Miracle-dz/UniFAR-FTUs huggingface dataset:
ANGEL: Optimal Configuration for High Available Service Composition

With the fast development of Internet and rapid acceptance of Web Service technology, more and more service resources have emerged. Service composition which integrates the functionalities of different services is a promising technique for developing applications across multiple organizations. However, in a distributed, dynamic and autonomous environment, such as a service composition-based system, the availability and reliability are big concerns in terms of nonfunctional properties. In this paper, we propose a novel service composition method, ANGEL, with the target of the improvement of system availability. We adopt redundant mechanism in ANGEL and propose a model to improve the property of the service availability. We model the multiple services selection problem based on redundant mechanism as a nonlinear mixed integer programming problem and therefore, we propose two heuristic algorithms to select multiple feasible services that have the same functions, but with better availability. In order to maintain the availability of composite services, we further introduce monitor and detection mechanisms. Through the comprehensive experiments, we find that our proposed techniques can indeed achieve better availability as expected.
Distributed Convex Optimization with Inequality Constraints over Time-Varying Unbalanced Digraphs

This paper considers a distributed convex optimization problem with inequality constraints over time-varying unbalanced digraphs, where the cost function is a sum of local objective functions, and each node of the graph only knows its local objective and inequality constraints. Although there is a vast body of literature on distributed optimization, most of them require the graph to be balanced, which is quite restrictive and not necessary. To solve it, this work proposes a novel idea of using the epigraph form of the constrained optimization, which can be easily used to study time-varying unbalanced digraphs. Under local communications, a simple iterative algorithm is then designed for each node. We prove that if the graph is uniformly jointly strongly connected, each node asymptotically converges to some common optimal solution.
Can crowdsensing beat dynamic cell-ID?

In this work we investigate the limits of crowdsensing in discovering the mapping of mobile network Cell-IDs to geographic locations. We employ original large-scale mobility simulations, derived using the NRC-Lausanne dataset, to determine the fraction of cells visited by a fixed number of users over a time interval. This is vital to judge the ability of crowdsensing to rapidly update an inadequate, malfunctioning or obsolete Cell-ID database, thus preventing mechanisms such as Dynamic Cell-ID from obfuscating the network. We show that crowdsensing is quite a powerful tool, with for example only 25% more users than cells sufficing to scan 99% of the network over a day.
The Informational Role of the Minimum Bid Increment Policy in a Repeated Simultaneous Auction with Synergies between Items

The informational role of the minimum bid increment (MBI) policy in a simultaneous repeated auction is analyzed when there exists synergies between pairs of items and the extent of such synergies is private information. The observed behaviour in the FCC auction namely that each bidder lowers the extent by which he shades his valuation over time is modelled by using a myopic strategy modified for the winning rule that is appropriate for repetitive simultaneous bidding. The seller is better off both in terms of expected revenue and the price obtained for the item using a MBI policy rather than the policy of announcing a reservation (ask) price at the start of each round. A given MBI yields the seller a higher expected revenue when synergies are present. The observed behavior of jump bids, with the size of the equilibrium jump increasing in the extent of synergy, is rationalized by modelling synergies as superadditivity of bidders' common value estimates. JEL Classification: D44, D82.
In situ data processing for extreme-scale computing

The U.S. Department of Energy established leadership-computing facilities in 2004 to provide scientists with capability computing for high-profile science. Since inception, the system capacity has grown from 14 TF to 1.8 PF, an increase of more than a factor of 100, and it will increase by another factor of 100 in the next five years. This growth, along with computing policies that enable users to run at scale for long periods, has allowed scientists to write unprecedented amounts of data to the file system. At the same time, the effective speed of the I/O system (time to write full system memory to the file system) has decreased, going from 350 seconds on ASCI Purple (49 TB at 140 GB/s) to 1500 seconds on Jaguar (300 TB at 200 GB/s). Because future systems will further intensify this imbalance, we need to extend the definition of I/O to include that of I/O pipelines, which blend together self-describing file formats, staging methods with visualization and analysis “plugins,” and new techniques to multiplex outputs using a novel service-oriented architecture approach—all in an easy-to-use I/O componentization framework that can add resiliency to large-scale calculations. Our approach to this has been via the community-created ADIOS system, which is driven by many of the leading-edge application teams and the top I/O researchers.
ABSUM : a Knowledge-Based Abstractive

ive summarization is one of the main goals of text summarization research, but also one of its greatest challenges. The authors of a recent literature review (Lloret and Palomar 2012) even conclude that “abstractive paradigms [. ] will become one of the main challenges to solve” in text summarization. In building an abstractive summarization system, however, it is often hard to imagine where to begin and how to proceed in order to incorporate some kind of semantic understanding of the source documents to create a shorter text that contains only the relevant elements for the task at hand. This paper introduces the Knowledge-Based Abstractive Summarization (K-BABS) approach, to address various summarization tasks and domains in a flexible and scalable way. Its architecture relies on an analysis of the source documents and on a task blueprint. This resource describes how to transform the representation of the text into natural language for the summary. It implicitly encodes knowledge about the summarization task into rules applied by the summarization system. The task blueprint, which can be constructed automatically, semiautomatically, or manually, guides every step of the summarization process. © 2005 Association for Computational Linguistics Computational Linguistics Volume xx, Number xx Annotated Parse Trees
PAX6 Regulates Melanogenesis in the Retinal Pigmented Epithelium through Feed-Forward Regulatory Interactions with MITF

During organogenesis, PAX6 is required for establishment of various progenitor subtypes within the central nervous system, eye and pancreas. PAX6 expression is maintained in a variety of cell types within each organ, although its role in each lineage and how it acquires cell-specific activity remain elusive. Herein, we aimed to determine the roles and the hierarchical organization of the PAX6-dependent gene regulatory network during the differentiation of the retinal pigmented epithelium (RPE). Somatic mutagenesis of Pax6 in the differentiating RPE revealed that PAX6 functions in a feed-forward regulatory loop with MITF during onset of melanogenesis. PAX6 both controls the expression of an RPE isoform of Mitf and synergizes with MITF to activate expression of genes involved in pigment biogenesis. This study exemplifies how one kernel gene pivotal in organ formation accomplishes a lineage-specific role during terminal differentiation of a single lineage.
Using the Fisher-Bingham distribution in stochastic models for protein structure

Protein structure prediction is at present an unsolved problem, partly due to lack of a suitable energy function and partly due to the high number of conformational parameters involved. Many protein structure prediction methods therefore use simplified models (Buchete et al., 2004). A popular approach is to represent a protein by its C atoms only, ie. by its C trace. Thus a protein can be regarded as a sequence of edges in . To a first approximation the length of each edge is constant (in practice one unit of length is about 3.8 Å). The angles between successive edges determine the shape of the protein. Here we introduce a probabilistic model of the geometry of a random protein’s C trace. Such a model has many applications, like for example steering the proposal of protein conformations in a Markov Chain Monte Carlo (MCMC) simulation. The model is based on machine learning techniques, and is trained from a set of representative protein structures. Central to the model is the Fisher-Bingham distribution on the 3D sphere (Kent, 1982), an analogue of the bivariate normal equation in the plane.
Web Page Prediction by Clustering and Integrated Distance Measure

The tremendous progress of the internet and the World Wide Web in the recent era has emphasized the requirement for reducing the latency at the client or the user end. In general, caching and prefetching techniques are used to reduce the delay experienced by the user while waiting to get the web page from the remote web server. The present paper attempts to solve the problem of predicting the next page to be accessed by the user based on the mining of web server logs that maintains the information of users who access the web site. The prediction of next page to be visited by the user may be pre fetched by the browser which in turn reduces the latency for user. Thus analyzing user's past behavior to predict the future web pages to be navigated by the user is of great importance. The proposed model yields good prediction accuracy compared to the existing methods like Markov model, association rule, ANN etc.
The Identification Of IT Project Manager Competencies: A Grounded Theory Approach

A good project manager needs to demonstrate a range of competencies during the course of an IT project. The eventual success of a project may be at risk if certain competences are either not present or not applied appropriately. Utilising the grounded theory methodology and behavioural event interviews this research seeks to identify the key competencies of a project manager when dealing with critical project situations. Interviews with 10 IT project managers with varying levels of experience uncovered a number of competencies, some of which have not be reported elsewhere or are potentially more complex than might have been previously considered. Being able to manage multiple modes of communication emerged as an important part of the project managers’ role and those that communicated the most, appeared to manage their projects in a more positive manner overall. Knowing when to involve higher authorities in order to get cooperation from others also emerged as an important issue. Finally, it was observed that inexperienced project managers were just as likely to demonstrate competencies as those with extensive experience.
Spaceflight Effects on Cytochrome P450 Content in Mouse Liver

Hard conditions of long-term manned spaceflight can affect functions of many biological systems including a system of drug metabolism. The cytochrome P450 (CYP) superfamily plays a key role in the drug metabolism. In this study we examined the hepatic content of some P450 isoforms in mice exposed to 30 days of space flight and microgravity. The CYP content was established by the mass-spectrometric method of selected reaction monitoring (SRM). Significant changes in the CYP2C29, CYP2E1 and CYP1A2 contents were detected in mice of the flight group compared to the ground control group. Within seven days after landing and corresponding recovery period changes in the content of CYP2C29 and CYP1A2 returned to the control level, while the CYP2E1 level remained elevated. The induction of enzyme observed in the mice in the conditions of the spaceflight could lead to an accelerated biotransformation and change in efficiency of pharmacological agents, metabolizing by corresponding CYP isoforms. Such possibility of an individual pharmacological response to medication during long-term spaceflights and early period of postflight adaptation should be taken into account in space medicine.
Teacher: An Important but Less Recognized Actor of School Curriculum Development in Nepal

Curriculum development is considered as a key factor in the process of educational transformation. In this process, teachers can play multiple roles such as translator of learning objectives into outcome, mediator between curriculum and students and so on. On the other hand, curriculum experts contribute to making a need assessment and contents development on the basis of educational theories and principles. But, contemporary literatures point gaps in exchange of knowledge and expertise between these two important actors of school curriculum development. On this backdrop, this study aims to explore what rolesteachers can perform and how their rolesare acknowledged in the curriculum development. Following social constructivist worldview, this study adopted qualitative approach with the scientific tool of in-depth interviewsand purposive sampling design. This study reveals teacher’s contribution inidentification of practical educational needsin the context of changing overall societal needs.Moreover, the teacherscan bridge existing gaps between national educational goals, social needs and the interest of people. But the current school curriculum development process takes place at the top where curriculum experts play decisive role. These experts seek school teacher’s contribution only at the review phase of curriculum development process which is not enough to incorporate teacher’s expertise. In this respect, teachers will be able to view curriculum not in terms of content to be covered, but as a transformative process. Rather, this looks like just maintaining a formality. The attitudinal and procedural process constrain in recognition and involvement of teacher in curriculum development process. Thus, school curriculum has missed opportunity to reflect local need and increase ownership of the teachers. This paper argues for the recognition of teacher’s role as a critical practitioner and change agent, and urges to provide sufficient space to incorporate their real-life experiences in school curriculum.
Robust Outlier Detection and Saliency Features Estimation in Point Cloud Data

This paper investigates outlier detection and reliable local saliency features (e.g. normal) estimation in point cloud data. We propose two highly robust outlier detection algorithms that are able to identify outliers and are efficient for reliable local saliency features estimation in noisy point cloud data. One is based on a univariate robust z-score and the other on a multivariate Mahalanobis type robust distance. They combine the ideas of orthogonal distance and local surface points consistency to get Maximum Consistency with Minimum Distance (MCMD). Experimental results are presented to show the algorithms' performance and are compared with other existing methods for synthetic and real datasets through segmentation for planar and non-planar surfaces of complex objects. The algorithms give more accurate and robust results, are fast and have the potential for local surface reconstruction, fitting, registration and covariance statistics based point cloud processing.
Rho3 of Saccharomyces cerevisiae, Which Regulates the Actin Cytoskeleton and Exocytosis, Is a GTPase Which Interacts with Myo2 and Exo70

ABSTRACT The Rho3 protein plays a critical role in the budding yeastSaccharomyces cerevisiae by directing proper cell growth. Rho3 appears to influence cell growth by regulating polarized secretion and the actin cytoskeleton, since rho3 mutants exhibit large rounded cells with an aberrant actin cytoskeleton. To gain insights into how Rho3 influences these events, we have carried out a yeast two-hybrid screen using an S. cerevisiae cDNA library to identify proteins interacting with Rho3. Two proteins, Exo70 and Myo2, were identified in this screen. Interactions with these two proteins are greatly reduced or abolished when mutations are introduced into the Rho3 effector domain. In addition, a type of mutation known to produce dominant negative mutants of Rho proteins abolished the interaction with both of these proteins. In contrast, Rho3 did not interact with protein kinase C (Pkc1), an effector of another Rho family protein, Rho1, nor did Rho1 interact with Exo70 or Myo2. Rho3 did interact with Bni1, another effector of Rho1, but less efficiently than with Rho1. The interaction between Rho3 and Exo70 and between Rho3 and Myo2 was also demonstrated with purified proteins. The interaction between Exo70 and Rho3 in vitro was dependent on the presence of GTP, since Rho3 complexed with guanosine 5′-O-(3-thiotriphosphate) interacted more efficiently with Exo70 than Rho3 complexed with guanosine 5′-O-(3-thiodiphosphate). Overlapping subcellular localization of the Rho3 and Exo70 proteins was demonstrated by indirect immunofluorescence. In addition, patterns of localization of both Exo70 and Rho3 were altered when a dominant active allele ofRHO3, RHO3E129,A131 , which causes a morphological abnormality, was expressed. These results provide a direct molecular basis for the action of Rho3 on exocytosis and the actin cytoskeleton.
An Evaluation of Gene Selection Methods for Multi-class Microarray Data Classification

The fundamental power of microarrays lies in the ability to conduct parallel surveys of gene expression patterns for tens of thousands of genes across a wide range of cellular responses, phenotypes and conditions. Thus microarray data contain an overwhelming number of genes relative to the number of samples, presenting challenges for meaningful pattern discovery. This paper provides a comparative study of gene selection methods for multi-class classification of microarray data. We compare several feature ranking techniques, including new variants of correlation coefficients, and Support Vector Machine (SVM) method based on Recursive Feature Elimination (RFE). The results show that feature selection methods improve SVM classification accuracy in different kernel settings. The performance of feature selection techniques is problem-dependent. SVM-RFE shows an excellent performance in general, but often gives lower accuracy than correlation coefficients in low dimensions.
EXPLOITING TOPIC PRAGMATICS FOR NEW EVENT DETECTION IN TDT-2004

TDT-2004 marked Stottler Henke’s second year of participation in the New Event Detection (NED) track of the Topic Detection and Tracking (TDT) evaluations. Our official entry this year consisted of three “pragmatics-based” classifiers operating in a majority voting framework. The system performed well, achieving by small margins the best optimized topic- and storyweighted CFSD scores for participating NED systems. We again validated the hypothesis that ensemble collections of classifiers can outperform the individual classifiers that compose them. Performance over the new TDT5 corpus was worse relative to previous corpora and overall accuracy within the NED community remains significantly below operationally desirable levels. We present a brief summary of our second year approach and a preliminary characterization of our performance results based on the experimental runs submitted to the TDT-2004 evaluation.
Software Product Lines Approach in Enterprise System Development

Enterprise software is an untapped area for software product lines (SPL) approach. Our current understanding of enterprise SPL is as follows. The enterprise SPL is based upon an application centric architecture, which manages variability of platform and non-functional requirements, and achieves variability management for functional requirements in an application layer. NRI has been executing this approach through two projects, (I) development of semi made-to-order package software for the retail chains and (II) restructuring of enterprise systems owned by Seven & i Holdings, the biggest conglomerate of retail industry in Japan. This paper mainly describes what application centric architecture is and how this approach differs from others with lessons learned for the last five years.
Informal household preparedness: methodological approaches to everyday practices

Abstract Despite increasing attention to individuals’ everyday lives in the literature on risk, few studies investigate household preparedness within the everyday life context. Preparedness is most often regarded as a predefined set of capacities for dealing with emergencies. This article presents methodological approaches for studying what I suggest calling informal preparedness activities that are performed as part of daily life in households. Starting with the assumption that everyday life is enacted through culturally and socially shared practices, it is argued that preparedness is interwoven into these practices. Contrary to studying preparedness as the degree to which households are aware of and act according to a formal definition of preparedness, informal household preparedness focuses on preparedness as embedded in the routinised practices that make up everyday life. The study of informal household preparedness is based on three methodological approaches that explore these practices: (i) Performance of everyday practices, where interviews that focus on performance ask questions about what practitioners actually do; (ii) materiality, where walk-alongs are used to connect performance interviews to the material surroundings; and (iii) visualisation, where the material aspects of informal preparedness are documented. These approaches were carried out in a study of Norwegian households’ management of and preparedness for electricity and Information and Communication Technology (ICT) infrastructure breakdowns. Addressing informal and formal preparedness activities expands our understanding of household preparedness and should help policy makers recognise the active role of households and their actual resources and constraints in future preparedness planning.
Effect of temporal perspective on subjective confidence.

Four studies examined whether people tend to lose confidence in their prospects for success the closer they are to the "moment of truth. " Study 1 found that students think they will do better on their midterm exams when asked on the 1st day of class than when asked on the day of the exam. Studies 2 and 4 replicated this finding under controlled conditions. Study 3 demonstrated that the same effect holds retrospectively: People are more confident that they would have performed well at a task long after the time to perform has passed. Data are presented indicating that these results stem from a tendency for people to feel more "accountable" for their assessments, and thus focus less on the causes of success and more on the causes of failure, as the time to perform approaches. Implications for the experience of regret are discussed.
Assessing the relationship between context, user preferences, and content in search behaviour

Searching information by using search engines and browsers is a tedious task for users. Navigational and informational search tasks are complicated by the fact that web servers always provide complete web pages and do not tailor their content to the user's current information need. In this paper, we present a proposal for the application of context-aware recommendation techniques to simulate human decision making when selecting elements of content to be included in an answer to an information need. As a first step towards live generation of content, we present results on our experimental study to capture decision criteria for this selection problem that web users apply in choosing content. These preferences could then later be formalized in terms of a knowledge-based context-aware and personalized model for recommending content during information search.