Miracle-dz/UniFAR-FTUs huggingface dataset:
Large-Area Mapping at 850 Microns. II. Analysis of the Clump Distribution in the ρ Ophiuchi Molecular Cloud

We present results from a survey of the central 700 arcmin2 region of the ρ Ophiuchi molecular cloud at 850 μm using the Submillimeter Common-User Bolometer Array (SCUBA) on the James Clerk Maxwell Telescope. Using the clump-finding procedure developed by Williams et al., we identify 55 independent objects and compute size, flux, and degree of central concentration. Comparison with isothermal, pressure-confined, self-gravitating Bonnor-Ebert spheres implies that the clumps have internal temperatures of 10-30 K and surface pressures P/k = 106-7 K cm-3, consistent with the expected average pressure in the ρ Ophiuchi central region, P/k ~ 2 × 107 K cm-3. The clump masses span 0.02-6.3 M☉ assuming a dust temperature Td ~ 20 K and a dust emissivity κ850 = 0.01 cm2 g-1. The distribution of clump masses is well characterized by a broken power law, N(M) ∝ M-α, with α = 1.0-1.5 for M > 0.6 M☉ and α = 0.5 for M ≤ 0.6 M☉, although significant incompleteness may affect the slope at the lower mass end. This mass function is in general agreement with the ρ Ophiuchi clump mass function derived at 1.3 mm by Motte et al. The two-point correlation function of the clump separations is measured and reveals clustering on size scales r < 3 × 104 AU with a radial power-law exponent γ = 0.75.
Analysis of the characteristics of TOADs subject to frequency-detuned control and signal picosecond pulses

A detailed numerical investigation has been undertaken of the dynamic responses of semiconductor optical amplifiers (SOAs) and hence the operating characteristics of terahertz optical asymmetric demultiplexers (TOADs) devices subject to frequency-detuned picosecond control and signal pulses, taking into account both gain saturation and nonlinear gain compression in the SOA. It is shown that the output behavior of TOADs exhibits significant differences depending on whether the signal and control pulses are at higher relative frequencies (positive detuning) or lower relative frequencies (negative detuning). The analysis indicates that negative frequency detuning can be used to achieve an enhanced output power in the switched region and a reduced width of switching window. Calculations are shown to be in good agreement with available experimental results.
Dictionary Learning for the Almost-Linear Sparsity Regime

Dictionary learning, the problem of recovering a sparsely used matrix $\mathbf{D} \in \mathbb{R}^{M \times K}$ and $N$ $s$-sparse vectors $\mathbf{x}_i \in \mathbb{R}^{K}$ from samples of the form $\mathbf{y}_i = \mathbf{D}\mathbf{x}_i$, is of increasing importance to applications in signal processing and data science. When the dictionary is known, recovery of $\mathbf{x}_i$ is possible even for sparsity linear in dimension $M$, yet to date, the only algorithms which provably succeed in the linear sparsity regime are Riemannian trust-region methods, which are limited to orthogonal dictionaries, and methods based on the sum-of-squares hierarchy, which requires super-polynomial time in order to obtain an error which decays in $M$. In this work, we introduce SPORADIC (SPectral ORAcle DICtionary Learning), an efficient spectral method on family of reweighted covariance matrices. We prove that in high enough dimensions, SPORADIC can recover overcomplete ($K>M$) dictionaries satisfying the well-known restricted isometry property (RIP) even when sparsity is linear in dimension up to logarithmic factors. Moreover, these accuracy guarantees have an ``oracle property"that the support and signs of the unknown sparse vectors $\mathbf{x}_i$ can be recovered exactly with high probability, allowing for arbitrarily close estimation of $\mathbf{D}$ with enough samples in polynomial time. To the author's knowledge, SPORADIC is the first polynomial-time algorithm which provably enjoys such convergence guarantees for overcomplete RIP matrices in the near-linear sparsity regime.
Isothermal magnetosheath electrons due to nonlocal electron cross talk

Heating of the various plasma species at the Earth's collisionless bow shock is not fully understood. Although the total amount of heating is constrained by the one‐fluid Rankine‐Hugoniot relations in terms of local plasma conditions, the partition of energy between, e.g., electrons and ions, is influenced by particle kinetics which are not considered in the Rankine‐Hugoniot approach. Additionally, in this paper we demonstrate the impact of nonlocal effects. Here we model the effects of shock‐heated electrons which traverse the magnetosheath to arrive at another point on the bow shock surface. We construct the distribution of electrons immediately downstream of each point on the bow shock from two populations: local solar wind electrons entering the magnetosheath for the first time and previously shocked electrons which have traversed the magnetosheath. We determine the self‐consistent cross‐shock potential at each point such that the resulting electron distribution gives a downstream plasma which is neutral and has zero parallel current. This leads to very little variation in the downstream electron temperature everywhere around the curved bow shock, in spite of large differences in the total (Rankine‐Hugoniot) downstream temperature. Consequently, the partition of heating between electrons and ions at the shock, i.e., the equation of state, contains nonlocal contributions. We show that heating properties at the point where the shock is exactly perpendicular controls electron heating throughout the rest of the shock surface.
Regression Model-based VCO Design Optimization Technique

Along with technology advancements, implementing digital signal processing has become easier through digital circuit design automation. However, an analog circuit has too many obstacles to adopt a design automation flow in a scaled-down technology due to the relatively increased PVT (process-voltage-temperature) variations and enlarged mismatch errors, thus requiring a careful full-custom analog circuit design or employing an intensive back-end digital calibration engine. In this study, we implement an analog circuit design flow that quickly finds the optimal design point enabled by a high-level simulator programmed in Ocean scripts with a machine learning algorithm. To reduce the analog design effort, we train an ANN regression model that predicts the top-performing candidates with reasonable SPICE simulations in a supervised learning process. Here, we aimed to design a ring oscillator in the 65nm CMOS process. By using the proposed analog design automation strategy, we focused on jitter-power figure-of-merit (FOMJ) optimization, resulting in 99.84% accuracy of the final performance in comparison with SPICE simulation.
Cloud-Based Architecture for Early Detection and Postoperative Monitoring of Hypospadias Patients in Indonesia

Covid-19 Epidemic has significantly changed how hypospadias patients are delivered to healthcare services, particularly after hypospadias repairs (postoperative care). Some studies reported that using telemedicine schemes by sending digital documentation such as images and videos through cell phones can facilitate an assessment of postoperative monitoring of hypospadias patients. However, this approach raises various concerns, such as managing digital documentation of hypospadias patients, analyzing the data, and the security of individuals' health information. This study proposes a design of cloud-based architecture for early detection and postoperative monitoring of hypospadias patients to address the concerns above. The user acceptance test shows that most users agree that this application may be used for early detection, monitoring hypospadias patients, and helping capture videos and provide labeling to patients' data.
An Electronically Steerable Antenna Designed for Accurate DoA Determination of U-NII-2-Extended WLAN Devices

Determining the location of the beam source of WLAN devices causing harmful interference to TWDR in the U-NII-2-Extended band requires effective methods and devices. Research regarding the construction of the directional finding antennas in this band is still lacking. An intelligent electronically steerable parasitic array radiatory (ESPAR) antenna design was constructed in this study to perform two critical tasks, i.e., to determine the direction and the location of the radiation source that causes interferences. An electronically beam steerable antenna was implemented in such way using a digitally controlled PE42424 SPDT switch which connected directly to each parasitic element. This allows each parasitic part to stay in one of the two states, i.e., ON or OFF. The RF switch circuit was designed on the plated-through-hole PCB structure. In the ON state, this connects the parasitic elements and the grounding part to reflect the induced RF signal of each element to all OFF-stated parasitic directions. The numerical computation of the designed antenna shows consistent radiation from the main beam pattern which varies at every 45° angle. The maximum gain achieved was up to 8.76 dBi. The reflection coefficient and VSWR obtained through the numerical assessment were −22.3 dB and 1.53, respectively.
Performance Analysis of Polar Codes Over Fox’s H-Fading Channels With RHI and IQI Impairments

This study examined the error probability performance of polar codes across Fox’s <inline-formula> <tex-math notation="LaTeX">$H$ </tex-math></inline-formula>-fading (FHF) channels while taking into account in-phase and quadrature-phase imbalance (IQI), as well as residual hardware impairments (RHI). This fading model generalizes most of the commonly used fading and turbulence models where Málaga-<inline-formula> <tex-math notation="LaTeX">$\mathcal {M}$ </tex-math></inline-formula> turbulence is taken into account as a specific case of FHF in this paper. Specifically, an upper bound on block error probability (BLER) for the successive cancellation (SC) decoding method of polar codes is derived in terms of the Fox’s <inline-formula> <tex-math notation="LaTeX">$H$ </tex-math></inline-formula>-function. According to numerical results, by lengthening polar codes and changing the properties of fading channels, it is possible to decrease the impact of system impairments on the error probability performance.
Study of a Wireless Power Transfer System for Electric Vehicles in Motion Using a Continuous Repeater Coil on the Power Transmission Side

Recently, the shift to electric vehicles (EVs) has become more pronounced worldwide. In line with this trend, several studies have been conducted on systems to wirelessly supply electric power to running EVs in many countries. To realize this system, it is essential to build a simple and inexpensive infrastructure, and one of the key issues is to reduce the number of power sources. Therefore, we have proposed a repeater coil method as a power transmission scheme that extends the power supply section per power source. In this paper, we report on our proposal and design a new repeater method that solves the problems that the repeater coil method has faced in the past and that can be used even when there is no load, as well as in laboratory-scale power supply experiments.
CoordViT: A Novel Method of Improve Vision Transformer-Based Speech Emotion Recognition using Coordinate Information Concatenate

Recently, in speech emotion recognition, a Transformer-based method using spectrogram images instead of sound data showed improved accuracy than Convolutional Neural Networks (CNNs). Vision Transformer (ViT), a Transformer-based method, achieves high classification accuracy by using divided patches from the input image, but has a problem in that pixel position information is not retained due to embedding layers such as linear projection. Therefore, in this paper, we propose a novel method of improve ViT-based speech emotion recognition using coordinate information concatenate. Since the proposed method retains pixel position information by concatenating coordinate information to the input image, the accuracy of CREMA-D is greatly improved by 82.96% compared to the state-of-art about CREMA-D. As a result, it proved that the coordinate information concatenate proposed in this paper is effective not only for CNNs but also for Transformers.
Investigation on Direct Current Arcs in a Busbar Setup Using a Power-Electronic Buck Converter Based High-Power Test Circuit

In this paper, an innovative test circuit based on a power-electronic buck converter is used for investigating direct current arcs in a parallel copper busbar setup. A parameter study regarding the influence of busbar distance as well as driving current on the arc behavior is conducted. The arc is investigated electrically by measuring current as well as arc voltage and optically by a high-speed camera setup. The optical recordings enable the investigation of the arc position as well as the derived arc velocity. It is noticed that increasing current leads to increasing arc velocities, while the arc velocity decreases for increasing busbar distances. The investigations demonstrate the applicability of the test circuit for this use case for the first time. Furthermore, a deeper understanding of dc arc behavior can be derived from the results which is eminent for the development of adequate dc switchgear.
Driver Behavior Modeling Toward Autonomous Vehicles: Comprehensive Review

Driver behavior models have been used as input to self-coaching, accident prevention studies, and developing driver-assisting systems. In recent years, driver behavior recognition has revolutionized autonomous vehicles (AVs) and traffic management studies. This comprehensive survey provides an up-to-date review of the different driver behavior models and modeling approaches. In heterogeneous streets where humans and autonomous vehicles operate simultaneously, predicting the intent and action of human drivers is crucial for AVs with the help of wireless communication and artificial intelligence (AI) technologies. Therefore, the review also summarizes the applications of driver behavior modeling (DBM) for effective behavior recognition and human-like AV driving. Moreover, the review also covers the application of DBM in capturing behaviors of complex dynamic driving tasks. In this review, we solely cover car-following (CF) and lane-changing (LC) maneuvers.
Composite Re-Ranking for Efficient Document Search with BERT

Although considerable efforts have been devoted to transformer-based ranking models for document search, the relevance-efficiency tradeoff remains a critical problem for ad-hoc ranking. To overcome this challenge, this paper presents BECR ( BE RT-based C omposite R e-Ranking), a composite re-ranking scheme that combines deep contextual token interactions and traditional lexical term-matching features. In particular, BECR exploits a token encoding mechanism to decompose the query representations into pre-computable uni-grams and skip-n-grams. By applying token encoding on top of a dual-encoder architecture, BECR separates the attentions between a query and a document while capturing the contextual semantics of a query. In contrast to previous approaches, this framework does not perform expensive BERT computations during online inference. Thus, it is significantly faster, yet still able to achieve high competitiveness in ad-hoc ranking relevance. Finally, an in-depth comparison between BECR and other start-of-the-art neural ranking baselines is described using the TREC datasets, thereby further demonstrating the enhanced relevance and efficiency of BECR.
Role of antioxidants in itch treatment: lessons learned from pain management

Chronic pain and chronic pruritus are both debilitating conditions that cause a significant burden to patients. Oxidative stress—driven by an imbalance between reactive oxygen species and antioxidants—has been shown to play a role both in pain disorders and conditions in which chronic itch is a prominent symptom. Antioxidants can be useful in treating oxidative stress-driven diseases and have shown promise in treating chronic pain conditions such as fibromyalgia and osteoarthritis. However, their role in treating pruritus and pruritic conditions such as psoriasis and atopic dermatitis remains unclear. Many of the current treatments for chronic itch are costly, associated with side effects, and have limited efficacy. Therefore, further controlled studies exploring antioxidants as a potential therapeutic option for chronic pruritus are warranted.
Variance reduced ensemble Kalman filtering

A number of algorithms to solve large-scale Kalman filtering problems have been introduced recently. The ensemble Kalman filter represents the probability density of the state estimate by a finite number of randomly generated system states. Another algorithm uses a singular value decomposition to select the leading eigenvectors of the covariance matrix of the state estimate and to approximate the full covariance matrix by a reduced-rank matrix. Both algorithms, however, still require a huge amount of computer resources. In this paper the authors propose to combine the two algorithms and to use a reduced-rank approximation of the covariance matrix as a variance reductor for the ensemble Kalman filter. If the leading eigenvectors explain most of the variance, which is the case for most applications, the computational burden to solve the filtering problem can be reduced significantly (up to an order of magnitude).
The shadow disintermediation of risk-sensitive capital∗

I investigate the risk implications of bank capital requirements in the presence of shadow banks. I show that in response to higher capital charges as an exogenous shock to loan retention, banks originate riskier loans. The probability of ex post borrower default rises by 8% (50% in relative terms). Defaults are absorbed by shadow banks. I uncover a novel pecking order of credit risk transfer with strategic adverse selection of banks vis-à-vis shadow banks. The riskier loans are sold to shadow banks with less monitoring expertise, but higher credit risk is not ex ante priced. I also find that the rise in default risk operates through lax screening ex ante as opposed to lax monitoring ex post. These findings collectively show that in the originate-to-distribute system, bank capital regulation distorts screening and triggers a credit risk transfer. While banks become safer, the credit risk originated by banks and borne by the shadow banking system is larger. ∗I am deeply indebted to my advisor Alex Edmans and Henri Servaes for their guidance and support throughout the generation of this paper. I also thank the LBS finance faculty and PhD students, seminar participants at London Business School, Warwick Business School, University of Alberta, Australia National University, Université de Laval, Kathy Yuan, Elias Papaioannou, Vania Stavrakeva, and Aytekin Ertan for the helpful comments. †London Business School, Department of Finance, ierten@london.edu
Towards Capturing the Temporal Dynamics for Trajectory Prediction: a Coarse-to-Fine Approach

: Trajectory prediction is one of the basic tasks in the autonomous driving ﬁeld, which aims to predict the future position of other agents around the ego vehicle so that a safe yet efﬁcient driving plan could be generated in the down-stream module. Recently, deep learning based methods dominate the ﬁeld. State-of-the-art (SOTA) methods usually follow an encoder-decoder paradigm. Specifically, the encoder is responsible for extracting information from agents’ history states and HD-Map and providing a representation vector for each agent. Taking these vectors as input, the decoder predicts multi-step future positions for each agent, which is usually accomplished by a single multi-layer perceptron (MLP) to directly output a Tx2 tensor. Though models with adoptation of MLP decoder have dominated the leaderboard of multiple datasets, ‘the elephant in the room is that the temporal correlation among future time-steps is ignored since there is no direct relation among output neurons of a MLP. In this work, we examine this design choice and investigate several ways to apply the temporal inductive bias into the generation of future trajectories on top of a SOTA encoder. We ﬁnd that simply using autoregressive RNN to generate future positions would lead to signiﬁcant performance drop even with techniques such as history highway and teacher forcing. Instead, taking scratch trajectories generated by MLP as input, an additional reﬁnement module based on structures with temporal prior such as RNN or 1D-CNN could remarkably boost the accuracy. Furthermore, we examine several objective functions to emphasize the temporal priors. By the combination of aforementioned techniques to introduce the temporal prior, we improve the top-ranked method’s performance by a large margin and achieve SOTA result on the Waymo Open Motion Challenge.
Metagenomic evidence for coexistence of SARS and H1N1 in patients from 2007-2012 flu seasons

By re-analzying public metagenomic data from 101 patients infected with influenza A virus during the 2007-2012 H1N1 flu seasons in France, we identified 22 samples with SARS-CoV sequences. In 3 of them, the SARS genome sequences could be fully assembled out of each. These sequences are highly similar (99.99% and 99.7%) to the artificially constructed recombinant 5 SARS-CoV (SARSr-CoV) strains generated by the J.
Multi-planet extrasolar systems — detection and dynamics

20 years after the discovery of the first planets outside our solar system, the current exoplanetary population includes more than 700 confirmed planets around main sequence stars. Approximately 50% belong to multiple-planet systems in very diverse dynamical configurations, from two-planet hierarchical systems to multiple resonances that could only have been attained as the consequence of a smooth large-scale orbital migration. The first part of this paper reviews the main detection techniques employed for the detection and orbital characterization of multiple-planet systems, from the (now) classical radial velocity (RV) method to the use of transit time variations (TTV) for the identification of additional planetary bodies orbiting the same star. In the second part we discuss the dynamical evolution of multi-planet systems due to their mutual gravitational interactions. We analyze possible modes of motion for hierarchical, secular or resonant configurations, and what stability criteria can be defined in each case. In some cases, the dynamics can be well approximated by simple analytical expressions for the Hamiltonian function, while other configurations can only be studied with semi-analytical or numerical tools. In particular, we show how mean-motion resonances can generate complex structures in the phase space where different libration islands and circulation domains are separated by chaotic layers. In all cases we use real exoplanetary systems as working examples.