Miracle-dz/UniFAR-FTUs huggingface dataset:
The neutron star soft X-ray transient 1H 1905+000 in quiescence *

In this paper, we report on our analysis of a ~25ks. Chandra X-ray observation of the neutron star soft X-ray transient (SXT) 1H 1905+000 in quiescence. Furthermore, we discuss our findings of the analysis of optical photometric observations which we obtained using the Magellan telescope and photometric and spectroscopic observations which we obtained using the Very Large Telescope (VLT) at Paranal. The X-ray counterpart of 1H 1905+000 was not detected in our Chandra data, with a 95 per cent confidence limit to the source count rate of 1.2 �10 -4 countss -1 . For different spectral models this yields an upper limit on the luminosity of 1.8 �10 31 ergs -1 (for an upper limit on the distance of 10kpc). This luminosity limit makes 1H 1905+000 the faintest neutron star SXT in quiescence observed to date. The neutron star luminosity is so low that it is similar to the lowest luminosities derived for black hole (BH) SXTs in quiescence. This low luminosity for a neutron star SXT challenges the hypothesis presented in the literature that BH SXTs in quiescence have lower luminosities than neutron star SXTs as a result of the presence of a BH event horizon. Furthermore, the limit on the neutron star luminosity obtained less than 20yr after the outburst has ceased, constrains the thermal conductivity of the neutron star crust. Finally, the neutron star core must be so cold that unless the time-averaged mass accretion rate is lower than 2 �10 -12 M solar yr -1 , core cooling has to proceed via enhanced neutrino emission processes. The time-averaged mass accretion rate can be derived from binary evolution models if the orbital period of the system is known. Our optical observations show that the optical counterpart discovered when the source was in outburst has faded. Near the outburst optical position we find two stars with a separation of 0.7arcsec and I = 19.3 +/- 0.1 and 21.3 +/- 0.1. VLT optical spectroscopy revealed that the spectrum of the brighter of the two sources is a G5-7V star. However, the outburst astrometric position of the optical counterpart does not coincide with the position of the G5-7V star nor with that of the fainter star. We derive a limit on the absolute I-band magnitude of the quiescent counterpart of M I > 7.8 assuming the source is at 10kpc. This is in line with 1H 1905+000 being an ultracompact X-ray binary, as has been proposed based on the low-outburst V-band absolute magnitude.
Capital, Distribution, and the Aggregate Production Function

Recent results in capital theory concerning the reswitching of techniques of production have shaken the foundations of a neoclassical parable according to which the total quantity of output per man is supposed to be a function of the total quantity of capital per man-the Surrogate Production Function-which can be used to "predict all behavior" in the sense of the wage and profit rates that would prevail in different long-run equilibria or steady states. ' The source of the difficulty, it would appear, lies in the fact that the neoclassical parable attempts, as it were, to kill two birds with one stone, namely 1) to provide a general representation (or "surrogate") of realistic technologies involving production with heterogeneous commodities, and 2) to link the determination of the (listribution of income directly to the technology itself and to the relative size of "factor endowments. " It turns out that, in general, not only are realistic
Framework for 3D object hole filling

In this paper we address the problem of hole filling in a point cloud of 3D object. Even with most popular 3D scanning devices like Microsoft Kinect and Time of Flight (ToF) cameras, occlusions during the scanning process result in occurrence of missing regions or holes in 3D data. We propose a framework for hole filling in a point cloud of 3D object using Riemannian metric tensor and Christoffel symbols as a set of geometric features, which capture the inherent geometry of the 3D object. The framework involves detection and extraction of the boundary points surrounding the hole, decomposition of boundary points into basic shapes and selective surface interpolation to fill the hole. We demonstrate the performance of the proposed method on point clouds with different complexities and sizes for both synthetically generated holes and real missing regions during the capturing process on 3D models of heritage sites.
Word Sense Disambiguation with the KORA-Ω Algorithm

We present a method for word sense disambiguation (WSD) based on the KORA-Ω supervised learning algorithm. The advantage of the method is its simplicity and a very small feature set used, though, as we show, this is achieved at the cost of lower accuracy of the final result than the complex stateof-the-art methods achieve.
The Importance of the Security Culture in SMEs as Regards the Correct Management of the Security of Their Assets

The information society is increasingly more dependent on Information Security Management Systems (ISMSs), and the availability of these kinds of systems is now vital for the development of Small and Medium-Sized Enterprises (SMEs). However, these companies require ISMSs that have been adapted to their special features, and which are optimized as regards the resources needed to deploy and maintain them. This article shows how important the security culture within ISMSs is for SMEs, and how the concept of security culture has been introduced into a security management methodology (MARISMA is a Methodology for “Information Security Management System in SMEs” developed by the Sicaman Nuevas Tecnologias Company, Research Group GSyA and Alarcos of the University of Castilla-La Mancha.) for SMEs. This model is currently being directly applied to real cases, thus allowing a steady improvement to be made to its implementation.
An intelligent UFastSLAM with MCMC move step

FastSLAM is a framework for simultaneous localization and mapping (SLAM). However, FastSLAM algorithm has two serious drawbacks, namely the linear approximation of nonlinear functions and the derivation of the Jacobian matrices. For solving these problems, UFastSLAM has been recently proposed. However, UFastSLAM is inconsistent over time due to the loss of particle diversity that is caused mainly by the particle depletion in the resampling step and incorrect a priori knowledge of process and measurement noises. To improve consistency, intelligent UFastSLAM with Markov chain Monte Carlo (MCMC) move step is proposed. In the proposed method, the adaptive neuro-fuzzy inference system supervises the performance of UFastSLAM. Furthermore, the particle impoverishment caused by resampling is restrained after the resample step with MCMC move step. Simulations and experiments are presented to evaluate the performance of algorithm in comparison with UFastSLAM. The results show the effectiveness of the proposed method.
Aestivation Induces Changes in the mRNA Expression Levels and Protein Abundance of Two Isoforms of Urea Transporters in the Gills of the African Lungfish, Protopterus annectens

The African lungfish, Protopterus annectens, is ammonotelic in water despite being ureogenic. When it aestivates in mucus cocoon on land, ammonia is detoxified to urea. During the maintenance phase of aestivation, urea accumulates in the body, which is subsequently excreted upon arousal. Urea excretion involves urea transporters (UT/Ut). This study aimed to clone and sequence the ut isoforms from the gills of P. annectens, and to test the hypothesis that the mRNA and/or protein expression levels of ut/Ut isoforms could vary in the gills of P. annectens during the induction, maintenance, and arousal phases of aestivation. Two isoforms of ut, ut-a2a and ut-a2b, were obtained from the gills of P. annectens. ut-a2a consisted of 1227 bp and coded for 408 amino acids with an estimated molecular mass of 44.7 kDa, while ut-a2b consisted of 1392 bp and coded for 464 amino acids with an estimated molecular mass of 51.2 kDa. Ut-a2a and Ut-a2b of P. annectens had a closer phylogenetic relationship with Ut/UT of tetrapods than Ut of fishes. While the mRNA expression pattern of ut-a2a and ut-a2b across various tissues of P. annectens differed, the transcript levels of ut-a2a and ut-a2b in the gills were comparable, indicating that they might be equally important for branchial urea excretion during the initial arousal phase of aestivation. During the maintenance phase of aestivation, the transcript level of ut-a2a increased significantly, but the protein abundance of Ut-a2a remained unchanged in the gills of P. annectens. This could be an adaptive feature to prepare for an increase in the production of Ut-a2a upon arousal. Indeed, arousal led to a significant increase in the branchial Ut-a2a protein abundance. Although the transcript level of ut-a2b remained unchanged, there were significant increases in the protein abundance of Ut-a2b in the gills of P. annectens throughout the three phases of aestivation. The increase in the protein abundance of Ut-a2b during the maintenance phase could also be an adaptive feature to prepare for efficient urea excretion when water becomes available.
UPTAKE OF MERCURY BY A BACTERIUM, PSEUDOMONAS SP. AN29, ISOLATED FROM INDUSTRIAL EFFLUENTS AND ITS POTENTIAL USE IN WASTEWATER TREATMENT

The present study is aimed at assessing the ability of Pseudomonas sp. AN29 to uptake Hg 2+ from the metal contaminated environment. The minimum inhibitory concentration (MICs) of Hg 2+ was 500 µg/ml. Pseudomonas sp. AN29 could tolerate Pb 2+ (600 g/ml), Cu 2+ (200 g/ml), Cd 2+ (50 g/ml), Zn 2+ (50 g/ml), Ni 2+ (550 g/ml) and Cr 6+ (150 g/ml). The isolate showed typical growth curve but phases (lag and log) extended in the presence of mercury. Bacterial isolate showed optimum growth at 37oC and at pH of 8. Metal processing ability of the isolate was determined in a medium containing 100 µg/ml of Hg 2+ . Pseudomonas sp. AN29 could decrease 85% of mercury from the culture medium after 40 hours and was also able to remove Hg 2+ 10%, 40%, 50% and 56% from the growth medium after 8, 16, 24 and 32 hours, respectively. Pseudomonas sp. AN29 was also able to uptake 74% of Hg 2+ (pellet) from the medium after 24 hours of incubation at 37 o C. Excellent metal uptake ability of Pseudomonas sp. AN29 indicates the possibility of using the bacterial strain for the removal of mercury from metal-contaminated wastewater.
Unstable Equity: Combining Banking with Private Equity Investing

Theoretical work suggests that banks can be driven by market mispricing to undertake activity in a highly cyclical manner, accelerating activity during periods when securities can be readily sold to other parties. While financial economists have largely focused on bank lending, banks are active in a variety of arenas, with proprietary trading and investing being particularly controversial. We focus on the role of banks in the private equity market. We show that bankaffiliated private equity groups accounted for a significant share of the private equity activity and the bank’s own capital. We find that banks’ share of activity increases sharply during peaks of the private equity cycles. Deals done by bank-affiliated groups are financed at significantly better terms than other deals when the parent bank is part of the lending syndicate, especially during market peaks. While bank-affiliated investments generally involve targets with better ex-ante characteristics, bank-affiliated investments have slightly worse outcomes than non-affiliated investments. Also consistent with theory, the cyclicality of banks’ engagement in private equity and favorable financing terms are negatively correlated with the amount of capital that banks commit to funding of any particular transaction.
Knowledge Media Institute Discovering Bayesian Networks in Incomplete Databases

Bayesian Belief Networks (bbns) are becoming increasingly popular in the Knowledge Discovery and Data Mining community. A bbn is deened by a graphical structure of conditional dependencies among the domain variables and a set of probability distributions deening these dependencies. In this way, bbns provide a compact formalism | grounded in the well-developed mathematics of probability theory | able to predict variable values, explain observations, and visualize dependencies among variables. During the past few years, several eeorts have been addressed to develop methods able to extract both the graphical structure and the conditional probabilities of a bbn from a database. All these methods share the assumption that the database at hand is complete, that is, it does not report any entry as unknown. When this assumption fails, these methods have to resort to expensive iterative procedures which are infeasible for large databases. This paper describes a new Knowledge Discovery system based on an eecient method able to extract the graphical structure and the probability distributions of a bbn from possibly incomplete databases. An application using a large real-world database will illustrate methods and concepts underlying the system and will assess its advantages as a Knowledge Discovery system.
Learning Representations for Multi-Dimensional Sentiment Analysis

This document received 22 “You rock” reactions, 1 “Teehee” reaction, and 1 “Wow, just wow. ” reaction. We can treat these reactions as a normalized distribution over reactions, [0.916, 0.041, 0, 0, 0.041]. Treating the reaction data as a normalized distribution allows us to ignore the differences in reaction counts across documents and instead focus only on how reactions are distributed within documents.
Dynamics of Timber Market Integration in Sweden

This paper addresses the performance of the timber markets (Scots pine, Pinus silvestris L. and Norway spruce, Picea abies (L.) Karst. ) by evaluating the order of market integration in three Swedish regions (Central, Northern, and Southern). Quarterly data of delivery prices are employed over the period 1999Q1–2012Q4. Various unit root and cointegration tests have been computed. The results indicate that the variables are integrated of first order and co-integrated, especially after controlling for structural breaks. This supports the law-of-one-price hypothesis (LOP). However, the effects of structural shocks on forestry are arguably significant and these are controlled for while performing a vector error-correction mechanism (VECM)-based Granger-causality test. Bi-directional causality between the Northern and central markets is uncovered in the short-run. In the long-run, a similar causal effect is detected between Northern and Southern markets while the central market emerges as the price leader. Further investigation is carried out using variance decompositions and impulse response functions and these approaches also tend to confirm the existence of a single market well, as price interdependence between markets.
Online Social Media in Crisis Events Investigation of recent disasters reveals use of online social media as an emergent, significant, and often accurate form of public participation and backchannel communication

© 2008 Leysia Palen My research group at the University of Colorado, Boulder, studies the relationship between human behavior and information and communication technology (ICT). The group, the connectivIT lab, includes researchers who are interested in how ICT connects people with each other and the information they seek (http://www.cs.colorado.edu/~palen/ connectivIT/). Our work is cross-disciplinary, with researchers possessing skills in empirical research, social theory development, and technology design. Our current, primary focus is on an area of research called crisis informatics, which examines the technical, social, and information aspects of disasters and crises. We believe that an informatics focus on matters of disasters is critical for the social good. With increasing attention from all sectors on disaster preparation, warning, response, and recovery, we hope that cross-disciplinary examination of information dissemination issues results in effective technology design and technology-related policy development for both official responders and members of the public alike. To that end, we collaborate closely with our colleagues at the University of Colorado’s Natural Hazards Center (http:// www.colorado.edu/hazards), an organization that conducts disaster research and serves as a worldwide information clearinghouse for social and behavioral disaster matters. Here, I report on a particular line of Online Social Media in Crisis Events
Disaggregated Forecasting for Large Office Buildings: Poster Abstract

In the direction of minimal and cost effective sensing, working with few meters/sub-meters together with other information in the context of energy models for office buildings is an important problem to address. In this paper we propose a technique dubbed as disaggregated forecasting using sophisticated function approximation. The results obtained using the real data of an office building justifies the usefulness and the efficacy of the proposal.
New multimodulus blind equalization algorithm with relaxation

A new multimodulus algorithm is presented for blind equalization of complex-valued communication channels. The proposed algorithm is obtained by solving a novel deterministic optimization criterion that constituted the dispersion minimization of a priori as well as a posteriori quantities, leading to an update equation having a particular zero-memory continuous nonlinearity. Analyses of automatic phase-recovery and interference cancellation capabilities of the proposed algorithm are provided
Increasing Performance of Rule Mining in the Medical Domain Using Natural Intelligence Concepts

—This paper discusses how concepts derived from nature can be applied successfully to improve the performance of the rule mining process. These concepts are derived from swarm intelligence and behavior of frogs. Swarm Intelligence (SI) is the property of a system whereby the collective behavior of agents interacting locally with their environment causes coherent functional global patterns to emerge. SI provides a basis with which it is possible to explore collective (or distributed) problem solving without centralized control or the provision of a global model. Association rule mining aims to extract interesting correlations, frequent patterns, associations or casual structures among sets of items in data repositories. Rules have advantages of simplicity, uniformity, transparency, and ease of inference which makes them a suitable approach for representing real world medical knowledge. In this paper, two new algorithms for rule mining have been implemented and their performance has been evaluated over a medical database. Results show that the usability of the rules thus uncovered, is high in the medical domain, and it can be further improved by refining the fitness function. Section I discusses the basic concepts of rule mining and swarm intelligence. Section II describes conventional rule mining techniques and states the motivation behind using swarm intelligence and frog leaping for rule mining and classification. Section III describes the various algorithms that have been implemented in our study. Section IV describes the details of the experiment. Section V presents the results of the practical experiment followed by conclusions and future scope in section VI.
Algebraic-geometric generalizations of the Parvaresh-Vardy codes

This paper is concerned with a new family of error-correcting codes based on algebraic curves over finite fields, and list decoding algorithms for them. The basic goal in the subject of list decoding is to construct error-correcting codes C over some alphabet Σ which have good rate R, and at the same every Hamming ball of (relative) radius p has few codewords of C, and moreover these codewords can be found in polynomial time. The trade-off between the rateR and the error-correction radius p is a central one governing list decoding. Traditional “unique decoding” algorithms can achieve p = (1 − R)/2, and this was improved in [7] to p = 1 − √ R through a new list decoding algorithm for Reed-Solomon (RS) codes. For several years, this remained the best known trade-off between rate and list decoding radius. In a recent breakthrough, Parvaresh and Vardy [11] define a variant of RS codes which can be list decoded beyond the 1 − √ R radius for rates R 6 1/16. We generalize the PV framework to algebraic-geometric (AG) codes, of which RS codes are an important special case. This shows that their framework applies to fairly general settings, and also better elucidates the key algebraic concepts underlying the new codes. Moreover, since AG codes of arbitrary block length exist over fixed alphabets Σ, we are able to almost match the trade-off between p andR obtained in [11] over alphabets of constant size. In contrast, the PV codes have alphabet size that is polynomially large in the block length. Similar to algorithms for AG codes from [7, 8], our encoding/decoding algorithms run in polynomial time assuming a natural polynomial-size representation of the code. For codes based on a specific “optimal” algebraic curve, we also present an expected polynomial time algorithm to construct the requisite representation. This in turn also presents an efficient construction of the representation needed by the list decoding algorithms for AG codes in [7]. ∗Research supported in part by NSF grant CCF-0343672 and a Sloan Research Fellowship. Electronic Colloquium on Computational Complexity, Report No. 132 (2005)
Distant-supervised Language Model for Detecting Emotional Upsurge on Twitter

Event-specific twitter streams often reveal sudden spikes triggered by users’ upsurge of emotions to crucial moments in the real world. Although upsurge of emotion is usually identified by a sudden rise in the number of tweets, the detection for diverse event streams is not a trivial task. In this paper, we propose a new method to extract spiking tweets with upsurge of emotions based on characteristic expressions used in tweets. The core part of our method is to use a distant-supervised language model (Spike LM) built from tweets in spikes to capture such expressions. We investigate the performance of detecting emotional spiking tweets using language models including Spike LM. Our experimental results show that the natural language expressions used in emotional upsurge fit specifically well to Spike LM.
Vector-based and landmark-guided navigation in desert ants inhabiting landmark-free and landmark-rich environments

SUMMARY Two species of desert ants – the North African Cataglyphis fortis and the central Australian Melophorus bagoti – differ markedly in the visual complexity of their natural habitats: featureless salt pans and cluttered, steppe-like terrain, respectively. Here we ask whether the two species differ in their navigational repertoires, in particular, whether in homing they place different emphasis on their vector-based and landmark-based routines. In trying to answer this question, we applied the same experimental paradigms to individual foragers of either species on either continent: training and/or testing with and/or without artificial landmark arrays. We found that the open-terrain species C. fortis runs off its (path integration) home vector much more readily even in unfamiliar landmark settings than the cluttered-terrain species M. bagoti. These data support the hypothesis that C. fortis has a higher propensity to rely on vector-mediated navigation, whereas in the same experimental situations M. bagoti more easily switches to landmark-guided behaviour. In the actual navigational performances, such species-specific propensities are most likely shaped by environment-dependent individual experiences.