Miracle-dz/UniFAR-FTUs huggingface dataset:
Heat Transfer Generated by the Interaction of Single and Multiple Tandem Jets in Crossflow

“Twin jets in Crossflow” is a common configuration that finds application in several large and/or small scale industrial fields. The interest in such a configuration is further enhanced by its dependence in several parameters, that may be geometric, dynamic, thermal, or relative to the handled fluid composition. We propose to focus in the present work on the effect of the number of the emitted jets on the generated heat transfer, in presence of an unchanged uniform crossflow. To reach this goal, single, double and triple jet configurations were simulated, based upon the resolution of the Navier Stokes equations by means of the RSM (Reynolds Stress Model) second order turbulent closure model, together with a non uniform grid system particularly tightened near the emitting nozzles. After validation, we tried to find out the impact of the number of the handled jets on their cooling “power” by tracking the temperature distribution of the resulting flowfield. Since in practically all applications we are in need of higher efficiencies and then of higher operating temperatures, we are constantly concerned about not going beyond the shielding material melting temperature. If the use of cooling jets proves to be efficient, this may bring a significant progress in the technological field. Keywords: twin jets, crossflow, jets‟ number, heat transfer.
Footprints of triggering in large area surveys of the nearby ISM and YSOs

Abstract Our goal is to evaluate the role of triggering effects on the star formation and early stellar evolution by presenting a statistically large sample of cloud and low-mass YSO data. We conducted large area surveys (ranging from 400 square-degree to 10800 square-degree) in optical, NIR and FIR. The distribution of the ISM and low-mass YSOs were surveyed. A relative excess was found statistically in the number of dense and cold core bearing clouds and low mass YSOs in the direction of the FIR loop shells indicating a possible excess in their formation.
Structural Identity Representation Learning for Blockchain-Enabled Metaverse Based on Complex Network Analysis

The metaverse and its underlying blockchain technology have attracted extensive attention in the past few years. How to mine, process, and analyze the tremendous data generated by the metaverse systems has posed a number of challenges. Aiming to address them, we mainly focus on modeling and understanding the blockchain transaction network from a structural identity perspective, which represents the entire network structure and reveals the relations among multiple entities. In this article, we analyze three metaverse-related systems: non-fungible token (NFT), Ethereum (ETH), and Bitcoin (BTC) from the structural-identity perspective. First, we conduct the complex network analysis of the metaverse network and obtain several new insights (i.e., power-law degree distribution, disconnection, disassortativity, preferential attachment, and non-rich-club effect). Secondly, based on such findings, we propose a novel representation learning method named structure-to-vector with random pace (SVRP) for learning both the latent representation and structural identity of the network. Thirdly, we conduct node classification and link prediction tasks with the integration of graph neural networks (GNNs). Empirical results on three real-world datasets demonstrate that our proposed SVRP outperforms other existing methods in multiple tasks. In particular, our SVRP achieves the highest node classification accuracy (Acc) (99.3%) and $F1$ -score (96.7%) while only requiring original non-attributed graphs.
Variable low-energy absorption in the X-ray spectrum of ESO 103–G35

L'observation RX de cette galaxie de Seyfert de type 1.9 revele une forte absorption dans le spectre RX de faible energie. Cette absorption est variable et les observations presentees indiquent une decroissance de la densite colonne d'un facteur 2 en 90 jours. Une interpretation possible est celle de nuages absorbants s'eloignant de la ligne de visee
Evidence for Local Anisotropy of the Hubble Flow

The Universe is accurately isotropic when measured by radio source counts and deep galaxy counts, or by the integrated microwave and X-ray backgrounds. On the other hand, galaxies are distributed in a decidedly clumpy way on scales of a few tens of megaparsecs, and it is natural therefore to ask whether galaxy redshifts show systematic departures from Hubble's law when averaged over similar scales. Discussions of this question have tended to develop along lines fixed by ideas for what might be reasonable patterns of deviations from Hubble's law. If the coherence length of the effect is large enough, it makes sense to expand the redshift field in a power series in distance, just as Oort (55) did for the velocity field in the Galaxy. This has been a convenient approach in theoretical discussions, but so far has proved to be only moderately useful as a framework for analysis of the data, perhaps because one coherence length contains too few independent groups of galaxies. A second framework is based on the thought that the mass concentration in a cluster of galaxies might induce a more or less radial flow toward the cluster in the surrounding field (24). In
Ultrafast structural dynamics in electronically excited solid neon. II. Molecular-dynamics simulations of the electronic bubble formation

Mol. -dynamics simulations of structural relaxation in electronically excited NO-doped solid neon are presented. The NO impurity is excited to its lowest A (3ss) Rydberg state, inducing a rearrangement of the surrounding medium in the form of a bubble, due to repulsion between the Rydberg electron and the closed-shell surrounding species. The simulations were carried out using the thermal harmonic quantum correction in order to account for quantum effects. The first shell response is characterized by an initial expansion and an oscillatory response, which point to coherent dynamics and confirm the exptl. obsd. slower dynamics than in solid argon. The medium response is characterized by a collective oscillatory behavior of the shells around the impurity. We investigated the role of quantum effects, nature of the NO-Ne ground- and excited-state potentials and of the Ne-Ne potential on the dynamics. It appears that the expansion stage is mainly detd. by the fact that the repulsive interaction between the excited impurity and the Ne lattice reaches out beyond the first shell, so that the first three shells are simultaneously pushed outward. Combined with the short-range character of the Ne-Ne interaction, this sets in motion a larger mass than in solid argon. The collective response is mainly due to the short-range Ne-Ne interaction and the tight nature of the Ne lattice. Quantum effects play a negligible role in the overall dynamics, at least to the level of approxn. of our simulations. [on SciFinder (R)]
Afterglow light curves from magnetized GRB flows

Abstract Using the RMHD code MRGENESIS and the radiative transfer code SPEV we compute multiwavelength afterglow light curves of magnetized ejecta of gamma-ray bursts interacting with a uniform circumburst medium. We are interested in the emission from the reverse shock when ejecta magnetization varies from σ0 = 0 to σ0 = 1. For typical parameters of the ejecta, the emission from the reverse shock peaks for magnetization σ0 ~ 0.01 − 0.1, and is suppressed for higher σ0. We fit the early afterglow light curves of GRB 990123 and 090102 and discuss the possible magnetization of the outflows of these bursts. Finally we discuss the amount energy left in the magnetic field which is available for dissipation at later afterglow stages.
Sound scattering by deformed cylinders of finite length

An approximate solution is derived for the scattering of sound by circular cylinders of finite length with a deformed axis and composition profile and (cross‐sectional) radius that vary arbitrarily along the axis. This solution is a generalization of previous work [T. K. Stanton, J. Acoust. Soc. Am. 83, 55–63 (1988) and T. K. Stanton, J. Acoust. SOc. Am. 83, 64–67 (1988)] where the scattering by straight finite cylinders of uniform fluid and elastic material, respectively, were described. The new formulation is used to calculate the scattering of sound at all frequencies from a prolate spheroid with a high aspect ratio (ratio of major axis to minor axis) and a uniformly bent finite cylinder of constant cross‐sectional radius. There is excellent agreement between the calculations involving the prolate spheroid and the exact spheroidal wave function solution. Furthermore, numerical integration of the deformed cylinder formula required far less computer time than calculating the exact solution. The calculati.
Effects of primordial fluctuations on the abundances of light elements

Some of the effects of primordial inhomogeneities on the production of H-2, He-3, and Li-7 are investigated. For the most part, temperature fluctuations have only small effects on the abundances. The density fluctuations are modeled by a unimodal distribution so that the Universe is characterized by the mean density and the relative amplitude of the density variations. It has been found that the constraint which H-2 production imposes on the mean mass density is eased somewhat by allowing for density inhomogeneities. However, unless the composition of the interstellar matter is atypical of most of the matter in the Universe, the mass density will be at least a factor of 3 below the critical density. For reasonable estimates of the pregalactic abundances, sufficient He-3 and Li-7 cannot be produced in the same model universe. Production of both Li-7 and H-2 requires large-amplitude primordial fluctuations, while sufficient He-3 and H-2 can be formed in very low-density, fairly homogeneous universes.
Auerbach's theorem and tensor products of Banach spaces

In his well-known treatise, Banach mentions that there exist complete normed bi-orthogonal systems in any finite-dimensional (real) Banach space—a result he attributes to H. Auerbach ((1), p. 238). The purpose of this note is to present a proof of this result (valid for complex as well as real Banach spaces), and to give some applications to the theory of tensor products of Banach spaces.
Deep Learning-Based Multipath DoAs Estimation Method for mmWave Massive MIMO Systems in Low SNR

To realize the direction-of-arrivals (DoAs) estimation without the prior information about the multipath number, a novel method using the deep learning is introduced for the millimeter (mmWave) massive multiple-input and multiple-output (MIMO) systems. In particular, the DoAs estimation is decomposed into three sub-problems, which are solved by the corresponding convolutional neural network (CNN), respectively. The estimation of multipath number is achieved by a multi-label classification model using the proposed CNN-I. Then, the proposed CNN-II is introduced for the DoA estimation of the line-of-sight (LOS) path. Based on the predicted multipath number obtained by the CNN-I, a regression model using the proposed CNN-III is applied for the DoAs estimation of non-line-of-sight (NLOS) paths. The proposed DoAs estimation method is implemented by learning the non-linear relationship between the sample covariance matrix of the received signal and the angles, thus reconstructing the mapping model. A series of results validate the superiority of the proposed DoAs estimation method in low signal-to-noise-ratio (SNR) regimes. The CNN-I is capable of achieving the good multipath number estimation performance across a range of SNRs. The classification model based on the proposed CNN-II and the regression model using the proposed CNN-III achieve the lower DoAs estimation root mean square error (RMSE) compared with some deep learning-based methods, estimation of signal parameters via rotational invariance techniques (ESPRIT) and Root-MUltiple SIgnal Classification (Root-MUSIC) methods. Remarkably, the proposed method using the CNN-II exhibits the good robustness in the DoA estimation of the LOS path. Furthermore, the low DoAs estimation RMSE is also achieved in the uniform planar array.
Power system observability with minimal phasor measurement placement

The placement of a minimal set of phasor measurement units (PMUs) so as to make the system measurement model observable, and thereby linear, is investigated. A PMU placed at a bus measures the voltage as well as all the current phasors at that bus, requiring the extension of the topological observability theory. In particular, the concept of spanning tree is extended to that of spanning measurement subgraph with an actual or a pseudomeasurement assigned to each of its branches. The minimal PMU set is found through a dual search algorithm which uses both a modified bisecting search and a simulated-annealing-based method. The former fixes the number of PMUs while the latter looks for a placement set that leads to an observable network for a fixed number of PMUs. In order to accelerate the procedure, an initial PMU placement is provided by a graph-theoretic procedure which builds a spanning measurement subgraph according to a depth-first search. From computer simulation results for various test systems it appears that only one fourth to one third of the system buses need to be provided with PMUs in order to make the system observable. >
MCFN: A Multichannel Fusion Network for Sleep Apnea Syndrome Detection

Sleep apnea syndrome (SAS) is the most common sleep disorder which affects human life and health. Many researchers use deep learning methods to automatically learn the features of physiological signals. However, these methods ignore the different effects of multichannel features from various physiological signals. To solve this problem, we propose a multichannel fusion network (MCFN), which learns the multilevel features through a convolution neural network on different respiratory signals and then reconstructs the relationship between feature channels with an attention mechanism. MCFN effectively fuses the multichannel features to improve the SAS detection performance. We conducted experiments on the Multi-Ethnic Study of Atherosclerosis (MESA) dataset, consisting of 2056 subjects. The experiment results show that our proposed network achieves an overall accuracy of 87.3%, which is better than other SAS detection methods and can better assist sleep experts in diagnosing sleep disorders.
HDGCN: Dual-Channel Graph Convolutional Network With Higher-Order Information for Robust Feature Learning

Graph convolutional network (GCN) algorithms have been employed to learn graph embedding due to its inductive inference property, which is extended to GCN with higher-order information. However, the application of these higher-order information is confusing and not effectively distinguished. In addition, single channel GCN using higher-order information is weak for robust feature learning, and existing dual-channel GCNs rarely take higher-order information into account. To alleviate the above problems, we propose a dual-channel GCN with higher-order information for robust feature learning, denoted as HDGCN. First, features of positive and negative higher-order graphs are extracted that fully exploits the self-contained attributes and higher-order geometric information. Meantime, the features of original graph structure are extracted by a conventional GCN that utilizes the self-contained feature attributes. Then, node features are represented as edge features by a feature fusion function. For the selection of negative samples, a fractional staggered negative sampling method is applied, by which the trainable graph model gains better topological features. Finally, the performance on seven real-world datasets demonstrates that HDGCN obtains the state-of-the-art performance on pairwise link prediction, higher-order structure prediction, and node classification tasks. By changing the attributes of multiple tasks, it can be proved that HDGCN has good robustness.
An inverse scattering formula that uses all the data

An inverse scattering formula is derived for an ensemble of experiments in which a three-dimensional scattering object is illuminated by an impulsive point source which successively occupies all positions on a surface surrounding the object. For each source position, the scattered field is recorded by receivers at all positions on the surface. The data from such a complete set of experiments contains redundant information about the scattering potential. The formula provides a way of integrating over the redundancy to give a perfect reconstruction of the scattering potential within the Born approximation. The formula involves three steps: first, the data as a function of receiver position are backpropagated (or focused) to an arbitrary image point inside the surface using the Kirchhoff integral; second, the source array is focused on the same point by a second Kirchhoff integral over source positions; finally, the image field created by the double focusing is filtered as a function of frequency and integrated over all frequencies. The formula relies upon an unusual representation of the spatial delta function which follows from an integral relation between the causal Green function, the anti-causal Green function, and their difference. The method can be extended to the case of an arbitrary background medium if ray-asymptotic approximations are used for the Green functions.
High relative accuracy with some special matrices related to Γ and β functions

For some families of totally positive matrices using Γ$$ \Gamma $$ and β$$ \beta $$ functions, we provide their bidiagonal factorization. Moreover, when these functions are defined over integers, we prove that the bidiagonal factorization can be computed with high relative accuracy and so we can compute with high relative accuracy their eigenvalues, singular values, inverses and the solutions of some associated linear systems. We provide numerical examples illustrating this high relative accuracy.
Children and Young People’s Involvement in Designing Applied Games: Scoping Review

Background User involvement is widely accepted as key for designing effective applied games for health. This especially holds true for children and young people as target audiences, whose abilities, needs, and preferences can diverge substantially from those of adult designers and players. Nevertheless, there is little shared knowledge about how concretely children and young people have been involved in the design of applied games, let alone consensus guidance on how to do so effectively. Objective The aim of this scoping review was to describe which user involvement methods have been used in the design of applied games with children and young people, how these methods were implemented, and in what roles children and young people were involved as well as what factors affected their involvement. Methods We conducted a systematic literature search and selection across the ACM Digital Library, IEEE Xplore, Scopus, and Web of Science databases using State of the Art through Systematic Review software for screening, selection, and data extraction. We then conducted a qualitative content analysis on the extracted data using NVivo. Results We retrieved 1085 records, of which 47 (4.33%) met the eligibility criteria. The chief involvement methods were participatory design (20/47, 43%) and co-design (16/47, 37%), spanning a wide range of 45 concrete activities with paper prototyping, group discussions, and playtesting being the most frequent. In only half of the studies (24/47, 51%), children and young people participated as true design partners. Our qualitative content analysis suggested 5 factors that affect their successful involvement: comprehension, cohesion, confidence, accessibility, and time constraints. Conclusions Co-design, participatory design, and similar high-level labels that are currently used in the field gloss over very uneven degrees of participation in design and a wide variety of implementations that greatly affect actual user involvement. This field would benefit from more careful consideration and documentation of the reason of user involvement. Future research should explore concrete activities and configurations that can address the common challenges of involving children and young people, such as comprehension, cohesion, confidence, and accessibility.
The relationship between multiple traumatic events and the severity of posttraumatic stress disorder symptoms – evidence for a cognitive link

ABSTRACT Background: Previous research has shown that multiple traumatic experiences cumulatively increase the risk for the development of severe symptoms of posttraumatic stress disorder (PTSD). Yet, little is known about the specific psychological mechanism through which this increased risk comes about. Objective: In the present study, we examined a possible cognitive link between multiple traumatic events and PTSD symptom severity through dysfunctional cognitions and expectations. Methods: A sample of patients with a diagnosed PTSD (N = 70; M Age = 42.06; 82% female) and high symptom burden (IES-R M = 79.24) was examined. On average, patients had experienced 5.31 different traumatic events. In a structural equation model, we tested the hypothesis that the relationship between multiple traumatic experiences and PTSD symptom severity is mediated through dysfunctional general cognitions and dysfunctional situation-specific expectations. General trauma-related cognitions were assessed with the Posttraumatic Cognition Inventory (PTCI) and trauma-related situational expectations were assessed with the Posttraumatic Expectations Scale (PTES). Results: The direct effect of the number of traumatic events on PTSD symptom severity was non-significant. Instead, as hypothesised, there was evidence for a significant indirect effect via dysfunctional general cognitions and situation-specific expectations. Conclusions: The current results further specify the cognitive model of PTSD by indicating that the relationship between the number of traumatic events and PTSD symptom severity is mediated through dysfunctional cognitions and expectations. These findings emphasise the importance of focused cognitive treatment approaches that seek to modify dysfunctional cognitions and expectations in people with multiple traumatic experiences. HIGHLIGHTS This study shows a cognitive link between the experience of multiple traumatic events and the severity of posttraumatic stress disorder (PTSD) symptoms. The aforementioned relationship is mediated through trauma-related general cognitions and situational expectations. The results provide further evidence for the cognitive model of PTSD and further specify it by considering different types of trauma-related cognitions.
Scattering of sound waves by a cylindrical vortex: a semi-analytical theory

A semi-analytical theory for the scattering of plane sound waves by a compressible, non-homentropic, circular-cylindrical, single vortex is presented in this paper. As a special case, the scattering of sound by a cylindrical inhomogeneity (hot spot) is investigated. Contrary to the otherwise analogous quantum-mechanical scattering problem, there are singularities in the modified acoustic wave equation for radii xs ∈ (0, ∞) when the scattering by a vortex is considered. It will be shown how these singularities can be treated. This sound-scattering theory is applied to the problem of the interaction of weak plane shock waves with a strong cylindrical vortex. The calculated scattered sound signal has a rather complicated structure in which a cylindrical wave with an essentially quadrupolar directivity pattern is discernible. In the case of shock–hot-spot interaction a scattered sound signal with dipole-like amplitude is obtained. Both results qualitatively agree with experimental findings.