Miracle-dz/UniFAR-FTUs huggingface dataset:
Substitution in Structural Operational Semantics and Value-passing Process Calculi 1 a Simple Language for Value-passing

Consider a process calculus that allows agents to communicate values. The structural operational semantics involves substitution of values for variables. Existing rule formats, such as the GSOS format, do not allow this kind of explicit substitution in the semantic rules. We investigate how to derive rule formats for languages with substitution, by using categorical logic to interpret the framework of the GSOS format in different categories. The categories in question are categories of 'substitution actions'. To set the scene, fix a set of channel names, and consider a set V of value-expressions, that includes the channel names. A simple untyped value-passing process language, V-CCS, is given in Figure 1 (c.f. [8]). The precise value expressions of V are not important, but note that since V includes the (static) channel names, V-CCS is a very primitive applied π-calculus without restriction or name generation; c.f. [1]. For the sake of illustration, consider the set V ex of value expressions determined by the following grammar:
March Test BDN: A new March Test for dynamic faults

High-density components and process scaling lead more and more to the occurrence of new class of dynamic faults, especially in Static Random Access Memories (SRAMs), thus requiring more and more sophisticated test algorithms. Among the different types of algorithms proposed for testing SRAMs, March Tests have proven to be the most performing due to their low complexity, their simplicity and regular structure. Several March Tests for dynamic faults have been published, with different fault coverage. In this paper we propose March BDN, an extended version of the March AB. We will prove that it is able to increase the fault coverage in order to target latest dynamic faults. We show that the proposed March BDN has the highest known fault coverage compared to March Tests with the same complexity.
Transgenic loblolly pine (Pinus taeda L.) plants expressing a modified delta-endotoxin gene of Bacillus thuringiensis with enhanced resistance to Dendrolimus punctatus Walker and Crypyothelea formosicola Staud.

A synthetic version of the CRY1Ac gene of Bacillus thuringiensis has been used for the transformation of loblolly pine (Pinus taeda L.) using particle bombardment. Mature zygotic embryos were used to be bombarded and to generate organogenic callus and transgenic regenerated plants. Expression vector pB48.215 DNA contained a synthetic Bacillus thuringiensis (B.t.) CRY1Ac coding sequence flanked by the double cauliflower mosaic virus (CaMV) 35S promoter and nopaline synthase (NOS) terminator sequences, and the neomycin phosphotransferase II (NPTII) gene controlled by the promoter of the nopaline synthase gene was introduced into loblolly pine tissues by particle bombardment. The transformed tissues were proliferated and selected on media with kanamycin. Shoot regeneration was induced from the kanamycin-resistant calli, and transgenic plantlets were then produced. More than 60 transformed plants from independent transformation events were obtained for each loblolly pine genotype tested. The integration and expression of the introduced genes in the transgenic loblolly pine plants was confirmed by polymerase chain reactions (PCR) analysis, by Southern hybridization, by Northern blot analysis, and by Western blot analysis. Effective resistance of transgenic plants against Dendrolimus punctatus Walker and Crypyothelea formosicola Staud was verified in feeding bioassays with the insects. The transgenic plants recovered could represent a good opportunity to analyse the impact of genetic engineering of pine for sustainable resistance to pests using a B. thuringiensis insecticidal protein. This protocol enabled the routine transformation of loblolly pine plants that were previously difficult to transform.
Advanced Authentication Scheme using Multimodal Biometric Scheme

Fingerprint recognition has attracted various researchers and achieved great success. But, fingerprint alone may not be able to meet the increasing demand of high accuracy in today’s biometric system. The purpose of our paper is to inspect whether the integration of palmprint and fingerprint biometric can achieve performance that may not be possible using a single biometric technology. Pre-processing is done for fingerprint and palmprint images separately in order to remove any noise. The next step is feature extraction. Minutiae algorithm is used for fingerprint feature extraction and Local Binary pattern for palmprint. Wavelet fusion is applied in order to fuse the extracted features and Support Vector Machine is used for matching. The main highlight of the project is multimodal biometrics which will give a better security and accuracy comparing to unimodel system.
Please Scroll down for Article International Journal of Neuroscience Multistable Visual Perception Induces a Slow Positive Eeg Wave

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Monetary policy spillovers and emerging market credit: The impact of Federal Reserve communications on sovereign CDS spreads

This paper studies the effects of Federal Funds target rate changes and related communications by members of the US Federal Open Market Committee (FOMC) on spreads for emerging market sovereign credit default swaps (CDS) and their volatility. Using GARCH models over the precrisis period 2002 to mid-2007, we find that CDS spreads react in a statistically significant and economically relevant fashion both to actual interest rate changes and FOMC communications. US interest rate cuts and speeches suggesting future rate cuts each have at least as much of an economic influence on emerging market CDS spreads over the sample period as have observed improvements in country ratings. In addition, changes in the Federal Funds target rate increase the volatility of CDS spread changes, whereas FOMC communications appear to dampen volatility.
$P^{2}$ : Privacy-Preserving Communication and Precise Reward Architecture for V2G Networks in Smart Grid

Vehicle-to-grid (V2G) networks are important components of the smart grid (SG) for their capability of providing better ancillary services and facilitating the adoption of renewable resources. The operation of the V2G networks is based on continuously monitoring the status of individual battery vehicle (BV) as well as a carefully designed incentive scheme to attract sufficient participating BVs. However, the close monitoring tends to raise privacy concerns from the BV owners about identity and location information leakage, which have not been considered in previous works. In this paper, we make the first attempt to identify the privacy-preserving issues and propose a precise reward scheme in V2G networks, both of which are important towards bringing the concept of V2G network into practice. In V2G networks, it is the service providers (individual BVs) who need privacy protection rather than the service consumer (power grid). This unique characteristic renders privacy protection solutions proposed for conventional network systems not directly applicable. To protect privacy of BVs in V2G networks, we present , a secure communication architecture which achieves privacy-preserving for both BVs' monitoring and rewarding processes. Extensive performance analysis shows that only incurs moderate communication and computational overheads.
Analysis and simulation of RF MEMS switch

Along with the fast development of the automotive electronics technology, the wireless communication technique on vehicles has huge market potential. This paper takes the cantilever beam MEMS switch as an example to discuss mechanical principle and function simulation of the RF MEMS switch used in Vehicle-carried radio frequency communication. We select three kinds of cantilever beams with different section to analyze their switch characteristics, compute and use ANSYS software to carry out multi-physical coupling analysis and simulation. The threshold voltage, inherent frequency and optimal design of three kinds of beams are also discussed. The results provide a satisfactory theoretical support to design various high performance RF MEMS switches with variational section beam.
Public Displays of Play: Studying Online Games in Physical Settings

As research on virtual worlds gains increasing attention in educational, commercial, and military domains, a consideration of how player populations are 'reassembled' through social scientific data is a timely matter for communication scholars. This paper describes a large-scale study of virtual worlds in which participants were recruited at public gaming events, as opposed to through online means, and explores the dynamic relationships between players and contexts of play that this approach makes visible. Challenging conventional approaches to quantitatively driven virtual worlds research, which categorizes players based on their involvement in an online game at a particular point in time, this account demonstrates how players' networked gaming activities are contingent on who they are playing with, where, and when.
Prosodic cues for backchannels and short questions: really?

Short questions can be ambiguous even after considering their preceding contexts. Hence, prosody may be useful for disambiguating different types of questions and their uses. For example, question bias has been linked to the presence of certain pitch accents. This paper presents a corpus study of very short questions and the contribution of prosodic cues to discourse disambiguation. This study focuses on backchannel questions which are by nature highly biased and yet sit between genuine questions and genuine backchannels. The study finds LDA and SVM classifiers do not perform better than random at separating backchannel and question really based on these prosodic cues. This means that, while intonation differs between broad categories of questions, theories that try to integrate prosodic cues with semantics and discourse require more than intonation, the final rise and the other usual prosodic suspects like duration and intensity.
Visualizing a Library of Vibrotactile Effects

The rapid proliferation of vibrotactile (VT) devices and applications calls for vibration libraries and tools that can support end-users in customizing their VT notifications. The question is: how can users find their desired effects in a library of VT effects? Which taxonomy of VT effects can better help users in browsing the library and finding their desired effects? Although VT designers usually use low-level engineering parameters, such as energy and tempo, to design vibrations, past researches [3, 4, 6] showed that end-users used to describe vibrations in different ways. Some of these include describing physical properties of vibrations or using sensory and emotional words, metaphors, or providing usage examples for a given vibration. Each of these ways can be used to categorize VT effects, and we refer to each as a vibration taxonomy. In this project, we aim to visualize a library of vibrations that are annotated according to the five abovementioned vibration taxonomies: physical, sensory, emotional, metaphor, and usage example.
Circumventing the Feature Association Problem in SLAM

In autonomous applications, a vehicle requires reliable estimates of its location and information about the world around it. To capture prior knowledge of the uncertainties in a vehicle's motion response to input commands and sensor measurements, this fundamental task has been cast as probabilistic Simultaneous Localization and Map building (SLAM). SLAM has been investigated as a stochastic filtering problem in which sensor data is compressed into features, which are consequently stacked in a vector, referred to as the map. Inspired by developments in the tracking literature, recent research in SLAM has recast the map as a Random Finite Set (RFS) instead of a random vector, with huge mathematical consequences. With the application of recently formulated Finite Set Statistics (FISST), such a representation circumvents the need for fragile feature management and association routines, which are often the weakest component in vector based SLAM algorithms. This tutorial demonstrates that true sensing uncertainty lies not only in the spatial estimates of a feature, but also in its existence. This gives rise to sensor probabilities of detection and false alarm, as well as spatial uncertainty values. By re-addressing the fundamentals of SLAM under an RFS framework, it will be shown that it is possible to estimate the map in terms of true feature number, as well as location. The concepts are demonstrated with short range radar, which detects multiple features, but yields many false measurements. Comparison of vector, and RFS SLAM algorithms shows the superior robustness of RFS based SLAM to such realistic sensing defects.
Alzheimer Aβ Peptide Induces Chromosome Mis-Segregation and Aneuploidy, Including Trisomy 21: Requirement for Tau and APP

Chromosome aneuploidy, especially trisomy 21, arises in both familial and sporadic Alzheimer's disease. Expression of FAD genes or exposure to Aβ peptide induces aneuploidy in tg-mice and cultured cells. The requirement for GSK-3β, calpain, and Tau in Aβ-induced chromosome mis-segregation points to MT dysfunction as contributing to AD pathogenesis.
Toward an exemplar-based computational model for cognitive grammar

An exemplar-based computational framework is presented which is compatible with Cognitive Grammar. In an exemplar-based approach, language acquisition is modeled as the incremental, data-oriented storage of experiential patterns, and language performance as the extrapolation of information from those stored patterns on the basis of a language-independent information-theoretic similarity metric. We show that this simple architecture works for many aspects of phonological, morphological, and morphosyntactic acquisition and processing. Furthermore, we sketch how the approach may also work for syntactic processing. A central insight of the approach, based on the results of computational modeling experiments, is that abstraction of representations is not only unnecessary to achieve generalization (i.e. to make the system productive, and to make it gòbeyond' the learned patterns), but even harmful, and that useful language-independent metrics can be found for deening similarity in the context of language processing. In the generative tradition, generality is achieved by means of abstraction, and the representations of choice to describe these abstractions are rules. This implies that redundancy and the storage of individual instances are to be avoided, except for exceptions to the generalizations expressed in rules. In Langacker, 1991 (Chapter 10), this methodology is critically examined, and cognitive grammar is described as an alternative usage-based model of language structure. In the latter, bottom-up, approach, patterns (rules, generalizations) and (redundant) instantiations of those rules are assumed to co-exist in the grammar, describing phenomena at all levels of generality, from exceptionless regularities to idiosyncratic exceptions. Rules are presumed to be necessary for the computation of novel instantiations. In the remainder of this paper we will introduce an exemplar-based approach to language acquisition and processing. The approach is in large part compatible with Lan-gacker's usage-based model, but is more radical in its "maximalism": language knowledge is supposed to consist only of "instantiations" (exemplars); there is no role for explicit abstractions corresponding to (sub)regularities. We will argue on the basis of computational modeling experiments that the adoption of abstractions (rules, patterns), taken as necessary for explaining generalization and productivity in both the generative and the cognitive grammar approach, is misguided. Furthermore, the exemplar-based approach contributes to making cognitive grammar ideas more concrete by providing computational operationalisations of both acquisition and processing in such a framework.
ACL-05 Empirical Modeling of Semantic Equivalence and Entailment

ii Introduction The last few years have seen a surge in interest in modeling techniques aimed at measuring semantic equivalence and entailment, with work on paraphrase acquisition/generation, WordNet-based expansion, distributional similarity, supervised learning of semantic variability in information extraction, and the identification of patterns in template-based QA. Being able to identify when two strings " mean the same thing " or that one entails the other are crucial abilities for a broad range of NLP-related applications, ranging from question answering to summarization. These proceedings contain a rich variety of papers centered on the problem of modeling semantic overlap between linguistic strings. This is a difficult problem space, encompassing issues of lexical choice, syntactic alternation, semantic inference, and reference/discourse structure. We were pleased by the strong level of interest in the workshop, which resulted in a number of high-quality submissions. Each paper was blind-reviewed by 2-3 members of the Program Committee, and we were forced to make some difficult choices in determining the final schedule. This workshop is intended to bring together people working on empirical, application-independent approaches to the practical problems of semantic inference. While different applications face similar underlying semantic problems, these problems have typically been addressed in an application-specific manner. In the absence of a generic evaluation framework, it is difficult to compare semantic methods that were developed for different applications. We are particularly hopeful that the workshop will help foster discussion around common datasets and evaluation strategies that will help guide future work in this area. We would like to express our deepest gratitude to the hard-working members of the program committee. We'd also like to thank Mirella Lapata, Jason Eisner, Philipp Koehn, and Dragomir Radev for their organizational help. Abstract This paper addresses the classification of semantic relations between pairs of sentences extracted from a Dutch parallel corpus at the word, phrase and sentence level. We first investigate the performance of human annotators on the task of manually aligning dependency analyses of the respective sentences and of assigning one of five semantic relations to the aligned phrases (equals, generalizes, specifies, restates and intersects). Results indicate that humans can perform this task well, with an F-score of . 98 on alignment and an F-score of . 95 on semantic relations (after correction). We then describe and evaluate a combined alignment and classification algorithm, which achieves an F-score on alignment of . 85 (using EuroWordNet) and an F-score of . 80 on …
How many planet-wide leaders should there be?

Geo-replication becomes increasingly important for modern planetary scale distributed systems, yet it comes with a specific challenge: latency, bounded by the speed of light. In particular, clients of a geo-replicated system must communicate with a leader which must in turn communicate with other replicas: wrong selection of a leader may result in unnecessary round-trips across the globe. Classical protocols such as celebrated Paxos, have a single leader making them unsuitable for serving widely dispersed clients. To address this issue, several all-leader geo-replication protocols have been proposed recently, in which every replica acts as a leader. However, because these protocols require coordination among all replicas, commiting a client's request at some replica may incure the so-called "delayed commit" problem, which can introduce even a higher latency than a classical single-leader majority-based protocol such as Paxos. In this paper, we argue that the "right" choice of the number of leaders in a geo-replication protocol depends on a given replica configuration and propose Droopy, an optimization for state machine replication protocols that explores the space between single-leader and all-leader by dynamically reconfiguring the leader set. We implement Droopy on top of Clock-RSM, a state-of-the-art all-leader protocol. Our evaluation on Amazon EC2 shows that, under typical imbalanced workloads, Droopy-enabled Clock-RSM efficiently reduces latency compared to native Clock-RSM, whereas in other cases the latency is the same as that of the native Clock-RSM.
Metabolism and Circadian Rhythms - Implications for Body Weight

Mammals have developed an endogenous circadian clock located in the suprachiasmatic nuclei (SCN) of the anterior hypothalamus that responds to the environmental light-dark cycle. Similar clocks are found in peripheral tissues, such as the liver and adipose tissue, regulating cellular and physiological functions. The circadian clock has been reported to regulate metabolism and energy homeostasis, including lipogenic and adipogenic pathways. This is achieved by mediating the expression and/or activity of certain metabolic enzymes and transport systems. In return, enzymes and transcription activators interact with and affect the core clock mechanism. Animals with clock gene mutations that disrupt cellular rhythmicity have provided evidence to the relationship between the circadian clock and metabolic homeostasis. In addition, clinical studies in obese patients accentuate the link between the circadian clock and metabolism. This review will focus on the inter-connection between the circadian clock and metabolism with implications for body weight and how the circadian clock is influenced by hormones that regulate metabolism.
Triangulation & Hough Transform Based Fusion of Sonar Data for Mobile Robotics

Polaroid sonar sensors are still one of the most widely used sensors in mobile robotics. In this paper a novel sensor fusion scheme called THF (triangulation Hough fusion), which combines the advantages of TBF (triangulation based fusion) and CIHT (cluster inhibiting Hough transform), is presented. The idea of THF lies in that a modified Hough transform is employed on the points extracted by TBF, not on the raw sonar data directly. THF algorithm applied on clustered and noisy sonar data could reliably detect both point and line segment features of the environment. We demonstrate the effectivity of THF algorithm by extracting geometric features in a simulated indoor environment, in which a mobile robot travels with pedestrians moving around casually. Experiments demonstrate that THF is an effective and efficient scheme for detecting both point features and line segment features, especially in the structured environment.
Translating Missions in James Worral’s game “Grand Theft Auto’s Missions”

The objectives of the study was to know the difficult words encountered by the gamers and to know their strategies in translating this unknown word. The researcher used interview as the instrument to collect the material needed for this particular study. It is found that unknown word combined with certain feeling such as dissappoinment creates retention. So, this particular study showed eventhough these students have low capacity in understanding words in English but in GTA game, they were still willing to play. From their willingness it could increase their motivation to translating the word in English. So, the game is a very effective way to building vocabullary skill.