Miracle-dz/UniFAR-FTUs huggingface dataset:
Fermi-LAT Detection of GeV γ-Ray Emission from the Highly Asymmetric Shell Supernova Remnant SNR G317.3-0.2

In this paper, we report the first extended GeV γ-ray emission, at a significant level of ∼8. 13σ, from the region of the supernova remnant SNR G317.3-0.2 by analyzing ∼12.2 yr of Fermi Large Area Telescope Pass 8 data in the work. The best-fit position of the new γ-ray source matches that of the 843 MHz radio energy band of SNR G317.3-0.2, and there is no significant variability of the photon flux of the corresponding light curve in the data for the 12.2 yr period. Therefore, by excluding other known γ-ray sources or candidates within a 2σ error radius from the best-fit position of SNR G317.3-0.2, we suggest that the γ-ray source is likely to be a GeV counterpart of SNR G317.3-0.2.
An Application-Driven Conceptualization of Corner Cases for Perception in Highly Automated Driving

Systems and functions that rely on machine learning (ML) are the basis of highly automated driving. An essential task of such ML models is to reliably detect and interpret unusual, new, and potentially dangerous situations. The detection of those situations, which we refer to as corner cases, is highly relevant for successfully developing, applying, and validating automotive perception functions in future vehicles where multiple sensor modalities will be used. A complication for the development of corner case detectors is the lack of consistent definitions, terms, and corner case descriptions, especially when taking into account various automotive sensors. In this work, we provide an application-driven view of corner cases in highly automated driving. To achieve this goal, we first consider existing definitions of the general outlier, novelty, anomaly, and out-of-distribution detection to show relations and differences to corner cases. Moreover, we extend an existing camera-focused systematization of corner cases by adding RADAR (radio detection and ranging) and LiDAR (light detection and ranging) sensors. For this, we describe an exemplary toolchain for data acquisition and processing, highlighting the interfaces of corner case detection. We also define a novel level of corner cases, the method layer corner cases, which appear due to uncertainty inherent in the methodology.
ShEF: shielded enclaves for cloud FPGAs

FPGAs are now used in public clouds to accelerate a wide range of applications, including many that operate on sensitive data such as financial and medical records. We present ShEF, a trusted execution environment (TEE) for cloud-based reconfigurable accelerators. ShEF is independent from CPU-based TEEs and allows secure execution under a threat model where the adversary can control all software running on the CPU connected to the FPGA, has physical access to the FPGA, and can compromise the FPGA interface logic of the cloud provider. ShEF provides a secure boot and remote attestation process that relies solely on existing FPGA mechanisms for root of trust. It also includes a Shield component that provides secure access to data while the accelerator is in use. The Shield is highly customizable and extensible, allowing users to craft a bespoke security solution that fits their accelerator's memory access patterns, bandwidth, and security requirements at minimum performance and area overheads. We describe a prototype implementation of ShEF for existing cloud FPGAs, map ShEF to a performant and secure storage application, and measure the performance benefits of customizable security using five additional accelerators.
XMMU J050722.1−684758: discovery of a new Be X-ray binary pulsar likely associated with the supernova remnant MCSNR J0507−6847

We report the discovery of a new high-mass X-ray binary pulsar, XMMU J050722.1−684758, possibly associated with the supernova remnant (SNR) MCSNR J0507−6847 in the Large Magellanic Cloud, using XMM–NewtonX-ray observations. Pulsations with a periodicity of 570 s are discovered from the Be X-ray binary XMMU J050722.1−684758 confirming its nature as a HMXB pulsar. The HMXB is located near the geometric centre of the SNR MCSNR J0507−6847(0.9 arcmin from the centre) which supports the XRB-SNR association. The estimated age of the SNR is 43–63 kyr years which points to a middle aged to old SNR. The large diameter of the SNR combined with the lack of distinctive shell counterparts in optical and radio indicates that the SNR is expanding into the tenuous environment of the superbubble N103. The estimated magnetic field strength of the neutron star is B ≳ 1014 G assuming a spin equilibrium condition which is expected from the estimated age of the parent remnant and assuming that the measured mass-accretion rate remained constant throughout.
Spatio-Temporal Decomposition of Sum-of-Squares Programs for the Region of Attraction and Reachability

This letter presents a method for calculating Region of Attraction of a target set (not necessarily an equilibrium) for controlled polynomial dynamical systems, using a hierarchy of semidefinite programming problems (SDPs). Our approach builds on previous work and addresses its main issue, the fast-growing memory demands for solving large-scale SDPs. The main idea in this work is in dissecting the original resource-demanding problem into multiple smaller, interconnected, and easier to solve problems. This is achieved by spatio-temporal splitting akin to methods based on partial differential equations. We show that the splitting procedure retains the convergence and outer-approximation guarantees of the previous work, while achieving higher precision in less time and with smaller memory footprint.
Using Dual-Network Analyser for extracting communities from Dual Networks

The representation of data and its relationships using networks is prevalent in many research fields such as computational biology, medical informatics and social networks. Recently, complex networks models have been introduced to better capture the insights of the modelled scenarios. Among others, dual networks -based models have been introduced, which consist in mapping information as pair of networks containing the same nodes but different edges. We focus on the use of a novel approach to visualise and analyse dual networks. The method uses two algorithms for community discovery, and it is provided as a Python-based tool with a graphical user interface. The tool is able to load dual networks and to extract both the densest connected subgraph as well as the common modular communities. The latter is obtained by using an adapted implementation of the Louvain algorithm. The proposed algorithm and graphical tool have been tested by using social, biological, and co-authorship networks. Results demonstrate that the proposed approach is efficient and is able to extract meaningful information from dual networks. Finally, as contribution, the proposed graphical user interface can be considered a valuable innovation to the context.
A Geometric Algebra Solution to Wahba's Problem

We retrace Davenport’s solution to Wahba’s classic problem of aligning two pointclouds using the formalism of Geometric Algebra (GA). GA proves to be a natural backdrop for this problem involving three-dimensional rotations due to the isomorphism between unit-length quaternions and rotors. While the solution to this problem is not a new result, it is hoped that its treatment in GA will have tutorial value as well as open the door to addressing more complex problems in a similar way.
Analyzing the Influence of Dataset Composition for Emotion Recognition

Recognizing emotions from text in multimodal architectures has yielded promising results, surpassing video and audio modalities under certain circumstances. However, the method by which multimodal data is collected can be significant for recognizing emotional features in language. In this paper, we address the influence data collection methodology has on two multimodal emotion recognition datasets, the IEMOCAP dataset and the OMG-Emotion Behavior dataset, by analyzing textual dataset compositions and emotion recognition accuracy. Experiments with the full IEMOCAP dataset indicate that the composition negatively influences generalization performance when compared to the OMG-Emotion Behavior dataset. We conclude by discussing the impact this may have on HRI experiments.
Polyhedral Lyapunov Functions with Fixed Complexity

Polyhedral Lyapunov functions can approximate any norm arbitrarily well. Because of this, they are used to study the stability of Linear Time Varying and Linear Parameter Varying systems without being conservative. However, the computational cost of finding them grows unbounded as the size of their representation increases. We present an algorithm that attempts to find polyhedral functions while keeping the size of the representation fixed, allowing us to ne-tune the trade-off between conservativeness and computational complexity. The algorithm first measures the gap from contraction for a given polyhedral function. The solution is then used to find perturbations on the polyhedral function that reduce the contraction gap. The process is repeated until a valid polyhedral Lyapunov function is obtained. Because the algorithm is rooted in linear programming, additional linear constraints and objectives can be directly included. This leads to a flexible approach that can tackle both analysis and control synthesis problems.
Adaptive Gaussian Fuzzy Classifier for Real-Time Emotion Recognition in Computer Games

Emotion recognition has become a need for more realistic and interactive machines and computer systems. The greatest challenge is the availability of high-performance algorithms to effectively manage individual differences and nonstationarities in physiological data, i.e., algorithms that customize models to users with no subject-specific calibration data. We describe an evolving Gaussian Fuzzy Classifier (eGFC), which is supported by a semi-supervised learning algorithm to recognize emotion patterns from electroencephalogram (EEG) data streams. We extract features from the Fourier spectrum of EEG data. The data are provided by 28 individuals playing the games ‘Train Sim World’, ‘Unravel’, ‘Slender The Arrival’, and ‘Goat Simulator’ – a public dataset. Different emotions prevail, namely, boredom, calmness, horror and joy. We analyze individual electrodes, time window lengths, and frequency bands on the accuracy of user-independent eGFCs. We conclude that both brain hemispheres may assist classification, especially electrodes on the frontal (Af3-Af4), occipital (O1-O2), and temporal (T7-T8) areas. We observe that patterns may be eventually found in any frequency band; however, the Alpha (8-13Hz), Delta (1-4Hz), and Theta (4-8Hz) bands, in this order, are more correlated with the emotion classes. eGFC has shown to be effective for real-time learning of EEG data. It reaches a 72.2% accuracy using a variable rule base, 10-second windows, and 1.8ms/sample processing time in a highly-stochastic time-varying 4-class classification problem.
Vertically Aligned GaP/GaAs Core-Multishell Nanowires Epitaxially Grown on Si Substrate

We report the core-multishell GaP/GaAs/GaP nanowires grown in a metalorganic vapor phase epitaxy system by a combination of the vapor–liquid–solid growth mode and conventional vapor phase epitaxy method. By growing GaAs sacrificial segments on the core GaP nanowires followed by selective chemical etching, Au particles were removed and top faceted core-shell nanowires were formed after the shell growth. Analysis by transmission electron microscopy indicated that the shell layers were epitaxially grown on the sides of core GaP nanowires.
The Discovery of a Highly Accreting, Radio-loud Quasar at z = 6.82

Radio sources at the highest redshifts can provide unique information on the first massive galaxies and black holes, the densest primordial environments, and the epoch of reionization. The number of astronomical objects identified at z > 6 has increased dramatically over the last few years, but previously only three radio-loud (R 2500 = f ν,5 GHz/f ν,2500 Å > 10) sources had been reported at z > 6, with the most distant being a quasar at z = 6.18. Here we present the discovery and characterization of PSO J172.3556+18.7734, a radio-loud quasar at z = 6.823. This source has an Mg ii-based black hole mass of ∼3 × 108 M ⊙ and is one of the fastest accreting quasars, consistent with super-Eddington accretion. The ionized region around the quasar is among the largest measured at these redshifts, implying an active phase longer than the average lifetime of the z ≳ 6 quasar population. From archival data, there is evidence that its 1.4 GHz emission has decreased by a factor of two over the last two decades. The quasar’s radio spectrum between 1.4 and 3.0 GHz is steep (α = −1.31). Assuming the measured radio slope and extrapolating to rest-frame 5 GHz, the quasar has a radio-loudness parameter R 2500 ∼ 90. A second steep radio source (α = −0.83) of comparable brightness to the quasar is only 23. ″1 away (∼120 kpc at z = 6.82; projection probability <2%), but shows no optical or near-infrared counterpart. Further follow-up is required to establish whether these two sources are physically associated.
A new transport model for flowing suspensions of active Brownian particles

A dilute suspension of motile micro-organisms subjected to a strong ambient flow, such as algae in the ocean, can be modelled as a population of non-interacting, orientable active Brownian particles (ABPs). Using the Smoluchowski equation (i.e. Fokker-Planck equation in space and orientation), one can capture the non-trivial transport phenomena of ABPs such as taxes and shear-induced migration. This work presents a method to transform the Smoluchowski equation into a physically-relevant transport equation analytically and an asymptotic approximation to the transformation. The approximation recovers the effective diffusivity given by the generalised Taylor dispersion (GTD) model in a quiescent flow as a dispersion tensor, but the approximation does not generate singularities in strain-dominant flows like the GTD model. The transformation has also unveiled the shear trapping mechanism previously shown by Bearon & Hazel (2015) and other new drift and dispersion mechanisms caused by the interactions between the orientational dynamics and the passive advection/diffusion of ABPs. Using gyrotactic suspensions in shear flow as an example, we show that the approximation is more accurate than the GTD model by accounting for shear trapping and the other new mechanisms for drift and dispersion. Lastly, we show that the dispersion from the translational diffusion can be negative, while the dispersion from the interaction between the rotational diffusion and the particles’ motility can be highly asymmetric, in contrast to the positive definite effective diffusivity of the GTD model. The results open a new perspective on the nature and physical origin of the dispersion of ABPs in a general flow field.
Energy-efficient Task Offloading for Relay Aided Mobile Edge Computing under Sequential Task Dependency

In this paper, we study a mobile edge computing (MEC) system in which the mobile device is assisted by a base station (BS) and a cooperative node. The mobile device has sequential tasks to complete, whereas the cooperative node assists the mobile device on both task offloading and task computation. In specific, two cases are investigated, which are 1) the cooperative node has no tasks to complete itself, and 2) the cooperative node has tasks to complete itself. Our target is to minimize the total energy consumption of the mobile device and the cooperative node through optimizing the transmit duration in task offloading, CPU frequency in task computing along with the task index to offload in the sequential tasks. In the first case, we decompose the mixed-integer non-convex problem into two levels. In the lower level problem, thanks to the convexity, Karush-Kuhn-Tucker (KKT) conditions are utilized to simplify the problem, which is then solved with bisection search. In the upper level problem, to find solution of the task index to offload, rather than utilizing traversal method, we develop a monotonic condition to simplify the searching process. In the second case, in order to guarantee the successful computation of the mobile device and cooperative node, the uploading transmission is classified into three schemes. Within each scheme, the non-convex problem is decomposed. In the lower level problem, semi-closed solution is found by Lagrangian dual method. In the upper level problem, traversal method is applied to find the optimal offloading index.
Preparation of Chloride Ion Selective Electrode and its Potential Response to Different Chloride Solutions Representing Concrete Environments

Ag/AgCl electrode was made from anodized Ag wire and the influence of anodization current density on stability of Ag/AgCl electrode was studied in this paper. Potential response of Ag/AgCl electrode was tested in synthetic concrete pore solutions with different concentrations of chloride ions and influences of sulfate, calcium, potassium and sodium ion on the potential response of Ag/AgCl electrode were also measured. The results show that Ag/AgCl electrode has the best potential stability when it is prepared with 0.4 mA/m2 of current density for 2 hours and there is no measurable potential difference among 20 electrodes prepared with such anodizing condition. The potential of Ag/AgCl electrode develops to a constant value in less than 60 seconds and maintains stable during the test period when immersed into synthetic concrete pore solution with different amount of chlorides. Ag/AgCl electrode shows a good linear potential response to a wide range of chloride concentrations from 0.005 to 1.0 M. Sulfate, calcium and sodium ions show inconsiderable influences on the potential of Ag/AgCl electrode. Therefore, it is suggested that Ag/AgCl electrodes can be used as chloride sensors in concrete exposed to different environments.
Indium and impurity incorporation in InGaN films on polar, nonpolar, and semipolar GaN orientations grown by ammonia molecular beam epitaxy

The effects of NH3 flow, group III flux, and substrate growth temperature on indium incorporation and surface morphology have been investigated for bulk InGaN films grown by ammonia molecular beam epitaxy. The incorporation of unintentional impurity elements (H, C, O) in InGaN films was studied as a function of growth temperature for growth on polar (0001) GaN on sapphire templates, nonpolar (101¯0) bulk GaN, and semipolar (112¯2), (202¯1) bulk GaN substrates. Enhanced indium incorporation was observed on both (101¯0) and (202¯1) surfaces relative to c-plane, while reduced indium incorporation was observed on (112¯2) for co-loaded conditions. Indium incorporation was observed to increase with decreasing growth temperature for all planes, while being relatively unaffected by the group III flux rates for a 1:1 Ga:In ratio. Indium incorporation was found to increase at the expense of a decreased growth rate for higher ammonia flows; however, smooth surface morphology was consistently observed for growth on s.
Assessment of The "IHI Global Trigger Tool" Reliability: New Perspectives From A Brazilian Study.

BACKGROUND The Institute for Healthcare Improvement Global Trigger Tool (IHI-GTT) is a simple and inexpensive method to identify adverse events (AEs) through retrospective search of triggers in medical records. Despite its large adoption in Brazilian hospitals, the reliability of the method has not been investigated locally. Moreover, availability of human resources might be a barrier to its implementation in low-resourced systems. The objective of this study was to evaluate the interrater reliability of an adapted version of IHI-GTT and compare it between nurses and medical students as primary reviewers in a hospital in Brazil. METHODS Two 4th-5th year-medical students and two experienced nurses applied GTT to a sample of 220 medical records randomly selected from 1,172 hospital admissions of adults (≥18 years) from Oct-Nov, 2016. Ability to identify AE was compared between pairs and against medical reviewer through percentage inter-examiner agreement and Kappa coefficient (K). Two outcomes - "AE identification" and "category of harm" - were evaluated according to two different denominators - "admissions" (the total number of admissions evaluated in the sample; reflects the presence or not of at least one AE in each admission) and "all possibilities of agreement" (obtained by adding each identified AE to the admissions without events; allows agreement assessment to be performed for each AE individually). RESULTS Were identified 199 adverse events in 90 hospitalizations, with rates of 40.9% of admissions with AEs, 76.1 AEs/1,000 patient-days and 90.5 AEs/100 admissions. Comparing student-pair and nurse-pair, we found K=0.76 (95%IC 0.62-0.88) and K=0.17 (95%IC 0.06-0.27) for "AE identification" outcome and K=0.28 (95%IC 0.01-0.55) and K=0.46 (95%IC 0.28-0.64) for "category of harm" outcome to denominators "admission" and "all possibilities of agreement", respectively. There was no significant difference between the performances of the different primary reviewers composed in any analyses. CONCLUSION IHI-GTT reliability varies considerably depending on the denominator used to calculate agreement. As the purpose of the tool is, in addition to measuring, promoting opportunities for quality of care improvement, the individual analysis of the AEs seems more appropriate. Further studies are needed to assess the implications of the slight agreement reached among primary reviewers on the test's overall accuracy. Moreover, advanced medical students may be considered for primary review in settings where unavailability of staff is a barrier to IHI-GTT adoption.
Lin–Wong divergence and relations on type I censored data

Abstract Divergence measures are statistical tools designed to distinguish between the information provided by distribution functions of f(x) and g(x). The magnitude of divergence has been defined using a variety of methods such as Shannon entropy and other mathematical functions through a history of more than a century. In the present study, we have briefly explained the Lin–Wong divergence measure and compared it to other statistical information such as the Kullback-Leibler, Bhattacharyya and divergence as well as Shannon entropy and Fisher information on Type I censored data. Besides, we obtain some inequalities for the Lin–Wong distance and the mentioned divergences on the Type I censored scheme. Finally, we identified a number of ordering properties for the Lin–Wong distance measure based on stochastic ordering, likelihood ratio ordering and hazard rate ordering techniques.
Metal Chelates as Flame Retardants and Smoke Suppressants for Flexible Poly (Vinyl Chloride)

The thermal degradation in air of flexible PVC treated with various metal chelates containing Fe, Co, Ni, Cu, or Zn combined with two compounds Al(OH)3 and Mg(OH)2, have been studied by differential thermal analysis and thermogravimetry from ambient temperature to 1023 K. The kinetic parameters were obtained using the equation of Kissinger. Flexible PVC treated with flame-retardants showed a high limiting oxygen index, char yield and a low smoke density rating, maximum smoke density, which indicated that the flame retardance of the treated PVC was improved.