Miracle-dz/UniFAR-FTUs huggingface dataset:
A tale of caution: the tails of NGC 752 are much longer than claimed

Understanding the exact extent and content of tidal tails of open clusters provides useful clues on how field stars populate the Milky Way. We reanalyse, using Gaia EDR3 data, the tails around the open cluster NGC 752. Compared to previous analyses, we look at a much wider region around the cluster and use first the convergent point method, coupled with a clustering analysis using dbscan. We find that the cluster, located 433 pc away and well described by a Plummer profile, has very long and asymmetric tails, extending more than 260 pc on the sky (from tip to tip) – four times larger than previously thought – and contains twice as many stars. Numerical models computed with petar serve as a guide and confirm our analysis. The tails follow the predictions from the models, but the trailing tail appears slightly distorted, possibly indicating that the cluster had a complicated history of galactic encounters. Applying an alternative method to the newly developed compact convergent point method, we potentially trace the cluster’s tidal tails to their full extent, covering several thousands of parsecs and more than 1 000 stars. Our analysis therefore opens a new window on the study of open clusters, whose potential will be fully unleashed with future Gaia data releases.
Classification of Abelian domain walls

We discuss domain walls from spontaneous breaking of Abelian discrete symmetries $Z_N$. A series of different domain wall structures are predicted, depending on the symmetry and charge assignments of scalars leading to the spontaneous symmetry breaking (SSB). A widely-existing type of domain walls are those separating degenerate vacua which are adjacent in the field space. We denote these walls as adjacency walls. In the case that $Z_N$ terms are small compared with the $U(1)$ terms, the SSB of $U(1)$ generates strings first and then adjacency walls bounded by strings are generated after the SSB of $Z_N$. For symmetries larger than $Z_3$, non-adjacent vacua exist, we regard walls separating them as non-adjacency walls. These walls are unstable if $U(1)$ is a good approximation. If the discrete symmetry is broken via multiple steps, we arrive at a complex structure that one kind of walls wrapped by another type. On the other hand, if the symmetry is broken in different directions independently, walls generated from the different breaking chains are blind to each other.
Hazard Estimation of Deep Seated Mass Movements by Microseismic Monitoring

The task of the ISDR-20 (TUW - Vienna University of Technology) and ISDR-21 (TUG – Graz University of Technology) projects is the integration of geodetic and geophysical monitoring into a uniform surveillance system for deep-seated mass movements. The combination of continuous GPS measurements, high resolution strain meter observations, and a local seismic monitoring network should lead into an Integrated Monitoring System (IMoS). Seismic monitoring yields information on fracture and stick-slip phenomena caused by the mass movement, the strain meter will monitor local strain changes, and GPS measurements result in the medium to long term trend of surface displacements. Another aspect of GPS and broad band seismic monitoring is the coverage of the whole spectrum of movement, which ranges from quasi-continuous displacement via stick-slip to critical fracture. The combination of the two methods offers the opportunity to monitor displacements over a very broad frequency band from periods of seismic waves (~1/100 second) via short-time oscillation (minutes to hours) to long-time trends (several years). Interpretation of IMoS data will be based on structural models of the mass movements, developed by earlier projects within IDNDR and ISDR. The development of IMoS is in tight cooperation with Prof. F.K. Brunner, TUG. The test site is the well-investigated deep-seated mass movement Gradenbach. Another seismic monitoring campaign has been accomplished at Niedergallmig/Matekopf (Tirol) in cooperation with alpS (project A.2.4). This cooperation includes the sharing of seismic equipment and scientific data. For the seismic monitoring tasks, cooperation with Dr. M. Joswig, Institute of Geophysics, University of Stuttgart, has already been established. E. Bruckl had the opportunity of a two weeks stay at Niigata University, Japan, and to participate also INTERPRAEVENT 2006 in September 2006. A paper covering the essential results of seismic monitoring within ISDR-20 was presented (Bruckl and Mertl, 2006) and a special report covering experiences and new ideas developed during this visit was already sent to OAW. In July 2007 E. Bruckl was invited to present a paper at the 11th congress of the International Society for Rock Mechanics at Lisbon, Portugal. The paper describes the current progress in event detection and localization of microseismic events on deep-seated mass movements gained within the ISDR-20 project (Mertl and Bruckl, 2007).
Singer Identification for Metaverse with Timbral and Middle-Level Perceptual Features

Metaverse is an interactive world that combines reality and virtuality, where participants can be virtual avatars. Anyone can hold a concert in a virtual concert hall, and users can quickly identify the real singer behind the virtual idol through the singer identification. Most singer identification methods are processed using the frame-level features. However, expect the singer's timbre, the music frame includes music information, such as melodiousness, rhythm, and tonal. It means the music information is noise for using frame-level features to identify the singers. In this paper, instead of only the frame-level features, we propose to use another two features that address this problem. Middle-level feature, which represents the music's melodiousness, rhythmic stability, and tonal stability, and is able to capture the perceptual features of music. The timbre feature, which is used in speaker identification, represents the singers' voice features. Furthermore, we propose a convolutional recurrent neural network (CRNN) to combine three features for singer identification. The model firstly fuses the frame-level feature and timbre feature and then combines middle-level features to the mix features. In experiments, the proposed method achieves comparable performance on an average F1 score of 0.81 on the benchmark dataset of Artist20, which significantly improves related works.
Flying-Qubit Control via a Three-level Atom with Tunable Waveguide Couplings

The control of flying qubits is at the core of quantum networks. As often carried by single-photon fields, the flying-qubit control involves not only their logical states but also their shapes. In this paper, we explore a variety of flying-qubit control problems using a three-level atom with time-varying tunable couplings to two input-output channels. It is shown that one can tune the couplings of a $\Lambda$-type atom to distribute a single photon into the two channels with arbitrary shapes, or use a $V$-type atom to catch an arbitrary-shape distributed single photon. The $\Lambda$-type atom can also be designed to transfer a flying qubit from one channel to the other, with both the central frequency and the photon shape being converted. With a $\Xi$-type atom, one can use the tunable coupling to shape a pair of correlated photons via cascaded emission. In all cases, analytical formulas are derived for the coupling functions to fulfil these control tasks, and their physical limitations are discussed as well. These results provide useful control protocols for high-fidelity quantum information transmission over complex quantum networks.
Co-optimization of Battery Routing and Load Restoration for Microgrids with Mobile Energy Storage Systems

Mobile energy storage systems (MESS) offer great operational flexibility to enhance the resiliency of distribution systems in an emergency condition. The optimal placement and sizing of those units are pivotal for quickly restoring the curtailed loads. In this paper, we propose a model for load restoration in a microgrid while concurrently optimizing the MESS routes required for the same. The model is formulated as a mixed-integer second order cone program by considering the state of charge and evolution of the lower and upper bounds of battery capacities. Simulation results tested on the IEEE 123-bus benchmark system demonstrate the efficacy of the proposed model.
Fast GPU bounding boxes on tree-structured scenes

Computation of bounding boxes is a fundamental problem in high performance rendering, as it is an input to visibility culling and binning operations. In a scene description structured as a tree, clip nodes and blend nodes entail intersection and union of bounding boxes, respectively. These are straightforward to compute on the CPU using a sequential algorithm, but an efficient, parallel GPU algorithm is more elusive. This paper presents a fast and practical solution, with a new algorithm for the classic parentheses matching problem at its core. The core algorithm is presented abstractly (in terms of a PRAM abstraction), then with a concrete mapping to the thread, workgroup, and dispatch levels of real GPU hardware. The algorithm is implemented portably using compute shaders, and performance results show a dramatic speedup over a sequential CPU version, and indeed a reasonable fraction of maximum theoretical throughput of the GPU hardware. The immediate motivating application is 2D rendering, but the algorithms generalize to other domains, and the core parentheses matching problem has other applications including parsing.
Optical polarization signatures of black hole X-ray binaries

Polarimetry provides an avenue for probing the geometry and physical mechanisms producing optical radiation in many astrophysical objects, including stellar binary systems. We present the results of multiwavelength (BVR) polarimetric studies of a sample of historical black hole X-ray binaries, observed during their outbursts or in the quiescent (or near-quiescent) state. We surveyed both long- and short-period systems, located at different Galactic latitudes. We performed careful analysis of the interstellar polarization in the direction on the sources to reliably estimate the intrinsic source polarization. Intrinsic polarization was found to be small (<0.2 per cent) in sources observed in bright soft states (MAXI J0637−430 and 4U 1957+115 ). It was found to be significant in the rising hard state of MAXI J1820+070 at the level of ∼0.5 per cent and negligible in the decaying hard state and during its failed outbursts, while Swift J1357.2−0933 showed its absence in the rising hard state. Three (XTE J1118+480 , V4641 Sgr , V404 Cyg ) sources observed during quiescence show no evidence of significant intrinsic polarization, while MAXI J1820+070 is the only black hole X-ray binary which showed substantial (>5 per cent) intrinsic quiescent-state polarization with a blue spectrum. The absence of intrinsic polarization at the optical wavelengths puts constraints on the potential contribution of non-stellar (jet, hot flow, accretion disc) components to the total spectra of quiescent black hole X-ray binaries.
Alleviating Robust Overfitting of Adversarial Training With Consistency Regularization

Adversarial training (AT) has proven to be one of the most effective ways to defend Deep Neural Networks (DNNs) against adversarial attacks. However, the phenomenon of robust overfitting, i.e., the robustness will drop sharply at a certain stage, always exists during AT. It is of great importance to decrease this robust generalization gap in order to obtain a robust model. In this paper, we present an in-depth study towards the robust overfitting from a new angle. We observe that consistency regularization, a popular technique in semi-supervised learning, has a similar goal as AT and can be used to alleviate robust overfitting. We empirically validate this observation, and find a majority of prior solutions have implicit connections to consistency regularization. Motivated by this, we introduce a new AT solution, which integrates the consistency regularization and Mean Teacher (MT) strategy into AT. Specifically, we introduce a teacher model, coming from the average weights of the student models over the training steps. Then we design a consistency loss function to make the prediction distribution of the student models over adversarial examples consistent with that of the teacher model over clean samples. Experiments show that our proposed method can effectively alleviate robust overfitting and improve the robustness of DNN models against common adversarial attacks.
Chunk-based Nearest Neighbor Machine Translation

Semi-parametric models, which augment generation with retrieval, have led to impressive results in language modeling and machine translation, due to their ability to retrieve fine-grained information from a datastore of examples. One of the most prominent approaches, kNN-MT, exhibits strong domain adaptation capabilities by retrieving tokens from domain-specific datastores (Khandelwal et al., 2021). However, kNN-MT requires an expensive retrieval operation for every single generated token, leading to a very low decoding speed (around 8 times slower than a parametric model). In this paper, we introduce a chunk-based kNN-MT model which retrieves chunks of tokens from the datastore, instead of a single token. We propose several strategies for incorporating the retrieved chunks into the generation process, and for selecting the steps at which the model needs to search for neighbors in the datastore. Experiments on machine translation in two settings, static and “on-the-fly” domain adaptation, show that the chunk-based kNN-MT model leads to significant speed-ups (up to 4 times) with only a small drop in translation quality.
Omnidirectional underwater surveying and telepresence

Exploratory dives are traditionally the first step for marine scientists to acquire information on a previously unknown area of scientific interest. Manned submersibles have been the platform of choice for such exploration, as they allow a high level of environmental perception by the scientist on-board, and the ability to take informed decisions on what to explore next. However, manned submersibles have extremely high operation costs and provide very limited bottom time. Remotely operated vehicles (ROVs) can partially address these two issues, but have operational and cost constraints that restrict their usage. This paper discusses new capabilities to assist scientists operating lightweight hybrid remotely operated vehicles (HROV) in exploratory missions of mapping and surveying. The new capabilities, under development within the Spanish National project OMNIUS, provide a new layer of autonomy for HROVs by exploring three key concepts: Omni-directional optical sensing for collaborative immersive exploration, Proximity safety awareness and Online mapping during mission time.
Low back pain in farmers: The association with agricultural work management, disability, and quality of life in Korean farmers

This study aimed to identify the associations among low back pain (LBP), LBP‐related disability, agricultural working condition management, and quality of life (QOL) in Korean farmers. Demographic information, agricultural work management, and outcomes of LBP were obtained by standardized questionnaires (Oswestry Disability Index [ODI] for disability and European Quality of Life‐5 Dimensions‐3‐Level version [EQ‐5D‐3L] for QOL). Presence of LBP was determined if the LBP had lasted longer than 1 week or had been more frequent than once a month, and presence of LBP‐related disability was determined if the ODI score was more than 12. Poor health checkups (OR [odds ratio] = 1.70–86, p < .05), were positively associated with LBP, and working at dawn (OR = 1.85–1.96, p < .05), was positively associated with LBP‐related disability after adjusting related demographic factors. EQ‐5D‐3L indexes were significantly lower in participants with LBP (0.83 ± 0.17 vs. 0.92 ± 0.06, p < .001) and disability (0.81 ± 0.18 vs. 0.93 ± 0.05, p < .001). This study showed that the presence of LBP was related to poor health checkups and that LBP‐related disability was related to a poor working time schedule. These results indicate poor QOL and suggest the need for coping strategies such as regular health checkups and a proper working time schedule.
Function-Based Modulation Control for Modular Multilevel Converters under Varying Loading and Parameters Conditions

This study presents a new function-based modulation control technique for modular multilevel converters (MMCs). The main contribution of this study is the formulation of two new modulation functions for the required switching signals of the MMC's upper and lower sub-modules, respectively. The output and circulating current equations of the converter are employed to attain the arm's currents which are utilised for the proposed modulation functions, which have two important features: (i) it is much less complex compared to the existing control methods of MMC; and (ii) the proposed controller can be regulated properly to deal with parameter variations in a bid to ensure stable and accurate performance. In this controller, the MMC output current magnitude and phase angle required for special active and reactive power sharing can be easily applied to the modulation functions. Also, the equivalent capacitors of upper and lower sub-modules are discussed based on the proposed modulation functions. Finally, simulations are performed in Matlab/Simulink environment to evaluate the performance of the proposed control technique in both the dynamic conditions of load as well as varying parameters.
S ECURE M ULTI -P ARTY C OMPUTATION : G ARBLED C IRCUITS

This paper presents Yao’s Garbled Circuit protocol to compute any boolean function F ( a , b ) where a and b are Alice and Bob’s private inputs. Assuming Alice and Bob are honest, this protocol is guaranteed to produce the correct result without leaking any additional information about a or b . Yao’s protocol is an example of Secure Multi-Party Computation, a process in which multiple parties with private inputs collectively compute a function without the use of a third-party. Before presenting the Garbled Circuit protocol, this paper introduces Secure Multi-Party Computation, explaining the canonical Millionaire Problem . We then examine Oblivious Transfer , a necessary tool in Yao’s protocol.
Comparison of sensitivity and resolution load sensor at various configuration polymer optical fiber

This study uses a load sensor with a macro-bending on polymer optical fiber loop model which is placed between two plates with a buffer spring. The load sensor with light intensity modulation principle is an infrared LED emits light through the polymer optical fiber then received by the phototransistor and amplifier. Output voltage from the amplifier continued to arduino sequence and displayed on the computer. Load augment on the sensor resulted in an increase of curvature on polymer optical fibers that can cause power losses gets bigger too. This matter will result in the intensity of light that received by phototransistor getting smaller, so that the output voltage that ligable on computer will be getting smaller too. The sensitivity and resolution load sensors analyzed based on configuration with various amount of loops, imperfection on the jacket, and imperfection at the cladding and core of polymer optical fiber. The results showed that the augment on the amount of load, imperfection on the jacket an.
Probability based estimation theory for respondent driven sampling

Many populations of interest present special challenges for traditional survey methodology when it is difficult or impossible to obtain a traditional sampling frame. In the case of such “hidden” populations at risk of HIV/AIDS, many researchers have resorted to chain-referral sampling. Recent progress on the theory of chain-referral sampling has led to Respondent Driven Sampling (RDS), a rigorous chain-referral methodwhich allows unbiased estimation of the target population. In this article we present new probability-theoretic methods for making estimates fromRDS data. The new estimators offer improved simplicity, analytical tractability, and allow the estimation of continuous variables. An analytical variance estimator is proposed in the case of estimating categorical variables. The properties of the estimator and the associated variance estimator are explored in a simulation study, and compared to alternative RDS estimators using data from a study of New York City jazz musicians. The new estimator gives results consistent with alternative RDS estimators in the study of jazz musicians, and demonstrates greater precision than alternative estimators in the simulation study.
Termite dispersal is influenced by their diet

Termites feed on vegetal matter at various stages of decomposition. Lineages of wood- and soil-feeding termites are distributed across terrestrial ecosystems located between 45°N and 45°S of latitude, a distribution they acquired through many transoceanic dispersal events. While wood-feeding termites often live in the wood on which they feed and are efficient at dispersing across oceans by rafting, soil-feeders are believed to be poor dispersers. Therefore, their distribution across multiple continents requires an explanation. Here, we reconstructed the historical biogeography and the ancestral diet of termites using mitochondrial genomes and δ13C and δ15N stable isotope measurements obtained from 324 termite samples collected in five biogeographic realms. Our biogeographic models showed that wood-feeders are better at dispersing across oceans than soil-feeders, further corroborated by the presence of wood-feeders on remote islands devoid of soil-feeders. However, our ancestral range reconstructions identified 33 dispersal events among biogeographic realms, 18 of which were performed by soil-feeders. Therefore, despite their lower dispersal ability, soil-feeders performed several transoceanic dispersals that shaped the distribution of modern termites.
A toy model for the effective density of acoustic metamaterials

We propose a simple mechanical system that can be used as a toy model for calculating the effective density of acoustic metamaterials. Through analytical calculations, it gives a better understanding of how the effective density can become negative, when the system responds elastically instead of inertially. We show that this toy model can reproduce, qualitatively, the acoustical behaviour of some real acoustic metamaterials.
Co-immunolocalization of Disc1 and Gas7 protein in adult mice brain

Objective: The aim of the present study was to check the potential interaction of two neurodevelopmental proteins, Disc1 and Gas7, in the adult mice brain. Methods: Twenty-four male Swiss albino mice were used for the study. The mice were 12 weeks old in the beginning of the experiment. Immunohistochemistry and co-immunofluorescence were performed on the coronal sections of mice brain and immunoblotting and co-immunoprecipitation were done on the whole brain lysate. Results: Data from immunohistochemistry and co-immunofluorescence indicate the occurrence and co-localization of Disc1 and Gas7 proteins in soma and projections of the brain cells. Immunostaining was observed in cerebral cortex, hypothalamus, midbrain, pons, medulla oblongata and CA3 of hippocampus of the brain. The data from Immunoblotting and co-immunoprecipitation validates the presence and interaction of Disc1 and Gas7 protein in whole brain lysate. Conclusion: Data indicates the potential interaction of Disc1 and Gas7 protein in adult brain. The study highlights the need for further research on Disc1–Gas7 protein interaction in brain development and neuro-disorders.