Miracle-dz/UniFAR-FTUs huggingface dataset:
Occurrence of two superoxide dismutases in Aeromonas hydrophila: molecular cloning and differential expression of the sodA and sodB genes.

Aeromonas spp. , considered as emerging opportunistic pathogens, belong to the family Vibrionaceae. Among the criteria currently used for their classification is the presence of a single FeSOD (iron-containing superoxide dismutase), which distinguishes them from Enterobacteriacea. In this paper the cloning of the sodA and sodB genes encoding two different SODs in Aeromonas hydrophila ATCC 7966 is reported. The sodB gene encoded an FeSOD (196 amino acids, 21.5 kDa), was constitutively expressed and showed 75% homology with the E. coli FeSOD. The sodA gene encoded a protein of 206 amino acids (22.5 kDa) with MnSOD (manganese-containing SOD) activity and showed 55% homology with the Escherichia coli MnSOD. The MnSOD of A. hydrophila was detected only during the stationary phase of growth under high aeration or when induced by lack of iron. Nevertheless, paraquat had no detectable effect on its production. The amino-terminal part of the Mn-containing protein contained a putative signal sequence which could permit a periplasmic localization.
Stability and robust position control of hysteretic systems

Position control of a wide class of hysteretic systems, which includes those described by a Preisach model, is considered. The main focus of this paper is stability, tracking and the trajectories of a hysteretic system controlled by a PI controller. The system output (not its derivative) is measured and controlled. It is shown that, for arbitrary reference signals, the closed‐loop system is bounded‐input–bounded‐output‐stable with a finite gain of one. Furthermore, the absolute value of the error decreases monotonically for a constant reference signal. In this case, provided that the desired output is within the limits of the system output, zero steady‐state error is guaranteed. A bound on the time required to achieve a specified error is obtained. Only a simple condition on the controller parameters is required. The results imply that stability and position control are guaranteed, even if large errors in the model exist. Copyright © 2009 John Wiley & Sons, Ltd.
Adaptive Drift-Diffusion Process to Learn Time Intervals

Animals learn the timing between consecutive events very easily. Their precision is usually proportional to the interval to time (Weber's law for timing). Most current timing models either require a central clock and unbounded accumulator or whole pre-defined populations of delay lines, decaying traces or oscillators to represent elapsing time. Current adaptive recurrent neural networks fail at learning to predict the timing of future events (the 'when') in a realistic manner. In this paper, we present a new model of interval timing, based on simple temporal integrators, derived from drift-diffusion models. We develop a simple geometric rule to learn 'when' instead of 'what'. We provide an analytical proof that the model can learn inter-event intervals in a number of trials independent of the interval size and that the temporal precision of the system is proportional to the timed interval. This new model uses no clock, no gradient, no unbounded accumulators, no delay lines, and has internal noise allowing generations of individual trials. Three interesting predictions are made.
On the Limit of Long Strings

To gain a clearer understanding of the dynamics of evolving populations the limit of innnitely long strings is examined. The limit clariies some of the behaviour of evolving systems. For example, this limit removes any complications due to transient behaviour. Care is required in taking the limit to ensure that the quantities considered are meaningful. For concreteness a simple Genetic Algorithm acting on the problem of ones-counting is considered. A population evolving under selection and mutation alone is rst examined. In this limit a remarkably simple picture of the evolutionary ow emerges. The discussion is widened to include crossover. This gives a new insight into how diversity induced by crossover improves search. Finally the approach to the limit is examined. The limit provides a way of separating the initial transient dynamics from the long time (asymptotic) dynamics.
What a mesh

Cooperative end-system multicast (CEM) is a promising paradigm for Internet video distribution. Several CEM systems have been proposed and deployed, but the tradeoffs inherent in the different designs are not well understood. In this work, we provide a common framework in which different CEM design choices can be empirically and systematically evaluated. Based on our results, we conjecture that all CEM systems must abide by a set of fundamental design constraints, which we express in a simple model. By necessity, existing system implementations couple the data- and control-planes and often use different transport protocols.
Buss–Perry Aggression Questionnaire

The Buss–Perry Aggression Questionnaire (BP-AQ) is a 29-item, four-factor instrument that measures physical aggression, verbal aggression, anger, and hostility. A large number of competing versions of the original BP-AQ have been proffered in the literature, but testing with aggressive offenders is limited. The present study used confirmatory factor analysis to compare the fit of seven models with a sample of 246 men and women who pled guilty to misdemeanor aggressive offenses. The study found two similar parsimonious 12-item versions of the four-factor BP-AQ that outperformed the other models and fit the data well while retaining acceptable reliability. Taken together, superior psychometric properties, acceptable reliability, and reduced item-burden are properties that clearly support the usage of either of these 12-item versions. The relative merits of these shorter versions of the BP-AQ are examined and implications for their use in applied contexts and further research are considered.
Conserved Fungal Genes as Potential Targets for Broad-Spectrum Antifungal Drug Discovery

ABSTRACT The discovery of novel classes of antifungal drugs depends to a certain extent on the identification of new, unexplored targets that are essential for growth of fungal pathogens. Likewise, the broad-spectrum capacity of future antifungals requires the target gene(s) to be conserved among key fungal pathogens. Using a genome comparison (or concordance) tool, we identified 240 conserved genes as candidates for potential antifungal targets in 10 fungal genomes. To facilitate the identification of essential genes in Candida albicans, we developed a repressible C. albicans MET3 (CaMET3) promoter system capable of evaluating gene essentiality on a genome-wide scale. The CaMET3 promoter was found to be highly amenable to controlled gene expression, a prerequisite for use in target-based whole-cell screening. When the expression of the known antifungal target C. albicans ERG1 was reduced via down-regulation of the CaMET3 promoter, the CaERG1 conditional mutant strain became hypersensitive, specifically to its inhibitor, terbinafine. Furthermore, parallel screening against a small compound library using the CaERG1 conditional mutant under normal and repressed conditions uncovered several hypersensitive compound hits. This work therefore demonstrates a streamlined process for proceeding from selection and validation of candidate antifungal targets to screening for specific inhibitors.
Using Tree Kernels for Classifying Temporal Relations between Events

The ability to accurately classify temporal relations between events is an important task in a large number of natural language processing and text mining applications such as question answering, summarization, and language specific information retrieval. In this paper, we propose an improved way of classifying temporal relations, using support vector machines (SVM). Along with gold-standard corpus features, the proposed method aims at exploiting useful syntactic features, which are automatically generated, to improve accuracy of the SVM classification method. Accordingly, a number of novel kernel functions are introduced and evaluated for temporal relation classification. Our evaluations clearly demonstrate that adding syntactic features results in a considerable performance improvement over the state of the art method, which merely employs gold-standard features.
Real-Time Context-Aware Network Security Policy Enforcement System (RC-NSPES)

The major technical objectives of the RC-NSPES are to provide a framework for the concurrent operation of reactive and pro-active security functions to deliver efficient and optimised intrusion detection schemes as well as enhanced and highly correlated rule sets for more effective alerts management and root-cause analysis. The design and implementation of the RC-NSPES solution includes a number of innovative features in terms of real-time programmable embedded hardware (FPGA) deployment as well as in the integrated management station. These have been devised so as to deliver enhanced detection of attacks and contextualised alerts against threats that can arise from both the network layer and the application layer protocols. The resulting architecture represents an efficient and effective framework for the future deployment of network security systems.
A Model-Driven Approach for Generating Business Processes and Process Interaction Semantics

Business process modeling (BPM) is one of the key technologies to benefit enterprises with higher efficiencies and greater business values. However, BPM requires intensive business expertise and human resources. Thus, it is valuable and challenging to enable fast delivery of reusable business process designs, regarding the existence of various popular business processes modeling languages and fast changing markets. In this paper, we generate language-specific business process models and process interaction semantics from UML 2.0 process models. A WS-BPEL metadata model and a process interaction semantics metadata model is defined to annotate UML 2.0 business process model as stereotypes; with a set of transformation patterns, we can generate a WS-BPEL business process model and a process interaction semantics file from each annotated UML 2.0 process model. Our approach can also be similarly applied to other process modeling languages to highly reuse the business process model in UML 2.0.
Pareto Optimal Control for Natural and Supernatural Motions

Optimization is a natural tool for designing natural motion control strategies. However, optimal motions can be expensive to compute. Furthermore, we are often interested in knowing an entire family of optimal motions rather than single motion. For a motion such as a jump, the solution family of interest is described by the pareto-optimal front that defines the trade-off between effort and jump height. In this paper we explore algorithms for computing a set of controllers that span the pareto-optimal front for jumping motions. Once computed, these controllers can then drive physics-based simulations in real time. We also develop supernatural jump controllers through the optimized introduction of external forces. We show that the pareto-optimal front can naturally span both natural and supernatural regimes. This allows for controllers that can naturally transition from physics-based motions to motions assisted by external forces as the task demands increase.
'There comes a point where people just can't cope': exploring the views and experiences of frontline officers

This study investigated the views and experiences of frontline officers. It aimed to explore: 1. Motivations for working on the frontline; 2. Factors influencing job satisfaction; 3. Communication and change; 4. Factors effecting operational performance and 5. Partnership working across the different participating agencies engaged in the criminal justice system. Semi-structured interviews were completed with 26 frontline officers working in a range of departments and roles. Qualitative data obtained via interviews were analysed thematically, using Braun and Clarke's (2006) six steps of thematic data analysis (1. Familiarisation; 2. Generation of initial codes; 3. Searching for themes; 4. Reviewing themes; 5. Defining and naming themes; 6. Write-up). This focus of this poster is the presentation of findings relating to the wellbeing of frontline officers. The analysis revealed how frontline officers were passionate about delivering positive outcomes for communities and people in need. In response to changing staffing levels and profiles, linked with a climate of economic constraint, accounts of frustration were linked with a desire to meet a (self-)imposed standard of quality in their engagements with the public. The data showed how frontline officers were going over-and-above to meet expectations, which has potential implications for stress, anxiety and an imbalanced home-work life. There were mixed viewpoints on the management of wellbeing by senior officers, with some being depicted as uncaring and not valuing the person outside of their formal role. The poster will present implications for the management of frontline officers by senior officers and call for a renewed focus on improving the wellbeing of officers on the frontline. While organisational strategies are welcomed, it is critical for supervising officers to create an everyday culture that prioritises wellbeing of frontline officers.
Does Nationality, Gender, and Age Affect Travel Motivation? a Case of Visitors to The Caribbean Island of Barbados

ABSTRACT. The study represents an exploratory attempt to capture the underlying reasons for tourists' decisions to visit a destination. The main objective of this study is to examine the specific case of a tourism destination, investigating first whether there are differences between motivations of those who are from different countries traveling to the destination of Barbados. Secondly, the study examines whether there are any differences in the motivations between male and female tourists, and among tourists of different age groups. Thus, it is a comparative study of differences in motives between specific groups. As a result, it attempts to incorporate the experiential view into a construct such as the image of the tourism destination. This article seeks to propose an integrated approach to understand tourist motivations based on origins and how these contribute to the tourists' perception of a destination.
The gopher game: a social, mobile, locative game with user generated content and peer review

This paper introduces 'Gophers', a social game for mobile devices that utilises task oriented gameplay to create a novel entertainment experience. The study combines a number of key research themes: mobile social gaming, acquiring useful data through gameplay and content sharing in mobile settings. The experience of trialling the game in the real world is discussed and the findings from the study are presented.
Motion prediction for moving objects: a statistical approach

This paper proposes a technique to obtain long term estimates of the motion of a moving object in a structured environment. Objects moving in such environments often participate in typical motion patterns which can be observed consistently. Our technique learns those patterns by observing the environment and clustering the observed trajectories using any pairwise clustering algorithm. We have implemented our technique using both simulated and real data coming from a vision system. The results show that the technique is general, produces long-term predictions and is fast enough for its use in real time applications.
Use of Timed Automata Models in the Design of Real-time Control Network Elements

The design of network elements for real-time control networks requires careful consideration of the fundamental timing requirements. The use of a timed automata approach for modelling and verifying the timing requirements promises to be beneficial. In this work a case study approach is shown where a model of the packet scheduler component for a network switch element is developed, based on a timed automata method. Using the Uppaal model checker certain properties are verified. The timed behaviour of the model can be assessed, based on clocks incorporated into the timed automata model.
An improved rough set data model for stock market prediction

Rough set theory is a well established tool for dealing with inconsistent data. The dependencies among the attributes, their significance, and evaluation can easily be performed using intelligent data analysis tool viz., rough set theory. The objective of this article is to modify the existing stock market predictive model based on rough set approach by A.E Hassanien et al. and to construct a data model that would generate fewer number of decision rules. Moreover the results obtained from the proposed data model are compared with well-known software tool Rough set Exploration system 2.2 popularly known as RSES 2.2. It is shown that the proposed model has a higher overall accuracy rate and generates more compact and fewer rules than RSES 2.2. Rough confusion matrix is used to evaluate the predicted classification performances. The effectiveness of this data model is demonstrated on data set consisting of daily movements of a stock traded in Kuwait Stock Exchange spanning over a period of five years.
On the Range of Equilibria Utilities of a Repeated Epidemic Dissemination Game with a Mediator

We consider eager-push epidemic dissemination in a complete graph. Time is divided into synchronous stages. In each stage, a source disseminates ν events. Each event is sent by the source, and forwarded by each node upon its first reception, to f nodes selected uniformly at random, where f is the fanout. We use Game Theory to study the range of f for which equilibria strategies exist, assuming that players are either rational or obedient to the protocol, and that they do not collude. We model interactions as an infinitely repeated game. We devise a monitoring mechanism that extends the repeated game with communication rounds used for exchanging monitoring information, and define strategies for this extended game. We assume the existence of a trusted mediator, that players are computationally bounded such that they cannot break the cryptographic primitives used in our mechanism, and that symmetric ciphering is cheap. Under these assumptions, we show that, if the size of the stream is sufficiently large and players attribute enough value to future utilities, then the defined strategies are Sequential Equilibria of the extended game for any value of f. Moreover, the utility provided to each player is arbitrarily close to that provided in the original game. This shows that we can persuade rational nodes to follow a dissemination protocol that uses any fanout, while arbitrarily minimising the relative overhead of monitoring.
Learning Embedded Discourse Mechanisms for Information Extraction

We address the problem of learning discourse-level merging strategies within the context of a natural language information extraction system. While we report on work currently in progress, results of preliminary experiments employing classiication tree learning , maximum entropy modeling, and clustering methods are described. We also discuss motivations for moving away from supervised methods and toward un-supervised or weakly supervised methods.
Novel Anticytomegalovirus Activity of Immunosuppressant Mizoribine and Its Synergism with Ganciclovir

Cytomegalovirus (CMV) infection is a prominent infection in transplant recipients. The immunosuppressive drug mizoribine was shown to have anti-CMV activity in vitro and was reported to have an anti-CMV effect in renal transplantation. This study characterized the anti-CMV activity of mizoribine in vitro and its synergistic activity with ganciclovir. Mizoribine suppressed replication and at the EC50 for plaque inhibition of 12.0 μg/ml. Mizoribine and ganciclovir exerted a strong synergism in anti-CMV activity. Mizoribine depletes guanosine nucleotides by inhibiting inosine monophosphate dehydrogenase and may increase the ratio of ganciclovir to guanosine in treated cells, resulting in a strong synergistic augmentation of the anti-CMV activity of ganciclovir. Two clinical isolates with UL97 mutations were less susceptible to mizoribine than the Towne strain but were equally susceptible in the presence of guanine. Two mizoribine-resistant strains were isolated after culture for 3 months with 100 μg/ml mizoribine, but they were as sensitive to ganciclovir as the parent Towne strain. The anti-CMV activity of mizoribine was antagonized by 2′-deoxyguanosine. Mizoribine inhibited CMV replication directly, and the sequence of mizoribine-resistant mutants of UL97 and UL54 was identical to that of the parent Towne strain, indicating the different anti-CMV action from ganciclovir, foscarnet, and maribavir. Mizoribine as an immunosuppressive and anti-CMV drug in the clinical regimen was suggested to suppress replication of CMV in vivo and control CMV infection in transplant recipients in combination with ganciclovir.
Sequencing and Analysis of the Pseudomonas fluorescens GcM5-1A Genome: A Pathogen Living in the Surface Coat of Bursaphelenchus xylophilus

It is known that several bacteria are adherent to the surface coat of pine wood nematode (Bursaphelenchus xylophilus), but their function and role in the pathogenesis of pine wilt disease remains debatable. The Pseudomonas fluorescens GcM5-1A is a bacterium isolated from the surface coat of pine wood nematodes. In previous studies, GcM5-1A was evident in connection with the pathogenicity of pine wilt disease. In this study, we report the de novo sequencing of the GcM5-1A genome. A 600-Mb collection of high-quality reads was obtained and assembled into sequence contigs spanning a 6.01-Mb length. Sequence annotation predicted 5,413 open reading frames, of which 2,988 were homologous to genes in the other four sequenced P. fluorescens isolates (SBW25, WH6, Pf0-1 and Pf-5) and 1,137 were unique to GcM5-1A. Phylogenetic studies and genome comparison revealed that GcM5-1A is more closely related to SBW25 and WH6 isolates than to Pf0-1 and Pf-5 isolates. Towards study of pathogenesis, we identified 79 candidate virulence factors in the genome of GcM5-1A, including the Alg, Fl, Waa gene families, and genes coding the major pathogenic protein fliC. In addition, genes for a complete T3SS system were identified in the genome of GcM5-1A. Such systems have proved to play a critical role in subverting and colonizing the host organisms of many gram-negative pathogenic bacteria. Although the functions of the candidate virulence factors need yet to be deciphered experimentally, the availability of this genome provides a basic platform to obtain informative clues to be addressed in future studies by the pine wilt disease research community.
State estimation from high-dimensional data

It is implicit in traditional discussions of linear or nonlinear state estimation filters that there is no relation specified between the dimension of the state and the observation vector dimension. If anything though, the state would often be thought to have higher dimension. But increasingly in practice problems are arising where the reverse is the case. In this paper we show that state estimation filters, such as the Kalman filter undergo a remarkable simplification in structure and computation when the observation dimension is much larger than the state dimension. Both linear and nonlinear cases (including point processes) are discussed.
Static Analysis of Value-passing Process Calculi (extended Abstract)

Standard approaches to providing a semantics for value passing process calculi involve an expansion into a basic calculus which only involves pure synchroni-sation. When the semantics is intended to provide a basis for static analysis of properties of the values, this expansion leads to an unacceptable loss of information. In this paper we present a model of value passing process calculi based on synchronisation trees which gives a direct treatment of value passing. We present an abstract interpretation which discovers the same information about programs as Schreiber's ow analysis.