Miracle-dz/UniFAR-FTUs huggingface dataset:
A Computational Study of Elongation Factor G (EFG) Duplicated Genes: Diverged Nature Underlying the Innovation on the Same Structural Template

Background Elongation factor G (EFG) is a core translational protein that catalyzes the elongation and recycling phases of translation. A more complex picture of EFG's evolution and function than previously accepted is emerging from analyzes of heterogeneous EFG family members. Whereas the gene duplication is postulated to be a prominent factor creating functional novelty, the striking divergence between EFG paralogs can be interpreted in terms of innovation in gene function. Methodology/Principal Findings We present a computational study of the EFG protein family to cover the role of gene duplication in the evolution of protein function. Using phylogenetic methods, genome context conservation and insertion/deletion (indel) analysis we demonstrate that the EFG gene copies form four subfamilies: EFG I, spdEFG1, spdEFG2, and EFG II. These ancient gene families differ by their indispensability, degree of divergence and number of indels. We show the distribution of EFG subfamilies and describe evidences for lateral gene transfer and recent duplications. Extended studies of the EFG II subfamily concern its diverged nature. Remarkably, EFG II appears to be a widely distributed and a much-diversified subfamily whose subdivisions correlate with phylum or class borders. The EFG II subfamily specific characteristics are low conservation of the GTPase domain, domains II and III; absence of the trGTPase specific G2 consensus motif “RGITI”; and twelve conserved positions common to the whole subfamily. The EFG II specific functional changes could be related to changes in the properties of nucleotide binding and hydrolysis and strengthened ionic interactions between EFG II and the ribosome, particularly between parts of the decoding site and loop I of domain IV. Conclusions/Significance Our work, for the first time, comprehensively identifies and describes EFG subfamilies and improves our understanding of the function and evolution of EFG duplicated genes.
Patterns of entry and correction in large vocabulary continuous speech recognition systems

A study was conducted to evaluate user performance andsatisfaction in completion of a set of text creation tasks usingthree commercially available continuous speech recognition systems.The study also compared user performance on similar tasks usingkeyboard input. One part of the study (Initial Use) involved 24users who enrolled, received training and carried out practicetasks, and then completed a set of transcription and compositiontasks in a single session. In a parallel effort (Extended Use),four researchers used speech recognition to carry out real worktasks over 10 sessions with each of the three speech recognitionsoftware products. This paper presents results from the Initial Usephase of the study along with some preliminary results from theExtended Use phase. We present details of the kinds of usabilityand system design problems likely in current systems and severalcommon patterns of error correction that we found.
Imitation, Group Selection and Cooperation

A prior signalling stage is added to the Prisoner's Dilemma and the overall population involved is divided into a number of subpopulations. Evolution involves both local and global imitation — so that the process is formally one of "group selection". A subpopulation that is not signalling and defecting against one and all can be invaded by two "secret handshake" mutants. A subpopulation that is composed entirely of the secret handshake strategy can be invaded by a single "sucker punch" mutant. Nevertheless, if there are at least three subpopulations, the population cooperates always, in the limit as the mutation rate tends to zero.
Mission planning in unstructured environments: A reinforcement learning approach

Mission planning scenarios in robotics typically involve one or more semi-autonomous agents and a human operator. The high-level goal is to find an optimal allocation of agents to tasks. Each individual task or collection of tasks may have subgoals, such as search, localization, or information gathering. Each of these lower-level goals are their own topics, and the high-level goal of task accomplishment can be categorized as a decision problem. The focus of this work is on solving decision problems through reinforcement learning. Tasks are completely parameterized by a minimal set of basis constraints—spatial, temporal, and (agent-task) coupling—which produces a single cost for each agent-task pairing. The cost completely captures the ability of a specific agent to perform a specific task. A novel state representation is presented that mitigates exponential growth of the state space by scaling independently of the spatial dimension. The decision problem is cast as an MDP and an optimal policy is found using Q-learning. Simulation results are presented for a two-agent two-task example, showing convergence of the value function and improved learning over time. To highlight the scalability of the learning algorithm, additional simulations compare the learned policy to a hand-coded greedy policy for varying number of tasks. The learned policy is shown to reliably allocate agents to tasks with minimal parameter tuning and is robust to low-level changes to agent dynamics as well as random agent motion.
Handling missing data by using stored truth values

This paper proposes a method for handling inapplicable and unknown missing data. The method is based on: (1) storing default values (instead of null values) in place of missing data, (2) storing truth values that describe the logical status of the default values in corresponding fields of corresponding tables. Four valued logic is used so that the logical status of the default data values can be described as, not just true or false, but also as inapplicable or unknown. This method, in contrast to the “hidden byte” approach, has two important advantages: (1) Because the logical status of all data is represented explicitly in tables, all 4-valued operations can be handled via a 2-valued data manipulation language, such as SQL. Language extensions for handling missing data (e.g., “IS NULL”) are not necessary. (2) Because data fields always contain a default value (as opposed to a null value or mark), it is possible to do arithmetic across missing data and to interpret the logical status of the result by means of logical operations on the corresponding stored truth values.
Correlation Between Playing Digital Game And Students English Learning Achievement

The purpose of this research is to find out the correlation between playing digital game and students English learning achievement for the eighth grade students of SMP Bawari Pontianak in Academic Year 2012 2013. This research involved 35 students of eighth grade (VIII B). This research was designed in the form of descriptive research therefore; the data of this research were obtained by administering the questionnaire and students English learning achievement score taken from the English teachers handbook. The questionnaire tested on 35 students with 25 questions. This research used Person Product Moment formula to see the correlation value. The result of analyzing data found that the correlation between playing digital game and their English learning achievement score were 0.86 which categorized by high correlation. The most dominant skill acquired is Reading skill. Based on the finding, it is found that there were 11 students got high level (above 70) deals with students response score and the rest of them are below 70.
A statistical model for signatures

A Bayesian model for off-line signature analysis involving the representation of a signature through its curvature is developed. The prior model makes use of a spatial point process for specifying the knots in an approximation restricted to a buffer region close to a template curvature, along with an independent time warping mechanism. In this way, prior shape information about the signature can be built into the analysis. The observation model is based on additive white noise superimposed on the underlying curvature. The approach is implemented using MCMC and applied to a collection of documented instances of Shakespeare’s signature.
Completing University: Characteristics and Outcomes of Completing and Non-Completing Students. Longitudinal Surveys of Australian Youth. Research Report 51.

This study, which is based on annual data collected on education, training, and labour market activities up until 2004 from the Longitudinal Surveys of Australian Youth (LSAY) program, examines the factors that influence course completion by young people at university and documents the post-university activities, especially labour market activities, of those who enrol at a university but do not obtain a qualification. Key findings indicated that: students’ regional and socioeconomic background has little influence on their likelihood of completing university; and university non-completion has not had substantial negative effects on the transition to the labour market compared to other groups of young people with the exception of university course completers. The contents are: Executive summary; Introduction; Data and methods; Completion of university degree courses; Labour market outcomes of university degree completers and non-completers; Discussion.
Advances in Campylobacter biology and implications for biotechnological applications

Campylobacter jejuni is a major foodborne pathogen of animal origin and a leading cause of bacterial gastroenteritis in humans. During the past decade, especially since the publication of the first C. jejuni genome sequence, major advances have been made in understanding the pathobiology and physiology of this organism. It is apparent that C. jejuni utilizes sophisticated mechanisms for effective colonization of the intestinal tracts in various animal species. Although Campylobacter is fragile in the environment and requires fastidious growth conditions, it exhibits great flexibility in the adaptation to various habitats including the gastrointestinal tract. This high adaptability is attributable to its genetically, metabolically and phenotypically diverse population structure and its ability to change in response to various challenges. Unlike other enteric pathogens, such as Escherichia coli and Salmonella, Campylobacter is unable to utilize exogenous glucose and mainly depends on the catabolism of amino acids as a carbon source. Campylobacter proves highly mutable in response to antibiotic treatments and possesses eukaryote‐like dual protein glycosylation systems, which modify flagella and other surface proteins with specific sugar structures. In this review we will summarize the distinct biological traits of Campylobacter and discuss the potential biotechnological approaches that can be developed to control this enteric pathogen.
Proposition of secure service oriented product line

SOPL approach (Service Oriented Product Line) can be used in various domains where SOA based applications are needed such as e/m government, e-business, e-learning and so on. This approach is a combination of Service-Oriented Architecture (SOA) and product line. SOA offers a solution to problems of integration and interoperability between services. But the SOA approach doesn't follow a specific reuse approach. In Product Line approach, reuse is systematic with two phases domain engineering and application engineering and offers mechanisms for the management of the variability. Ensure secure services are vital in order to establish trust between users and service providers. In this context, we aim to extend SOPL phases with security activities in order to produce secure service-oriented applications and for such activity we indicate means (methods, tools, etc.) that that allow us to perform security activities that we have introduced. In this work, we propose Secure SOPL: a development process that integrates security in the SOPL process. The originality of our work is on the integration of security in SOPL. Notes that existing works are either oriented to the integration of security in classical development processes or they are oriented enrichment of SPL by security activities but not treat the SOPL approach.
Shoot-Look-Shoot: A Review and Extension

We consider the optimal use of information in shooting at a collection of targets, generally with the object of maximizing the average number (or value) of targets killed. The shooting problem is viewed as a Markov decision process, and the modal solution technique is stochastic dynamic programming. Information obtained about target status may or may not be perfect, and there may or may not be constraints on the number of shots. Previous results are reviewed, and some new results are obtained.
The Concept of a Software-Free Resilience Infrastructure for Cyber-Physical Systems

This paper presents the architectural concept of a digital system that can be attached as an infrastructure to a "Client" system to enhance its resilience. This system, called "Resilience Infrastructure" RI, has four attributes. First, the RI is structured as a tree network of Monitor modules that are implemented by hardware and firmware only and can protect one or more Client systems. Second, the RI is separate from the Client. The only connections between them are error messages and data requests from the Client and error responses and data messages from the RI. Third, the RI is generic, that is, it can be attached to any Client that can issue error messages and data requests, and can receive Client-specified error responses and data messages from the Infrastructure. Fourth, the Infrastructure is self-protecting, that is, it is fully fault-tolerant while employing only hardware and firmware. The architecture and fault tolerance of the Resilience Infrastructure are illustrated by an elementary design.
MuVM: Higher Order Mutation Analysis Virtual Machine for C

Mutation analysis is a method for evaluating the effectiveness of a test suite by seeding faults artificially and measuring the fraction of seeded faults detected by the test suite. The major limitation of mutation analysis is its lengthy execution time because it involves generating, compiling and running large numbers of mutated programs, called mutants. Our tool MuVM achieves a significant runtime improvement by performing higher order mutation analysis using four techniques, meta mutation, mutation on virtual machine, higher order split-stream execution, and online adaptation technique. In order to obtain the same behavior as mutating the source code directly, meta mutation preserves the mutation location information which may potentially be lost during bit code compilation and optimization. Mutation on a virtual machine reduces the compilation and testing cost by compiling a program once and invoking a process once. Higher order split-stream execution also reduces the testing cost by executing common parts of the mutants together and splitting the execution at a seeded fault. Online adaptation technique reduces the number of generated mutants by omitting infeasible mutants. Our comparative experiments indicate that our tool is significantly superior to an existing tool, an existing technique (mutation schema generation), and no-split-stream execution in higher order mutation.
A hierarchical computational model of visual attention using multi-layer analysis

Computational model of visual attention is very useful in image processing. It can improve the efficiency and save computational resource. A hierarchical computational model of visual attention based on multi-layer analysis is proposed in this paper. This model simulates the human visual attention mechanism using multi-layer data competition. Firstly, different parts of the input image compete for attention at the first layer with coarsest resolution based on their visual saliency. When a region gets the focus of attention, the sub-regions of it compete for attention at the next layer with a finer resolution. This process is done iteratively until every salient region and its sub-regions have been processed at the final layer with the finest resolution. The proposed model was tested on many natural images. Experimental results and analysis are presented in this paper. The proposed model is valid and the attention results are consistent with human visual system.
Empirical Support for Two Refactoring Studies Using Commercial C# Software

Objective. This paper documents a study of the application of refactorings in commercial C# software comprising 270 versions over a two-month period. The software was developed in a continuous integration environment in a large, multi-national company where each software change committed to the source control was regarded as a new version. The aim of the research was to compare and contrast the results from two previous refactoring studies with those of the C# software. Method. A tool was developed to compare each version with the previous and detect occurrences of fifteen types of refactorings in both production and test classes. In total, over one thousand separate refactorings were identified. We then extended the profile of refactorings to compare (separately) the types of refactorings identified in test code and those in production code. Finally, we explored the interrelationships between a subset of the fifteen refactorings as a part explanation for the results. Conclusions. While 'simpler' refactorings were common, the more 'complex' structural refactorings were relatively rare. This supported the key result of an earlier empirical study by Advani et al. where Java open-source was used. Distinct differences were found in the types of refactoring applied to each code type. Support was found for a recent observation of Zaidman et al. in terms of parallel effort devoted to production and test classes. The study thus illustrates a strong commonality between refactoring trends found in both previous studies. Analysis of, and insight into all of our results were informed by follow-up discussions and consultation with the company's Architect.
Cue-Induced Cocaine Seeking and Relapse Are Reduced by Disruption of Drug Memory Reconsolidation

Long-lasting vulnerability to drug cue-induced relapse to a drug-taking habit is a major challenge to the treatment of drug addiction. Here we show that blockade of drug memory reconsolidation, through infusion of Zif268 antisense oligodeoxynucleotides into the basolateral amygdala shortly before reexposure to a cocaine-associated stimulus but not simply to the training context, severely impaired subsequently cue-maintained cocaine seeking under a second-order schedule of reinforcement and abolished cue-induced reinstatement of and relapse to cocaine seeking. This reduction in relapse after disrupted memory reconsolidation was not only seen after several hundred pairings of the stimulus with self-administered cocaine, but older, as well as recent, memories were also disrupted. Reconsolidation blockade may thus provide a potential therapeutic strategy for the prevention of relapse in drug addiction.
Handwritten Signature Authentication Scheme using Integrated Statistical Analysis of Bi-Color Images

In this paper, we propose data hiding, extraction and handwritten signature authentication algorithms for binary images. Handwritten signature Image can be transmitted from source to target securely over network after processing the source image by using this proposed data hiding algorithm. According to the algorithm, size of the carrier image must be double (or more) the size of source image. If necessary then additional bytes or noise needed to be injected into carrier image to attain the required size. To do this, the header is updated by the new value (sum of original size of file and amount of noise). There are numerous biometric authentication methods also proposed. In this paper, we propose a novel and new alternative. Entire work can be divided into two phases- a. security on transmission; and b. Recognition and authentication. Our scheme supports the application environment and we strongly believe that "user authentication by statistical analysis" could be a solid platform for future research and study. This proposed scheme could be applied for ownership protection, copy control, annotation and authentication of digital media. This work is focused on authentication of handwritten signature.
Grammatical constructions and linguistic generalizations: The What's X doing Y? construction

Our goal is to present, by means of the detailed analysis of a single grammatical problem, some of the principal commitments and mechanisms of a grammatical theory that assigns a central role to the notion of GRAMMATICAL CONSTRUCTION . To adopt a constructional approach is to undertake a commitment in principle to account for the entirety of each language. This means that the relatively general patterns of the language, such as the one licensing the ordering of a finite auxiliary verb before its subject in English, often known as SAI, and the highly idiomatic patterns, like kick the bucket , stand on an equal footing as data for which the grammar must account. An explicit grammar that covers the full range of constructions must represent all constructions, of whatever degree of generality or idiomaticity, in a common notation and must provide an explicit account of how each sentence of a language is licensed by a subset of the leaves of the inheritance hierarchy of constructions which constitutes the grammar of that language. Language-internal generalizations are captured by inheritance relations among constructions. Cross-language generalizations are captured by the architecture of the representation system and by the sharing of abstract constructions across languages. The particular grammatical phenomenon used here to introduce construction grammar (CG) is the construction that licenses the surprising syntactic and semantic features of a sentence like What are they doing resuscitating constructions?
Enhancing Effectiveness of Density-Based Outlier Mining

Outlier mining is an important work of data mining and a density-similarity-neighbor based outlier factor (DSNOF) algorithm is proposed to indicate the degree of outlier-ness of an object. The proposed algorithm calculates the densities of an object and its neighbors and constructs the similar density series (SDS) in the neighborhood of the object. Based on the SDS, the proposed algorithm computes the average series cost (ASC) of the object and the DSNOF of the object can be obtained according to the ASC of the object and those of the neighbors of the object. The experiments are performed on the synthetic and the real datasets. The experiments results verify that the proposed algorithm not only can detect outlier more effectively and but also do not increase the time and the space complexities.