Miracle-dz/UniFAR-FTUs huggingface dataset:
Differential transcription of virulence genes in Aggregatibacter actinomycetemcomitans serotypes

Background Aggregatibacter actinomycetemcomitans serotypes are clearly associated with periodontitis or health, which suggests distinct strategies for survival within the host. Objective We investigated the transcription profile of virulence-associated genes in A. actinomycetemcomitans serotype b (JP2 and SUNY 465) strains associated with disease and serotype a (ATCC 29523) strain associated with health. Design Bacteria were co-cultured with immortalized gingival epithelial cells (OBA-9). The adhesion efficiency after 2 hours and the relative transcription of 13 genes were evaluated after 2 and 24 hours of interaction. Results All strains were able to adhere to OBA-9, and this contact induced transcription of pgA for polysaccharide biosynthesis in all tested strains. Genes encoding virulence factors as Omp29, Omp100, leukotoxin, and CagE (apoptotic protein) were more transcribed by serotype b strains than by serotype a. ltxA and omp29, encoding the leukotoxin and the highly antigenic Omp29, were induced in serotype b by interaction with epithelial cells. Factors related to colonization (aae, flp, apaH, and pgA) and cdtB were upregulated in serotype a strain after prolonged interaction with OBA-9. Conclusion Genes relevant for surface colonization and interaction with the immune system are regulated differently among the strains, which may help explaining their differences in association with disease.
Responsibility Analysis for Lineages of Conjunctive Queries with Inequalities

This paper investigates the problem of efficiently computing responsibility for lineages of conjunctive queries with inequalities on databases. We classify the lineages of a class of queries with inequalities, called IQ queries, into path and composite lineages. We first compile path lineages into lineage graphs and transform lineage graphs into matrices. Then we reduce the problem of computing responsibility for path lineages to the shortest path problem, which can be solved by the dynamic programming algorithm in PTIME. We further prove composite lineages can be decomposed into path lineages for computing responsibility. Thus, our first main result shows it is in PTIME to compute responsibility for lineages of IQ queries. We generalize the previous results on dichotomy of responsibility analysis for lineages of conjunctive queries with equalities, now in the presence of inequalities. After decomposing composite lineages into path lineages, the data population needed for computing responsibility decreases more than one order of magnitude. Thus, our algorithm can efficiently compute responsibility for composite lineages. In order to compute responsibility for lineages in general, we introduce a greedy algorithm, consisting of a reduction to the set cover problem. Finally, we demonstrate the benefits of the proposed algorithms with extensive experimental results.
El valor subjetivo del tiempo de viaje de los estudiantes universitarios cuando las preferencias son heterogéneas

En este trabajo se analiza la sensibilidad de los valores subjetivos del tiempo de viaje (VSTV) a los supuestos adoptados sobre las preferencias de los estudiantes. Para ello se estiman modelos de eleccion discreta que permiten captar la heterogeneidad de las preferencias de los estudiantes por el tiempo de viaje introduciendo tanto interacciones entre caracteristicas observadas de los individuos y atributos de los modos de transporte como parametros aleatorios. Los resultados muestran que una parte de la variacion del VSTV viene explicada por el sexo de los viajeros, mientras que la variacion restante es de caracter aleatorio. La evidencia empirica sugiere, ademas, que los VSTV tienden a subestimarse cuando se impone homogeneidad de las preferencias. Sin embargo, de la discusion teorica de los modelos y de la evidencia empirica existente se desprende que este resultado no es general.
Communication Security in Mobile Ubiquitous Systems

Security in ubiquitous computing gains special importance, because there are much more mobile devices interacting via wireless connection with each other. Other challenges are the limitations given due to the tiny sizes of various devices and also the limited power resources, which affect especially cryptographic computations. In this paper we will look at the problems arising in environments with mobile devices considering the security in communication, discuss the methods, how they were applied in wired systems and the problems arising when trying to transfer them directly to mobile systems. Furthermore, we present methods for achieving similar security in these mobile environments.
Deep Cascaded Regression for Face Alignment

We propose a novel cascaded regression framework for face alignment based on a deep convolutional neural network (CNN). In most existing cascaded regression methods, the shape-indexed features are either obtained by hand-crafted visual descriptors or by leaning from the shallow models. This setting may be suboptimal for the face alignment task. To solve this problem, we propose an end-to-end CNN architecture to learn highly discriminative shape-indexed features. First, our deep architecture encodes the image into high-level feature maps in the same size of the image via three main operations: convolution, pooling and deconvolution. Then, we propose "Shape-Indexed Pooling" to extract the deep features from these high level descriptors. We refine the shape via sequential regressions by using the deep shape-indexed features, which demonstrates outstanding performance. We also propose to learn the probability mask for each landmark that can be used to choose the initialization from the shape space. Extensive evaluations conducted on several benchmark datasets demonstrate that the proposed deep framework shows significant improvement over the state-of-the-art methods.
Generating Referring Expressions with OWL2

The task of generating referring expressions, an important subtask of Natural Language Generation is to generate phrases that uniquely identify do- main entities. Until recently, many GRE algorithms were developed using only simple and essentially home-made formalisms. Following the fast development of ontology-based systems, reinterpretations of GRE in terms of description logic have been studied. However, the quantifiers generated are still limited, not ex- ceeding the works covered by existing GRE approaches. In this paper, we propose an DL-based approach to GRE that exploits the full power of OWL2 to generate referring expressions that goes beyond the expressivity of previous GRE algo- rithms. The potential of DL reasoning in GRE is also discussed.
Coupling Availability and Efficiency for Aspect Oriented Runtime Weaving Systems

Performance and availability are two critical requirements of today’s systems. Current dynamic AOP approaches have addressed the performance issue from one specific dimension: the performance of code after the weaving process. Other performance factors may have a great impact on overall system performance. This includes performance of the weaving process itself and also system availability in single and multithread environment. In this paper, we present Dynamic Aspect C++ (DAC++), a new runtime aspect weaving system that addresses the performance and availability issues in an integrated approach. By addressing the following issues we increase system availability for runtime aspect weaving: We propose a finergrained of atomic weaving, we introduce two new efficient aspect-weaving techniques and we support multithreading. The scope of performance impact has been extended to include a more general evaluation of the overall system performance. This includes the performance of both the woven product and the weaving/unweaving time. The synergy of these two contributions, increasing availability and overall performance consideration, led to runtime weaving systems of better throughput, response time, and accessibility to resources. General Terms Languages, Performance, Design
Fisher information as a performance metric for locally optimum processing

For a known weak signal in additive white noise, the asymptotic performance of a locally optimum processor (LOP) is shown to be given by the Fisher information (FI) of a standardized even probability density function (PDF) of noise in three cases: (i) the maximum signal-tonoise ratio (SNR) gain for a periodic signal; (ii) the optimal asymptotic relative efficiency (ARE) for signal detection; (iii) the best cross-correlation gain (CG) for signal transmission. The minimal FI is unity, corresponding to a Gaussian PDF, whereas the FI is certainly larger than unity for any non-Gaussian PDFs. In the sense of a realizable LOP, it is found that the dichotomous noise PDF possesses an infinite FI for known weak signals perfectly processed by the corresponding LOP. The significance of FI lies in that it provides a upper bound for the performance of locally optimum processing.
Majorana Neutrinos and their Electromagnetic Properties

To help develop a picture of Majorana neutrinos, we study their electromagnetic properties. We show that CPT invariance forbids a Majorana neutrino from having a magnetic or electric dipole moment. Then, by considering the process . gamma --> nu.nu-bar, we find the most general expression for the matrix element of the electromagnetic current of a Majorana neutrino. The result is verified in a way which leads us to explore the behavior under parity of such a particle. Next, we see how electromagnetic properties which follow from one-loop diagrams conform to our general results. Finally, we show how the striking electromagnetic differences between Majorana and Dirac neutrinos can become invisible as the neutrino mass goes to zero.
Hetereogeneity in Neuronal Intrinsic Properties: A Possible Mechanism for Hub-Like Properties of the Rat Anterior Cingulate Cortex during Network Activity

Abstract The anterior cingulate cortex (ACC) is vital for a range of brain functions requiring cognitive control and has highly divergent inputs and outputs, thus manifesting as a hub in connectomic analyses. Studies show diverse functional interactions within the ACC are associated with network oscillations in the β (20–30 Hz) and γ (30-80 Hz) frequency range. Oscillations permit dynamic routing of information within cortex, a function that depends on bandpass filter–like behavior to selectively respond to specific inputs. However, a putative hub region such as ACC needs to be able to combine inputs from multiple sources rather than select a single input at the expense of others. To address this potential functional dichotomy, we modeled local ACC network dynamics in the rat in vitro. Modal peak oscillation frequencies in the β- and γ-frequency band corresponded to GABAAergic synaptic kinetics as seen in other regions; however, the intrinsic properties of ACC principal neurons were highly diverse. Computational modeling predicted that this neuronal response diversity broadened the bandwidth for filtering rhythmic inputs and supported combination—rather than selection—of different frequencies within the canonical γ and β electroencephalograph bands. These findings suggest that oscillating neuronal populations can support either response selection (routing) or combination, depending on the interplay between the kinetics of synaptic inhibition and the degree of heterogeneity of principal cell intrinsic conductances.
Distinct values of design in organisational culture

This paper explores attributes of design derived from previous research. It investigates an identified set of attributes by subjecting them to an empirical analysis. Case studies conducted among academics and consultants, in the fields of management and design are aimed at establishing what is the perceived emotional investment in these attributes. By combining the evidence gathered from statistical analysis of questionnaires and content analysis of discussions within focus groups, we have identified a potentially distinct group of values shared by designers. These include values concerning: visual thinking, intuitiveness, aesthetics, artistic creativity, emotions, multisensoriality, sustainability of solutions and tacit knowledge. Although the results are not conclusive they provide an insight into which design-derived values might contribute to organizational cultures.
Head Tracking Based on Histogram and Shape Model

A new model-based method is presented for real-time tracking a person ’s head in gray image sequences. Multidimensional receptive field histogram and ellipse shape model is used to describe the tracking object (head). A robust nonparametric technique called mean shift algorithm is adopted to estimate the most probable head location in the current frame, in which histogram matching is used during mean shift iteration. In order to locate the head more accurately and obtain the best scale size of the head, a local search for maximizing the gradient magnitude around the boundary of the elliptical head is preformed after mean shift estimation. It is demonstrated to be a real-time tracker and robustness to scale variation, arbitrary camera movement, partocclusion and so on, for several image sequences.
Implementation of Distributed Algorithm with Network Coding for Multicast Network

In today's practical networks, end-to-end information delivery is performed by routing. Network coding generalizes routing by allowing a node to generate output data by mixing (i.e., computing certain functions of) its received data. Network coding techniques are used to find the minimum cost in given network. In wire line network, solving for the optimal coding subgraphs in network coding is equivalent to finding the optimal routing scheme in a multi-commodity flow problem. Multicast is an important factor for the communication in wireless network. This problem is also known as NP-complete. This paper focuses on the solution for the above problem and provides the analytical framework as well as distributed algorithm in multicast session. A set of node based distributed algorithm are designed at sources node and virtual at intermediate node. Keyword-Network coding, multi-commodity flow problem, distributed algorithm, wireless networks.
Distinctive Tropical Forest Variants Have Unique Soil Microbial Communities, But Not Always Low Microbial Diversity

There has been little study of whether different variants of tropical rainforest have distinct soil microbial communities and levels of diversity. We compared bacterial and fungal community composition and diversity between primary mixed dipterocarp, secondary mixed dipterocarp, white sand heath, inland heath, and peat swamp forests in Brunei Darussalam, Northwest Borneo by analyzing Illumina Miseq sequence data of 16S rRNA gene and ITS1 region. We hypothesized that white sand heath, inland heath and peat swamp forests would show lower microbial diversity and relatively distinct microbial communities (compared to MDF primary and secondary forests) due to their distinctive environments. We found that soil properties together with bacterial and fungal communities varied significantly between forest types. Alpha and beta-diversity of bacteria was highest in secondary dipterocarp and white sand heath forests. Also, bacterial alpha diversity was strongly structured by pH, adding another instance of this widespread pattern in nature. The alpha diversity of fungi was equally high in all forest types except peat swamp forest, although fungal beta-diversity was highest in primary and secondary mixed dipterocarp forests. The relative abundance of ectomycorrhizal (EcM) fungi varied significantly between forest types, with highest relative abundance observed in MDF primary forest. Overall, our results suggest that the soil bacterial and fungal communities in these forest types are to a certain extent predictable and structured by soil properties, but that diversity is not determined by how distinctive the conditions are. This contrasts with the diversity patterns seen in rainforest trees, where distinctive soil conditions have consistently lower tree diversity.
Channel tracking scheme using block-based kalman algorithm for MIMO wireless systems

This paper presents a novel block-based channel tracking scheme using the Kalman algorithm for MIMO wireless systems that operate in a wideband frequency selective fading Doppler environment. The block-based concept is employed to allow group of received samples and detected symbols to be jointly considered in order to minimise the rate of tracking within a data frame. Preliminary results show that the performance of the proposed 'estimator-tracker' is bounded by the time-varying characteristic of different Doppler channels and the choice of block-length used within the Kalman decision feedback filtering where trade-off must be achieved. The performances and analyses of the proposed 'estimator-tracker' are provided in conjunction with its BER results for MIMO system at different mobile velocities.
Overnight park visitor constraints to participation and interests potentially served in interpretive programs

Interpretive programs are offered by parks and public lands to inspire the visitors to further appreciate the heritage resources presented and protected within parks. These programs and services add an additional dimension to park visits, may increase enjoyment, provide visitors with a richer understanding of heritage resources, create opportunities to influence visitor behaviors in ways helpful to managers, and possibly provide motivations for visitors to extend their stay. Any potential desired outcome resulting from the strategic use of interpretative programs requires participants, and the broader the audience, the wider the influence. Consequently, a study of the variety of reasons that people are attentive or not to interpretive services could provide ways to modify programming in terms of publicizing, delivery, and content. Specifically, this study explored the types of constraints to attending interpretive (or ranger-led) programs to that visitors experience. Visitors who attended interpretive programming and those who do not were asked to describe their perceptions about the value of interpretive programming, the types of people who attend interpretive programming, how content is presented, and the topics of the programs. Qualitative interviews and demographic surveys were conducted with 57 campers at three different developed campgrounds at state parks in the southern Appalachian Mountains. Using a pragmatic approach, the themes that developed included the role of unstructured time, information availability, lifestages, environmental issues programming, and competing activities. Through increased awareness of constraints to participation, interpreters should be able to troubleshoot existing programs, schedule programs at optimal times and locations, and Interpretation Constraints iii publicize programs more effectively. Through this process, interpreters could increase their ability to meet park management objectives.
The REFLECT project in Norway: interactive pedagogy using email

Abstract Given the constraints in teacher education at the Norwegian University of Science and Technology, (NTNU), one-to-one interaction via email between the student teacher out on teaching practice and a professor or a university supervisor is a favoured approach. The case studies from NTNU describe how student teachers learn to reflect over episodes from the classroom in a structured interaction with their supervisors. The cases formed part of the European REFLECT project. The article also discusses the processes of reflection and preparation to use free writing over email as a way of opening up resources. We have connected all these analyses, interpretations and the more overarching ideas to build on an interactional principle (Hoel, 1995, p. 13). In this project, the email messages had a double function. First, the writing in itself was intended as a tool for the student teacher's own thinking. Secondly, email is intended to enable communication between the student teacher and their tutors. On the b.
Semisupervised Dimensionality Reduction With Pairwise Constraints for Hyperspectral Image Classification

Dimensionality reduction is an important task in the analysis of hyperspectral image data. While traditional dimensionality reduction methods use class labels as prior information, this letter presents a general semisupervised dimensionality reduction framework for hyperspectral image classification based on new prior information, i.e., pairwise constraints which specify whether a pair of examples belongs to the same class or not. The proposed semisupervised dimensionality reduction framework contains two terms: 1) a discrimination term that assesses the separability between classes; and 2) a regularization term that characterizes some property of the original data set. Furthermore, a novel semisupervised dimensionality reduction method is derived from the framework based on sparse representation. Experimental results on two hyperspectral image data sets show that the proposed algorithms are remarkably effective in comparison to traditional dimensionality reduction methods.
The impact of enterprise architecture's absence in e-Government development: The Greek case

Enterprise Architecture (EA) is a dynamically evolved area, suggesting frameworks and methods to handle complexity and change in an enterprise or in a public agency. Major international e-Strategies follow EA frameworks, which oblige distributed authorities to design and implement their e-Government projects under specific standards and directions. In Europe, European States implement their e-Strategies usually according to European political objectives, directives and frameworks, but not under a common EA. Some European countries have developed their own EAs, while others limited their efforts in aligning their strategies to the European one. In this paper we present the EAs followed by major e-Strategies, together with their recent outcomes. On the contrary, we present e-Government implementation in Greece, where no EA was followed. We use some tenders' data in order to present the impact of EA's absence in project design, implementation and sustainability.
Disfluency and speech recognition profile factors

This paper reports on work bringing together disfluency coding carried out by Lickley [7] and recognition work carried out as part of the ERF project (Bard, Thompson & Isard, [2]) at Edinburgh University. A set of factors are investigated which characterise the behaviour of the ASR during recognition based on an analysis of the resulting word lattice. These factors can be grouped as: Entropy Factors ‐ the entropy of the acoustic and language model likelihoods, within the word lattice, over a 10 ms frame, and, Arc Factors ‐ the number of non-unique and unique arcs in the word lattice in any given 10ms time frame, together with the variance of start and end times of these arcs, and the number of arcs starting or ending in the frame. The values of all factors were used to train a simple CART model. The CART model was used to predict: recognition failure, interruption point location (the point where a disfluency begins), and whether the location was in a repair or a reparandum. The entropy of the language model values contributed most to the models prediction of recognition failure, and whether a frame was in a repair or reparandum. In contrast, the number of unique word hypotheses contributed most to the successful prediction of a frame being close to an interruption point.