Miracle-dz/UniFAR-FTUs huggingface dataset:
Von Neumann, Morgenstern, and the creation of game theory: From chess to social science, 1900-1960 [Book Review]

Review(s) of: Von Neumann, Morgenstern, and the Creation of Game Theory. From Chess to Social Science, 1900-1960, by Robert Leonard, Cambridge, Cambridge University Press, 2010, Pp. x + 390, ISBN 978-0-521-56266-9, A$130 (hb).
Conceptual Clustering over One-to-many Relationships

This paper focuses on the problem of clustering sets of objects. An extension of the traditional attribute-value formalism is proposed, which conforms to well-known database modeling techniques. The mechanism described allows clustering over one-to-many relationships, i.e. objects may be represented with a variable number of components. Several experiments are provided to evaluate the algorithm.
LIMSIILES: Basic English Substitution for Student Answer Assessment at SemEval 2013

In this paper, we describe a method for assessing student answers, modeled as a paraphrase identification problem, based on substitution by Basic English variants. Basic English paraphrases are acquired from the Simple English Wiktionary. Substitutions are applied both on reference answers and student answers in order to reduce the diversity of their vocabulary and map them to a common vocabulary. The evaluation of our approach on the SemEval 2013 Joint Student Response Analysis and 8th Recognizing Textual Entailment Challenge data shows promising results, and this work is a first step toward an opendomain system able to exhibit deep text understanding capabilities.
Java Micro Edition and Adobe Flash Lite for arcade-style mobile phone game development: a comparative study

The pervasiveness of mobile devices has created a substantial market for mobile applications and games that continues to grow extremely rapidly. Consequently, the mobile game industry has firmly asserted itself as a significant industry with major development houses. In order to achieve a maximum target audience reach, it is crucial for developers to target the right mobile platforms and development environments. Simultaneously, the right tools are required to ensure the rapid, efficient creation and deployment of these mobile games. This paper offers an analysis and comparison of the well-established Java Micro Edition (JME) and the emerging Adobe Flash Lite platforms, based on our experiences developing a mobile phone game. An arcade-style game was developed that allowed key features to be tested using the JME and Flash Lite development platforms. The game adopted a tile-based, top-down perspective common to arcade games that are created using a tile-based game engine. The results obtained showed the strengths and weaknesses of the two environments, enabling optimal trade-offs to be made when developing mobile phone games. Our conclusion is that although it is possible to create tile-based games in both environments, JME currently provides better support, especially in the areas of collision detection and multi-threading.
DESCRIPTOR-BASED SOUND TEXTURE SAMPLING

Existing methods for sound texture synthesis are often concerned with the extension of a given recording, while keeping its overall properties and avoiding artefacts. However, they generally lack controllability of the resulting sound texture. After a review and classification of existing approaches, we propose two methods of statistical modeling of the audio descriptors of texture recordings using histograms and Gaussian mixture models. The models can be interpolated to steer the evolution of the sound texture between different target recordings (e.g. from light to heavy rain). Target descriptor values are stochastically drawn from the statistic models by inverse transform sampling to control corpus-based concatenative synthesis for the final sound generation, that can also be controlled interactively by navigation through the descriptor space. To better cover the target descriptor space, we expand the corpus by automatically generating variants of the source sounds with transformations applied, and storing only the resulting descriptors and the transformation parameters in the corpus.
On the Relation between Color Image Denoising and Classification

Large amount of image denoising literature focuses on single channel images and often experimentally validates the proposed methods on tens of images at most. In this paper, we investigate the interaction between denoising and classification on large scale dataset. Inspired by classification models, we propose a novel deep learning architecture for color (multichannel) image denoising and report on thousands of images from ImageNet dataset as well as commonly used imagery. We study the importance of (sufficient) training data, how semantic class information can be traded for improved denoising results. As a result, our method greatly improves PSNR performance by 0.34 - 0.51 dB on average over state-of-the art methods on large scale dataset. We conclude that it is beneficial to incorporate in classification models. On the other hand, we also study how noise affect classification performance. In the end, we come to a number of interesting conclusions, some being counter-intuitive.
Online Failure Prediction in Cloud Datacenters

Once failures occur in a cloud datacenter accommodating a large number of virtual resources, they tend to spread rapidly and widely, impacting many cloud services and their users. One of the best ways to prevent a failure from spreading in the system is to identify signs of a failure before its occurrence and deal with it proactively before it causes serious problems. Although several approaches have been proposed to predict failures by analyzing past logs of system messages and identifying the relationship between the messages and the failures, it is still difficult to automatically predict the failure for several reasons such as variation of log message formats and frequent changes in their configurations. Based on this understanding, we propose a new failure prediction method that Fujitsu Laboratories has developed. The method automatically learns message patterns as signs of failure by classifying messages by their similarity regardless of their format and re-learning the message patterns in frequently changed configurations. We evaluated our method in an actual cloud datacenter. The experimental results showed that our approach predicted failures with 80% precision and 90% recall in the best case.
Semantic relation extraction with kernels over typed dependency trees

An important step for understanding the semantic content of text is the extraction of semantic relations between entities in natural language documents. Automatic extraction techniques have to be able to identify different versions of the same relation which usually may be expressed in a great variety of ways. Therefore these techniques benefit from taking into account many syntactic and semantic features, especially parse trees generated by automatic sentence parsers. Typed dependency parse trees are edge and node labeled parse trees whose labels and topology contains valuable semantic clues. This information can be exploited for relation extraction by the use of kernels over structured data for classification. In this paper we present new tree kernels for relation extraction over typed dependency parse trees. On a public benchmark data set we are able to demonstrate a significant improvement in terms of relation extraction quality of our new kernels over other state-of-the-art kernels.
A New Identity Based Proxy Re-Encryption Scheme

The concept of proxy re-cryptography comes from the work of Blaze, Bleumer, and Strauss in 1998. The goal of proxy re-encryption is to securely enable the re-encryption of ciphertexts from one key to another, without relying on trusted parties. Identity based proxy re-encryption extends proxy re-encryption to the identity based setting. In this paper, we construct an identity based proxy re-encryption (IBPRE) scheme which can achieve master secret secure, while almost all of the previous efficient IBPRE schemes can not.
Continuous and Non-intrusive Reauthentication of Web Sessions Based on Mouse Dynamics

We propose a system for continuous reauthentication of Web users based on the observed mouse dynamics. Key feature of our proposal is that no specific software needs to be installed on client machines, which allows to easily integrate continuous reauthentication capabilities into the existing infrastructure of large organizations. We assess our proposal with real data from 24 users, collected during normal working activity for several working days. We obtain accuracy in the order of 97%, which is aligned with earlier proposals requiring instrumentation of client workstations for intercepting all mouse activity-quite a strong requirement for large organizations. Our proposal may constitute an effective layer for a defense-in-depth strategy in several key scenarios: Web applications hosted in the cloud, where users authenticate with standard mechanisms, organizations which allow local users to access external Web applications, and enterprise applications hosted in local servers or private cloud facilities.
Developing an Interactive Video Game-Based Learning Environment

With advanced computer and network technologies of nowadays, learners could benefit from well- developed distance learning systems for obtaining vast learning content, as well as performing learning exercises at anytime anywhere. However, to attract learners and to keep them active would be difficult in those content-based learning systems. One possible solution is to include some motivator factors in the online learning activities. Gaming could be considered as sort of learning. It also features in attraction and motivation. Thus, more and more researches are interested in developing game-oriented learning models and related game-based learning systems to attract learners during such learning activities. In this paper, we would like to combine the video-based course materials and game elements with an integrated learning platform called “V-GBL” environment. Course designers could easily design GBL courses and learners could enjoy their learning activities in the serious adventure game world.
Grid interactive service-oriented programming environment

Improvements in distributed computing, and the technologies that enable them, have led to significant improvements in middleware functionality and quality, mainly through networking and protocols. However, the distributed programming style has changed little over the years. Most programs are still written line per line of code in languages like C, C++, and Java. These conventional programs that can provide grid operations and grid data can be considered as common grid resources and shared by research and education communities worldwide. However, there are no relevant programming methodologies to utilize efficiently these shared service providers as a potentially vast grid repository, except through the manual writing of code. Realization of the potential of grid computing requires significant improvements in grid programming methodologies. The Grid Interactive Service-Oriented (GISO) methodology is presented that provides a programming environment with development tools that permit interactive (point-and-click), true grid programming, thus permitting the different elements of programming to be stored, reused, aggregated, and executed with a level of concurrency and grid-level control strategy not achievable in the conventional programming languages.
Alpha-Synuclein Aggregates Activate the Nlrp3 Inflammasome Following Vesicle Rupture

ix CHAPTER ONE: INTRODUCTION 1 STATEMENT OF THE PROBLEM 1 REVIEW OF RELATED LITERATURE 3 SYNUCLEINOPATHIES 3 Pathology 5 Oxidative Stress 6 α-synuclein 8 α-synuclein Aggregation 10 Microglia Mediated Inflammation 11 INNATE IMMUNE RESPONSE 15 The NLR Family 16 THE INFLAMMASOME 18 The NLRP3 Inflammasome 22 IL-1 AND IMMUNITY 29 CHAPTER TWO: EXPERIMENTAL METHODS AND RATIONALE 31 CELL LINES AND REAGENTS 31 CELL CULTURE 31 ALPHA-SYNUCLEIN 32 IMMUNOFLUORESCENCE MICROSCOPY 32 MEASUREMENT OF IL-1Β SECRETION 32 QUANTIFICATION OF CASPASE-1 ACTIVATION 33 CFP-ASC EXPRESSING THP-1 CELLS 33 ROS ASSAY 34 CHAPTER THREE: RESULTS 35 ALPHA-SYNUCLEIN INDUCE VESICLE RUPTURE 35 ALPHA-SYNUCLEIN INDUCES IL-1Β RELEASE FROM THP-1 CELLS 37 ALPHA-SYNUCLEIN ACTIVATION THE NLRP3 INFLAMMASOME 40 REACTIVE OXYGEN SPECIES AND K EFFLUX ARE INVOLVED IN ALPHA-SYNUCLEIN MEDIATED INFLAMMASOME ACTIVATION 42 CHAPTER FOUR: DISCUSSION 45 REFERENCES 48 VITA 58
Pronunciation variant selection for spontaneous speech synthesis - a summary of experimental results

To make synthesized speech more natural and colloquial the regularity of synthesized speech has to be overcome and spontaneous speech effects have to be integrated into the synthesis process. In a first step towards spontaneous speech we introduced different duration control methods in speech synthesis. In this paper we summarize the results of previous works (see for instance [1]) of changing the speaking rate indirectly by controlling the grapheme-to-phoneme conversion through different pronunciation variant selection algorithms. The presented results of listening experiments show a significant improvement in the category colloquial impression. To evaluate the quality of the most outstanding variant selection approach compared to the canonical synthesis (as the state-of-the-art system), we performed a new listening test on longer speech samples. The variant synthesis applying a pronunciation variant sequence model achieved a significant lower listening effort and a higher overall rate (MOS) compared to the canonical synthesis.
Ground-Based Optical Deep Pencil Beam Surveys

The initial results of the Deep Lens Survey ( http://dls.bell-labs.com ) to identify possible brown dwarfs and extremely metal poor red halo subdwarfs near the hydrogen burning limit are presented. Individual deep CCD high galactic latitude survey fields appear to offer a low probability of discovering field BD's, but taken collectively offer an opportunity to begin addressing questions regarding the scale height and distribution of these objects. In all likelihood, the very depth of such surveys will greatly increase our knowledge of the coolest extreme halo objects, which currently are known in far fewer numbers than T dwarfs. Ultimately, the large volume surveyed by the Large Synoptic Survey Telescope will identify vast numbers of such objects, providing a more complete picture of their spatial distribution.
Abundance of type I toxin–antitoxin systems in bacteria: searches for new candidates and discovery of novel families

Small, hydrophobic proteins whose synthesis is repressed by small RNAs (sRNAs), denoted type I toxin–antitoxin modules, were first discovered on plasmids where they regulate plasmid stability, but were subsequently found on a few bacterial chromosomes. We used exhaustive PSI-BLAST and TBLASTN searches across 774 bacterial genomes to identify homologs of known type I toxins. These searches substantially expanded the collection of predicted type I toxins, revealed homology of the Ldr and Fst toxins, and suggested that type I toxin–antitoxin loci are not spread by horizontal gene transfer. To discover novel type I toxin–antitoxin systems, we developed a set of search parameters based on characteristics of known loci including the presence of tandem repeats and clusters of charged and bulky amino acids at the C-termini of short proteins containing predicted transmembrane regions. We detected sRNAs for three predicted toxins from enterohemorrhagic Escherichia coli and Bacillus subtilis, and showed that two of the respective proteins indeed are toxic when overexpressed. We also demonstrated that the local free-energy minima of RNA folding can be used to detect the positions of the sRNA genes. Our results suggest that type I toxin–antitoxin modules are much more widely distributed among bacteria than previously appreciated.
Development of Al-Mu'awwidhah computing for personal data protection against abnormal attacks

Personal data is constantly being compromised not just by the normal identity thefts but also abnormal attacks. The Islamic concept of Al-Mu'awwidhah inspired the discovery of non-parametric cryptographs for personal data protection against abnormal (paranormal and asymmetric) cyber-attacks. A continuous search on new paradigm of non- parametric cryptographs led to the discovery of ethno-mathematics for substitution block-cipher boxes. The objects based on extracted Al-Qur'an and Al-Hadith symbols by use of ethno-mathematical functions. The extracted objects were insufficient to build the 256 bit block-ciphers. The development of expanding objects from Aramaic, Hebrew, Chinese, Hindu and other symbols are found to fill the gap but only up to 216bit out of the 256 bit block-cipher. Initial tests for algebraic attacks indicate Al-Mu'awwidhah Block Cipher resistance to be better than the random parameteic Khazad and Annubis Block Ciphers.
First-time homebuying: attitudes and behaviors of low-income renters through the financial crisis

Abstract We use psychological theory to investigate how attitudes toward homebuying relate to first-time home purchases over the past decade. Homeownership rates in the US have dropped to 20-year lows, but whether views toward homebuying shifted due to the financial crisis is not known because studies have not compared attitudes for the same respondents pre- and post-crisis. We address this gap with 2004–2014 panel data from low-income renters. We find that a negative shift in homebuying attitudes is associated with a decline in first-time home purchases. Older renters aged more than 35 years at baseline report the greatest declines in homebuying intentions. Younger renters aged 18–34 also report diminished homebuying intentions, yet express highest overall levels of homebuying intentions pre- and post-crisis. Blacks report greater homebuying intentions although their odds of home purchase are 29 per cent lower than whites. Homebuying norms and favorability are associated with homebuying intentions but not with actual purchases, while perceived control over homebuying influences both outcomes.
Ambient Displays : A Designer ’ s Synopsis

Research in the field of ambient displays has burgeoned within the past several years, but a coherent view of the design space has yet to be articulated. We present a synopsis of key design dimensions for ambient displays based on a survey of existing ambient displays. This paper presents our findings, referencing representative work for each design component, and in the process introduce research areas and display designs not yet investigated.
Tubular lysosomes accompany stimulated pinocytosis in macrophages

A network of tubular lysosomes extends through the cytoplasm of J774.2 macrophages and phorbol ester-treated mouse peritoneal macrophages. The presence of this network is dependent upon the integrity of cytoplasmic microtubules and correlates with high cellular rates of accumulation of Lucifer Yellow (LY), a marker of fluid phase pinocytosis. We tested the hypothesis that the efficiency of LY transfer between the pinosomal and lysosomal compartments is increased in the presence of tubular lysosomes by asking how conditions that deplete the tubular lysosome network affect pinocytic accumulation of LY. Tubular lysosomes were disassembled in cells treated with microtubule-depolymerizing drugs or in cells that had phagocytosed latex beads. In unstimulated peritoneal macrophages, which normally contain few tubular lysosomes and which exhibit relatively inefficient transfer of pinocytosed LY to lysosomes, such treatments had little effect on pinocytosis. However, in J774 macrophages and phorbol ester-stimulated peritoneal macrophages, these treatments markedly reduced the efficiency of pinocytic accumulation of LY. We conclude that a basal level of solute accumulation via pinocytosis proceeds independently of the tubular lysosomes, and that an extended tubular lysosomal network contributes to the elevated rates of solute accumulation that accompany macrophage stimulation. Moreover, we suggest that the transformed mouse macrophage cell line J774 exhibits this stimulated pinocytosis constitutively.
Bradykinin restores left ventricular function, sarcomeric protein phosphorylation, and e/nNOS levels in dogs with Duchenne muscular dystrophy cardiomyopathy.

AIMS Cardiomyopathy is a lethal result of Duchenne muscular dystrophy (DMD), but its characteristics remain elusive. The golden retriever muscular dystrophy (GRMD) dogs produce DMD pathology and mirror DMD patient's symptoms, including cardiomyopathy. We previously showed that bradykinin slows the development of pacing-induced heart failure. Therefore, the goals of this research were to characterize dystrophin-deficiency cardiomyopathy and to examine cardiac effects of bradykinin in GRMD dogs. METHODS AND RESULTS At baseline, adult GRMD dogs had reduced fractional shortening (28 ± 2 vs. 38 ± 2% in control dogs, P < 0.001) and left ventricular (LV) subendocardial dysfunction leading to impaired endo-epicardial gradient of radial systolic velocity (1.3 ± 0.1 vs. 3.8 ± 0.2 cm/s in control dogs, P < 0.001) measured by echocardiography. These changes were normalized by bradykinin infusion (1 µg/min, 4 weeks). In isolated permeabilized LV subendocardial cells of GRMD dogs, tension-calcium relationships were shifted downward and force-generating capacity and transmural gradient of myofilament length-dependent activation were impaired compared with control dogs. Concomitantly, phosphorylation of sarcomeric regulatory proteins and levels of endothelial and neuronal nitric oxide synthase (e/nNOS) in LV myocardium were significantly altered in GRMD dogs. All these abnormalities were normalized in bradykinin-treated GRMD dogs. CONCLUSIONS Cardiomyopathy in GRMD dogs is characterized by profound LV subendocardial dysfunction, abnormal sarcomeric protein phosphorylation, and impaired e/nNOS, which can be normalized by bradykinin treatment. These data provide new insights into the pathophysiological mechanisms accounting for DMD cardiomyopathy and open new therapeutic perspectives.
Force modeling of inhomogeneous material using unsupervised learning and model identification

In this paper a force modeling method for inhomogeneous materials is introduced. This modeling method is based on samples during haptic operations, for instance presses. Using biomimetic unsupervised learning, the model is primarily identified, including the distribution and material parameters of the inhomogeneous regions, and in this learning the parameter initial estimation, the principal component analysis, the cluster analysis and the quadratic discriminant analysis are applied. Then the material parameters and boundaries of the different regions are accurately optimized using the Gauss-Newton algorithm. Further more the modeling method is tested and verified by a set of simulations. In addition, the suggestions and prospect of the modeling method are also given.
Comprehensive analysis of the short channel effect in the SOI gate controlled hybrid transistor (GCHT)

A comprehensive analysis of the short channel effect (SCE) in the SOI gate controlled hybrid transistor (GCHT) is presented for the first time in comparison with the SOI MOSFET. Based on the numerical simulation, the controllability of the threshold voltage for different channel lengths and drain voltages is investigated, together with the subthreshold swing and the standby current. It is found that, with process compatibility with CMOS technology, the short channel behaviour is substantially improved in the GCHT due to its novel operating mechanism. The impact of the technological parameters on the short-channel characteristics is also discussed. It can be concluded that the SOI GCHT exhibits much lower sensitivity to technology variation than the MOSFET, resulting in a greatly expanded allowable design region and alleviation of contradiction between reduction of the short channel effect and suppression of the hot carrier effect. In addition, the turning-on/off performance of the SOI GCHT is reported in .