Miracle-dz/UniFAR-FTUs huggingface dataset:
Discussion of [Grefenstette, 1993]

1 Auto-generated Thesaurus Thesaurus is not only a useful resource to help understand related words and phrases in a document , it can also catalog correlation between words across multiple domains that were previously not obvious. For example, the word " mouse " in a document about animals is related to " cat " and " rabbit " , while in an article from a different domain it may relate with the words " printer " and " keyboard " [Dorow and Widdows, 2003]. Both concepts should appear in a thesaurus. Creating a thesaurus therefore requires a high degree of knowledge across many domains. Doing so manually requires domain experts and therefore can be expensive, yet incomplete. [Grefenstette, 1993] explores the possibility of automatically generating thesauri with domain-independent algorithm. Domain independence is what is being referred to as " knowledge-poor ". Given a large source of documents that contain sentences about some topic, the idea is to comb through this data and find terms that may relate to each other. In [Grefenstette, 1993], four specific strategies to mine related concepts were investigated. Before proceeding, the words were syntactically analyzed. They were put through a part of speech tagger and labeled as the appropriate part of speech. Their morphological deviations were standardized to reduce the number of different words. Each word now becomes a feature on its own. Words that are modifiers for other words (such as adjectives and verbs for nouns) were considered to be additional attributes for that word feature. • Related nouns Using the attributes as additional information about the noun words, each word pair can be assigned a similarity value. Words with attributes that are highly similar implies they were often used in similar ways, and therefore there is a high probability the two words are related. For additional robustness, two words are only considered related if they are among the top-N number of similar words for each other. • Related verbs Similarly for verbs, the attributes are in turn the nouns and phrases that are subjects or objects of the verbs. Verbs with similar attributes are related. • Noun phrases Noun phrases are similar to nouns, except that a larger number of adjacent words are used as attributes. This was found to produce more relevant attributes than a more stringent, smaller scope. • Morphology discovery Creative morphological development varied in form depending on the domain. A …
Macroeconomic Effects from Government Purchases and Taxes

For U.S. annual data that include WWII, the estimated multiplier for temporary defense spending is 0.4-0.5 contemporaneously and 0.6-0.7 over two years. If the change in defense spending is "permanent" (gauged by Ramey's defense-news variable), the multipliers are higher by 0.1-0.2. The estimated multipliers are all significantly less than one and apply for given average marginal income-tax rates. We cannot estimate reliable multipliers for non-defense purchases because of the lack of good instruments. Since the defense-spending multipliers are less than one, greater spending crowds out other components of GDP, mainly investment, but also non-defense government purchases and net exports. Consumer expenditure on non-durables and services has only a small response. In a post-1950 sample, increases in average marginal income-tax rates (measured by a newly constructed time series) have significantly negative effects on GDP. When interpreted as a tax multiplier, the magnitude is around 1.1. When we hold constant marginal tax rates, we find no statistically significant effects on GDP from changes in federal tax revenue (using the Romer-Romer exogenous federal tax-revenue change as an instrument). In contrast, with revenue held constant, increases in marginal tax rates still have a statistically significant negative effect on GDP. Therefore, tax changes seem to affect GDP mainly through substitution effects, rather than wealth effects. The combination of the estimated spending and tax multipliers implies that balanced-budget multipliers for defense spending are negative.
An improved similarity measure in particle filters for robust object tracking

Infrared object tracking plays a key role in many research fields, and there is a series of work on applying particle filter to this tracking problem. Most of the PF-based tracking algorithms utilize the Bhattacharyya coefficient as a similarity measure, however, its performance in infrared object tracking is limited due to insufficient discriminative power. In this paper, we present a combined similarity measure under the particle filter framework, which integrates the advantages of the Bhattacharyya coefficient, histogram intersection, and structural similarity. The experimental results are gained by using different infrared image sequences, which show that the proposed measure gives superior discriminative power and achieves more robust and stable tracking performance than the traditional approach.
A TESTING FRAMEWORK FOR FIBER TRACTOGRAPHY

The in vivo visualization of the complex human brain is always a tremendous challenge for biomedical imaging tools. Diffusion Tensor Imaging (DTI) is a new imaging technique based on monitoring water molecule diffusions in 3D space. Fiber tractography is the process of extracting nerve fiber tracts. In combination with DTI, fiber tractography can be used for medical research and the diagnosis of various diseases. A number of algorithms have been proposed for fiber tracking. However, few software tools have been developed for testing these algorithms. This project aimed to develop a comprehensive testing framework for the various fiber tracking algorithms. Based on research and user testing, FiberTK is a toolkit developed for creating and visualizing nerve fiber tracts. Various fiber tracking algorithms can be applied in the program and results are to be compared and analyzed visually. It is concluded that the project has been carried out in an appropriate manner and the resulting software has met its original requirement. However, future developments such as Automatic Analysis Report are possible and encouraged for the project.
A Comparative Based Phylogenetic Study in the Evolution of 16 S rRNA and RadA Genes in Archaea

Archaea are ubiquitous with key role in the biogeochemical cycles of the earth. Archaea are assigned a third domain of life in addition to Bacteria and Eukarya, based on universal small sub unit ribosomal RNA (SSU rRNA) and protein trees. The Archaea look like organisms that use eukaryotic-like proteins in a bacteria like context. The identification of archaeal genomic signatures gives a measure of the distinctiveness of Archaea as a coherent group, although these signatures can differ according to the degree of stringency. A comparative phylogenetic study using highly conserved 16s rRNA and the RadA genes may reveal the distinctiveness of the Archae.
Relative risk of death in UK haemodialysis patients in relation to achieved haemoglobin from 1999 to 2005: an observational study using UK Renal Registry data incorporating 30,040 patient-years of follow-up.

BACKGROUND Much controversy has been generated in recent times over the optimal target haemoglobin in chronic kidney disease patients receiving erythropoiesis-stimulating agent therapy. This has arisen from the paradoxical conclusions obtained from large retrospective or epidemiological studies versus interventional randomized controlled trials. METHODS Data from haemodialysis patients in the UK Renal Registry from 1999 to 2005 were analysed year by year for the relative risk of death at different haemoglobin concentrations, compared with a reference of 10-11 g/dl. The population size varied from 2291 in 1999 to 8209 in 2005. The data were analysed by chi-square tests, and a multivariate analysis was performed. RESULTS Across the years 1999 to 2005, there was a consistent relationship between the haemoglobin achieved and the risk of death (P < 0.0001). In 2005, the relative risk (RR) of death = 1.32 for a haemoglobin (Hb) of 9-10 g/dl; RR = 0.44 for Hb > 13 g/dl. The relationship between Hb and the RR of death is nevertheless remarkably consistent across the 7 years of study, with an S-shaped correlation (polynomial) between an Hb range of <9 g/dl and an Hb range of >13 g/dl (P < 0.0001). Multivariate analysis also showed age, time on dialysis and diabetes to be strongly predictive of death across all 7 years analysed (P < 0.0001 in all cases). CONCLUSION There is a significant relationship between achieved haemoglobin and mortality across the 7 years analysed, with no increase in risk seen with higher Hb levels.
Combining Derivative and Parametric Kernels for Speaker Verification

Support vector machine-based speaker verification (SV) has become a standard approach in recent years. These systems typically use dynamic kernels to handle the dynamic nature of the speech utterances. This paper shows that many of these kernels fall into one of two general classes, derivative and parametric kernels. The attributes of these classes are contrasted and the conditions under which the two forms of kernel are identical are described. By avoiding these conditions, gains may be obtained by combining derivative and parametric kernels. One combination strategy is to combine at the kernel level. This paper describes a maximum-margin-based scheme for learning kernel weights for the SV task. Various dynamic kernels and combinations were evaluated on the NIST 2002 SRE task, including derivative and parametric kernels based upon different model structures. The best overall performance was 7.78% EER achieved when combining five kernels.
A Service-Oriented Distributed Semantic Mediator: Integrating Multiscale Biomedical Information

Biomedical research continuously generates large amounts of heterogeneous and multimodal data spread over multiple data sources. These data, if appropriately shared and exploited, could dramatically improve the research practice itself, and ultimately the quality of health care delivered. This paper presents DIstributed Semantic MEDiator (DISMED), an open source semantic mediator that provides a unified view of a federated environment of multiscale biomedical data sources. DISMED is a Web-based software application to query and retrieve information distributed over a set of registered data sources, using semantic technologies. It also offers a user-friendly interface specifically designed to simplify the usage of these technologies by nonexpert users. Although the architecture of the software mediator is generic and domain independent, in the context of this paper, DISMED has been evaluated for managing biomedical environments and facilitating research with respect to the handling of scientific data distributed in multiple heterogeneous data sources. As part of this contribution, a quantitative evaluation framework has been developed. It consist of a benchmarking scenario and the definition of five realistic use-cases. This framework, created entirely with public datasets, has been used to compare the performance of DISMED against other available mediators. It is also available to the scientific community in order to evaluate progress in the domain of semantic mediation, in a systematic and comparable manner. The results show an average improvement in the execution time by DISMED of 55% compared to the second best alternative in four out of the five use-cases of the experimental evaluation.
PTK7 is essential for polarized cell motility and convergent extension during mouse gastrulation

Despite being implicated as a mechanism driving gastrulation and body axis elongation in mouse embryos, the cellular mechanisms underlying mammalian convergent extension (CE) are unknown. Here we show, with high-resolution time-lapse imaging of living mouse embryos, that mesodermal CE occurs by mediolateral cell intercalation, driven by mediolaterally polarized cell behavior. The initial events in the onset of CE are mediolateral elongation, alignment and orientation of mesoderm cells as they exit the primitive streak. This cell shape change occurs prior to, and is required for, the subsequent onset of mediolaterally polarized protrusive activity. In embryos mutant for PTK7, a novel cell polarity protein, the normal cell elongation and alignment upon leaving the primitive streak, the subsequent polarized protrusive activity, and CE and axial elongation all failed. The mesoderm normally thickens and extends, but on failure of convergence movements in Ptk7 mutants, the mesoderm underwent radial intercalation and excessive thinning, which suggests that a cryptic radial cell intercalation behavior resists excessive convergence-driven mesodermal thickening in normal embryos. When unimpeded by convergence forces in Ptk7 mutants, this unopposed radial intercalation resulted in excessive thinning of the mesoderm. These results show for the first time the polarized cell behaviors underlying CE in the mouse, demonstrate unique aspects of these behaviors compared with those of other vertebrates, and clearly define specific roles for planar polarity and for the novel planar cell polarity gene, Ptk7, as essential regulators of mediolateral cell intercalation during mammalian CE.
THE EVOLUTION OF STATIC ALLOMETRY IN SEXUALLY SELECTED TRAITS

Abstract Although it has been the subject of verbal theory since Darwin, the evolution of morphological trait allometries remains poorly understood, especially in the context of sexual selection. Here we present an allocation trade-off model that predicts the optimal pattern of allometry under different selective regimes. We derive a general solution that has a simple and intuitive interpretation and use it to investigate several examples of fitness functions. Verbal arguments have suggested cost or benefit scenarios under which sexual selection on signal or weapon traits may favor larger individuals with disproportionately larger traits (i.e., positive allometry). However, our results suggest that this is necessarily true only under a precisely specified set of conditions: positive allometry will evolve when the marginal fitness gains from an increase in relative trait size are greater for large individuals than for small ones. Thus, the optimal allometric pattern depends on the precise nature of net selection, and simple examples readily yield isometry, positive or negative allometry, or polymorphisms corresponding to sigmoidal scaling. The variety of allometric patterns predicted by our model is consistent with the diversity of patterns observed in empirical studies on the allometries of sexually selected traits. More generally, our findings highlight the difficulty of inferring complex underlying processes from simple emergent patterns.
Efficient comparison of enterprise privacy policies

Enterprise privacy policies often reflect different legal regulations, promises made to customers, as well as more restrictive enterprise-internal practices. The notion of policy refinement is fundamental for privacy policies, as it allows one to check whether a company's policy fulfills regulations or adheres to standards set by customer organizations, to realize the "sticky policy paradigm" that addresses transferring data from one realm to another in a privacy-preserving way, and much more. Although well-established in theory, the problem of how to efficiently check whether one policy refines another has been left open in the privacy policy literature. We present a practical algorithm for this task, concentrating on those aspects that make refinement of privacy policies more difficult than, for example refinement for access control policies, such as a more sophisticated treatment of deny rules and a suitable way for dealing with obligations and conditions on context information.
A Kinematics Significance Based Skeleton Map for Rapid Viewpoint Selection

Viewpoint selection has become a very active area of research during the last decade. Computation of good viewpoints is important in graph drawing, scene understanding, etc. A good viewpoint can give us rich information about a scene. In this study, we present a novel Kinematics Significance based Skeleton Map (KSSM) during iterative Laplacian contraction. Inspired by salient viewpoint selection, we propose a new rapid computation method based on a few initial viewpoints for iteration. It allows us to compute the final best viewpoint via Loop subdivision stencil rapidly for iterative decision under a threshold. Experimental results demonstrate that the KSSM can describe the topology information of 3D mesh effectively. It also presents the validity and effectiveness of viewpoint selection based on KSSM.
A Robust Approach for the Background Subtraction Based on Multi-Layered Self-Organizing Maps

Motion detection in video streams is a challenging task for several computer vision applications. Indeed, segmentation of moving and static elements in the scene allows to increase the efficiency of several challenging tasks, such as human-computer interface, robot visions, and intelligent surveillance systems. In this paper, we approach motion detection through a multi-layered artificial neural network, which is able to build for each background pixel a multi-modal color distribution evolving over time through self-organization. According to the winner-take-all rule, each layer of the network models an independent state of the background scene, in response to external disturbing conditions, such as illumination variations, moving backgrounds, and jittering. As a result, our background subtraction method exhibits high generalization capabilities that in combination with a post-processing filtering schema allow to produce accurate motion segmentation. Moreover, we propose an approach to detect anomalous events (such as camera motion) that require background model re-initialization. We describe our method in full details and we compare it against the most recent background subtraction approaches. Experimental results for video sequences from the 2012 and 2014 CVPR Change Detection data sets demonstrate how our methodology outperforms many state-of-the-art methods in terms of detection rate.
Walk the Walk: A Lightweight Active Transtibial Prosthesis

Active transtibial prostheses that can overcome the deficiencies of passive prostheses are gaining popularity in the research field. In addition to the advantages in joint torque and gait symmetry, terrain adaptation and total weight are other benefits that can help push active prostheses into the commercial market. In this article, we present a lightweight robotic transtibial prosthesis with damping behaviors for terrain adaptation. The proposed prosthesis, which mainly consists of a low-power motor, weighs only 1.3 kg, excluding the battery. It focuses on terrain adaptation instead of providing positive work at the stance phase. A damping control strategy is proposed to enable the prosthesis to manipulate the ankle impedance during stance with little power consumption. Experiments with three amputee subjects using the robotic prosthesis on different terrains show similar angle trajectories to the intact limb during the controlled flexion (CF) period as well as improved gait symmetry and walking stability compared with the robotic prosthesis in the maximal damping mode. The average power consumption of the prosthesis during one gait cycle is around 3.5 W, and a 0.28-kg rechargeable lithium-ion (Li-ion) battery can sustain a usage duration of more than 12 h or 20,000 steps.
How We Remember Conversation: Implications in Legal Settings

Memory for the content of our conversations reflects two partially conflicting demands. First, to be an effective participant in a conversation, we use our memory to follow its trajectory, to keep track of unresolved details, and to model the intentions and knowledge states of our partners. Second, to effectively remember a conversation, we need to recall the gist of what was said, by whom, and in what context. These two sets of demands are often different in their content and character. In this article, we review what is known about distant memory for conversations, focusing on issues that have particular relevance for legal contexts. We highlight evidence likely to be of importance in legal contexts, including estimates of how much information can be recalled, the quantity and types of errors that are likely to be made, and the situational factors that shape memory for conversation. The biases we see in distant memory for a conversation reflect in part the interplay of the conflicting demands that conversation places upon us.
A Short Signature Scheme in the Standard Model

In this paper, by elaborately choosing the parameters of Waters Hash function, we propose a new efficient signature scheme. It is shown that the scheme is secure against strongly unforgeable chosen-message attacks in the standard model under Computational Diffie-Hellman (CDH) assumption. Further, among all the known secure signatures in the standard model, our scheme is the shortest one and has the efficient security reduction as well.
Genetic approach for arabic part of speech tagging

With the growing number of textual resources available, the ability to understand them becomes critical. An essential first step in understanding these sources is the ability to identify the part of speech in each sentence. Arabic is a morphologically rich language, wich presents a challenge for part of speech tagging. In this paper, our goal is to propose, improve and implement a part of speech tagger based on a genetic alorithm. The accuracy obtained with this method is comparable to that of other probabilistic approaches.
The Validity and Reliability of the MyJump2 Application to Assess Vertical Jumps in Trained Junior Athletes

ABSTRACT This study aimed to assess the validity and reliability of jump assessments using the MyJump2 application. Eleven junior athletes (15 ± 1.4 years) performed five countermovement (CMJ) and drop jumps (DJ) measured simultaneously by a force platform and MyJump2. Additionally, intra- and inter-day reliability was assessed over two sessions, 7 days apart. Extremely high agreement between MyJump2 and the force platform (intra-class correlation coefficient, ICC ≥ 0.99) and the intra- and inter-operator agreement (ICC = 0.98–0.99) confirmed the validity and reliability of MyJump2. Mean typical errors (coefficient of variation percentage, CV%) within the first and second sessions were 4.9% and 4.5% respectively for CMJs, and 8.0% to 11.8% for DJ outcomes. CMJ height held acceptable inter-day reliability (CV < 10%; ICC > 0.8), while DJ did not. Results supported MyJump2 to be a valid and reliable tool for assessing jumps; however, with variability in DJs in this cohort, appropriate caution should be taken if including in a junior assessment battery.
Transfer components between subjects for EEG-based emotion recognition

Addressing the structural and functional variability between subjects for robust affective brain-computer interface (aBCI) is challenging but of great importance, since the calibration phase for aBCI is time-consuming. In this paper, we propose a subject transfer framework for electroencephalogram (EEG)-based emotion recognition via component analysis. We compare two state-of-the-art subspace projecting approaches called transfer component analysis (TCA) and kernel principle component analysis (KPCA) for subject transfer. The main idea is to learn a set of transfer components underlying source domain (source subjects) and target domain (target subject). When projected to this subspace, the difference of feature distributions of both domains can be reduced. From the experiments, we show that the two proposed approaches, TCA and KPCA, can achieve an improvement on performance with the best mean accuracies of 71.80% and 79.83%, respectively, in comparison of the baseline of 58.95%. The significant improvement shows the feasibility and efficiency of our approaches for subject transfer emotion recognition from EEG signals.