Miracle-dz/UniFAR-FTUs huggingface dataset:
Very low latency search pipeline for low mass compact binary coalescences in the LIGO S6 and Virgo VSR2 data

A very low latency search pipeline has been developed for the LIGO S6 and Virgo VSR2 science runs, targeting signals from coalescing compact binary systems with total mass from 2 to 35 solar masses. The goal of this search is to provide both single-detector triggers and multi-detector coincident triggers with a latency of a few minutes, the former for online detector monitoring and the latter to allow searching for electromagnetic counterparts to possible gravitational wave candidates. The features and current performance of this low latency search pipeline are presented.
On a modification of GLS stabilized FEM for solving incompressible viscous flows

We deal with 2D flows of incompressible viscous fluids with high Reynolds numbers. Galerkin Least Squares technique of stabilization of the finite element method is studied and its modification is described. We present a number of numerical results obtained by the developed method, showing its contribution to solving flows with high Reynolds numbers. Several recommendations and remarks are included. We are interested in positive as well as negative aspects of stabilization, which cannot be divorced. Copyright © 2005 John Wiley & Sons, Ltd.
Collapse Safe and Scalable Acyclic Graph Generation using Scale Free Distributions

Most of the generators currently used to build acyclic graphs do so via random selection of edges. Unfortunately, the graphs thus generated inherently have a tendency to collapse, i.e., the resulting graphs always have almost the same and predictable structure. Specifically, we show that if $O(n \log n \log n)$ edges are added to a binary tree of $n$ nodes then with probability more than $O(1/(\log n)^{1/n})$ the depth of all but $O({\log \log n} ^{\log \log n})$ collapses to 1. Experiments show that the maximum depth is very small (less than 3) thereby reducing the DAG to almost a bipartite graph. Their irregularity, as measured by distribution of length of random walks from root to leaves, is also predictable and small. In this work, we develop an approach for generating directed acyclic graphs (DAGs) that have "truly irregular" structure, non-trivial depth distribution, and scale to multi million nodes. With such attributes, these graphs would more appropriately represent real world graphs to be dealt with in near future. The generator provides the user knobs to control the structure and shape of the resulting DAG. We conjecture that structurally sound (collapse safe) scalable acyclic graphs require scale free distributions (just as they were crucial in R-MAT for generating real world interaction graphs). Experiments are presented for graphs of size $2^{23}$ and varying edge densities, and in and out degree distributions.
THE XMM-NEWTON X-RAY EMISSION OF THE SUPERNOVA REMNANT N 120 IN THE LARGE MAGELLANIC CLOUD

We present new XMM-Newton observations of the supernova remnant (SNR) N 120 in the Large Magellanic Cloud, and numerical simulations on the evolution of this SNR which we compare with the X-ray observations. The SNR N 120, together with several H ii regions, forms a large nebular complex (also called N 120) whose shape resembles a semicircular ring. From the XMM-Newton data, we generate images and spectra of this remnant in the energy band between 0.2 and 2.0 keV. The images show that the X-ray emission is brighter toward the east (i.e., toward the rim of the large nebular complex). The EPIC/MOS1 and MOS2 data reveal a thermal spectrum in soft X-rays. Two-dimensional axisymmetric numerical simulations with the Yguazú-a code were carried out assuming that the remnant is expanding into an inhomogeneous interstellar medium with an exponential density gradient and showing that thermal conduction effects are negligible. Simulated X-ray emission maps were obtained from the numerical simulations in order to compare them with the observations. We find good agreement between the XMM-Newton data, previous optical kinematic data, and the numerical simulations; the simulations reproduce the observed X-ray luminosity and surface brightness distribution. We have also detected more extended diffuse X-ray emission that is possibly due to the N 120 large H ii complex or superbubble.
Singularity Elimination of Parallel Mechanism by Redundant Actuations

Singularity is a basic problem for parallel mechanism design because of its many negative influences on the mechanism performances. Traditionally, three kinds of singularities are suitable for analysis of the parallel mechanisms. By considering both the common and redundant actuation parallel mechanisms, general kinematic model is used to obtain input factor matrix and output factor matrix. Based on ranks of the two matrices, the singularity type becomes easy to judge. And the second kind of singularity can be reduced or eliminated by adding special redundant actuation sub-chains. A two-degree-of-freedom parallel mechanism is provided to illustrate the method about how to create the needed redundant actuation sub-chains.
Tornado Frequency and its Large-Scale Environments Over Ontario, Canada

Over the last two decades, there exist ever-increasing changes in tornado frequency over Ontario, Canada. It is shown through a composite analysis that the tornado events occur more frequently over Ontario with stronger low-level cyclonic circulations and stronger baroclinicity under conditions of warmer atmospheric temperature. Tornado has high impacts on Canadian society in terms of loss of life and damage of property. In Canada, during an average year about 80 tornadoes have been reported that result in, on average, 2 deaths, 20 injuries, and tens of mil- lions of dollars in property damage. Because of its small- scale nature, tornado is a localized short-lived phenomenon and it is therefore difficult to detect and predict. Up to date, the detection and prediction of tornado almost solely rely on observations and related analyses. Using proximity sound- ings and analysis data to examine mesoscale environments for severe storms and tornadoes have been extensively documented in previous studies (e.g., (1-3)). Different from these researches, in this work we attempt to diagnose rela- tionships between tornado frequency and its large scale envi- ronments from climatological point of view and to examine the large scale environments associated with large and small frequency of tornado occurrence. Our goal is therefore to anticipate large scale environments that are favorable for more tornadogenesis rather than to forecast an individual tornado. In this study, we examine Ontario tornado fre- quency variability and its relationship with large scale at- mospheric conditions using a composite analysis technique. To our knowledge, this technique is the first time being em- ployed in tornado frequency analysis. 2. DATA
A comparative study between IPSO and MIP for co-ordinated scheduling of electricity and heat within a microgrid

In this paper, an optimization model is developed for co-ordinately scheduling electricity and heat production within a microgrid. The model achieves the minimization of total operating cost including electricity and fuel consumption with various operational constraints considered. Comparative research between the mathematical method of mixed-integer programming (MIP) and meta-heuristic technique of improved particle swarm optimization (IPSO) for solving this model is implemented. Simulation results for the scheduling problem with different sizes and different operational constraints show that the solution precision achieved by IPSO and MIP is very similar, IPSO is much less time-consuming than MIP for the large-scale scheduling problem when the non-linear constraints of power flow within the microgrid are considered and the situation is the opposite when power flow constraints are not considered.
Solving the integrated lot-sizing and job-shop scheduling problem

Production planning and scheduling are usually performed in a sequential manner, thus generating unfeasibility conflicts. Moreover, solving these problems in complex manufacturing systems (with several products sharing different resources) is very challenging in production management. This paper addresses the solution of multi-item multi-period multi-resource single-level lot-sizing and scheduling problems in general manufacturing systems with job-shop configurations. The mathematical formulation is a generalisation of the one used for the Capacitated Lot-Sizing Problem, including detailed capacity constraints for a fixed sequence of operations. The solution method combines a Lagrangian heuristic, determining a feasible production plan for a fixed sequence of operations, with a sequence improvement method which iteratively feeds the heuristic. Numerical results demonstrate that this approach is efficient and more appropriate than a standard solver for solving complex problems, regarding solution quality and computational requirements.
Sharing Design Knowledge Through Codification in Interdisciplinary DSR Collaborations

The goals of design science research (DSR) projects are to generate novel and useful artifacts and to produce rigorous and generalizable design knowledge. Often, DSR projects are conducted in collaborative, interdisciplinary project teams. Different disciplinary approaches to codifying design knowledge result in challenging project interactions. To study this situation, we analyze design knowledge codification in interdisciplinary teams over time. We gain insights from a survey of recent DSR papers that have been published in the AIS Senior Scholars’ Basket. We then present a detailed case study of a longitudinal project that brought to light issues of sharing design knowledge across disciplinary borders. Drawing from the survey and case study, we provide actionable guidance on how to effectively codify and share design knowledge to support researchers and practitioners to build useful artifacts and to make interdisciplinary design knowledge contributions reusable and applicable.
A Practical and Empirical Comparison of Three Topic Modeling Methods Using a COVID-19 Corpus: LSA, LDA, and Top2Vec

This study was prepared as a practical guide for researchers interested in using topic modeling methodologies. This study is specially designed for those with difficulty determining which methodology to use. Many topic modeling methods have been developed since the 1980s namely, latent semantic indexing or analysis (LSI/LSA), probabilistic LSI/LSA (pLSI/pLSA), naïve Bayes, the Author-Recipient-Topic (ART), Latent Dirichlet Allocation (LDA), Topic Over Time (TOT), Dynamic Topic Models (DTM), Word2Vec, Top2Vec and \variation and combination of these techniques. For researchers from disciplines other than computer science may find it challenging to select a topic modeling methodology. We compared a recently developed topic modeling algorithm-Top2Vec- with two of the most conventional and frequently-used methodologies-LSA and LDA. As a study sample, we used a corpus of 65,292 COVID-19-focused s. Among the 11 topics we identified in each methodology, we found high levels of correlation between LDA and Top2Vec results, followed by LSA and LDA and Top2Vec and LSA. We also provided information on computational resources we used to perform the analyses and provided practical guidelines and recommendations for researchers. © 2023 IEEE Computer Society. All rights reserved.
Numerical analysis on propagation of light in turbid media using path-length assigned Monte-Carlo simulation

Using a new algorithm of Monte-Carlo simulation, we simulate the propagation of scattered light under the restricted optical configurations which is corresponds to practical experimental setups of OCTs and DOTs. We demonstrate the path-length distributions of scattered light and the dependence of the distributions of scattering points on the path-length and the scattering order. From numerical results, we discuss the dependence of propagation of scattered light on the scattering order and path-length. This algorithm can speedy and accurately simulate the multiple scattering phenomena under the restricted optical configurations compared with the conventional Monte-Carlo simulation.
Determinition of best set of adjustable parameters with full search and limited search methods

In case of optimization of biochemical networks the best combination of adjustable parameters has to be found keeping low the costs of modification of biochemical network and reducing the risk of unpredicted side effects of processes outside the scope of the model. Dynamic models of biochemical networks usually are in form of system of differential equations and therefore can not be optimized analytically. Usually they are optimized using computationally demanding global stochastic optimization methods which may have hardly predictable duration of optimization. Optimization of all the possible combinations is necessary to find the best set of adjustable parameters per number of parameters in combination. Due to the combinatorial explosion the full search often is not feasible approach if computational and time resources are limited. In this study the performance of full search is compared with forward selection and three metabolic control based methods which need significantly less combinations to be examined. It is found that forward selection is a good compromise in case of larger number of adjustable parameters where the number of possible combinations exceeds the available resources needed for full search in the adjustable parameter space. It is proposed to combine full search for small number of adjustable parameters with forward selection at larger number of adjustable parameters per combination.
Selective Partial Domain Adaptation

Partial Domain Adaptation (PDA), which assumes that the label space of the target domain is a subset of that in the source domain, has attracted much attention in recent years. Due to the difference in the label space of these two domains, it is hard to directly align these two domains in PDA. To solve this problem, we propose a Selective Partial Domain Adaptation (SPDA) method, which selects useful data for the adaptation to the target domain. Speciﬁcally, we ﬁrstly design a Maximum of Cosine (MoC) similarity function customized for PDA to select useful data in the source domain to decrease the domain discrepancy. In the MoC similarity function, for each target sample, we select the source sample with the maximal cosine similarity for adaptation. Moreover, a selective training method is designed to add useful target data into the source domain. In detail, the selective training method ﬁrstly assigns pseudo-labels to target samples with the self-training strategy and then adds target samples with high conﬁdence in terms of pseudo-labels to the source domain. Based on these two selection operations, the proposed SPDA method can select useful data for domain adaptation. Experiments on several datasets demonstrate the effectiveness of the proposed SPDA method.
Assessment of summer monsoon precipitation derived from five reanalysis datasets over East Asia

Precipitation, which is the predominant component of the East Asian summer monsoon (EASM), may have large uncertainties among reanalysis datasets. We comprehensively evaluate the performance of five reanalysis datasets in reproducing the EASM precipitation. These datasets are NCEP/NCAR Reanalysis 1 project (NCEP1), NCEP/US Department of Energy Atmospheric Model Intercomparison Project II reanalysis (NCEP2), Japanese 25‐year Reanalysis project (JRA‐25), Interim ECMWF Reanalysis (ERA‐Interim), and Modern Era Retrospective‐analysis for Research and Applications (MERRA). Results show that the five reanalysis datasets can generally reproduce the climatology and interannual variability of EASM precipitation. Especially, MERRA and ERA‐Interim have the highest skills. Considering different‐class precipitation, large uncertainties exist in the category of non‐rainfall and heavy rainfall. The five reanalysis datasets overestimate the non‐rainfall frequency, and JRA‐25 and NCEP2 overestimate the heavy rainfall frequency. The well‐known interdecadal variation around the mid‐1990s can also be better depicted by ERA‐Interim and MERRA. For the linear trend of precipitation, only MERRA can reasonably reproduce the increasing tendency over southern China and the western Pacific and the decreasing tendency over the Indo‐China Peninsula. Based on EOF analysis, the spatial–temporal structure of EASM precipitation has been examined. MERRA, NCEP1 and ERA‐Interim can better capture both the spatial patterns and principle components of the first two EOF modes. Based on our evaluation, the preferential reanalysis datasets for investigating the EASM precipitation are ERA‐Interim and MERRA, which also permit the more precise investigation of interannual to decadal variability.
Kinetic Models and Brillouin Scattering in a Molecular Gas

Within the framework of the Wang Chang–Uhlenbeck kinetic equation, we propose a model description of molecular gases. The model is related to the models earlier discussed by Hanson and Morse. In our formulation, the model requires no adjustable parameters to analyze the light scattering spectrum from a molecular gas. We apply the model theory to recent Brillouin scattering experiments on hydrogen, deuterium, and hydrogen deuteride and find excellent agreement.
MATLAB Functions for Mie Scattering and Absorption

A set of Mie functions has been developed in MATLAB to compute the four Mie coefficients an, bn, cn and dn, efficiencies of extinction, scattering, backscattering and absorption, the asymmetry parameter, and the two angular scattering functions S1 and S2. In addition to the scattered field, also the absolute-square of the internal field is computed and used to get the absorption efficiency in a way independent from the scattered field. This allows to test the computational accuracy. This first version of MATLAB Mie Functions is limited to homogeneous dielectric spheres without change in the magnetic permeability between the inside and outside of the particle. Required input parameters are the complex refractive index, m= m’+ im”, of the sphere (relative to the ambient medium) and the size parameter, x=ka, where a is the sphere radius and k the wave number in the ambient medium. 1 Equation on p. 16 corrected, April 2006
Critical nuclear charge of quantum mechanical three-body problem

The critical nuclear charge Zc for a three-body quantum mechanical system consisting of positive and negative charges is the minimum charge for the system to remain in a bound state. This work presents a study of the critical nuclear charge for heliumlike systems with infinite nuclear mass, and also a range of the reduced mass up to μ M = 0.5. The results help us to resolve a discrepancy in the literature for the infinite mass case, and they are the first to study the dependence on μ M . It is found that Zc has a maximum at μ M = 3525, which is intermediate between the atomic structure of helium, and the molecular structure of H 2 . Zc for the infinite mass case is found to be 0.911028267. This value is compatible with the result of Baker, et al, who found the upper bound for Zc to be 0.91103. However, it does not agree with other results in the literature. The understanding of the critical charge will bring us a deeper appreciation of the stability of a three-body system as a function of the reduced mass, correlation effects of coulombic potential and more importantly, the physics of a three-body quantum mechanical system.
PaRK-Detect: Towards Efficient Multi-Task Satellite Imagery Road Extraction via Patch-Wise Keypoints Detection

Automatically extracting roads from satellite imagery is a fundamental yet challenging computer vision task in the field of remote sensing. Pixel-wise semantic segmentation-based approaches and graph-based approaches are two prevailing schemes. However, prior works show the imperfections that semantic segmentation-based approaches yield road graphs with low connectivity, while graph-based methods with iterative exploring paradigms and smaller receptive fields focus more on local information and are also time-consuming. In this paper, we propose a new scheme for multi-task satellite imagery road extraction, Patch-wise Road Keypoints Detection (PaRK-Detect). Building on top of D-LinkNet architecture and adopting the structure of keypoint detection, our framework predicts the position of patch-wise road keypoints and the adjacent relationships between them to construct road graphs in a single pass. Meanwhile, the multi-task framework also performs pixel-wise semantic segmentation and generates road segmentation masks. We evaluate our approach against the existing state-of-the-art methods on DeepGlobe, Massachusetts Roads, and RoadTracer datasets and achieve competitive or better results. We also demonstrate a considerable outperformance in terms of inference speed.
Edge detection using 2-D local structural information

A description is presented of three related methods for detecting 2-D region discontinuities. One method extends Leclerc's (1985) 2-D work. The other two arise from the concept behind the maximum-homogeneity filter. All of the methods use some form of 2-D neighborhood-partitioning mechanism, like that of Leclerc, and hence use 2-D local structural information. Also, all the methods allow detection of multiple edges about an image point. The methods are described and illustrative results presented. <<ETX>>
A general Multidimensional Monte Carlo Approach for Dynamic Hedging under stochastic volatility

In this work, we introduce a Monte Carlo method for the dynamic hedging of general European-type contingent claims in a multidimensional Brownian arbitrage-free market. Based on bounded variation martingale approximations for Galtchouk-Kunita-Watanabe decompositions, we propose a feasible and constructive methodology which allows us to compute pure hedging strategies w.r. t arbitrary square-integrable claims in incomplete markets. In particular, the methodology can be applied to quadratic hedging-type strategies for fully path-dependent options with stochastic volatility and discontinuous payoffs. We illustrate the method with numerical examples based on generalized Follmer-Schweizer decompositions, locally-risk minimizing and mean-variance hedging strategies for vanilla and path-dependent options written on local volatility and stochastic volatility models.
Optical current and voltage sensor using differential spectroscopy

A novel optical system that combines a polarimetric current sensor based on the Faraday effect, and a voltage sensor based on the Pockels effect, is described. The proposed device uses polarizers that possess high polarization ratios in specific spectral ranges. This allows the simultaneous codification of current and voltage information in differ- ent spectral regions, which, in turn, enables independent measurements of both magnitudes. Validation experiments are presented. © 2009 Society
Fibonacci Identities via the Determinant Sum Property

Mike Spivey (mspivey@ups.edu) received his B.S. from Samford University and his Ph.D. from Princeton, and he currently teaches at the University of Puget Sound (Tacoma, WA 98416). His research background is in optimization, but he also enjoys dabbling in combinatorics and elementary number theory. Lately, he hasn’t been able to stop himself from playing around with matrices made up of various mathematical entities.