Miracle-dz/UniFAR-FTUs huggingface dataset:
Bare Quark Stars or Naked Neutron Stars? The Case of RX J1856.5–3754

In a cool neutron star (T ≲ 106 K) endowed with a rather high magnetic field (B ≳ 1013 G), a phase transition may occur in the outermost layers. As a consequence, the neutron star becomes "bare," i.e., no gaseous atmosphere sits on the top of the crust. The surface of a cooling, bare neutron star does not necessarily emit a blackbody spectrum because the emissivity is strongly suppressed at energies below the electron plasma frequency, ωp. Since ωp ≈ 1 keV under the conditions typical of the dense electron gas in the condensate, the emission from a T ~ 100 eV bare neutron star will be substantially depressed with respect to that of a perfect Planckian radiator at most energies. Here we present a detailed analysis of the emission properties of a bare neutron star. In particular, we derive the surface emissivity for an Fe composition in a range of magnetic fields and temperatures representative of cooling isolated neutron stars, like RX J1856.5-3754. We find that the emitted spectrum is strongly dependent on the electron conductivity in the solid surface layers. In the cold electron gas approximation (no electron-lattice interactions), the spectrum turns out to be a featureless depressed blackbody in the 0.1-2 keV band with a steeper low-energy distribution. When damping effects due to collisions between electrons and the ion lattice (mainly due to electron-phonon interactions) are accounted for, the spectrum is more depressed at low energies and spectral features may be present, depending on the magnetic field strength. Details of the emitted spectrum are found, however, to be strongly dependent on the assumed treatment of the transition from the external vacuum to the metallic surface. The implications of our results for RX J1856.5-3754 and other isolated neutron stars are discussed.
Prion Protein Polymorphisms Affect Chronic Wasting Disease Progression

Analysis of the PRNP gene in cervids naturally infected with chronic wasting disease (CWD) suggested that PRNP polymorphisms affect the susceptibility of deer to infection. To test this effect, we orally inoculated 12 white-tailed deer with CWD agent. Three different PRNP alleles, wild-type (wt; glutamine at amino acid 95 and glycine at 96), Q95H (glutamine to histidine at amino acid position 95) and G96S (glycine to serine at position 96) were represented in the study cohort with 5 wt/wt, 3 wt/G96S, and 1 each wt/Q95H and Q95H/G96S. Two animals were lost to follow-up due to intercurrent disease. The inoculum was prepared from Wisconsin hunter-harvested homozygous wt/wt animals. All infected deer presented with clinical signs of CWD; the orally infected wt/wt had an average survival period of 693 days post inoculation (dpi) and G96S/wt deer had an average survival period of 956 dpi. The Q95H/wt and Q95H/G96S deer succumbed to CWD at 1,508 and 1,596 dpi respectively. These data show that polymorphisms in the PRNP gene affect CWD incubation period. Deer heterozygous for the PRNP alleles had extended incubation periods with the Q95H allele having the greatest effect.
Total generalized variation for graph signals

This paper proposes a second-order discrete total generalized variation (TGV) for arbitrary graph signals, which we call the graph TGV (G-TGV). The original TGV was introduced as a natural higher-order extension of the well-known total variation (TV) and is an effective prior for piecewise smooth signals. Similarly, the proposed G-TGV is an extension of the TV for graph signals (G-TV) and inherits the capability of the TGV, such as avoiding staircasing effect. Thus the G-TGV is expected to be a fundamental building block for graph signal processing. We provide its applications to piecewise-smooth graph signal inpainting and 3D mesh smoothing with illustrative experimental results.
The Effects of Morning and Evening Endurance Training on TSH And FT4 Hormones

This study was carried out in order to determine the effects of endurance training during the morning hours and endurance training during the evening hours on TSH and FT4 hormones. 38 students volunteered to participate in the study. The subjects were divided into morning, evening and control groups and their hormone levels were checked with the blood samples given at 07.00 in the morning and 16.00 in the evening. In the evaluation of durability, "Conconi Test" was applied as exercise protocol. After 6 weeks of exercise protocol, blood samples were taken and the "conconi test" protocol was reapplied. IBM SPSS 21.0 package program was used to analyze the data. Descriptive Statistics were used to determine the distributions of the data, Pearson Correlation analysis was used to examine intervariable relations, and Anova was used to determine differences between groups. The results are presented as mean and standard deviation, with a P <0.05 significance. As a result, there was no significant difference between the comparison groups between morning, evening and control groups. It was determined that the relationship between TSH and FT4 was significant in the relation between variables. The Online Journal of Recreation and Sport – January 2018 Volume 7, Issue 1 www.tojras. com Copyright © The Online Journal of Recreation and Sport 2
The Algorithm of Connected Dominating Set Based Clustering in Sensor Networks

In this paper, we present a novel Algorithm of Connected Dominating Set Based Clustering in Sensor Networks. Considering the characteristics and location information of nodes in sensor networks, a modified directed transfer model of sensor networks, and a novel clustering algorithm based on area is proposed in this paper. Theoretical analyses and simulation results show that, the above new methods can reduce the energy costs of nodes in data transferring efficiently for sensor networks. Therefore, it can prolong the lifetime of the whole networks to a greater degree.
Trust vs. threats: recovery and survival in electronic commerce

The paper analyzes threats and attacks in the Internet commerce world and suggests schemes to detect the attacks when they occur, prevent further loss once an attack is detected, and provides remedial corrective actions so as to enable victims of commerce-related attacks to resume conducting business transactions. Some commerce based transaction recovery mechanisms are suggested to recover from losses these attacks may have caused. Suitable cryptographic primitives and protocols that realize an anonymous complaint and an anonymous receipt are developed to provide trust and security against e-commerce related attacks.
Multitemporal image classification and change detection with kernels

We explicitly formulate a family of kernel-based methods for (supervised and partially supervised) multitemporal classification and change detection. The novel composite kernels developed account for the static and temporal cross-information between pixels of subsequent images simultaneously. The methodology also takes into account spectral, spatial, and temporal information, and contains the familiar difference and ratioing methods in the kernel space as a particular cases. The methodology also permits straightforward fusion of multisource information. Several scenarios are considered in which partial or complete labeled information at the prediction time is available. The developed methods are then tested under different classification frameworks: (1) inductive support vector machines (SVM), and (2) one-class support vector data description (SVDD) classifier, in which only samples of a class of interest are used for training. The proposed methods are tested in a challenging real problem for urban monitoring. The composite kernel approach is additionally used as a fusion methodology to combine synthetic aperture radar (SAR) and multispectral data, and to integrate the spatial and textural information at different scales and orientations through Gabor filters. Good results are observed in almost all scenarios; the SVDD classifier demonstrates robust multitemporal classification and adaptation capabilities when few labeled information is available, and SVMs show improved performance in the change detection approach.
Design of mobile wellness applications: identifying cross-cultural factors

This paper explores the design of mobile applications for supporting wellness activities. A cross-cultural user study was conducted in India and Finland. 16 participants used a technology probe (a mobile application called Wellness Diary) for the duration of two weeks. The focus of the study was to identify design factors that need to be considered when designing culturally sensitive mobile wellness applications. The findings are based on the subjective user experience reported by the participants, data collected with the technology probe, and ideas and needs of the participants that surfaced during the study. Results show that both cultural and environmental factors affect the needs towards the wellness application and usage of it. Differences were identified, for example, in how users defined wellness, what wellness concerns they had, attitudes towards setting goals, and how built and natural environments affected wellness activities.
UniMelb at SemEval-2016 Task 3: Identifying Similar Questions by combining a CNN with String Similarity Measures

This paper describes the results of the participation of The University of Melbourne in the community question-answering (CQA) task of SemEval 2016 (Task 3-B). We obtained a MAP score of 70.2% on the test set, by combining three classifiers: a NaiveBayes classifier and a support vector machine (SVM) each trained over lexical similarity features, and a convolutional neural network (CNN). The CNN uses word embeddings and machine translation evaluation scores as features.
WebGlimpse: combining browsing and searching

The two paradigms of searching and browsing are currently almost always used separately. One can either look at the library card catalog, or browse the shelves; one can either search large WWW sites (or the whole web), or browse page by page. In this paper we describe a software tool we developed, called WebGlimpse, that combines the two paradigms. It allows the search to be limited to a neighborhood of the current document. WebGlimpse automatically analyzes collections of web pages and computes those neighborhoods (at indexing time). With WebGlimpse users can browse at will, using the same pages; they can also jump from each page, through a search, to "close-by" pages related to their needs. In a sense, our combined paradigm allows users to browse using hypertext links that are constructed on the fly through a neighborhood search. The design of WebGlimpse concentrated on four goals: fast search, efficient indexing (both in terms of time and space), flexible facilities for defining neighborhoods, and non-wasteful use of Internet resources. Our implementation was geared towards the World-Wide Web, but the general design is applicable to any large-scale information bases. We believe that the concept of combining browsing and searching is very powerful, and deserves much more attention. Further information about WebGlimpse, including the complete source code, documentations, demos, and examples of use, can be found at http://glimpse.cs. arizona.edu/webglimpse/.
Adapting Network Structure for Efficient Team Formation

The concept of team formation is central to a wide variety of disciplines, including planning and learning in multiagent systems, artificial social systems, and distributed artificial intelligence. Typically, models of agent-based systems do not focus on the nature and structure of the interconnection network that dictates agent interaction, although recent findings suggest that real-world networks of many different types have rich, purposeful, and meaningful structures. Using a simple agent-based computational model of team formation, our previous work suggests that organizational network structure can have a significant effect on the dynamics of team formation. We present several strategies for locally adapting network structure in a simple team formation scenario, and give empirical results that show that such adaptation methods are capable of significantly improving organizational efficiency. These methods prove to be especially useful for adapting agent networks in the presence of attack faults that target the most highly connected nodes in the network.
Trends in Recent Debt Management and the Nature of Economic Crises

The East Asian crisis of 1997-99 was essentially the external debt problems between financial institutions in both host and recipient countries, while the crises in other emerging market economies—such as Russia (1998), Brazil (1999) and Argentina (2001)—were associated with the external debt problems between sovereign borrowers and private investors. Although both crises were triggered by a reversal of such capital inflows caused by the change in investors’ sentiment, the conflicts of interests among creditors were more complicated in the case of Russia, Brazil, and Argentina than those in East Asia, since the presence of a large number of individual investors made it extremely difficult to practice restructuring negotiations over the foreign debt of indebted countries in the case of bond finance. Given that both private loan and sovereign bond problems may re-emerge in the future, it is crucial to examine external debt management practices applied to each case. This paper examines external debt management practices with respect to sovereign bonds as well as private sector external financing.
Efficient Query Processing Techniques for Spatial Time Series Data †

A spatial time series dataset is a collection of time series, each referencing a location in a common spatial framework. Correlation analysis is often used to identify pairs of potentially interacting elements from the cross product of two spatial time series datasets (the two datasets may be the same). However, the computational cost of correlation analysis is very high when the dimension of the time series and the number of locations in the spatial frameworks are large. In this paper, I use a spatial autocorrelation-based search tree structure to propose new processing strategies for correlation-based similarity range queries and similarity joins. I provide a preliminary evaluation of the proposed strategies using experimental studies with Earth science datasets.
Enhanced multiuser resource allocation using near-continuous loading algorithms with adaptive coding for digital subscriber loops

In this paper, we present a multi-user resource allocation technique for multi-carrier digital subscriber loop (DSL) systems using an adaptive coding/modulation scheme. Traditional bit loading based on only adaptive modulation requires the number of bits to be integer and hence causes granularity loss that can be significant in dynamic spectrum management (DSM) when each user's sub-carrier-specific power is implicitly constrained due to other user's rate demand. By adaptively varying the code rate of a programmable Reed Solomon (RS) code, a fine-granularity loading in conjunction with the purely distributed iterated water filling (IWF) is proposed to recover such granularity losses. Simulation results for various VDSL-DMT scenarios show that the proposed scheme can provide higher rates than the distributed IWF and centralized optimum spectrum management (OSM) with integer-bit loading
Near Real-Time Geo-Referenced UAV Imagery Collection and Web-Based Processing on a Server for Targeting and Mapping

This paper discusses new capabilities designed and tested by NAVSYS to provide near real-time support of targeting and mapping applications by incorporating advanced software and database techniques for collecting, distributing, and organizing geo-referenced imagery. In this paper, we describe the design of the WebGRIM Enterprise Server and its employment of the Oracle tool suite for spatial processing. We present a demonstration of the type of imagery products that they provide for targeting and mapping applications. We also describe a concept of operations for further use of this technology for real-time precision targeting.
Greedy Approach vs . GVA Optimal Scheme : Simulation on the Competitive Ratio and Revenues

Combinatorial auction is an auction such that multiple goods are available and bidders can post bids for subsets of the goods. An auction mechanism is composed of a goods allocation rule and a payment scheme, which balance the goal of maximizing the sellers’ revenue and encouraging truthful declaration of bidders. The original Generalized Vickrey Auction (GVA) allocates the goods by maximizing the declared value of allocations and adopts a generalized second price payment scheme (Clarke’s scheme) to enforce truthfulness. However, the implementation of GVA is NP-hard even under the assumption of Single Minded Bidders (SMB). To solve the problem, a greedy allocation mechanism is proposed to achieve polynomial time in the number of goods k. The best greedy allocation can reach the competitive ratio of √ k to the optimal GVA allocation. However, Clarke’s payment scheme no longer guarantees the truthfulness for greedy allocations. In exploring the truthfulness design, Lehmann et al [3] proposed a sufficient condition for truthful mechanisms and a truthful greedy payment scheme.
An Arabic-Hebrew parallel corpus of TED talks

We describe an Arabic-Hebrew parallel corpus of TED talks built upon WIT3, the Web inventory that repurposes the original content of the TED website in a way which is more convenient for MT researchers. The benchmark consists of about 2,000 talks, whose subtitles in Arabic and Hebrew have been accurately aligned and rearranged in sentences, for a total of about 3.5M tokens per language. Talks have been partitioned in train, development and test sets similarly in all respects to the MT tasks of the IWSLT 2016 evaluation campaign. In addition to describing the benchmark, we list the problems encountered in preparing it and the novel methods designed to solve them. Baseline MT results and some measures on sentence length are provided as an extrinsic evaluation of the quality of the benchmark.
FPGA Implementation of a MIMO Receiver Front-end for UMTS

great attention in the past years as a means to boost capacity of wireless communication systems. Multiple antennas at the transmitter and receiver are used to exploit the spatial diversity in a rich scattering environment to concurrently transmit multiple data streams in the same frequency band thereby increasing spectral efficiency. Besides the actual MIMO decoder a significant part of the implementation complexity of such a system turns out to be in the receiver front-end. In this paper an efficient implementation of a UMTS-based MIMO receiver front-end based on a new method for the efficient realization of a MIMO channel estimation is presented. We also discuss the implementation of the RAKE receiver and the frequency-offset estimation.
Healing from Moral Injury: A Qualitative Evaluation of the Impact of Killing Treatment for Combat Veterans

ABSTRACT This paper evaluates the Impact of Killing (IOK) treatment—a psychological intervention designed to address moral injury and trauma associated with killing in war. Using qualitative data from interviews with 28 combat veterans, we examine IOK’s impact, how it differs from other trauma-focused treatments, and how it can be improved to better meet veterans’ needs. We found that many veterans processed their killing experiences for the first time in IOK, even though all had previously completed evidence-based treatments for posttraumatic stress disorder. Several described killing in war as the most distressing and transformative trauma of their lives, and all affirmed the value of an intervention focused directly and explicitly on moral injury and killing. IOK helped veterans to acknowledge their grief, shame, and distress; gently but critically examine their thoughts and beliefs about killing in war; and make strides toward acceptance, reconciliation, and forgiveness.
Poisoning attacks to compromise face templates

Adaptive biometric systems update clients' templates during operation to account for natural changes over time (e.g., aging of biometric templates). Recently, it has been shown that this update can be exploited by an attacker to compromise the clients' templates: by presenting a proper sequence of fake biometric traits to the sensor, the attacker may eventually impersonate the targeted clients without any fake trait, and even force the system to deny access to them. This attack has however been shown only for PCA-based face verification, with one template per client, under worstcase assumptions about the attacker's knowledge of the sys-tem. In this paper, we show that it can be successful even in the case of multiple templates per client, for different matchers, and under more realistic scenarios, and validate it by experiments to highlight its practical relevance.
A multi-sample, multi-tree approach to bag-of-words image representation for image retrieval

The state-of-the-art content based image retrieval systems has been significantly advanced by the introduction of SIFT features and the bag-of-words image representation. Converting an image into a bag-of-words, however, involves three non-trivial steps: feature detection, feature description, and feature quantization. At each of these steps, there is a significant amount of information lost, and the resulted visual words are often not discriminative enough for large scale image retrieval applications. In this paper, we propose a novel multi-sample multi-tree approach to computing the visual word codebook. By encoding more information of the original image feature, our approach generates a much more discriminative visual word codebook that is also efficient in terms of both computation and space consumption, without losing the original repeatability of the visual features. We evaluate our approach using both a ground-truth data set and a real-world large scale image database. Our results show that a significant improvement in both precision and recall can be achieved by using the codebook derived from our approach.
Bacterial community structure and soil properties of a subarctic tundra soil in Council, Alaska

The subarctic region is highly responsive and vulnerable to climate change. Understanding the structure of subarctic soil microbial communities is essential for predicting the response of the subarctic soil environment to climate change. To determine the composition of the bacterial community and its relationship with soil properties, we investigated the bacterial community structure and properties of surface soil from the moist acidic tussock tundra in Council, Alaska. We collected 70 soil samples with 25-m intervals between sampling points from 0–10 cm to 10–20 cm depths. The bacterial community was analyzed by pyrosequencing of 16S rRNA genes, and the following soil properties were analyzed: soil moisture content (MC), pH, total carbon (TC), total nitrogen (TN), and inorganic nitrogen ( and ). The community compositions of the two different depths showed that Alphaproteobacteria decreased with soil depth. Among the soil properties measured, soil pH was the most significant factor correlating with bacterial community in both upper and lower-layer soils. Bacterial community similarity based on jackknifed unweighted unifrac distance showed greater similarity across horizontal layers than through the vertical depth. This study showed that soil depth and pH were the most important soil properties determining bacterial community structure of the subarctic tundra soil in Council, Alaska.