Miracle-dz/UniFAR-FTUs huggingface dataset:
Oncogenic induction of cellular high CpG methylation by Epstein-Barr virus in malignant epithelial cells

Epstein-Barr virus (EBV) is a well-known human herpesvirus associated with virtually all nasopharyngeal carcinoma (NPC) and ∼10% of gastric cancer (GC) worldwide. Increasing evidence shows that acquired genetic and epigenetic alterations lead to the initiation and progression of NPC and GC. However, even deep whole exome sequencing studies showed a relatively low frequency of gene mutations in NPC and EBV-associated GC (EBVaGC), suggesting a predominant role of epigenetic abnormities, especially promoter CpG methylation, in the pathogenesis of NPC and EBVaGC. High frequencies of promoter methylation of tumor suppressor genes (TSGs) have been frequently reported in NPC and EBVaGC, with several EBV-induced methylated TSGs identified. Further characterization of the epigenomes (genome-wide CpG methylation profile—methylome) of NPC and EBVaGC shows that these EBV-associated tumors display a unique high CpG methylation epigenotype with more extensive gene methylation accumulation, indicating that EBV acts as a direct epigenetic driver for these cancers. Mechanistically, oncogenic modulation of cellular CpG methylation machinery, such as DNA methyltransferases (DNMTs), by EBV-encoded viral proteins accounts for the EBV-induced high CpG methylation epigenotype in NPC and EBVaGC. Thus, uncovering the EBV-associated unique epigenotype of NPC and EBVaGC would provide new insight into the molecular pathogenesis of these unique EBV-associated tumors and further help to develop pharmacologic strategies targeting cellular methylation machinery in these malignancies.
Learning from water

The concept of life is central to biology and related life sciences, but there is no convergence on a defi nition. With the aim to resolve this problem analogies were studied between defi nitions of water and life. The concept of water refers to two phenomena: material particles (the H 2 O molecules) and interacting water molecules (liquid water). Likewise, the concept of life can be viewed as referring to a property of special material particles (the organisms) and to the system of interacting organisms (the ecosystem). In a comparable way as chemical theory has solved the problem of defi ning the water molecule, one can apply the Operator Theory for solving the problem of defi ning the organism concept. The analogy with water subsequently offers inspiration for two ontologically distinct defi nitions of life: (1) a defi nition of life as a general indication for a property that all organisms have, and (2) a defi nition of life that refers to a system of interacting organisms. These two defi nitions refer to different ontological kinds and accordingly cannot be merged into a single defi nition. For this reason the concept of life can be viewed as involving two, complementary, defi nitions. It is discussed how fi ndings based on the water-life analogy contribute to current discussions about the defi nition of life.
STRUCTURAL EDGE LEARNING FOR 3-D RECONSTRUCTION FROM A SINGLE STILL IMAGE

Learning 3-D scene structure from a single still image has become a hot research topic recently, during which edges played a very important role as they provided critical information about the structures. While not all the intensity edges are useful, existing 3-D reconstruction methods suffered heavily when not differentiating structural edges with non-structural ones. In this report, we consider learning structural edges rather than edges from intensity values of the image. Through supervised learning, the learnt edges as shown in this report carries more stuctural information and less noise than intensity edges. The comparison of two kinds of edges are also shown in the report.
ANALISANDO OS DISCURSOS DOS DEPUTADOS FEDERAIS: A LINGUÍSTICA DA INFORMAÇÃO CONTÁBIL NOS DISCURSOS SOBRE CONTABILIDADE PÚBLICA / ANALYZING THE SPEECHES OF FEDERAL DEPUTIES: A STUDY ON THE LANGUAGE OF ACCOUNTING INFORMATION IN THE DISCOURSE ON PUBLIC ACCOUNTS

No sistema republicano-democratico, a ciencia contabil obtem um papel central no apoio a fiscalizacao das contas publicas. Pressupoe, entao, que a Contabilidade Publica deva desempenhar um papel singular nas discussoes internas das Casas Legislativas em razao de seu papel de transmutacao dos atos de gestao em informacoes possiveis de serem examinadas. O objetivo deste trabalho e examinar a linguistica das informacoes contabeis nos discursos Parlamentares feitos no Plenario da Câmara dos Deputados. Como metodologia, optou-se por realizar uma pesquisa documental sobre os discursos pronunciados em plenario pelos Deputados no periodo de 2010 a 2014 e analisa-los pelo metodo de analise de conteudo de Bardin. Como resultado, verificou-se que a maioria dos deputados prefere analisar a confiabilidade da informacao contabil pela dimensao semântica da semiotica contabil.
The steering effect PM motor drives for automotive systems

The steer-by-wire (SBW) system requires the use of enhanced fuel economy, assist action given two motor drives, the first for the mechanical steering system and the second for the torque feedback to the steering wheel. An interior permanent magnet (IPM) synchronous motor is used for the steering actuator whereas a fractional-slot surface-mounted permanent magnet (SPM) synchronous motor is used for the torque feedback.
Hoprield neural network approach for single machine scheduling problem

This paper presents a Hopfield neural network approach for the problem of scheduling n jobs in a single machine to minimize total weighted tardiness. A binary encoding scheme is introduced to represent the solutions, together with a heuristic to decode. A 10-job problem is solved by sequencing the job using different methods viz. weighted shortest processing time (WSPT) rule, earliest due date (EDD) rule, binary representation and Hopfield neural network. The results show that the Hopfield neural network performs better over others
Statistical Study of the Yoga on Mental Health among Children of the Residential School

This paper summarizes the statistical evidence on the effects of yoga interventions on various components of mental health. Tension, stress, anxiety, depression or traumatic experiences are some mental illness. Adolescence is a stage in one's life when a variety of mental health problems are more likely to develop. In the present study, yoga has been shown to be effective in reducing mental imbalance conditions. We perform our study over school children of age group 8-14 of Birla Education Trust's residential school at Pilani. We involve 276 male and female students from Birla Public School, Birla Balika Vidyapeeth, Birla School for an experiment. Different tests are conducted before and after yoga to measure mental status and results are compared statistically. All inferences are depicted in tables and conclusions are drawn in the last.
Retention-Aware Test Scheduling for BISTed Embedded SRAMs

In this paper we address the test scheduling problem for built-in self-tested (BISTed) embedded SRAMs (e-SRAMs) when data retention faults (DRFs) are considered. The proposed test scheduling algorithm utilizes the "retention-aware" test power model (Wang et al., 2005) to minimize the total testing time of e-SRAMs while not violating given power constraints. Without losing generality, we consider both cases where the pause time for data retention faults is fixed and cases where it can be varied. Experimental results show that the "retention-aware" test scheduling algorithm can reduce the testing time of e-SRAMs up to more than 98 percent at the computational time within a second
Fractional martingales and characterization of the fractional Brownian motion

In this paper we introduce the notion of fractional martingale as the fractional derivative of order $\alpha$ of a continuous local martingale, where $\alpha\in(-{1/2},{1/2})$, and we show that it has a nonzero finite variation of order $\frac{2}{1+2\alpha}$, under some integrability assumptions on the quadratic variation of the local martingale. As an application we establish an extension of L\'evy's characterization theorem for the fractional Brownian motion.
Applications of Bayesian Probability Theory in Astrophysics

Bayesian Inference is a powerful approach to data analysis that is based almost entirely on probability theory. In this approach, probabilities model {\it uncertainty} rather than randomness or variability. This thesis is composed of a series of papers that have been published in various astronomical journals during the years 2005-2008. The unifying thread running through the papers is the use of Bayesian Inference to solve underdetermined inverse problems in astrophysics. Firstly, a methodology is developed to solve a question in gravitational lens inversion - using the observed images of gravitational lens systems to reconstruct the undistorted source profile and the mass profile of the lensing galaxy. A similar technique is also applied to the task of inferring the number and frequency of modes of oscillation of a star from the time series observations that are used in the field of asteroseismology. For these complex problems, many of the required calculations cannot be done analytically, and so Markov Chain Monte Carlo algorithms have been used. Finally, probabilistic reasoning is applied to a controversial question in astrobiology: does the fact that life formed quite soon after the Earth constitute evidence that the formation of life is quite probable, given the right macroscopic conditions?
The Industrial Revolution in Miniature: The Spinning Jenny in Britain, France, and India

The spinning jenny helps explain why the Industrial Revolution occurred in Britain rather than in France or India. Wages were exceptionally high relative to capital prices in Britain, so the jenny was profitable to use in Britain but not elsewhere. Since it was only profitable to use the jenny in Britain, that was the only country where it as worth incurring the costs of developing it. Irrespective of the quality of their institutions or the progressiveness of their cultures, neither the French nor the Indians would have found it profitable to mechanize cotton production in the eighteenth century.
Job satisfaction and organizational commitment: An empirical investigation among ICT-SMEs.

Purpose The aim of this study is to examine the structural relationship between Spector’s nine job satisfaction facets (supervision, nature of the work, communication, contingent rewards, co-worker, fringe benefits, payment, promotion and operating procedures), organizational commitment facets (normative commitment, affective commitment and continuance commitment) and the influence of employees’ years of experience on satisfaction and commitment relationships. Owing to the nature of the industry, employee satisfaction, retention and commitment in Information and Communications Technology-Small and Medium-sized Enterprise (ICT-SME) is a matter of great concern. Design/methodology/approach A total of 256 valid questionnaires were collected among employees of Information and Communications Technology-Small and Medium-sized Enterprises (ICT-SMEs) to evaluate the measurement and structural model using partial least squares path modelling approach. Findings The findings indicate that payment, promotion, fringe benefits, co-worker, communication, operating procedures and nature of the work are positively associated with affective commitment. Furthermore, payment, promotion, fringe benefits, supervision, contingent rewards, operating procedures and nature of the work have a positive relationship with normative commitment. Considering employees’ years of experience as a categorical moderating variable, the results of partial least squares multi-group analysis show how the discrepancies between employees’ years of experience influence their level of commitment. Originality/value This study reveals that employees’ affective and normative commitments are positively associated and their continuance commitment is contingent upon their affective commitment, and not normative commitment. There are only three factors, i.e. promotion, fringe benefits and operating procedures, that are conductive to employees’ continuance commitment. Contributions, implications and limitations of the study are discussed.
Ontology-Based Application Framework for Network Education Resources Library

In past twenty years, as the rapid growth of Internet application, network education has grown a main part of current education. At the same time, semantic-based network educational resource became an important research field in computer education technology and AI. So far, however, there is a serious of bottlenecks in the progress of their applications, e. g. the criterion of web resource is not compatible, the semantic definition is not strict and the validity and well-structure are absent. Addressing this issue, the work presented in this paper shows the design, implementation of a new application framework for network education resources library. By using ontology-based semantic technology, it creates an open platform for new educational resources, achieves interoperation between heterogeneous resources and realizes the centralized management of resources and contents distributed stored.
Detection of an Anticorrelated Hard X-Ray Time Lag in Cygnus X-3

The wide-band X-ray spectra of the high-mass X-ray binary Cyg X-3 exhibit a pivoting behavior in the "low" (as well as "hard") state, correlated to the radio emission. The timescale of the soft and hard X-rays' anticorrelation, which gave rise to the pivoting feature, was found to be less than a day from the monitoring observations by the Rossi X-Ray Timing Explorer all-sky monitor and the Compton Gamma Ray Observatory BATSE. In this Letter we report the detection of a lag of ≲1000 s in the anticorrelation of the hard X-ray emission (20-50 keV) to that of the soft X-ray emission (2-7 keV), which may be attributed to the viscous timescale of the flow of matter in the accretion disk. This suggests the geometrical picture of a truncated accretion disk with a Compton cloud inside the disk, the relative sizes of which determine the spectral shape. Any change in the disk structure will take place in a viscous timescale, with corresponding anticorrelated change in the Compton cloud. We also report the pivoting in the spectra in one span of a pointed observation when an episode of the rearranging of the accretion system is serendipitously observed. This is the first such observation of hard X-ray delay seen in the persistent Galactic microquasars, within the precincts of the hard state.
ec 2 00 0 Essentials of Classical Brane Dynamics

Contribution to proc. Peyresq 5 meeting (June, 2000): " Quantum spacetime, brane cosmology, and stochastic effective theories " Abstract: This article provides a self contained overview of the geometry and dynamics of relativistic brane models, of the category that includes point particle, string, and membrane representations for phenomena that can be considered as being confined to a worldsheet of the corresponding dimension (respectively one, two, and three) in a thin limit approximation in an ordinary 4 dimensional spacetime background. This category also includes " brane world " models that treat the observed universe as a 3-brane in 5 or higher dimensional background. The first sections are concerned with purely kinematic aspects: it is shown how, to second differential order, the geometry (and in particular the inner and outer curvature) of a brane worldsheet of arbitrary dimension is describable in terms of the first, second, and third fundamental tensor. The later sections show how – to lowest order in the thin limit – the evolution of such a brane worldsheet will always be governed by a simple tensorial equation of motion whose left hand side is the contraction of the relevant surface stress tensor T µν with the (geometrically defined) second fundamental tensor K µν ρ , while the right hand side will simply vanish in the case of free motion and will otherwise be just the orthogonal projection of any external force density that may happen to act on the brane.
Social Tagging: Exploring the Image, the Tags, and the Game

An increasing amount of images are being uploaded, shared, and retrieved on the Web. These large image collections need to be properly stored, organized and easily retrieved. Tags have a key role in image retrieval but it is difficult for those who upload the images to also undertake the quality tag assignment for potential future retrieval by others. Relying on professional keyword assignment is not a practical option for large image collections due to resource constraints. Although a number of content-based image retrieval systems have been launched, they have not demonstrated sufficient utility on large-scale image sources on the web, and are usually used as a supplement to existing text-based image retrieval systems. An alternative to professional image indexing can be social tagging -- with two major types being photo-sharing networks and image labeling games. Here we analyze these applications to evaluate their usefulness from the semantic point of view. We also investigate whether social tagging behaviour can be managed. The findings of the study have shown that social tagging can generate a sizeable number of tags that can be classified as interpretive for an image, and that tagging behaviour has a manageable and adjustable nature depending on tagging guidelines.
A Framework for Goal-driven Learning 1 Why Goals? an Everyday Example

In cognitive science, artiicial intelligence, psychology, and education, a growing body of research supports the view that learning is largely a goal-directed process. Experimental studies show that people with diierent goals process information diierently; work in machine learning presents functional arguments for goal-based focusing of learner eeort. Recent work in these elds has focussed on issues of how learning goals arise, how they aaect learner decisions of when and what to learn, and how they guide the learning process. It is increasingly evident that investigation of goal-driven learning can beneet from bringing these perspectives together in a multidisciplinary eeort (Leake & Ram, 1993). The central idea underlying goal-driven learning is that because the value of learning depends on how well the learning contributes to achieving the learner's goals, the learning process should be guided by reasoning about the information that is needed to serve those goals. The eeectiveness of goal-driven learning depends on being able to make good decisions about when and what to learn, on selecting appropriate strategies for achieving the desired learning, and on guiding the application of the chosen strategies. Research into such topics includes the development of computational models for goal-driven learning, the testing of those models through psychological experiments and empirical experiments with computer programs, the justiication of the models through functional arguments about the role and utility of goals in learning, and the use of models of goal-driven learning in guiding the design of educational environments. The common themes in these research eeorts are the investigation of types of learning goals, the origins of learning goals, and the role of goals in the learning process. Research on goal-driven learning in artiicial intelligence has been motivated largely by computational arguments. The problem of combinatorial explosion of inferences is well known; in any realistic task domain, time and resource constraints prohibit consideration of all but a few of the possible inferential paths. Consequently , any reasoner, human or machine, must focus its attention and resources on pursuing those inferential paths that are likely to be most useful. Similarly, in any realistic situation, there are several diierent types 1 This is an extended abstract of a chapter to appear in A. Ram and D. Leake (eds.), Goal-Driven Learning, MIT Press/Bradford Books. of learning that a reasoner might perform, several kinds of new knowledge that a reasoner might acquire, and several kinds of reformulation or reorganization of existing …
A novel routing scheme for paired peers in P2P network

Peer-to-Peer (P2P) networks have been shown to be a promising approach to provide instant voice services over the Internet for its potential high scalability. However, for one paired peers, how to efficiently transmit voice data among peers in such networks remains a major challenge. Hereby this paper proposed some hybrid routing schemes for P2P transmitting system, which include improved random detection algorithm, delay binary tree search algorithm, AS-aware discovery algorithm. With the help of these novel routing schemes, we can choose the correct algorithm to transfer media data, in small size but low delay, among peers in P2P network. Simulations show that these new routing strategies achieve obvious effect.
Rules of Designing Routing Metrics for Greedy, Face, and Combined Greedy-Face Routing

Different geographic routing protocols have different requirements on routing metric designs to ensure proper operation. Combining a wrong type of routing metrics with a geographic routing protocol may produce unexpected results, such as geographic routing loops and unreachable nodes. In this paper, we propose a novel routing algebra system to investigate the compatibilities between routing metrics and three geographic routing protocols including greedy, face, and combined greedy-face routing. Five important algebraic properties, respectively, named odd symmetry, transitivity, strict order, source independence, and local minimum freeness, are defined in this algebra system. Based on these algebraic properties, the necessary and sufficient conditions for loop-free, delivery-guaranteed, and consistent routing are derived when greedy, face, and combined greedy-face routing serve as packet forwarding schemes or as path discovery algorithms, respectively. Our work provides essential criteria for evaluating and designing geographic routing protocols.
Detecting false testimonies in reputation systems using self-organizing maps

It has been demonstrated that rating trust and reputation of individual nodes is an effective approach in distributed environments in order to improve security, support decision-making and promote node collaboration. Nevertheless, these systems are vulnerable to deliberate false or unfair testimonies. In one scenario, the attackers collude to give negative feedback on the victim in order to lower or destroy its reputation. This attack is known as bad mouthing attack. In another scenario, a number of entities agree to give positive feedback on an entity (often with adversarial intentions). This attack is known as ballot stuffing. Both attack types can significantly deteriorate the performances of the network. The existing solutions for coping with these attacks are mainly concentrated on prevention techniques. In this work, we propose a solution that detects and isolates the abovementioned attackers, impeding them in this way to further spread their malicious activity. The approach is based on detecting outliers using clustering, in this case self-organizing maps. An important advantage of this approach is that we have no restrictions on training data, and thus there is no need for any data pre-processing. Testing results demonstrate the capability of the approach in detecting both bad mouthing and ballot stuffing attack in various scenarios.