Miracle-dz/UniFAR-FTUs huggingface dataset:
Measurement of the binding energy of ultracold 87 Rb 133 Cs molecules using an offset-free optical frequency comb

We report the binding energy of Rb87Cs133 molecules in their rovibrational ground state measured using an offset-free optical frequency comb based on difference frequency generation technology. We create molecules in the absolute ground state using stimulated Raman adiabatic passage (STIRAP) with a transfer efficiency of 88%. By measuring the absolute frequencies of our STIRAP lasers, we find the energy-level difference from an initial weakly bound Feshbach state to the rovibrational ground state with a resolution of ∼5 kHz over an energy-level difference of more than 114THz; this lets us discern the hyperfine splitting of the ground state. Combined with theoretical models of the Feshbach-state binding energies and ground-state hyperfine structure, we determine a zero-field binding energy of h×114268135.24(4)(3)MHz. To our knowledge, this is the most accurate determination to date of the dissociation energy of a molecule.
DocEE: A Large-Scale Dataset for Document-level Event Extraction

Event extraction (EE) is the task of identi-001 fying events and their types, along with the 002 involved arguments. Despite the great suc-003 cess in sentence-level event extraction, events 004 are more naturally presented in the form of 005 document, with event arguments scattering in 006 multiple sentences. However, a major bar-007 rier to promote document-level event extrac-008 tion has been the lack of large-scale and prac-009 tical training and evaluation datasets. In this 010 paper, we present DocEE, a new document-011 level EE dataset including 20,000+ events, 012 100,000+ arguments. We highlight three fea-013 tures: large-scale annotations, ﬁne-grained 014 event arguments and application-oriented set-015 tings. Experiments show that even SOTA mod-016 els show inferior performance on DocEE, espe-017 cially in cross-domain settings, indicating that 018 DocEE is still a challenging task. We will pub-019 lish DocEE upon acceptance. 020
Speaking in quiet and in noise: Do auditory and articulatory properties pattern together?

It is common that noise is present when speaking and listening and speech perception is detrimentally affected by it. When speaking in noise, talkers change the way they articulate and the way that speech sounds. In terms of acoustic properties, speech in noise typically has greater duration, an increase in F0 and increased energy at higher frequencies [1] and such speech is more intelligible than speech produced in quiet (when noise is mixed with both at the same signal to noise ratio, see [2]). Although the changes in acoustic properties that differentiate speech produced in noise from that produced in quiet have been studied at length, relatively little work has been done on the corresponding articulatory properties. It has been reported that speech in noise is produced with increased motion (both for movements directly related to articulation as well as those for that typically accompany speech, e.g., head motion [3]. Further, it has been shown that when a listener can see the talker, articulations produced in noise provide a more effective boost to intelligibility than those produced in quiet [4]. The aim of the current research is to provide some basic information about the way that auditory and articulatory properties change as a function of the production environment (in quiet or in noise) and the relationship between these changes. This was done by measuring auditory and articulatory (via motion tracking) properties of speech produced in quiet and noise and leveraging the variability across the productions of 8 speakers.
Optimal frequency ﬁltering for speech intelligibility boosting under a constant energy constraint

Natural or synthetic speech is increasingly used in less-than-ideal listening conditions. While talkers have a range of potential strategies available to promote successful communication by adapting to the listener’s context, speech output technology has in the past been largely insensitive to the changing needs of the listener. Recently, context-sensitive speech output algorithms have been proposed and evaluated [1, 2, 3, 4, 5] for both recorded and synthetic speech. These approaches typically modify the speech signal to maintain speech intelligibility without increasing signal level or duration. Two problems need to be solved to deliver beneﬁts in context-sensitive speech output technology. First, speech modiﬁcations must be found which lead to intelligibility increases. Second, the acoustic context (e.g. background noise type, level) must be known, predictable or estimated with sufﬁcient accuracy to enable speech modiﬁcation algorithms to make optimal adjustments. In [6] we evaluated a range of modiﬁcation techniques which reallo-cated speech energy across time and frequency while preserving overall signal-to-noise ratio (SNR), demonstrating substantial listener beneﬁts. However, the most successful modiﬁcations required detailed local noise estimates over time which may be difﬁcult to deliver in practice. An intermediate approach to the use of context is to estimate noise descriptors, and to use these to select a modiﬁcation which has been optimised ofﬂine. The current study focuses on the problem of ofﬂine optimisation of speech modiﬁcations designed to promote intelligibility
Working Paper Series Consumer payment preferences in the euro area

Payments are a key focus of central banks, as - together with the safe, efficient operation of the payments market – wide access to cash is fundamentally important for a healthy economy. In this study, three main research areas were investigated: 1. socioeconomic characteristics that can be associated with financial inclusion; 2. factors behind consumers´ payment choices; 3. underlying factors for holding cash in a wallet (i.e. for transactional pur-poses). Regression results for the first research question confirmed the findings of international literature, i.e. mainly older age, lower income and lower educational level is associated with the lack of access to electronic payment options. The study pursues various approaches to investigate consumer payments choices, and the results from most models showed that those with higher level of income and education, or lower level of cash income are more likely to prefer and actually use electronic payment methods. Finally, concerning the holding of cash the initial expectations were confirmed i.e. those who do not use cash for daily transactions tend to keep less cash in their wallet, while those who indicated preference for cash payments or higher importance of cash payment option are more likely to keep higher cash amounts.
Expression Profiles and Functional Analysis of Plasma Exosomal Circular RNAs in Acute Myocardial Infarction

Acute myocardial infarction (AMI) is a common cardiovascular disease with high rates of morbidity and mortality globally. The dysregulation of circular RNAs (circRNAs) has been shown to be closely related to various pathological aspects of AMI. However, the function of exosomal circRNAs in AMI has yet to be investigated. The purpose of this study was to investigate the expression profiles of plasma exosomal circRNAs in AMI and explore their potential functionality. The expression profiles of plasma exosomal circRNAs in patients with AMI, stable coronary heart atherosclerotic disease (CAD), and healthy controls were obtained from a GEO expression dataset (GSE159657). We also analyzed bioinformatics functionality, potential pathways, and interaction networks related to the microRNAs associated with the differentially expressed circRNAs. A total of 253 exosomal circRNAs (184 up- and 69 down-regulated) and 182 exosomal circRNAs (94 up- and 88 down-regulated) were identified as being differentially expressed between the control group and the AMI and CAD patients, respectively. Compared with the CAD group, 231 different exosomal circRNAs (177 up- and 54 down-regulated) were identified in the AMI group. Functional analysis suggested that the parental genes of exosomal has_circ_0061776 were significantly enriched in the biological process of lysine degradation. Pathway interaction network analysis further indicated that exosomal has_circ_0061776 was associated with has-miR-133a, has-miR-214, has-miR-423, and has-miR-217 and may play a role in the pathogenesis of AMI through the MAPK signaling pathway. This study identified the differential expression and functionality of exosomal circRNAs in AMI and provided further understanding of the potential pathogenesis of an exosomal circRNA-related competing endogenous RNA (ceRNA) network in AMI.
25-Hydroxy vitamin D level is associated with sleep disturbances 25-Hydroxy vitamin D level is associated with sleep disturbances in patients with chronickidney disease on hemodialysis: a cross- in patients with chronickidney disease on hemodialysis: a cross-sectional study sectional study

Background/aim: Deficient levels of vitamin D are an important factor in the pathogenesis of some neurodegenerative diseases. The aim of this study is to determine the relationship between vitamin D deficiency and depression status and sleep disorders of patients on dialysis. Materials and methods: In this cross-sectional study, 121 hemodialysis patients were enrolled. All patients had been on hemodialysis for at least six months at the time of the study. Sleep quality and depression status were measured by using specific inventories. All the patients filled out Pittsburg Sleep Quality Index (PSQI) and Beck Depression Inventory (BDI), and gave blood samples. Vitamin D levels were measured for 121 patients, and statistical analysis was done by using SPSS. Results: Regression analyses demonstrated that low levels of 25(OH)D and high BDI score were independent risk factors for poor sleep quality [ORs were 0.668 (0.566–0.789), 1.080 (1.001–1.164), and 1.080 (1.001–1.164), respectively]. Conclusion: Our results suggest that deficiency of 25(OH)D is an important independent risk factor for poor sleep quality in hemodialysis patients.
Non-LTE time-dependent spectroscopic modelling of Type II-plateau supernovae from the photospheric to the nebular phase: case study for 15 and 25 M⊙ progenitor stars

We present the first non-LTE time-dependent radiative-transfer simulations of supernovae (SNe) II-Plateau (II-P) covering both the photospheric and nebular phases, from similar to 10 to greater than or similar to 1000 d after the explosion, and based on 1.2 B piston-driven ejecta produced from a 15 M-circle dot and a 25 M-circle dot non-rotating solar-metallicity star. The radial expansion of the gradually cooling photosphere gives rise to a near-constant luminosity up to greater than or similar to 100 d after the explosion. The photosphere remains in the outer 0.5 M-circle dot of the ejecta for up to similar to 50 d after the explosion. As the photosphere reaches the edge of the helium core, the SN luminosity drops by an amount mitigated by the progenitor radius and the 56Ni mass. Synthetic light curves exhibit a bell-shaped morphology, evolving faster for more compact progenitors, and with an earlier peak and narrower width in bluer filters. UV and U-band fluxes are very sensitive to line blanketing, the metallicity and the adopted model atoms. During the recombination epoch synthetic spectra are dominated by H i and metal lines, and are largely insensitive to the differing H/He/C/N/O composition of our two progenitor stars. In contrast, synthetic nebular-phase spectra reveal a broader/stronger O i doublet line in the higher-mass progenitor model, reflecting the larger masses of oxygen and nickel that are ejected. Our simulations overestimate the typical luminosity and the visual rise time of standard SNe II-P, most likely a consequence of our progenitor stars being too big and/or too hydrogen rich. Comparison of our simulations with photospheric-phase observations of SN1999em of the same colour is satisfactory. Our neglect of non-thermal excitation/ionization leads to a fast disappearance of continuum radiation and Balmer-line emission at the end of the plateau phase. With the exception of H i lines, our nebular spectra show a striking similarity to contemporaneous observations of SN1999em.
InAlAs/InGaAs/InP field effect transistor with carbon-doped InAlAs buffer layers

InGaAs/InP composite channel transistors have potential applications in high speed optoelectronic integrated circuits due to their dynamic and DC performances. Indeed, the high mobility of InGaAs combined with the high breakdown field and high electron velocity of InP are favorable parameters to obtain high cutoff frequency and low leakage current, and so, make it a good candidate for such application. In this paper we investigate MOVPE structures, in particular HFETs on InAlAs buffer layers, and the influence of the InGaAs channel parameters-thickness and doping-on both gate leakage current and breakdown voltage. Furthermore, the reverse doped structure has been optimized for highest Hall mobility.
WATER IN PROTOPLANETARY DISKS: DEUTERATION AND TURBULENT MIXING

We investigate water and deuterated water chemistry in turbulent protoplanetary disks. Chemical rate equations are solved with the diffusion term, mimicking turbulent mixing in a vertical direction. Water near the midplane is transported to the disk atmosphere by turbulence and is destroyed by photoreactions to produce atomic oxygen, while the atomic oxygen is transported to the midplane and reforms water and/or other molecules. We find that this cycle significantly decreases column densities of water ice at r ≲ 30 AU, where dust temperatures are too high to reform water ice effectively. The radial extent of such region depends on the desorption energy of atomic hydrogen. Our model indicates that water ice could be deficient even outside the sublimation radius. Outside this radius, the cycle decreases the deuterium-to-hydrogen (D/H) ratio of water ice from ∼2 × 10−2, which is set by the collapsing core model, to 10−4–10−2 in 106 yr, without significantly decreasing the water ice column density. The resultant D/H ratios depend on the strength of mixing and the radial distance from the central star. Our finding suggests that the D/H ratio of cometary water (∼10−4) could be established (i.e., cometary water could be formed) in the solar nebula, even if the D/H ratio of water ice delivered to the disk was very high (∼10−2).
Geometrial: Development of Educational Digital Game for Combined Two-Dimensional Figure Learning

Mathematics is one of the subjects that is often considered difficult and boring for students. This is evidenced by the poor scores obtained by the students. One of the chapters that are considered difficult is the geometry chapter, especially on the topic of combined two-dimensional figures studied by students at the Vocational High School (SMK) level. Spatial skills are needed for students to be able to solve combined two-dimensional figures questions, which to learn will be very difficult without using assisted learning media. While the learning so far is still using the conventional learning approach which is considered boring for students. This is due to the absence of learning media that is fun and can be easily accessed by students. This study tries to present a solution to this problem in the form of a mobile-based educational digital game design that can be accessed by all students. This digital educational game is called Geometry. This study uses Research & Development (R&D) combined with the Agile-Extreme Programming method to develop this educational digital game. Tests were carried out using an expert validation approach to game prototypes. This study uses a questionnaire that adapts the Computer System Usability Questionnaire (CSUQ) to assess the usability aspect of the game system built. Meanwhile, to assess this game from the point of view of educational media, this study used an evaluation questionnaire of material experts and media experts. The development process occurs in 3 iterations of development which includes the ideation, conceptualization, and prototyping stages. The results obtained from the assessment of material experts are 88.9% in the aspect of material suitability, and 85.7% in the suitability aspect of learning evaluation. While the results of the assessment obtained from media experts were 77.1% on the software engineering aspect, 76.3% on the visual design aspect, 80% on the media design aspect, and 77.6% on the system usability aspect (CSUQ).
IMPROVED BACKGROUND SUBTRACTION FOR THE SLOAN DIGITAL SKY SURVEY IMAGES

We describe a procedure for background subtracting Sloan Digital Sky Survey (SDSS) imaging that improves the resulting detection and photometry of large galaxies on the sky. Within each SDSS drift scan run, we mask out detected sources and then fit a smooth function to the variation of the sky background. This procedure has been applied to all SDSS-III Data Release 8 images, and the results are available as part of that data set. We have tested the effect of our background subtraction on the photometry of large galaxies by inserting fake galaxies into the raw pixels, reanalyzing the data, and measuring them after background subtraction. Our technique results in no size-dependent bias in galaxy fluxes up to half-light radii r50 ∼ 100 arcsec; in contrast, for galaxies of that size the standard SDSS photometric catalog underestimates fluxes by about 1.5 mag. Our results represent a substantial improvement over the standard SDSS catalog results and should form the basis of any analysis of nearby galaxies using the SDSS imaging data.
Quiver Gauge theories from Lie Superalgebras

We discuss quiver gauge models with matter fields based on Dynkin diagrams of Lie superalgebra structures. We focus on A(1,0) case and we find first that it can be related to intersecting complex cycles with genus $g$. Using toric geometry, A(1,0) quivers are analyzed in some details and it is shown that A(1,0) can be used to incorporate fundamental fields to a product of two unitary factor groups. We expect that this approach can be applied to other kinds of Lie superalgebras;
Goodman–Kruskal Measures of Association

The measures of association proposed by Goodman and Kruskal between 1954 and 1972 can all be described as proportional reduction in error (PRE) measures. They describe the association between two categorical variables in terms of the increase in the probability of correctly predicting the category of one variable when information is supplied about the category of the other variable. The measures λ and τ are for use with any categorical variables, whereas the measure γ is for use when both variables are ordinal. Keywords: association; categorical variable; contingency table; γ; Goodman–Kruskal; λ; measure of association; ordinal variable; proportional reduction in error; PRE; τ
The Bar and Spiral Structure Legacy (BeSSeL) Survey: Mapping the Milky Way with VLBI Astrometry†

Astrometric Very Long Baseline Interferometry (VLBI) observations of maser sources in the Milky Way are used to map the spiral structure of our galaxy and to determine fundamental parameters such as the rotation velocity (Theta(0)) and curve and the distance to the Galactic center (R-0). Here, we present an update on our first results, implementing a recent change in the knowledge about the Solar motion. It seems unavoidable that the IAU recommended values for R0 and Theta(0) need a substantial revision. In particular the combination of 8.5 kpc and 220 km s(-1) can be ruled out with high confidence. Combining the maser data with the distance to the Galactic center from stellar orbits and the proper motion of Sgr A* gives best values of R-0 = 8.3 +/- 0.23 kpc and Theta(0) = 239 or 246 +/- 7 km s(-1), for Solar motions of V-circle dot = 12.23 and 5.25 km s(-1), respectively. Finally, we give an outlook to future observations in the Bar and Spiral Structure Legacy (BeSSeL) survey. (C) 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim
Towards Automatic Facility Layout Design Using Reinforcement Learning

—The accuracy and perfection of layout designing signiﬁcantly depend on the designer’s ability. Quick and near-optimal designs are very difﬁcult to create. In this study, we propose an automatic design mechanism that can more easily design layouts for various unit groups and sites using reinforce- ment learning. Speciﬁcally, we devised a mechanism to deploy units to be able to ﬁll the largest rectangular space in the current site. We aim to successfully deploy given units within a given site by ﬁlling a part of the site. We apply the mechanism to the three sets of units in benchmark problems. The performance was evaluated by changing the learning parameters and iteration count. Consequently, it was possible to produce a layout that successfully deployed units within a given one-ﬂoor site.
Detection of Cardiac Arrhythmia Using Multi-Perspective Convolutional Neutral Network for ECG Heartbeat Classification

The leading death cause all over the world is heart disease. The presence of arrhythmias has to be examined to detect heart disease in early stage. The abnormality in heart beat rhythm is known as Arrhythmia. The speed of heart beat can be detected by Arrhythmia, it may be too slow, too fast or irregular patterns of heart beat are considered as Arrhythmia and there are various types of Arrhythmia. The electrocardiogram (ECG) produces signals, classification of such signals is very crucial for knowing the irregularity in the patterns of heart beat. As detection of arrhythmia is a challenging task, there is a great demand for an automatic detection technique to identify abnormal signals produced by heart which cannot be done manually. Therefore this paper provides a method for detection of Cardiac Arrhythmia using Multi-Perspective Convolutional Neutral Network (MPCNN) for ECG Heartbeat Classification. Basing on Physionet's MIT-BIH Arrhythmia Dataset the signals of ECG arrhythmia can be categorized into five classes. Number of layers, filters and size of the filter are appropriate parameters which are heuristically optimized for operating swiftly for operation of MPCNN effectively. Compared with the ultra-modern methods as Quantum Neural Networks and Deep Convolutional Neural Networks, the proposed method results in efficient performance having high level accuracy of 96.46%, 98.1% and 96.2% are the F1 scores for SVP and PVC respectively. The effective detection of heartbeat rhythm and irregularities can be identified using this model.