Miracle-dz/UniFAR-FTUs huggingface dataset:
Soft X-Ray Transmission Spectroscopy of a Warm/Hot Intergalactic Medium with XEUS

We discuss the detectability of a Warm/Hot Intergalactic Medium (WHIM) via absorption lines toward bright point sources with a future X-ray satellite mission, XEUS. While we consider bright QSOs as specific examples, the methodology can be applied to bright gamma-ray burst afterglows. We created mock absorption spectra for bright QSOs (more than 20 QSOs over all sky) using the light-cone output of a cosmological hydrodynamic simulation. We assumed that the WHIM is under collisional and photo-ionization equilibrium. If WHIM has a constant metallicity of Z =0.1Z� , approximately 2 O VII absorption line systems with >3σ will be detected on average along a random line-of-sight toward bright QSOs up to z =0 . 3 for a 30ks exposure.
Meta-analysis of free-response studies, 1992-2008: assessing the noise reduction model in parapsychology.

We report the results of meta-analyses on 3 types of free-response study: (a) ganzfeld (a technique that enhances a communication anomaly referred to as "psi"); (b) nonganzfeld noise reduction using alleged psi-enhancing techniques such as dream psi, meditation, relaxation, or hypnosis; and (c) standard free response (nonganzfeld, no noise reduction). For the period 1997-2008, a homogeneous data set of 29 ganzfeld studies yielded a mean effect size of 0.142 (Stouffer Z = 5.48, p = 2.13 x 10(-8)). A homogeneous nonganzfeld noise reduction data set of 16 studies yielded a mean effect size of 0.110 (Stouffer Z = 3.35, p = 2.08 x 10(-4)), and a homogeneous data set of 14 standard free-response studies produced a weak negative mean effect size of -0.029 (Stouffer Z = -2.29, p = .989). The mean effect size value of the ganzfeld database was significantly higher than the mean effect size of the standard free-response database but was not higher than the effect size of the nonganzfeld noise reduction database [corrected]. We also found that selected participants (believers in the paranormal, meditators, etc.) had a performance advantage over unselected participants, but only if they were in the ganzfeld condition.
FACT: A fusion architecture with contract templates for semantic and syntactic integration

Linking components with end-user requests for processing is problematic when there are fundamental language differences between component specifications and how individual users state their needs. Appropriate components may not exist, the users may not know if a component exists until a one matching their requirements is generated, or the users may adjust their requirements. For complex systems governed by a community of interest, we introduce a Fusion Architecture coupled with Contract Templates (FACT). The Fusion Architecture assists with syntactic and semantic unification of user directives. Contract Templates provide a standardized mechanism to collect heterogeneous systems within domains of interest. Based upon specific analysis of each component, Contract Templates attach connectors to generate integrated systems to which queries can be directed. A case study demonstrates how FACT enables military analysts to direct the use of simulation software for the experimentation of command and control behaviors within missions.
Monetary Policy, Job Flows, and Unemployment in a Sticky Price Framework

The paper presents a general equilibrium model that combines a non-Walrasian labor market with firms setting prices on a staggered basis. The model is utilized to analyze the impact of different shocks on a set of variables under two alternative monetary policy rules. The main characteristic of the labor market is the existence of a search friction that results in a positive equilibrium rate of unemployment. Sticky prices, on the other hand, introduce a demand-sided transmission mechanism for the monetary policy that allows analysis of the effects of different shocks. The model is able to generate a positive correlation between inflation and employment (the Phillips curve) as well as the observed correlation pattern between job creation and employment and job destruction and employment. It also replicates the contemporaneous negative correlation between job creation and job destruction that is observed in the data.
Efficient Interactive Multiclass Learning from Binary Feedback

We introduce a novel algorithm called upper confidence-weighted learning (UCWL) for online multiclass learning from binary feedback (e.g., feedback that indicates whether the prediction was right or wrong). UCWL combines the upper confidence bound (UCB) framework with the soft confidence-weighted (SCW) online learning scheme. In UCB, each instance is classified using both score and uncertainty. For a given instance in the sequence, the algorithm might guess its class label primarily to reduce the class uncertainty. This is a form of informed exploration, which enables the performance to improve with lower sample complexity compared to the case without exploration. Combining UCB with SCW leads to the ability to deal well with noisy and nonseparable data, and state-of-the-art performance is achieved without increasing the computational cost. A potential application setting is human-robot interaction (HRI), where the robot is learning to classify some set of inputs while the human teaches it by providing only binary feedback—or sometimes even the wrong answer entirely. Experimental results in the HRI setting and with two benchmark datasets from other settings show that UCWL outperforms other state-of-the-art algorithms in the online binary feedback setting—and surprisingly even sometimes outperforms state-of-the-art algorithms that get full feedback (e.g., the true class label), whereas UCWL gets only binary feedback on the same data sequence.
Global Analysis of Gene Expression in the Developing Brain of Gtf2ird1 Knockout Mice

Background Williams-Beuren Syndrome (WBS) is a neurodevelopmental disorder caused by a hemizygous deletion of a 1.5 Mb region on chromosome 7q11.23 encompassing 26 genes. One of these genes, GTF2IRD1, codes for a putative transcription factor that is expressed throughout the brain during development. Genotype-phenotype studies in patients with atypical deletions of 7q11.23 implicate this gene in the neurological features of WBS, and Gtf2ird1 knockout mice show reduced innate fear and increased sociability, consistent with features of WBS. Multiple studies have identified in vitro target genes of GTF2IRD1, but we sought to identify in vivo targets in the mouse brain. Methodology/Principal Findings We performed the first in vivo microarray screen for transcriptional targets of Gtf2ird1 in brain tissue from Gtf2ird1 knockout and wildtype mice at embryonic day 15.5 and at birth. Changes in gene expression in the mutant mice were moderate (0.5 to 2.5 fold) and of candidate genes with altered expression verified using real-time PCR, most were located on chromosome 5, within 10 Mb of Gtf2ird1. siRNA knock-down of Gtf2ird1 in two mouse neuronal cell lines failed to identify changes in expression of any of the genes identified from the microarray and subsequent analysis showed that differences in expression of genes on chromosome 5 were the result of retention of that chromosome region from the targeted embryonic stem cell line, and so were dependent upon strain rather than Gtf2ird1 genotype. In addition, specific analysis of genes previously identified as direct in vitro targets of GTF2IRD1 failed to show altered expression. Conclusions/Significance We have been unable to identify any in vivo neuronal targets of GTF2IRD1 through genome-wide expression analysis, despite widespread and robust expression of this protein in the developing rodent brain.
Optimizing Adaptive Transmission Policies for Wireless Vehicular Communications

The adoption of wireless vehicular communication technologies would strongly depend on the technologies transmission reliability, required by QoS demanding traffic safety applications, and the system's scalability as the technology is gradually introduced. To this aim, this work proposes the use of opportunistic transmission policies that dynamically adapt the transmission parameters based on the operating conditions and potential traffic safety risks. The work analyses different configuration proposals with the aim to meeting the strong traffic safety QoS requirements, while maximizing the technology's robustness and minimising channel congestion, which in turn is crucial to guarantee the future system's scalability.
Sliding Mode Control of a Finger for a Prosthetic Hand

A prosthetic finger model, intended to imitate a real human hand and for use in replacing the real index finger of an amputee, is designed using tendons instead of joint motors. A dynamic model of the prosthetic finger model is developed, and a non-chattering robust sliding mode control is applied to make the model follow a certain trajectory. Trajectory planning of the finger model is based on images of the closing motion of a human hand, and time varying reference joint angles are obtained using these images. The robustness of the controller is confirmed by introducing an unexpected sudden joint friction induced in the prosthetic finger.
Analysing Features of Lecture Slides and past Exam Paper Materials - Towards Automatic Associating E-materials for Self-revision

Digital materials not only provide opportunities as enablers of e-learning development, but also create a new challenge. The current e-materials provided on a course website are individually designed for learning in classrooms rather than for revision. In order to enable the capability of e-materials to support a students revision, we need an efficient system to associate related pieces of different e-materials. In this case, the features of each item of e-material, including the structure and the technical terms they contain, need to be studied and applied in order to calculate the similarity between relevant e-materials. Even though difficulties regarding technical term extraction and the similarities between two text documents have been widely discussed, empirical experiments for particular types of e-learning materials (for instance, lecture slides and past exam papers) are still rare. In this paper, we propose a framework and relatedness model for associating lecture slides and past exam paper materials to support revision based on Natural Language Processing (NLP) techniques. We compare and evaluate the efficiency of different combinations of three weighted schemes, term frequency (TF), inverse document frequency (IDF), and term location (TL), for calculating the relatedness score. The experiments were conducted on 30 lectures (900 slides) and 3 past exam papers (12 pages) of a data structures course at the authors institution. The findings indicate the appropriate features for calculating the relatedness score between lecture slides and past exam papers.
Comparison of VQ and DTW classifiers for speaker verification

An investigation into the relative speaker verification performance of various types of vector quantisation (VQ) and dynamic time warping (DTW) classifiers is presented. The study covers a number of algorithmic issues involved in the above classifiers, and examines the effects of these on the verification accuracy. The experiments are based on the use of a subset from the Brent (telephone quality) speech database. This subset consists of repetitions of isolated digit utterances 1 to 9 and zero. The paper describes the experimental work, and presents an analysis of the results.
Assessing the value of clean air in a developing country: a hedonic price analysis of the Jakarta housing market, Indonesia

This paper is motivated by the common argument that clean air is a luxury good and has much less or even no value in a less developed country. It applies a hedonic property value analysis, a method commonly used to infer the value of clean air in developed countries, using a combination of data on house values and their characteristics from the Indonesian Family Life Survey, and data of the ambient level of six different pollutants in Jakarta, Indonesia. The result suggests that air quality may affect property value in Jakarta, indicating a preference toward environmental amenities. Moreover, this study is one of the first hedonic studies that may potentially give comparable estimates of the value of clean air in developing countries.
VISIO‐SPATIAL CASE‐BASED REASONING: A CASE STUDY IN PREDICTION OF PROTEIN STRUCTURE

We show that visio‐spatial representations and reasoning can be used as a similarity metric for case‐based protein structure prediction. Our system retrieves pairs of α‐helices based on contact map similarity, then transfers and adapts the structure information to an unknown helix pair. We show that similar protein contact maps predict a similar three‐dimensional protein structure. The success of this method provides support for the notion that changing representations can enable similarity metrics in case‐based reasoning.
Social interaction in virtual environments : the relationship between mutual gaze, task performance and social presence

ii Acknowledgements . vi 1 Chapter 1: Introduction . 2 1.1 Background . 2 1.2 Aims . 2 1.2.1 Methodological aim . 2 1.2.2 Staring and mutual gaze . 3 1.2.3 Mutual gaze, task performance and social presence . 4 1.2.4 Function of mutual gaze . 5 1.3 Study outline . 5 2 Chapter 2: Background and Literature Review . 6 2.1 Social Presence . 6 2.1.1 Why measure Social Presence? 9 2.1.2 How do you measure Social Presence? 11 2.2 Mutual Gaze . 16 2.3 Mutual gaze and task performance . 21 2.4 Gaze, task performance and social presence . 24 2.5 From avatars to embodied conversational agents . 28 2.6 Eye Tracking and ECAs . 31 2.7 Avatars, agents and social interaction . 34 2.8 Social facilitation and inhibition . 38 2.9 Research questions . 41
Alternative Healthy Eating Index and mortality over 18 y of follow-up: results from the Whitehall II cohort123

Background: Indexes of diet quality have been shown to be associated with decreased risk of mortality in several countries. It remains unclear if the Alternative Healthy Eating Index (AHEI), designed to provide dietary guidelines to combat major chronic diseases, is related to mortality risk. Objective: We aimed to examine the association between adherence to the AHEI and cause-specific mortality over 18 y of follow-up in a British working population. Design: Analyses are based on 7319 participants (mean age: 49.5 y; range: 39–63 y; 30.3% women) from the Whitehall II Study. Cox proportional hazards regression models were performed to analyze associations of the AHEI (scored on the basis of intake of 9 components: vegetables, fruit, nuts and soy, white or red meat, trans fat, polyunsaturated or saturated fat, fiber, multivitamin use, and alcohol) with mortality risk. Results: After potential confounders were controlled for, participants in the top compared with the bottom third of the AHEI score showed 25% lower all-cause mortality [hazard ratio (HR): 0.76; 95% CI: 0.61, 0.95] and >40% lower mortality from cardiovascular disease (CVD; HR: 0.58; 95% CI: 0.37, 0.91). Consumption of nuts and soy and moderate alcohol intake appeared to be the most important independent contributors to decreased mortality risk. The AHEI was not associated with cancer mortality or noncancer/non-CVD mortality. Conclusion: Our findings suggest that the encouragement of adherence to the AHEI dietary recommendations constitutes a valid and clear public health recommendation that would decrease the risk of premature death from CVD.
Reclassification of species of the spiral-shaped phototrophic purple non-sulfur bacteria of the alpha-Proteobacteria: description of the new genera Phaeospirillum gen. nov., Rhodovibrio gen. nov., Rhodothalassium gen. nov. and Roseospira gen. nov. as well as transfer of Rhodospirillum fulvum to Phae

The 165 rDNA sequence of Rhodospirillum mediosalinum was determined and compared with corresponding sequences from other spiral-shaped purple non-sulfur bacteria classified as or related to the genus Rhodospirillum in the alpha subclass of the Proteobacteria. Sequence similarities separate the currently recognized Rhodospirillum species into five different groups with no more than 91% sequence similarity, clearly indicating the necessity to recognize these groups as different genera. Major diagnostic properties of these bacteria are compared and new genera Phaeospirillum gen. nov., Roseospira gen. nov., Rhodothalassium gen. nov. and Rhodovibrio gen. nov. are described with the species Phaeospirillum fulvum comb. nov., Phaeospirillum molischianum comb. nov., Rhodovibrio salinarum comb. nov., Rhodovibrio sodomensis comb. nov., Rhodothalassium salexigens comb. nov. and Roseospira mediosalina comb. nov. The genus Rhodospirillum is represented by Rhodospirillum rubrum and Rhodospirillum photometricum and an emended description of this genus is also given.
Excluded From All Humanity

Past research suggested that—from the perspective of perpetrators—animal metaphors are a powerful means to reinforce social exclusion and to foster hostile behaviors against the targets of social exclusion. In the current work, we focus on the consequences of this dehumanizing form of social exclusion from the perspective of victims. In two studies, we manipulated the presence of animal metaphors in a variety of contexts of interpersonal social exclusion. Our results showed that when social exclusion is associated with animal metaphors, its consequences are exacerbated. In particular, labelling targets of social exclusion as animals indirectly caused them to display more aggressive tendencies compared with when they are labelled with corresponding offending, but nondehumanizing, attributes. Crucially, this increased aggressiveness was mediated by higher perceptions of being treated (Study 1) or viewed (Study 2) by others as animal-like. Overall, our research showed the detrimental effects of the interplay between social exclusion and animal metaphors from the perspective of victims.
Computing of related concepts in a context

Word sense disambiguation is an opened issue in the text mining and natural language processing for some time. Automatic acquisition of all distinct senses for polysemy words is still a big problem in the computer science. This paper discusses an approach to generate related words for an input word in some context. The context is used for the filtering of the related words for their distinct sense subsets. This approach is based on the associative learning of concepts and can be a step forward to the word sense disambiguation problem solving.
Incremental mining of frequent patterns without candidate generation or support constraint

In this paper, we propose a novel data structure called CATS Tree. CATS Tree extends the idea of FPTree to improve storage compression and allow frequent pattern mining without generation of candidate item sets. The proposed algorithms enable frequent pattern mining with different supports without rebuilding the tree structure. Furthermore, the algorithms allow mining with a single pass over the database as well as efficient insertion or deletion of transactions at any time.
The Design and Implementation of Postprocessing for Depth Map on Real-Time Extraction System

Depth estimation becomes the key technology to resolve the communications of the stereo vision. We can get the real-time depth map based on hardware, which cannot implement complicated algorithm as software, because there are some restrictions in the hardware structure. Eventually, some wrong stereo matching will inevitably exist in the process of depth estimation by hardware, such as FPGA. In order to solve the problem a postprocessing function is designed in this paper. After matching cost unique test, the both left-right and right-left consistency check solutions are implemented, respectively; then, the cavities in depth maps can be filled by right depth values on the basis of right-left consistency check solution. The results in the experiments have shown that the depth map extraction and postprocessing function can be implemented in real time in the same system; what is more, the quality of the depth maps is satisfactory.
Generic vanishing, gaussian maps, and Fourier-Mukai transform

In the first part of this paper we prove a vanishing criterion for higher direct images of projective families of line bundles on a Cohen-Macaulay variety X. The result involves certain first-order deformations of certain curves on X, and makes essential use of the notion of global co-gaussian maps, a generalization of Wahl's gaussian maps. In the second part we apply the criterion above, combined with Fourier-Mukai transform on abelian varieties, to prove an algebraic version of Green-Lazarsfeld's Generic Vanishing Theorem. In fact we prove a stronger result concerning higher direct images of Poincar\'e line bundles, which -- in the compact K\"ahler setting -- was conjectured by Green and Lazarsfeld and was recently proved, by completely different methods, by Hacon (math.AG/0308198)
On the Size of Shortest Modal Descriptions

We address the problems of separation and description in some fragments of modal logics. The former consists in finding a formula that is true in some given subset of the domain and false in another. The latter is a special case when one separates a singleton from the rest. We are interested in the shortest size of both separations and descriptions. This is motivated by applications in computational linguistics. Lower bounds are given by considering the minimum size of Spoiler’s strategies in the classical Ehrenfeucht-Fraisse game. This allows us to show that the size of such formulas is not polynomially bounded (with respect to the size of the finite input model). Upper bounds for these problems are also studied. Finally we give a fine hierarchy of succinctness for separation over the studied logics.
Learning to rerank images with enhanced spatial verification

Reranking is one of the commonly used schemes to improve the initial ranking performance for content based image retrieval (CBIR). The state-of-the-art reranking methods for CBIR are mainly based on spatial verification and global feature. To mine the complementary properties of different reranking strategies, we combine features representing images from different perspectives with RankSVM to obtain a reranking model to refine the initial ranking list. Besides, compared with traditional spatial verification based methods which measure image similarity only with single inlier's statistical properties, we bind close inlier visual words together to mine more geometric information from images. Through organizing inliers into sequence and computing the relative positions among inliers, we define an efficient similarity measurement with the order consistency between inlier sequences. Experimental results on both Oxford and imageNet datasets demonstrate that our proposed reranking method is effective and promising.