Miracle-dz/UniFAR-FTUs huggingface dataset:
The dim inner accretion disk of the quiescent black hole A0620-00

We observed the X-ray nova A0620-00 with the Hubble Space Telescope (HST) Faint object Spectrograph 16 yr after its 1975 outburst. We present a single spectrum (1250-4750 A), which is approximately an average over a full 7.8 hr orbital cycle of the source. The continuum can be fitted approximately by a blackbody model with T = 9000 K and a small projected source area, which is approximately 1 % of the expected area of the accretion disk. AS0620-00 is faint in the far-UV band; its luminosity is comparable to the luminosity of the quiescent dwarf-nova accretion disk (i.e., excluding the white dwarf). By analogy with dwarf novae, the optical luminosity of the disk (M(sub nu) approximately = 7) and the orbital period of A0620-00 imply that the rate of mass transfer onto the outer disk in M(sub d) approximately 10(exp -10) solar mass/yr. We also observed A0620-00 with the ROSAT PSPC X-ray detector for 3 x 10(exp 4) s and detected a faint source (5 sigma) at the location of the X-ray nova. For an assumed blackbody spectrum the source temperature and luminosity are approximately 0.16 keV and 6 x 10(exp 30) ergs/s, respectively (d = 1 kpc). This luminosity implies that the rate of mass transfer into the black hole is extraordinarily small: M(sub BH) less than 5 x 10(exp -15) solar mass/yr. The much larger mass transfer rate onto the outer disk, and the UV/X-ray faintness of the inner disk confirm key predictions of the disk instability model for the nova outburst of A0620-00 published by Huang and Wheeler and by Mineshige and Wheeler.
“Such a Good Night”: Analyses of Korean-English code-switching and music video comments of ASTRO’S songs

To attract global multilingual audiences, English lyrics had been included in K-Pop songs for decades as a strategy (Lauren, 2018; Sea, 2018). This paper analyzed the English usage of “All Night”, “Blue Flame”, and “Knock” by ASTRO, a third-generation K-Pop group from a non-mainstream agency to examine code-switching and the global recognition of K-Pop songs. All songs were examined by using code-switching theories from Poplack (1980) and Bullock and Toribio (2009) and other theories on function analysis by Lawrence (2010) and Lee (2004) and comment analysis by Fernandez-Martinez et al. (2014) and Kwon (2019). The findings revealed that the majority of code switches in “All Night” and “Blue Flame” were inter-sentential, yet “All Night” and “Knock” were more similar in utilizing English by having a new function (i.e., emphasizing a dialog from one’s perspective), an important addition to Lee’s (2004) functions. Furthermore, from the usage and function analysis and the comment analysis, the audience responses seemed to be influenced by the singers’ mispronunciations and the non-existence of a new function that failed to create uniqueness in English usage in “Blue Flame,” which may have led to the song’s failure to win awards. In conclusion, the research suggested that, in the near-absence of promotional support from the agency, the interplay among the number of switches, accurate pronunciations, and a new English-switching function seemed to play an important role in making “All Night” and “Knock” popular among multilingual audiences.
Local vibrational modes in Mg-doped GaN grown by molecular beam epitaxy

Local vibrational modes in the region of the acoustic and optical phonons are reported for Mg-doped GaN grown by molecular beam epitaxy. The modes, studied by Raman spectroscopy, appear in addition to the known modes in the high-energy region around 2200 cm−1. We suggest disorder-activated scattering and scattering from Mg-related lattice vibrations to be the origin of the low-energy modes. Our assignment is supported by calculations based on a modified valence-force model of Kane. Temperature-dependent measurements between 4 and 300 K exclude an electronic Raman-scattering mechanism. We also report a new line at 2129 cm−1 and discuss the origin of all five observed high-energy modes.
Effect of Danhong injection on prognosis and inflammatory factor expression in patients with acute coronary syndrome during the perioperative period of percutaneous coronary intervention: A systematic review and meta-analysis

Objectives In China, Danhong injection (DHI) is recommended by expert consensus and is widely used in the perioperative management of patients with acute coronary syndrome (ACS). This study investigates the effect of perioperative DHI administration and the timing of DHI administration on patients with ACS undergoing percutaneous coronary intervention (PCI) by analyzing the prognosis and anti-inflammatory effects. This article summarizes the most up-to-date clinical evidence on DHI, and in this study, we assesses treatment efficacy of DHI in patients with ACS. Methods A total of seven databases (PubMed, Embase, Cochrane Library, SINOMED, CNKI, Wanfang, and VIP) were searched from the time of their inception to 1 July 2022. Clinical randomized controlled trials (RCTs) of DHI combined with PCI for the treatment of ACS were included. RCT quality was assessed using the Cochrane Handbook risk-of-bias tool, and STATA 17.0 was used for meta-analysis. Results In total, 33 studies including 3,458 patients with ACS undergoing PCI were included in the meta-analysis. Compared with conventional therapy alone, the combination of DHI and conventional therapy significantly decreased the incidence of major adverse cardiovascular events (MACEs; P<0.001) and improved the reperfusion rate (P < 0.001). Serum high-sensitivity C-reactive protein (hs-CRP) and interleukin (IL)-6 levels were substantially reduced in the test group (P<0.001). In addition, the plasma levels of myocardial injury markers and cardiac troponin T (cTnT) declined significantly (P < 0.01). Compared with the control group, DHI improved the left ventricular ejection fraction (LVEF; P < 0.001) and reduced B-type natriuretic peptide (BNP; P < 0.001) levels. Subgroups were established based on different timings of DHI administration: preoperative, intraoperative, and postoperative groups. The results showed that the incidence of MACEs and the reperfusion rate did not differ between the groups. Among the subgroups, the postoperative group exhibited significantly lower levels of BNP, hs-CRP, and IL-6 serum and a significantly higher level of LVEF (P < 0.05). Conclusion The combination of DHI and conventional therapy results in a better therapeutic effect than that observed with conventional therapy alone in patients with ACS. To improve treatment efficacy, postoperative initiation of DHI is recommended as a standard treatment. Further research is needed to confirm these results. Systematic review registration Identifier: CRD42022344830.
Impact of Maximum Hops Per Cycle On Network-on-Chip Router using Express Bypass Channels

We investigate the effect of maximum hops per cycle in a Network-on-Chip (NoC) router which uses Express Bypass Channels (EBC). To reduce transmission latency, NoC with EBC sends all bypass requests and flits at the same time. The flits are allowed to traverse both one-and two-dimension paths without getting latched in any of the routers. According to the simulation results, the transmission latency is reduced significantly even when only two nodes are permitted to be skipped using EBC.
Ear your heart: transcutaneous auricular vagus nerve stimulation on heart rate variability in healthy young participants

Background Transcutaneous auricular vagus nerve stimulation (taVNS) stimulating the auricular branch of the vagus nerve along a well-defined neuroanatomical pathway, has promising therapeutic efficacy. Potentially, taVNS can modulate autonomic responses. Specifically, taVNS can induce more consistent parasympathetic activation and may lead to increased heart rate variability (HRV). However, the effects of taVNS on HRV remain inconclusive. Here, we investigated changes in HRV due to brief alteration periods of parasympathetic-vagal cardiac activity produced by taVNS on the cymba as opposed to control administration via the helix. Materials and Methods We compared the effect of 10 min of active stimulation (i.e., cymba conchae) to sham stimulation (i.e., helix) on peripheral cardiovascular response, in 28 healthy young adults. HRV was estimated in the time domain and frequency domain during the overall stimulation. Results Although active-taVNS and sham-taVNS stimulation did not differ in subjective intensity ratings, the active stimulation of the cymba led to vagally mediated HRV increases in both the time and frequency domains. Differences were significant between active-taVNS and both sham-taVNS and resting conditions in the absence of stimulation for various HRV parameters, but not for the low-frequency index of HRV, where no differences were found between active-taVNS and sham-taVNS conditions. Conclusion This work supports the hypothesis that taVNS reliably induces a rapid increase in HRV parameters when auricular stimulation is used to recruit fibers in the cymba compared to stimulation at another site. The results suggest that HRV can be used as a physiological indicator of autonomic tone in taVNS for research and potential therapeutic applications, in line with the established effects of invasive VNS. Knowledge of the physiological effect of taVNS short sessions in modulating cardiovagal processing is essential for enhancing its clinical use.
Fractal analysis of the dark matter and gas distributions in the Mare-Nostrum universe

We develop a method of multifractal analysis of N-body cosmological simulations that improves on the customary counts-in-cells method by taking special care of the effects of discreteness and large scale homogeneity. The analysis of the Mare-Nostrum simulation with our method provides strong evidence of self-similar multifractal distributions of dark matter and gas, with a halo mass function that is of Press-Schechter type but has a power-law exponent -2, as corresponds to a multifractal. Furthermore, our analysis shows that the dark matter and gas distributions are indistinguishable as multifractals. To determine if there is any gas biasing, we calculate the cross-correlation coefficient, with negative but inconclusive results. Hence, we develop an effective Bayesian analysis connected with information theory, which clearly demonstrates that the gas is biased in a long range of scales, up to the scale of homogeneity. However, entropic measures related to the Bayesian analysis show that this gas bias is small (in a precise sense) and is such that the fractal singularities of both distributions coincide and are identical. We conclude that this common multifractal cosmic web structure is determined by the dynamics and is independent of the initial conditions.
Global Asymptotic Stability for General Linear MIMO Distributed Systems: An Approach Based on Robust-Adaptive Controllers

Global asymptotic stability of a decentralised control architecture usually can be guaranteed if: (i) conservative controllers are designed, (ii) collective stability conditions are satisfied, or (iii) interaction terms are neutral. This paper extends the collective stability method to incorporate adaptive controllers and shows that this method is insufficient for systems with large-gain interconnections. Subsequently, we show that global asymptotic stability can be systematically ensured by exploiting vector Lyapunov functions and algebraic Riccati equations. This leads to a scalable distributed architecture where local controllers require information from corresponding subsystems and neighbouring controllers. Conveniently, the communication flow has the same topology as the coupling graph. Theoretical results are validated through application of the proposed architecture to voltage control of a DC power network.
Implementing DASH-Aligned Meals and Self-Measured Blood Pressure to Reduce Hypertension at Senior Centers: A RE-AIM Analysis

Low-income, minority seniors face high rates of hypertension that increase cardiovascular risk. Senior centers offer services, including congregate meals, that can be a valuable platform to reach older adults in underserved communities. We implemented two evidence-based interventions not previously tested in this setting: DASH-aligned congregate meals and Self-Measured Blood Pressure (SMBP), to lower blood pressure (BP) at two senior centers serving low-income, racially diverse communities. The study enrolled congregate meal program participants, provided training and support for SMPB, and nutrition and BP education. DASH-aligned meals delivered 40% (lunch) or 70% (breakfast and lunch) of DASH requirements/day. Primary outcomes were change in BP, and BP control, at Month 1. Implementation data collected included client characteristics, menu fidelity, meal attendance, SMBP adherence, meal satisfaction, input from partner organizations and stakeholders, effort, and food costs. We used the RE-AIM framework to analyze implementation. Study Reach included 94 older, racially diverse participants reflecting neighborhood characteristics. Effectiveness: change in systolic BP at Month 1 trended towards significance (−4 mmHg, p = 0.07); change in SMBP reached significance at Month 6 (−6.9 mmHg, p = 0.004). We leveraged existing community-academic partnerships, leading to Adoption at both target sites. The COVID pandemic interrupted Implementation and Maintenance and may have attenuated BP effectiveness. DASH meals served were largely aligned with planned menus. Meal attendance remained consistent; meal satisfaction was high. Food costs increased by 10%. This RE-AIM analysis highlights the acceptability, feasibility, and fidelity of this DASH/SMBP health intervention to lower BP at senior centers. It encourages future research and offers important lessons for organizations delivering services to older adults and addressing cardiovascular risk among vulnerable populations.
Diffusion approximations for load balancing mechanisms in cloud storage systems

Abstract In large storage systems, files are often coded across several servers to improve reliability and retrieval speed. We study load balancing under the batch sampling routeing scheme for a network of n servers storing a set of files using the maximum distance separable (MDS) code (cf. Li (2016)). Specifically, each file is stored in equally sized pieces across L servers such that any k pieces can reconstruct the original file. When a request for a file is received, the dispatcher routes the job into the k-shortest queues among the L for which the corresponding server contains a piece of the file being requested. We establish a law of large numbers and a central limit theorem as the system becomes large (i.e. n → ∞), for the setting where all interarrival and service times are exponentially distributed. For the central limit theorem, the limit process take values in ℓ2, the space of square summable sequences. Due to the large size of such systems, a direct analysis of the n-server system is frequently intractable. The law of large numbers and diffusion approximations established in this work provide practical tools with which to perform such analysis. The power-of-d routeing scheme, also known as the supermarket model, is a special case of the model considered here.
Intelligent Control Scheme Formulation for the Biotechnological Filter

The problem of air pollution is significant, as there is a negative impact on human health. This problem is especially relevant in large cities with many people living there and many enterprises. As part of the research, a solution is proposed where a non-standard approach is implemented using moss to purify the air in specific locations. This solution, if appropriately scaled, can have a significant environmental and social impact by replacing the planting of many trees. It is planned to create a prototype of a biotechnological filter and further monitoring and analysis of the performance of systems, including the cultivation of a plant crop - moss. The article describes the planned experiments to create an autonomous control system supporting moss growth using reinforcement learning algorithms. For the algorithms, the most crucial part is available data. For this reason, the process of data collection from the biofilter is described. This approach will allow us to analyze the operation of the filter components both in the laboratory and actual conditions, as well as maintain all the requirements. In general, reducing air pollution will protect the climate and the environment. The research group develops an effective biofilter for the environment through a carefully selected and unique combination of biology and control technologies.
Linking Sleep and Aggression: Examining the Role of Response Inhibition and Emotional Processing

Although sleep loss is theorized to increase aggression risk, knowledge regarding the sleep–aggression relationship or explanatory psychological processes is limited. In this study, we examined whether recent sleep duration predicted subsequent laboratory aggression and whether neurocognitive indices of attentional and motor inhibition and negative emotional processing explained the sleep–aggression relationship. Participants (n = 141) wore Fitbit Flex devices and kept a sleep diary for 3 days. Event-related potentials were measured during an emotional-linguistic go/no-go task, followed by a laboratory aggression paradigm. Results of mixed-model repeated measures analyses of variance linked shorter sleep duration with reduced motor inhibition processing during negative and neutral word blocks and greater aggression. However, neurocognitive indices did not explain the sleep–aggression link. This is the first evidence that naturally occurring sleep loss predicts increases in laboratory aggression across the task and suggests that shorter sleepers are more vulnerable to rash action in negative and neutral contexts. Implications of these findings for understanding aggression are discussed.
A Novel Probabilistic Network Model for Estimating Cognitive-Gait Connection Using Multimodal Interface

Research in human gait analysis has captivated several computer vision researchers to solve human identification problems. The proposed work provides a novel approach for cognitive state estimation via multimodal analysis. The advantage of the multimodal system is to provide adequate motion signatures with the ensemble of multimodal gait data to ensure data reliability for classification. The relationship between human cognitive states and gait is predicted using both temporal and nontemporal probabilistic models. We estimate prior probability tables for the nontemporal probabilistic model known as a simple Bayesian model after analyzing the data acquired from the inertial measurement unit (IMU), electroencephalography (EEG), and multiple Kinect V2.0 sensors. A novel dynamic Bayesian network (DBN) is used as a probabilistic temporal model for estimating the most probable sequence of transitions among human cognitive states. We apply Gaussian mixture modeling with expectation maximization (GMM-EM) to tune transition and emission probabilities for maximizing the probability of the observed sequence. A promising estimation accuracy of 88.6% is obtained. Also, principal component analysis (PCA) and $k$ -nearest neighbor (kNN) algorithms are applied separately to calculate the input probabilities for DBN model. It is observed that both GMM-EM and kNN-based approaches outperform all the state-of-the-art techniques. Moreover, standard statistical tests are performed on the acquired data set to validate the experimental results.
Low-symmetry ferroelectric phases stabilized by anisotropic misfit strain

The complete thermodynamic potential of (111) ferroelectric thin ﬁlms including anisotropic in-plane misﬁt strain, in-plane shear strain, and external stress is developed based on the Landau-Ginzburg-Devonshire thermodynamic theory. Anisotropic strain-tuned low-symmetry equilibrium phases in (111) single-domain ferroelectric PbTiO 3 ﬁlms were investigated via the developed nonlinear thermodynamic potential and the misﬁt strain– misﬁt strain phase diagram was constructed. It was found that the anisotropic epitaxial strain can effectively control the orientations of polarization vectors, which determine the symmetry of equilibrium phases, and their functionalities. In particular, two types of low-symmetry triclinic phases, disappearing under isotropic strain states, can be stabilized by anisotropic strains. Low-symmetry monoclinic and triclinic ferroelectric phases and ﬁeld-induced phase transitions were also analyzed in depth. It was indicated that the monoclinic ( M 1 A ) symmetry rhombohedral-like–tetragonal-like transition and triclinic ( T 1r )-monoclinic ( M 1 B ) phase transition would give rise to the superior piezoelectric properties as compared to other structure phase transitions. Electric ﬁeld-enhanced piezoelectric response in triclinic structure originates from the elastic softening that is related to the shear u 5 . These results provide guidance for interpreting and understanding more experimental observations as well as the designing of high-performance piezoelectric ﬁlms.
Scale-free Monte Carlo method for calculating the critical exponent γ of self-avoiding walks

We implement a scale-free version of the pivot algorithm and use it to sample pairs of three-dimensional self-avoiding walks, for the purpose of efficiently calculating an observable that corresponds to the probability that pairs of self-avoiding walks remain self-avoiding when they are concatenated. We study the properties of this Markov chain, and then use it to find the critical exponent γ for self-avoiding walks to unprecedented accuracy. Our final estimate for γ is 1.15695300(95).
Application of Machine Learning to Ranking Predictors of Anti-VEGF Response

Abstract Age-related macular degeneration (AMD) is a heterogeneous disease affecting the macula of individuals and is a cause of irreversible vision loss. Patients with neovascular AMD (nAMD) are candidates for the anti-vascular endothelial growth factor (anti-VEGF) treatment, designed to regress the growth of abnormal blood vessels in the eye. Some patients fail to maintain vision despite treatment. This study aimed to develop a prediction model based on features weighted in order of importance with respect to their impact on visual acuity (VA). Evaluations included an assessment of clinical, lifestyle, and demographic factors from patients that were treated over a period of two years. The methods included mixed-effects and relative importance modelling, and models were tested against model selection criteria, diagnostic and assumption checks, and forecasting errors. The most important predictors of an anti-VEGF response were the baseline VA of the treated eye, the time (in weeks), treatment quantity, and the treated eye. The model also ranked the impact of other variables, such as intra-retinal fluid, haemorrhage, pigment epithelium detachment, treatment drug, baseline VA of the untreated eye, and various lifestyle and demographic factors. The results identified variables that could be targeted for further investigation in support of personalised treatments based on patient data.