Miracle-dz/UniFAR-FTUs huggingface dataset:
A polarized infrared flare from Sagittarius A* and the signatures of orbiting plasma hotspots

In this article we summarize and discuss the infrared, radio and X-ray emission from the supermassive black hole in the Galactic Centre, SgrA*. We include new results from near-infrared polarimetric imaging observations obtained on 2006 May 31. In that night, a strong flare in K s band (2.08 μm) reaching top fluxes of ∼16 mJy could be observed. This flare was highly polarized (up to ∼40 per cent) and showed clear substructure on a time-scale of 15 min, including a swing in the polarization angle of about 70°. For the first time we were able to observe both polarized flux and short-time variability, with high significance in the same flare event. This result adds decisive information to the puzzle of the SgrA* activity. The observed polarization angle during the flare peak is the same as observed in two events in 2004 and 2005. Our observations strongly support the dynamical emission model of a decaying plasma hotspot orbiting SgrA* on a relativistic orbit. The observed polarization parameters and their variability with time might allow to constrain the orientation of accretion disc and spin axis with respect to the Galaxy.
Mental health consumers' with medical co‐morbidity experience of the transition through tertiary medical services to primary care

Abstract Medical comorbidity in people with long‐term mental illness is common and often undetected; however, these consumers frequently experience problems accessing and receiving appropriate treatment in public health‐care services. The aim of the present study was to understand the lived experience of mental health consumers with medical comorbidity and their carers transitioning through tertiary medical to primary care services. An interpretative, phenomenological analysis approach was used, and semistructured, video‐recorded, qualitative interviews were used with 12 consumers and four primary caregivers. Four main themes and related subthemes were abstracted from the data, highlighting consumer's and carers’ experience of transition through tertiary medical to primary care services: (i) accessing tertiary services is difficult and time consuming; (ii) contrasting experiences of clinician engagement and support; (iii) lack of continuity between tertiary medical and primary care services; and (iv) Mental Health Hospital Admission Reduction Programme (MH HARP) clinicians facilitating transition. Our findings have implications for organisational change, expanding the role of MH HARP clinicians (whose primary role is to provide consumers with intensive support and care coordination to prevent avoidable tertiary medical hospital use), and the employment of consumer and carer consultants in tertiary medical settings, especially emergency departments.
Identification and characterization of the two isoforms of the vertebrate H2A.Z histone variant

Histone variants play important roles in the epigenetic regulation of genome function. The histone variant H2A.Z is evolutionarily conserved from yeast to vertebrates, and it has been reported to have multiple effects upon gene expression and insulation, and chromosome segregation. Recently two genes encoding H2A.Z were identified in the vertebrate genome. However, it is not yet clear whether the proteins transcribed from these genes are functionally distinct. To address this issue, we knocked out each gene individually in chicken DT40 cells. We found that two distinct proteins, H2A.Z-1 and H2A.Z-2, were produced from these genes, and that these proteins could be separated on a long SDS–PAGE gel. The two isoforms were deposited to a similar extent by the SRCAP chromatin-remodeling complex, suggesting redundancy to their function. However, cells lacking either one of the two isoforms exhibited distinct alterations in cell growth and gene expression, suggesting that the two isoforms have differential effects upon nucleosome stability and chromatin structure. These findings provide insight into the molecular basis of the multiple functions of the H2A.Z gene products.
Development research on SOA-based Postgraduate Education Administration Systems

Nowadays, "Information Islands", inadequate flexibility and reusability are primary problems existing in postgraduate education administration systems (PEAS). To solve those problems, in this paper, Service Oriented Architecture is introduced into Rational Unified Process (RUP) for developing integrated PEAS with much improved flexibility and reusability. Models devised in three core workflows of RUP: business modeling, requirements, analysis and design, are presented in sequence and the feasibility of those models is validated by a prototype implemented by using web services.
The Cell Image Segmentation Based on the K-L Transform and OTSU Method

Automatic analysis of medical cell images has been gaining more importance in pharmacology research. Segmentation of cell images is the crucial step in their analysis since results of segmentation directly affect the following quantitative analysis steps. In this paper, we present a cell image segmentation method based on the K-L transform and OTSU method. By K-L transform we choose one channel and ensure an automatic threshold value by OTSU method. The method has been applied to the segmentation of several kinds of cell images. The experimental results show that the method is practical and effective; it has good robustness and ensures the accuracy.
Semi-Probabilistic Routing in Intermittently Connected Mobile Ad Hoc Networks

ICMANs (intermittently connected mobile ad hoc networks) are wireless networks where most of the time there does not exist a complete path from the source to the destination. In this paper, a novel routing approach, SPR (semi-probabilistic routing), is proposed to address routing problem in ICMANs. SPR takes into account information about host mobility and connectivity changes to produce estimates enabling more accurate message forwarding. These include maintaining proactive routing zones for stable local topology to minimize blind message forwarding, and identifying potential carriers to maximize message delivery despite network partitions and intermittent connectivity. We compare the performance of our protocol against others, using a mobility model validated with real-world traces.
Scalable similarity search for SimRank

SimRank, proposed by Jeh and Widom, provides a good similarity score and has been successfully used in many of the above mentioned applications. While there are many algorithms proposed so far to compute SimRank, but unfortunately, none of them are scalable up to graphs of billions size. Motivated by this fact, we consider the following SimRank-based similarity search problem: given a query vertex u, find top-k vertices v with the k highest SimRank scores s(u,v) with respect to u. We propose a very fast and scalable algorithm for this similarity search problem. Our method consists of the following ingredients: (1) We first introduce a "linear" recursive formula for SimRank. This allows us to formulate a problem that we can propose a very fast algorithm. (2) We establish a Monte-Carlo based algorithm to compute a single pair SimRank score s(u,v), which is based on the random-walk interpretation of our linear recursive formula. (3) We empirically show that SimRank score s(u,v) decreases rapidly as distance d(u,v) increases. Therefore, in order to compute SimRank scores for a query vertex u for our similarity search problem, we only need to look at very "local" area. (4) We can combine two upper bounds for SimRank score s(u,v) (which can be obtained by Monte-Carlo simulation in our preprocess), together with some adaptive sample technique, to prune the similarity search procedure. This results in a much faster algorithm. Once our preprocess is done (which only takes O(n) time), our algorithm finds, given a query vertex u, top-20 similar vertices v with the 20 highest SimRank scores s(u,v) in less than a few seconds even for graphs with billions edges. To the best of our knowledge, this is the first time to scale for graphs with at least billions edges(for the single source case).
Multi-directional crowded objects segmentation based on optical flow histogram

This paper proposes an adaptive crowded objects segment algorithm. First, a real time global optical flow method is employed to calculate velocity field and the background noise is eliminated by setting threshold. Second, the angle matrix of foreground optical flow is treated as gray scale image, and its histogram curve is segmented instead of optical flow foreground. Through the histogram derivative curve, a set of segment points is picked up, and then foreground area is segmented into different flows. During the segmentation, some small blocks appear. A block absorption approach is proposed to solve this problem, which makes use of the color characteristic of flows. Some experimental results show the algorithm is efficient. Compared to clustering methods, the proposed approach has similar segment result, but is very time saving. The approach is more suitable for real time applications.
Auditory sensory processing in children with sensory processing disorder and autism spectrum disorder

ii ACKNOWLEDGEMENTS . iv CHAPTER ONE . 1 The History of Sensory Integration Theory . 2 The Evolution of Modern Sensory Integration Theory. 3 Sensory Modulation . 4 Clinical Relevance of Sensory Integration Theories . 6 ASD and SPD: An Introduction to Relevant Clinical Groups . 7 Sensory Processing Disorder (SPD) Information and Prevalence . 7 SPD and auditory sensory processing. 8 Autism Spectrum Disorders Information and Prevelance . 8 ASD and auditory sensory processing. 9 Introduction to Measures Relevant to this Paper . 9 Neurophysiological Measurement Technique . 10 Neurophysiological Measures . 11 Sensory gating. 11 Sensory registration. 12 Purpose of the Current Study . 13 Introduction to the Paper to be Replicated: Davies and Gavin (2007) . 13 CHAPTER TWO . 18 Clinical Populations and Sensory Integration . 19
Divide-and-Conquer Bidirectional

We present a new algorithm to reduce the space complexity of heuristic search. It is most effective for problem spaces that grow polynomially with problem size, but contain large numbers of cycles. For example, the problem of finding a lowest-cost corner-to-corner path in a D-dimensional grid has application to gene sequence alignment in computational biology. The main idea is to perform a bidirectional search, but saving only the OPEN lists and not the CLOSED lists. Once the search completes, we have one node in the middle of an optimal path, but don’t have the solution path itself. The path is then reconstructed by recursively applying the same algorithm between the initial node and the middle node, and also between the middle node and the goal node. If n is the length of the grid in each dimension, and d is the number of dimensions, this algorithm reduces the memory requirement from O(n d) to O(nd-1). For example, in a two-dimensional problem, the space complexity is reduced from quadratic to linear. The time complexity only increases by a constant factor of ~r in 2 dimensions, and ~rv/3/3 ~ 1.8 in 3 dimensions.
Brand Placement in Emotional Scenes: Excitation Transfer or Direct Affect Transfer?

ABSTRACT Using excitation transfer and direct affect transfer as theoretical foundations, emotions and branded product placements were examined. Results from the 2 (low/high arousal) × 2 (positive/negative valence) × 2 (positive/negative brand) between subjects experiment revealed a three-way interaction. When a positive (unfamiliar) brand was placed in a highly arousing positive scene, intentions to purchase the brand were greatest. Main effects were found for valence on brand attitude and purchase intention. As a result, not only valence but arousal of media should also be considered when placing unknown brands.
Pseudo Spectral pada Model Gelombang 1 D Boussinesq

In the design of a numerical wave tank, it is necessary to use an accurate wave model as well as to choose an accurate and efficient numerical scheme for implementing the model. In this paper, we use a Pseudo-Spectral (PS) implementation for a wave model so called Variational Boussinesq Model. The implementation is aimed to obtain a higher time efficiency in the calculation of wave simulations. The performance of the PS implementation is compared in CPU-time with a Finite Element (FE) implementation of the wave model for simulating a focusing wave group. Results of both implementations give a good agreement with wave data from laboratory experiment. The PS-implementation is more efficient in computational time compared to the FE-implementation.
Robust Spectral Learning for Unsupervised Feature Selection

In this paper, we consider the problem of unsupervised feature selection. Recently, spectral feature selection algorithms, which leverage both graph Laplacian and spectral regression, have received increasing attention. However, existing spectral feature selection algorithms suffer from two major problems: 1) since the graph Laplacian is constructed from the original feature space, noisy and irrelevant features may have adverse effect on the estimated graph Laplacian and hence degenerate the quality of the induced graph embedding, 2) since the cluster labels are discrete in natural, relaxing and approximating these labels into a continuous embedding can inevitably introduce noise into the estimated cluster labels. Without considering the noise in the cluster labels, the feature selection process may be misguided. In this paper, we propose a Robust Spectral learning framework for unsupervised Feature Selection (RSFS), which jointly improves the robustness of graph embedding and sparse spectral regression. Compared with existing methods which are sensitive to noisy features, our proposed method utilizes a robust local learning method to construct the graph Laplacian and a robust spectral regression method to handle the noise on the learned cluster labels. In order to solve the proposed optimization problem, an efficient iterative algorithm is proposed. We also show the close connection between the proposed robust spectral regression and robust Huber M-estimator. Experimental results on different datasets show the superiority of RSFS.
Stochastic Flow Networks for Synthesizing Target Distributions

A stochastic flow network is a directed graph with incoming edges (inputs) and outgoing edges (outputs), tokens enter through the input edges, travel stochastically in the network and can exit the network through the output edges. Each node in the network is a splitter, namely, a token can enter a node through an incoming edge and exit on one of the output edges according to a predefined probability distribution. We address the following synthesis question: Given a finite set of possible splitters and an arbitrary rational probability distribution, design a stochastic flow network, such that every token that enters the input edge will exit the outputs with the prescribed probability distribution. The problem of probability transformation dates back to von Neumann’s 1951 work and was followed, among others, by Knuth and Yao in 1976. Most existing works have been focusing on the “simulation” of target distributions. Motivated by stochastic computation based on chemical reaction networks, we consider this problem of probability transformation from a synthetic perspective, namely, we design optimal-sized stochastic flow networks for “synthesizing” target distributions. It shows that when each splitter has two outgoing edges and is unbiased, an arbitrary rational probability a b with a ≤ b ≤ 2 can be realized by a stochastic flow network of size n that is optimal. Compared to the other stochastic systems, feedback (cycles in networks) strongly improves the expressibility of stochastic flow networks.
A Cost-driven Approach for Metamorphic Testing

Metamorphic testing has been applied in various systems from different domains. Many studies showed that the selection of metamorphic relations greatly affected the effectiveness of metamorphic testing. However, these studies mainly focused on the fault-detection effectiveness. They did not consider the cost that metamorphic relations involved, such as the number of test inputs. Good metamorphic relations should have high fault-detection effectiveness with a low cost. In this paper, we propose a cost-driven approach for metamorphic testing. The key idea is to design metamorphic relations sharing the same test inputs to reduce the testing cost. We conduct a case study on a bank system and compare the cost-effectiveness of metamorphic relations derived from this approach and those constructed by the conventional approach. The experimental results show that metamorphic relations derived from our approach are more cost-effective. We also find that this approach not only reduces the cost of metamorphic testing, but also helps to construct different metamorphic relations to detect different types of faults.
Press coverage of lone-actor terrorism in the UK and Denmark: shaping the reactions of the public, affected communities and copycat attackers

ABSTRACT Following 9/11, Al-Qaeda-orchestrated plots were considered the greatest threat to Western security and sparked the coalition’s war on terror. Close to a decade later, the post-9/11 threat landscape had shifted significantly, leading then CIA-director Leon Panetta to describe “the lone-wolf strategy” as the main threat to the United States. Subsequent lone-actor attacks across the West, including the cities of London, Nice, Berlin, Stockholm, Ottawa and Charleston, further entrenched perspectives of a transformed security landscape in the “after, after-9/11” world. The unique features of lone-actor terrorism, including the challenges of interdiction and potential of copycat attacks, mean that the media is likely to play a particularly important role in shaping the reactions of the public, affected communities and copycat attackers. This article presents findings from a content analysis of British and Danish newspaper reporting of lone-actor terrorism between January 2010 and February 2015. The study highlights that lone-actor terrorism is framed, with national variations, as a significant and increasing problem in both countries; that Islamist lone-actors are often represented as distinct from far-right lone-actors; and that some reporting, despite relatively limited amplification of specific terrorist messages, potentially aids lone-actors by detailing state vulnerabilities to attacks.
The effect of surface roughness of the impeller to the performance of pump as turbine pico power plant

Pump as Turbine (PAT) is one of a hydropower plant that applies a pump with a reversed flow, working as a turbine to generate electrical power. It has the advantages of low-cost, widely available in the market and user-friendly. However, like other hydropower plants, PAT technology has low performance in term of power output. The impeller surface roughness is one of critical aspect, which influences PAT performance because poor surface roughness causes losses and cavitation. The objective of the research is to increase the PAT performance by improving the quality of the surface roughness and validate by the experimental tests. A low-cost and customize hand grinding process was applied to produce five impellers with three different levels of surface roughness (average surface roughness of 0.16 mm, 0.24 mm, and 0.40 mm), an edge rounded impeller, and a varnish lacquer coated impeller. All of the impellers undergo performance testing. The performance of the original impeller (without modification) used as a comparison. The experiment result shows that an impeller with a lower surface roughness (lower Ra number) has a higher performance. An impeller with an average surface roughness of 0.16 mm improved 10.9% of its initial performance. Additional edge rounding for a 0.16 mm surface roughness impeller would improve its performance by 13.1%. The optimum turbine efficiency of 15.45% was achieve-able by implementing an impeller with the lowest surface roughness.
Changes in Liver Gene Expression Indicate Genetic Pathways Associated with Rabbit Haemorrhagic Disease Infection in Wild Rabbits

Rabbit Haemorrhagic Disease Virus (RHDV) is of worldwide significance for both, domestic and wild rabbits (Oryctolagus cuniculus). While the loss of natural populations of wild rabbits in south-western Europe is of major conservation concern because rabbits are a key-stone species in natural ecosystems, the virus has been successfully used as a biological control of pest rabbits in Australia. However, rabbit numbers in Australia are currently rising again suggesting ongoing host adaptive changes. Accordingly, from both conservation and control perspectives it is important to know how rabbits are adapting and to work towards understanding the underlying genetic basis of this adaptation. Pathogenicity of a viral disease is not only influenced by the pathogen itself but likely also by the host's immune gene expression which is poorly understood for wild animals. Here we used cDNA microarrays to obtain a general picture of the genetic pathways expressed in the liver during acute RHD infections in wild rabbits. We found that typical immune response pathways are activated during RHD but also identified differences in our results from those that might have been anticipated from laboratory studies. The down-regulation of cell surface protein genes in wild rabbits that avoided infection also suggests that the lower expression of certain surface proteins could confer protection from RHDV infection. This study expands our understanding of the molecular mechanisms at the host-pathogen interface during RHDV infection and pathogenesis and constitutes a step towards determination of genetic mechanisms that may eventually prove important in host-pathogen co-evolution under natural conditions.
FrameNet-based Semantic Parsing using Maximum Entropy Models

As part of its description of lexico-semantic predicate frames or conceptual structures, the FrameNet project defines a set of semantic roles specific to the core predicate of a sentence. Recently, researchers have tried to automatically produce semantic interpretations of sentences using this information. Building on prior work, we describe a new method to perform such interpretations. We define sentence segmentation first and show how Maximum Entropy re-ranking helps achieve a level of 76.2% F-score (answer among topfive candidates) or 61.5% (correct answer).
Parallel molecular dynamics: communication requirements for massively parallel machines

Molecular mechanics and dynamics are becoming widely used to perform simulations of molecular systems, from large-scale computations of materials to the design and modeling of drug compounds. In this paper we address two major issues: a good decomposition method that can take advantage of future massively parallel processing systems for modest-sized problems in the range of 50,000 atoms and the communication requirements needed to achieve 30 to 40% efficiency on MPPs. We analyzed a scalable benchmark molecular dynamics program executing on the Intel Touchstone Deleta parallelized with an interaction decomposition method. Using a validated analytical performance model of the code, we determined that for an MPP with a four-dimensional mesh topology and 400 MHz processors the communication startup time must be at most 90 clock cycles and the network bandwidth must be at least 2.3 GB/s. This configuration results in 30 to 40% efficiency of the MPP for a problem with 50,000 atoms executing on 50,000 processors. <<ETX>>