Miracle-dz/UniFAR-FTUs huggingface dataset:
Prototyping QoS based architecture for power plant control applications

The goal of the project is to gain experience on QoS (quality of service) based distributed system for EDF's power control applications. EDF is the French power utility. QoS is related to time constraints in this case. We adopted a distributed system approach to build our execution platform. The first prototype uses a modified ChorusOS micro-kernel with a real-time inter-process communication facility based on an ATM network and supports a specific real-time Java Virtual Machine. Our second proposal attempts to build an equivalent architecture using off-the-shelf products. Reality constraints lead to a CoS (classification of service) based design. We show that there is no available off-the-shelf QoS or CoS based technology for real-time object oriented distributed applications.
ECONOMIC MODELS AND COINTEGRATING REGRESSIONS

Economic models often imply cointegration. This chapter illustrates how to derive cointegration restrictions from economic models. In order to derive cointegration restrictions, one must show that a linear combination of difference stationary random variables is stationary. This is often done by showing that a linear combination of difference stationary variables is a time independent function of a finite number of stationary random variables (see Proposition 2.2). For many economic models, Proposition 2.2 can be directly used to show coin-tegration. In some other models, one more step is necessary. There are cases in which economic models imply that a linear combination of difference stationary variables is a conditional expectation of a variable. For example, suppose that an economic model implies b y t = E(z t |I t), where z t can be shown to be a stationary random variable because of Proposition 272
The Generalized Web Surfer

Different models have been proposed for improving the results of Web search by taking into account the link structure of the Web. The PageRank algorithm models the behavior of a random surfer alternating between random jumps to new pages and following out links with equal probability. We propose to improve on PageRank by using an intelligent surfer that combines link structure and content to decide on its next transition. The intelligent surfer is guided by the textual authority of the web page. The textual authority gives a non-topical estimate of the intrinsic quality of a web page, and when combined with the link-based social authority gives a more complete and robust estimate of the document authoritativeness. Experiments on a number of queries indicate that our algorithm significantly outperforms PageRank algorithms in the human-rated quality of the pages returned while retaining the efficiency and topic-independence characteristics of PageRank.
The West European party system

Part 1 The development of the mass party: the origin of political parties, Joseph La Palombara and Myron Weiner the advent of plebiscitarian democracy, Max Weber caucus and branch, cadre parties and mass parties, Maurice Duverger the party of democratic integration, Sigmund Neumann the catchall party, Otto Kirchheimer parties in pluralism, Alessandro Pizzorno. Part 2 The stabilization of party systems: structuring the party system, Giovanni Sartori the "reach" of the party system, Hans Daalder cleavage structures, party systems and voter alignments, Seymour Martin Lipset and Stein Rokkan towards a generalized concept of "Verzuiling", Stein Rokkan the sociology of parties, Giovanni Sartori. Part 3 The transformation of party systems: persistence and change in western party systems, 1945-1969, Richard Rose and Derek W.Urwin electoral volatility in Western Europe, 1948-1977, Mogens N.Pedersen parameters of change, Peter Mair the transformation of Western European party systems, Steven B.Wolinetz models of change, Scott C.Flanagan and Russell J.Dalton the nature of value change, Ronald Inglehart dimensions of ideology in European party systems, Arend Lijphart from class-based to value-based politics, Ronald Inglehart. Part 4 Types of party system: the two-party system and the multi-party system, Maurice Duverger party systems and patterns of opposition, Robert A.Dahl types of party system, Jean Blondel the electoral balance, Stein Rokkan a typology of party systems, Giovanni Sartori.
Global identification of storage objects in network attached storage

Network attached disk storage is an independent Internet node and provides geographical distribution, mutual identification and exchange of storage objects. The paper describes a method for global identification of storage objects and a structure of object registry. For the identification word-wide unique identifiers are generated by double hash transformation based on the Advanced Encryption Standard (Rijndael) with no collisions.
Enhancing query retrieval efficiency using BGIT coding

Data compression techniques are used to optimize time and space while sending and retrieving data. In information retrieval, data compression techniques are used by Search engines to reduce the size of their indexes which will result in optimizing the speed and performance of retrieving relevant information. The goal of this research project is to propose some enhancements on search engines indexing using Bigram index term coding. Evaluation of the improvements on search-engine performance resulting from encoding the terms of its index is also conducted. Our experiments showed a good reduction in the size of index terms which contributes to the overall index size. It also showed a significant reduction of the number of comparisons made to process the user queries as a result of reducing the number of symbols representing each index term.
Insulin resistance and associated factors: a cross-sectional study of bank employees

OBJECTIVE: Insulin resistance is characterized by the failure of target cells to respond to normal levels of circulating insulin, and this condition is related to cardiovascular disease. This study sought to evaluate the prevalence of insulin resistance and its association with markers of metabolic abnormalities and metabolic syndrome in bank employees. METHODS: A cross-sectional study was performed on 498 working men and women aged ≥20 years old. The Homeostasis Model Assessment (HOMA-IR) was used to determine the presence of insulin resistance based on cut-off values of ≤2.71 for normal insulin levels and >2.71 for insulin resistance, as established for the adult Brazilian population. RESULTS: It was observed that the 52 (10.4%) overweight individuals with insulin resistance were 4.97 times (95%CI 1.31-18.83) more likely to have high HOMA-IR values than the normal-weight participants; among those who were obese, the likelihood increased to 17.87 (95%CI 4.36-73.21). Individuals with large waist circumferences were 3.27 times (95%CI 1.03-10.38) more likely to develop insulin resistance than those who were within normal parameters. The HOMA-IR values differed between subjects with and without metabolic syndrome, with values of 2.83±2.5 and 1.10±0.81 (p=0.001), respectively. The levels of insulin, ultrasensitive C-reactive protein and uric acid were also associated with insulin resistance. CONCLUSION: The prevalence of insulin resistance among bank employees is high, and insulin resistance is associated with and serves as a marker of metabolic syndrome. Cardiovascular disease and metabolic syndrome-associated metabolic abnormalities were observed, and insulin resistance may be a risk factor in this group of professionals.
Organizing the space and behavior of semantic models

Semantic models play an important role in cognitive science. These models use statistical learning to model word meanings from co-occurrences in text corpora. A wide variety of semantic models have been proposed, and the literature has typically emphasized situations in which one model outperforms another. However, because these models often vary with respect to multiple sub-processes (e.g., their normalization or dimensionality-reduction methods), it can be difficult to delineate which of these processes are responsible for observed performance differences. Furthermore, the fact that any two models may vary along multiple dimensions makes it difficult to understand where these models fall within the space of possible psychological theories. In this paper, we propose a general framework for organizing the space of semantic models. We then illustrate how this framework can be used to understand model comparisons in terms of individual manipulations along sub-processes. Using several artificial datasets we show how both representational structure and dimensionality-reduction influence a model's ability to pick up on different types of word relationships.
The quasiparticle band structure of zincblende and rocksalt ZnO

We present the quasiparticle band structure of ZnO in its zincblende (ZB) and rocksalt (RS) phases at the Γ point, calculated within the GW approximation. The effect of the p–d hybridization on the quasiparticle corrections to the band gap is discussed. We compare three systems, ZB-ZnO which shows strong p–d hybridization and has a direct band gap, RS-ZnO which is also hybridized but includes inversion symmetry and therefore has an indirect band gap, and ZB-ZnS which shows a weaker hybridization due to a change of the chemical species from oxygen to sulfur. The quasiparticle corrections are calculated with different numbers of valence electrons in the Zn pseudopotential. We find that the Zn20 + pseudopotential is essential for the adequate treatment of the exchange interaction in the self-energy. The calculated GW band gaps are 2.47 eV and 4.27 eV respectively, for the ZB and RS phases. The ZB-ZnO band gap is underestimated compared to the experimental value of 3.27 by ∼ 0.8 eV. The RS-ZnO band gap compares well with the experimental value of 4.5 eV. The underestimation for ZB-ZnO is correlated with the strong p–d hybridization. The GW band gap for ZnS is 3.57 eV, compared to the experimental value of 3.8 eV.
Empirical Analysis and Ranging Using Environment and Mobility Adaptive RSSI Filter for Patient Localization during Disaster Management

During emergency response to mass casualty disasters, one of the main logistic impediments faced by the On-site Organization Chief is to track the patients at the disaster site. We had proposed a new system based on a location aware wireless sensor network (WSN) to overcome these impediments and assist the responders in providing efficient emergency response. In this paper we have implemented a new ranging algorithm called Ranging using Environment and Mobility Adaptive RSSI (REMA) Filter which will provide the distance estimates and yield the real time localization of patients at the disaster site. We have conducted Ranging experiments both in indoor and outdoor environments and have built an offline database which is given as input for the REMA filter simulation. The output of REMA filter is given as input to the new position estimation algorithm currently being developed by us and the position estimation error is calculated using simulation. The REMA filter simulation results show the suitability of the algorithm for ranging during tracking of patients at the disaster site.
Past, Present, and Possibilities for the Future of the Pell Grant Program

An increase of over 100% in program expenditures for the Pell Grant program over a five year period of time, from $14.7 billion in the 2007–08 award year to $33.4 billion in the 2011–12 award year, places an otherwise popular program under scrutiny. This article considers the factors and options informing federal policy related to the Pell Grant program that are being considered to limit further growth of program costs, if not reduce them. To best understand the current context and pending options, I revisit the past of the Pell Grant program by first noting the evolution of federal student aid policy, the basic structure of the Pell Grant program, and then documenting trends in the Pell Grant program from its beginning to the 2006–07 award year. I then examine factors that have contributed to growth in the program between 2007–08 and 2011–12, focusing on legislative changes and contextual factors, and ultimately present a typology of proposed and enacted options to maintain or reduce program costs. The article closes with considerations related to the future of the Pell Grant program.
Study on machine learning classifications based on OLI images

Classification for remote sensing images needs to build rules through machine learning. OLI images are useful multi spectral images put into use in 2013. Three kinds of machine learning algorithms were studied for classifying an OLI image in this paper. Samples and 22 features are put in use to test the three kinds of machine learning algorithms. The results are shown as quantitative analysis, visual analysis and feature importance comparison. The results are as follows: In this three machine learning algorithms, using SVM can get the best results, BPNN make the worst results and different classifiers use different features for training and classification.
The Efficient Computation of Sparse Jacobian Matrices Using Automatic Differentiation

This paper is concerned with the efficient computation of sparse Jacobian matrices of nonlinear vector maps using automatic differentiation (AD). Specifically, we propose the use of a graph coloring technique, bicoloring, to exploit the sparsity of the Jacobian matrix J and thereby allow for the efficient determination of J using AD software. We analyze both a direct scheme and a substitution process. We discuss the results of numerical experiments indicating significant practical potential of this approach.
Mobile Video Quality Assessment Database

We introduce a new research tool – the LIVE Mobile Video Quality Assessment (VQA) database. The database consists of pristine reference and distorted videos, along with human/subjective opinion scores of the associated video quality. The database was designed towards improving our understanding of human judgements of time-varying video quality in heavilytrafficked wireless networks. A byproduct of a better understanding could be quantitative models useful for the development of perceptually-aware algorithms for resource allocation and rate adaptation for video streaming. The database consists of 200 distorted videos created from 10 RAW HD videos acquired using a RED ONE digital cinematographic camera. It includes static distortions such as compression and wireless packet loss, as well as dynamically varying distortions. We describe the creation of the database, simulated distortions and the human study that we conducted to obtain 5,300 time-sampled subjective traces of quality and summary subjective scores. We analyze the results obtained for certain subclasses of distortions from this large database of interest in context of wireless video delivery. The LIVE Mobile VQA database, including the human subjective scores, will be made available to researchers in the field at no cost in order to aid the development of novel strategies for videoaware resource allocation.
Mining of predictive patterns in Electronic health records data

The emergence of large-scale datasets in health care that record large amounts of information about the patients, their diseases and treatments and provide us with an opportunity to understand better the dynamics of the disease, efficacy of treatments, and various influences affecting the well-being of a patient. The development of computer methods and tools that would enable to analyze and utilize such data is badly needed. The objective of this report is to briefly review data mining and machine learning methods we have developed since 2009 [7, 10, 6, 11, 8, 9, 12, 5, 4, 13] that aim to extract predictive patterns characterizing patient subgroups and their predictive differences in electronic health records (EHRs). Identification of such predictive patterns can be extremely useful for both knowledge discovery purposes and for feature engineering facilitating the construction of various predictive models from complex clinical time-series data. The temporal pattern mining approach we have investigated and developed builds upon the temporal abstraction framework [19], that converts multivariate time-series data into sequences of discrete values, and combines their components using temporal logic operators [2] to form more complex temporally extended patterns. We have studied and made the following contributions to this line of work. First, we have proposed and developed a new minimal predictive pattern mining approach t at lets us describe the predictive differences in the data by stratifying the data into subpopulations represented by patterns of different complexity, that let us better predict the patient outcomes. Second we have developed and tested two statistical criteria to filter random (or spurious) patterns that represent subpopulation with significantly different outcomes. Finally, we have developed and tested a new pattern mining heuristic that can be applied to event detection tasks. The heuristic searchers for minimum predictive patterns backwards in time, starting from the time of the event, such that more recent patterns with respect to the event are preferred and more likely included in the predictive pattern set constructed by the algorithm. We have shown our approaches leads to a smaller number of predictive patterns
Transcriptome and Gene Expression Analysis of the Rice Leaf Folder, Cnaphalocrosis medinalis

Background The rice leaf folder (RLF), Cnaphalocrocis medinalis (Guenee) (Lepidoptera: Pyralidae), is one of the most destructive pests affecting rice in Asia. Although several studies have been performed on the ecological and physiological aspects of this species, the molecular mechanisms underlying its developmental regulation, behavior, and insecticide resistance remain largely unknown. Presently, there is a lack of genomic information for RLF; therefore, studies aimed at profiling the RLF transcriptome expression would provide a better understanding of its biological function at the molecular level. Principal Findings De novo assembly of the RLF transcriptome was performed via the short read sequencing technology (Illumina). In a single run, we produced more than 23 million sequencing reads that were assembled into 44,941 unigenes (mean size = 474 bp) by Trinity. Through a similarity search, 25,281 (56.82%) unigenes matched known proteins in the NCBI Nr protein database. The transcriptome sequences were annotated with gene ontology (GO), cluster of orthologous groups of proteins (COG), and KEGG orthology (KO). Additionally, we profiled gene expression during RLF development using a tag-based digital gene expression (DGE) system. Five DGE libraries were constructed, and variations in gene expression were compared between collected samples: eggs vs. 3rd instar larvae, 3rd instar larvae vs. pupae, pupae vs. adults. The results demonstrated that thousands of genes were significantly differentially expressed during various developmental stages. A number of the differentially expressed genes were confirmed by quantitative real-time PCR (qRT-PCR). Conclusions The RLF transcriptome and DGE data provide a comprehensive and global gene expression profile that would further promote our understanding of the molecular mechanisms underlying various biological characteristics, including development, elevated fecundity, flight, sex differentiation, olfactory behavior, and insecticide resistance in RLF. Therefore, these findings could help elucidate the intrinsic factors involved in the RLF-mediated destruction of rice and offer sustainable insect pest management.
Pattern discovery in e-learning courses: a timebased approach

This work relies on connectivism and focuses on the interactions between learners and resources of e-learning materials aiming to discover patterns [13]. The theory of connectivism mainly tells, that knowledge is available through a network of connections. Based on Social Network Analysis, our Time-graph representation uses temporal metrics [12]. Even though longitudinal networks are the most widely used representations of temporal factors, here we considerer time-distribution criterion within a single graph. Path following techniques are not new, but the Time-graph configuration makes it in a specific fashion, that orders resources over a timeline. A resource has not the same impact at the start or at the end of a course. Hence given a specific instant, the Time-graph can inform learners, about important resources.
Molecular Evolution and Mosaicism of Leptospiral Outer Membrane Proteins Involves Horizontal DNA Transfer

ABSTRACT Leptospires belong to a genus of parasitic bacterial spirochetes that have adapted to a broad range of mammalian hosts. Mechanisms of leptospiral molecular evolution were explored by sequence analysis of four genes shared by 38 strains belonging to the core group of pathogenic Leptospira species: L. interrogans, L. kirschneri, L. noguchii, L. borgpetersenii, L. santarosai, and L. weilii. The 16S rRNA and lipL32 genes were highly conserved, and the lipL41 and ompL1 genes were significantly more variable. Synonymous substitutions are distributed throughout the ompL1 gene, whereas nonsynonymous substitutions are clustered in four variable regions encoding surface loops. While phylogenetic trees for the 16S, lipL32, and lipL41 genes were relatively stable, 8 of 38 (20%) ompL1 sequences had mosaic compositions consistent with horizontal transfer of DNA between related bacterial species. A novel Bayesian multiple change point model was used to identify the most likely sites of recombination and to determine the phylogenetic relatedness of the segments of the mosaic ompL1 genes. Segments of the mosaic ompL1 genes encoding two of the surface-exposed loops were likely acquired by horizontal transfer from a peregrine allele of unknown ancestry. Identification of the most likely sites of recombination with the Bayesian multiple change point model, an approach which has not previously been applied to prokaryotic gene sequence analysis, serves as a model for future studies of recombination in molecular evolution of genes.
Mathematical models of cardiac pacemaking function

Over the past half century, there has been intense and fruitful interaction between experimental and computational investigations of cardiac function. This interaction has, for example, led to deep understanding of cardiac excitation-contraction coupling; how it works, as well as how it fails. However, many lines of inquiry remain unresolved, among them the initiation of each heartbeat. The sinoatrial node, a cluster of specialized pacemaking cells in the right atrium of the heart, spontaneously generates an electro-chemical wave that spreads through the atria and through the cardiac conduction system to the ventricles, initiating the contraction of cardiac muscle essential for pumping blood to the body. Despite the fundamental importance of this primary pacemaker, this process is still not fully understood, and ionic mechanisms underlying cardiac pacemaking function are currently under heated debate. Several mathematical models of sinoatrial node cell membrane electrophysiology have been constructed as based on different experimental data sets and hypotheses. As could be expected, these differing models offer diverse predictions about cardiac pacemaking activities. This paper aims to present the current state of debate over the origins of the pacemaking function of the sinoatrial node. Here, we will specifically review the state-of-the-art of cardiac pacemaker modeling, with a special emphasis on current discrepancies, limitations, and future challenges.
Hispanics in the United States

1. Hispanics in American Life. 2. History: The Hispanics Appear. 3. The Diversity of Hispanics. 4. Portrait of the Hispanics: I. 5. Portrait of the Hispanics: II. 6. The Hispanic Community: Stability and Change. 7. Culture and Language. 8. Hispanics and Institutions of the Modern State: I. 9. Hispanics and Institutions of the Modern State: II. 10. Politics and the Hispanic Community. Epilogue. Index.