collapsing optimization of the TI C6x DSP _fft32×32 code that enables software pipelining and the Burrus technique for using bit-reversal in high-radix FFT implementations. Performance evaluations are performed on the Kalray KV3 core, which implements a 64-bit vector-scalar VLIW architecture with level-l cache bypass load instructions.
An Incremental Learning-based Framework for Non-stationary Traffic Representations Clustering and Forecasting

To curb the growth of COVID-19, many rules, including a work-from-home policy, were issued in 2020. While these limits successfully prevented the virus's transmission, they completely altered original mobility patterns, resulting in considerable reductions in travel time and vehicle miles traveled. Under this non-stationary data stream, the US Department of Transportation struggled to anticipate future traffic conditions. Obviously, two essential challenges need to be addressed immediately: 1) it is challenging for transportation agencies to learn representative traffic patterns from the continually changing traffic circumstances. And 2) when and how should the forecasting model be updated to learn new patterns without forgetting previous tasks? We proposed an incremental learning-based framework for non-stationary data clustering and forecasting in transportation scenarios to tackle the issues mentioned above. It is a dual-module architecture that includes a Temporal Neighborhood Clustering module and an Incremental Learning module. The objective of the first component is to dynamically detect the optimal boundary for clustering statistically similar neighbors by enlarging both the in-group similarity and between-group dissimilarity. The second module applies the online-EWC approach, which is commonly used in image classification tasks but rarely in regression models, to learn new tasks and avoid catastrophic forgetting, which is a typical occurrence while training neural networks with multiple tasks. Experiments on the Greater Seattle Area employed loop detector data collected in 2020 yielded reliable prediction performance in both robustness and accuracy. The dual-module framework can generate promising results from pre-COVID-19 to post-COVID-19 time frames. This framework would aid government agencies and the general public in developing long-term policies and strategies for post-pandemic intelligent transportation systems.
ACCURATE OH MASER POSITIONS FROM THE SPLASH PILOT REGION

We report on high spatial resolution observations, using the Australia Telescope Compact Array (ATCA), of ground-state OH masers. These observations were carried out toward 196 pointing centers previously identified in the Southern Parkes Large-Area Survey in Hydroxyl (SPLASH) pilot region, between Galactic longitudes of 334° and 344° and Galactic latitudes of −2° and +2°. Supplementing our data with data from the MAGMO (Mapping the Galactic Magnetic field through OH masers) survey, we find maser emission toward 175 of the 196 target fields. We conclude that about half of the 21 nondetections were due to intrinsic variability. Due to the superior sensitivity of the followup ATCA observations, and the ability to resolve nearby sources into separate sites, we have identified 215 OH maser sites toward the 175 fields with detections. Among these 215 OH maser sites, 111 are new detections. After comparing the positions of these 215 maser sites to the literature, we identify 122 (57%) sites associated with evolved stars (one of which is a planetary nebula), 64 (30%) with star formation, two sites with supernova remnants, and 27 (13%) of unknown origin. The infrared colors of evolved star sites with symmetric maser profiles tend to be redder than those of evolved star sites with asymmetric maser profiles, which may indicate that symmetric sources are generally at an earlier evolutionary stage.
Effects of Non-Driving-Related Tasks with Different Resource Demands on Driver Gaze Behavior

Automated driving systems can perform dynamic driving tasks without drivers' intervention, thus leading to increasing driver engagement in non-driving-related tasks (NDRT). However, drivers' engagement in NDRT may result in a decrease in situation awareness and driving performance. There is a need to study the driver's level of monitoring the environment during NDRT. This study divided the resource demands of NDRT into cognitive, visual, and physical and examined the difference in driver's visual attention allocation patterns in NDRT with different resource demands. Meanwhile, four NDRTs was examined (none, cognitive, cognitive-visual, and cognitive-visual-physical) with different engagement time (5 min, 15 min). Results show that the driver devoted high attention resources to the driving environment in the control group and cognitive tasks. While the engagement time significantly affects the driver's attention level to the driving environment in the control group. The driver's attention to the driving environment is significantly reduced in the cognitive-visual and the cognitive-visual-physical tasks. Furthermore, it is more difficult for drivers to disengage from NDRT to observe the driving environment in tasks that occupy physical resource demands.
A 3.5G 500W Asymmetric Doherty Amplifier Employing Subharmonic Oscillation Suppression

This paper presents a novel Asymmetric Doherty Amplifier in 3way (ADPA-3way) for 5G macro station application at the pioneer band (3.4∼3.8 GHz). This ADPA-3way contains a main path and a two-paths peak that combines two auxiliary Gallium Nitride (GaN) high electron mobility transistors (HEMT) as a single-end high power path. An oscillation suppression network is designed at the input circuit of the two-paths peak, to mitigate the subharmonic oscillation. This ADPA-3way demonstrates over 500 watts peak power capability over the pioneer band, of linear gain 12 dB. Drain efficiency at average output power of 76 watts achieves 47.5 %, Adjacent Channel Power Ratio (ACPR) of −55 dBc with 2 adjacent Long-Term-Evolution (LTE) signals after Digital Pre-Distortion (DPD) correction.
Privacy-Preserved Data-Enabled Predictive Control for Connected and Automated Vehicles in Mixed Traffic

Data-driven predictive control has emerged as a promising model-free paradigm when an explicit system model is difficult or expensive to obtain. However, this framework may be vulnerable to privacy leakage since data sharing is needed. In this paper, we empower it with privacy protection and develop a privacy-preserved data-enabled predictive control scheme for cooperative cruise control of connected and automated vehicles (CAVs) in a mixed traffic environment. We tackle external eavesdroppers who wiretap the communication channel of the mixed traffic system and intend to infer the CAVs' state and input information. An affine masking-based privacy protection method is developed to conceal the true state and input signals, and an extended form of the data-enabled predictive control is derived to achieve privacy-preserved optimal control for CAVs. Our proposed scheme can protect the privacy of CAVs against external eavesdroppers without affecting the control performance or incurring heavy computations. Numerical simulations confirm the efficacy of the proposed approach.
Effects of Visual Planning Support on Take-over Performance in Conditional Automated Driving

L3 automated driving system allows the driver to leave from driving tasks within its Operational Design Domain (ODD), while the driver has to take over control of the vehicle once the system reaches the boundary of its functions. It will be a challenge for the Human-Machine Interface (HMI) to issue a Take-over Request (TOR) to get the driver back in the driving loop. This study investigated the effects of different types of visual planning support on take-over performance via a driving simulator experiment with 24 participants. We evaluated three types of visual planning support: Normal, Text, and Icon during emergency scenarios. Moreover, two Non-Driving Related Tasks (NRDTs) were hypothesized to affect the driver's performance. Based on a total of 8 objective metrics, the results showed that the type of visual planning support did not influence the reaction time; however, it had considerable effects on take-over performance. Compared with normal type which only included vocal alarm, the success rate under visual planning support was higher and the lateral control of vehicle was also more stable, which indicated an improvement of take-over performance.
Application of an autonomous multi-agent system using Proximal Policy Optimisation for tactical deconfliction within the urban airspace

The present paper formalises the development of a Multi-agent Reinforcement Learning (MARL) solver for U-space Service Providers (USSPs) supporting the tactical conflict resolution and exhibited in the Air Mobility Urban - Large Experimental Demonstration (AMU-LED) project. It relies on an Advantage Actor Critic (A2C) model with a Proximal Policy Optimisation (PPO) learning baseline. The application of the autonomous system is demonstrated under a synthetic (with live and virtual) air/unmanned traffic management (ATM/UTM) environment. The Unmanned Aircraft Systems (UASs) are flying in cruise phase at low altitudes, whose respective flight plan generates intersections for enforcing a high collision frequency. The study adopts a step-wise complexity approach of scenarios that confront two agents’ observation methods and showcases a practical case of tactical conflict resolution. The experiments show encouraging deconfliction performance with promising prospects for seeing a such solver deployed.
Antenna Pattern Shaping through Functionalized Metasurface Coatings

In this contribution, we discuss the possibility to exploit functionalized metasurface coats wrapping wired antennas for manipulating their radiation pattern. Through a proper design of the Huygens metasurface coating, the quasi-cylindrical wave front of the field radiated by the antenna is locally transformed into a plane wave, leading to the generation of multiple or single radiating beams from the original omnidirectional pattern. The semi-analytical model of the device is presented, and some relevant examples are provided.
Protoplanetary Disks in ρ Ophiuchus as Seen from ALMA

We present a high angular resolution ( ), high-sensitivity ( mJy) survey of the 870 μm continuum emission from the circumstellar material around 49 pre-main-sequence stars in the ρ Ophiuchus molecular cloud. Because most millimeter instruments have resided in the northern hemisphere, this represents the largest high-resolution, millimeter-wave survey of the circumstellar disk content of this cloud. Our survey of 49 systems comprises 63 stars; we detect disks associated with 29 single sources, 11 binaries, 3 triple systems, and 4 transition disks. We present flux and radius distributions for these systems; in particular, this is the first presentation of a reasonably complete probability distribution of disk radii at millimeter wavelengths. We also compare the flux distribution of these protoplanetary disks with that of the disk population of the Taurus–Auriga molecular cloud. We find that disks in binaries are both significantly smaller and have much less flux than their counterparts around isolated stars. We compute truncation calculations on our binary sources and find that these disks are too small to have been affected by tidal truncation and posit some explanations for this. Lastly, our survey found three candidate gapped disks, one of which is a newly identified transition disk with no signature of a dip in infrared excess in extant observations.
User Perception towards Telemedicine Before and During COVID-19

Telemedicine provides various conveniences and solutions to several problems related to health services. The number of downloads of telemedicine apps has increased during the COVID-19 pandemic. However, the continuance mainly depends on user satisfaction associated with user perception of service quality. This study aims to figure out whether there are any changes in user perception toward telemedicine before and during the pandemic. This study proposes an approach that utilizes customer reviews of Halodoc and Alodokter from the Google Play Store. User perception extracted from user reviews includes sentiment polarity and the most discussed topics of telemedicine apps. Further analysis was conducted by mapping the most discussed topics to dimensions of service quality. The results show that the percentage of reviews with negative sentiment during the pandemic increased compared to before the pandemic. The highest percentage of topics discussed in negative nuance during pandemic is about system quality, which are payment methods, unauthorized deduction of user balances, and suspected leaks of users' private data. The findings of this research contribute to the preliminary information related to the sustainability of telemedicine usage. This research also extends the literature on the potential use of textual reviews in user perception on health platforms.
Semileptonic decays of 
B(*)
, 
D(*)
 into 
νl
 and pseudoscalar or vector mesons

We perform a study of the $B^{(*)}$, $D^{(*)}$ semileptonic decays, using a different method than in conventional approaches, where the matrix elements of the weak operators are evaluated and a detailed spin-angular momentum algebra is performed to obtain very simple expressions at the end for the different decay modes. Using only one experimental decay rate in the $B$ or $D$ sectors, the rates for the rest of decay modes are predicted and they are in good agreement with experiment. Some discrepancies are observed in the $\tau$ decay mode for which we find an explanation. We perform evaluations for $B^*$ and $D^*$ decay rates that can be used in future measurements, now possible in the LHCb collaboration.
3D Anisotropy of Solar Wind Turbulence, Tubes, or Ribbons?

We study the anisotropy with respect to the local magnetic field of turbulent magnetic fluctuations at magnetofluid scales in the solar wind. Previous measurements in the fast solar wind obtained axisymmetric anisotropy, despite that the analysis method allows nonaxisymmetric structures. These results are probably contaminated by the wind expansion that introduces another symmetry axis, namely, the radial direction, as indicated by recent numerical simulations. These simulations also show that while the expansion is strong, the principal fluctuations are in the plane perpendicular to the radial direction. Using this property, we separate 11 yr of Wind spacecraft data into two subsets characterized by strong and weak expansion and determine the corresponding turbulence anisotropy. Under strong expansion, the small-scale anisotropy is consistent with the Goldreich & Sridhar critical balance. As in previous works, when the radial symmetry axis is not eliminated, the turbulent structures are field-aligned tubes. Under weak expansion, we find 3D anisotropy predicted by the Boldyrev model, that is, turbulent structures are ribbons and not tubes. However, the very basis of the Boldyrev phenomenology, namely, a cross-helicity increasing at small scales, is not observed in the solar wind: the origin of the ribbon formation is unknown.
Ego-Vehicle Speed Prediction with Walk-Ahead

Intelligent vehicle technology is becoming more and more important to counteract high emission levels and climate change while at the same time maintaining a reliable and accessible transportation system. To this end, ego-vehicle speed prediction, i.e., the forecasting of the own vehicle speed in the near future, has emerged as an important research direction for enabling advanced driver assistance systems. In this paper, we propose the WHEELS (Walk-Ahead Ego Vehicle Speed) model for ego-vehicle speed prediction. Our WHEELS combines vehicle speed information retrieved with contextual information such as road network information, weather information, or the day of the week. At the core, WHEELS introduces the so-called walk-ahead that takes all possible further routes into account. We conducted an extensive evaluation on a large-scale real-world dataset collected from a ride-pooling service. Our experiments confirm that WHEELS reliably outperforms existing baselines and achieves an average performance gain of 19.4% compared to the best-performing baseline.
Ground- and Space-based Detection of the Thermal Emission Spectrum of the Transiting Hot Jupiter KELT-2Ab

We describe the detection of water vapor in the atmosphere of the transiting hot Jupiter KELT-2Ab by treating the star–planet system as a spectroscopic binary with high-resolution, ground-based spectroscopy. We resolve the signal of the planet’s motion with deep combined flux observations of the star and the planet. In total, six epochs of Keck NIRSPEC L-band observations were obtained, and the full data set was subjected to a cross-correlation analysis with a grid of self-consistent atmospheric models. We measure a radial projection of the Keplerian velocity, KP, of 148 ± 7 km s−1, consistent with transit measurements, and detect water vapor at 3. 8σ. We combine NIRSPEC L-band data with Spitzer IRAC secondary eclipse data to further probe the metallicity and carbon-to-oxygen ratio of KELT-2Ab’s atmosphere. While the NIRSPEC analysis provides few extra constraints on the Spitzer data, it does provide roughly the same constraints on metallicity and carbon-to-oxygen ratio. This bodes well for future investigations of the atmospheres of non-transiting hot Jupiters.
Agricultural light-trapped pest detection methods under unbalanced data

This paper designs an improved YOLOX method for agricultural pest detection under unbalanced data. With the expansion of food demand due to rapid population growth in recent years, many crops have been damaged by pests due to frequent natural disasters, which have caused serious damage to farmers’ economic development. As an important biological disaster in agricultural production in China and the world, crop pests and diseases are the biggest cause of sustainable and stable development of agricultural production, with a wide range of species, high impact and high potential for outbreaks becoming its label. Accurate detection of pests is therefore an urgent necessity for the excellent development of the crop industry. In this paper, the binary cross-entropy loss in YOLOX is changed to Focal loss, an attention mechanism is added to its backbone feature extraction network Backbone to make the model more edge-oriented, and a depth-separable convolution is introduced to reduce the number of parameters. The improved pest detection model obtained a recall of 93% and an average accuracy of 87.6%, which can be effectively applied in real life.
Driving Safety Monitoring and Warning for Connected and Automated Vehicles via Edge Computing

In this paper, we systematically study how to use edge computing to monitor the movements of multiple connected and automated vehicles (CAV) and warn of potential accidents (e.g., lane departures, collisions). Compared to conventional approaches that only use the sensing data of individual vehicles, cooperative vehicle infrastructure systems directly collect the movement data of vehicles via vehicle-to-everything (V2X) communications and thus easily calculate the risk of every vehicle synthetically. We propose a fast algorithm and the corresponding data structure model to calculate collision risks based on the timely received data. We also discuss the data accuracy and transmission delay requirements to guarantee the driving safety of CAVs. Testing results show the effectiveness of the proposed approach.
Quasi-periodic Pulse Amplitude Modulation in the Accreting Millisecond Pulsar IGR J00291+5934

We introduce a new method for analyzing the aperiodic variability of coherent pulsations in accreting millisecond X-ray pulsars (AMXPs). Our method involves applying a complex frequency correction to the time-domain light curve, allowing for the aperiodic modulation of the pulse amplitude to be robustly extracted in the frequency domain. We discuss the statistical properties of the resulting modulation spectrum and show how it can be correlated with the non-pulsed emission to determine if the periodic and aperiodic variability are coupled processes. Using this method, we study the 598.88 Hz coherent pulsations of the AMXP IGR J00291+5934 as observed with the Rossi X-ray Timing Explorer and XMM-Newton. We demonstrate that our method easily confirms the known coupling between the pulsations and a strong 8 mHz quasi-periodic oscillation (QPO) in XMM-Newton observations. Applying our method to the RXTE observations, we further show, for the first time, that the much weaker 20 mHz QPO and its harmonic are also coupled with the pulsations. We discuss the implications of this coupling and indicate how it may be used to extract new information on the underlying accretion process.
FRB 121102: A Repeatedly Combed Neutron Star by a Nearby Low-luminosity Accreting Supermassive Black Hole

The origin of fast radio bursts (FRBs) remains mysterious. Recently, the only repeating FRB source, FRB 121102, was reported to possess an extremely large and variable rotation measure (RM). The inferred magnetic field strength in the burst environment is comparable to that in the vicinity of the supermassive black hole Sagittarius A* of our Galaxy. Here, we show that all of the observational properties of FRB 121102 (including the high RM and its evolution, the high linear polarization degree, an invariant polarization angle across each burst and other properties previously known) can be interpreted within the “cosmic comb” model, which invokes a neutron star with typical spin and magnetic field parameters whose magnetosphere is repeatedly and marginally combed by a variable outflow from a nearby low-luminosity accreting supermassive black hole in the host galaxy. We propose three falsifiable predictions (periodic “on/off” states, and periodic/correlated variation of RM and polarization angle) of the model and discuss other FRBs within the context of the cosmic comb model as well as the challenges encountered by other repeating FRB models in light of the new observations.
Analysis of the LRU Cache StartUp Phase and Convergence Time and Error Bounds on Approximations by Fagin and Che

We compare exact and approximate performance evaluation methods of the Least Recently Used (LRU) caching strategy, which is widely applied in local caches and in distributed web cache architectures in core and edge networks. Based on the independent reference model (IRM), the LRU startup behaviour and convergence time (CT) is derived. The result is related to hit ratio approximations by Fagin and Che et al. We evaluate the precision of the approximations by identifying maximum errors, which are shown to decrease with the cache size. For different object sizes, we extend the analytical LRU hit ratio formula, which is tractable for small caches. The Che and CT approximations are subject to larger deviations for high variability of the object sizes and small caches due to partially unused cache space. We propose an estimation scheme for the fraction of unused LRU cache space, which is shown to improve the accuracy.