Miracle-dz/UniFAR-FTUs huggingface dataset:
Measuring the Effectiveness of Partial Evaluation

We introduce a framework for assessing the eectiveness of partial evaluators for functional logic programs. Our framework is based on properties of the rewrite system that models a functional logic pro- gram and, consequently, our assessment is independent of any specic language implementation or computing environment. We dene several criteria for measuring the cost of a computation: number of steps, num- ber of function applications, and eort for pattern matching. Most im- portantly, we express the cost of each criterion by means of recurrence equations over algebraic data types, which can be automatically inferred from the partial evaluation process itself. In some cases, the equations can be solved by transforming their arguments from arbitrary data types to natural numbers. In other cases, it is possible to estimate the improve- ment of a partial evaluation by analyzing the recurrence equations.
The pregnancy hormone relaxin is a player in human heart failure

Human congestive heart failure is characterized by complex neurohumoral activation associated with the up‐regulation of vasoconstricting and salt‐retaining mediators and the compensatory rise of counter‐regulatory hormones. In the present study, we provide the first evidence that relaxin (RLX), known as a pregnancy hormone, represents a potential compensatory mediator in human heart failure: plasma concentrations of RLX and myocardial expression of the two RLX genes (H1 and H2) correlate with the severity of disease and RLX responds to therapy. The failing human heart is a relevant source of circulating RLX peptides, and myocytes as well as interstitial cells produce RLX. Elevation of ventricular filling pressure up‐regulates RLX expression and the hormone acts as a potent inhibitor of endothelin 1, the most powerful vasoconstrictor in heart failure. Furthermore, RLX modulates effects of angiotensin II, another crucial mediator. Our data identify RLX as a new player in human heart failure with potential diagnostic and therapeutic relevance. —Dschietzig, T. , Richter, C. , Bartsch, C. , Laule, M. , Armbruster, F. P., Baumann, G. , Stangl, K. The pregnancy hormone relaxin is a player in human heart failure. FASEB J. 15, 2187–2195 (2001)
A Novel QoS Multipath Path Routing in MANET

Mobile ad hoc networks are typically characterized by high mobility and frequent link failures that result in low throughput and high end-to-end delay. The increasing use of MANETs for transferring multimedia applications such as voice, video and data, leads to the need to provide QoS support. We introduce a routing algorithm, Ad hoc on-demand multipath routing, which provides quality of service (QoS) support,(Q-AOMDV) in terms of bandwidth, hop count and end-to-end delay in mobile ad hoc networks. The results validate that Q-AOMDV provides QoS support in mobile ad hoc wireless networks with high reliability and low overhead.
Relay Selection for Cooperative NOMA

This letter studies the impact of relay selection (RS) on the performance of cooperative non-orthogonal multiple access (NOMA). In particular, a two-stage RS strategy is proposed, and analytical results are developed to demonstrate that this two-stage strategy can achieve the minimal outage probability among all possible RS schemes, and realize the maximal diversity gain. The provided simulation results show that cooperative NOMA with this two-stage RS scheme outperforms that based on the conventional max-min approach, and can also yield a significant performance gain over orthogonal multiple access.
Single image fog removal algorithm based on an improved dark channel prior method

Recently, how to make surveillance cameras running in all weather conditions become a very important research topic. Because surveillance images are often influenced by the weather conditions in a real world. In this paper, a fast single image fog removal algorithm based on an improved dark channel prior method is proposed. Compared to the latest works, the proposed algorithm can increase 28.5% computing speed and 41.8% image contrast ratio. Meanwhile, it can remove fog efficiently without the influence in the night too.
Downlink resource reuse for Device-to-Device communication underlaying cellular networks using a generalized Knapsack framework

In this paper, we investigate the resource allocation problem to improve the performance of Device-to-Device (D2D) communications underlaying downlink cellular networks. We aim to optimize the sum-rate of D2D communications while fulfilling Quality of Service (QoS) requirements of prioritized cellular network. To achieve this, we formulate the problem as a Knapsack utility maximization problem for each cellular resource and generalize a recursive algorithm based on dynamic programming as a solution. In order to improve the spectrum utilization we exploit multiuser diversity in which, a cellular frequency resource is allowed to be shared by multiple D2D users (DUs) and a DU is allowed to reuse more than one frequency resource. The simulation results demonstrate that the proposed scheme leads to near-optimal performance on D2D sum-rate.
An FPGA Architecture of Stable-Sorting on a Large Data Volume : Application to Video Signals

This paper proposes a single-chip scalable and compact field programmable gate array (FPGA) based architecture of a modified counting sort algorithm which specifically addresses the issue of sorting large volume of integer or fractional data. The proposed architecture is successfully co-simulated with C/MATLAB and VHDL. Performance analysis shows that our approach achieves orders of magnitude performance improvements over the existing hardware-based methods and pure software-based implementations. The area utilization and timing performance of the proposed sorting core are invariant to the number of keys (N), but to the number of bits (k) in N. The design is easily placed and routed to run with a clock rate of 133 MHz while utilizing minimal hardware resources and power. The proposed architecture is verified for performance and accuracy on a Virtex II-Pro FPGA evaluation platform.
How Synchronized are Central and East European Economies with the Euro Area? Evidence from a Structural Factor Model

A high degree of cyclical synchronization between central and east European countries (CEECs) and the euro area is generally seen as a prerequisite for successful EMU enlargement. This paper investigates comovements between CEECs and the euro area. We first establish stylized facts on economic linkages using dynamic correlation and cohesion measures. By means of a large-scale dynamic factor model, we then identify the main structural common euro-area shocks and investigate their transmission to the CEECs in comparison to the current EMU members. We finally carry out a counterfactual experiment which allows us to assess the costs and benefits of accession to EMU for individual CEECs in terms of economic volatilities and the implications of enlargement for synchronization. Overall, our results are mixed. Dynamic business cycle and inflation correlations between CEECs and the euro area are, on average, lower than between individual EMU members and the euro area, but they are higher than for some small peripheral EMU countries. This is confirmed by our other measure, variance shares of output and inflation explained by common euro-area factors. The proliferation of euro-area shocks to the CEECs does not differ significantly from the propagation to EMU countries in most cases. Based on our counterfactual experiment, we do not find significant stabilizing or destabilizing effects through a common monetary policy and fixed exchange rates. We also find that business cycle synchronization between CEECs and between most CEECs and the euro area will increase. There seems to be considerable heterogeneity across CEECs, implying that for some countries, accession to EMU would be more costly than for others. According to our analysis and based on our measures, Poland, Slovenia, Hungary and Estonia are more suitable EMU candidates than other countries.
Skp2 Directs Myc-Mediated Suppression of p27Kip1 yet Has Modest Effects on Myc-Driven Lymphomagenesis

The universal cyclin-dependent kinase inhibitor p27Kip1 functions as a tumor suppressor, and reduced levels of p27Kip1 connote poor prognosis in several human malignancies. p27Kip1 levels are predominately regulated by ubiquitin-mediated turnover of the protein, which is marked for destruction by the E3 ubiquitin ligase SCFSkp2 complex following its phosphorylation by the cyclin E–cyclin-dependent kinase 2 complex. Binding of phospho-p27Kip1 is directed by the Skp2 F-box protein, and this is greatly augmented by its allosteric regulator Cks1. We have established that programmed expression of c-Myc in the B cells of Eμ-Myc transgenic mice triggers p27Kip1 destruction by inducing Cks1, that this response controls Myc-driven proliferation, and that loss of Cks1 markedly delays Myc-induced lymphomagenesis and cancels the dissemination of these tumors. Here, we report that elevated levels of Skp2 are a characteristic of Eμ-Myc lymphomas and of human Burkitt lymphoma that bear MYC/Immunoglobulin chromosomal translocations. As expected, Myc-mediated suppression of p27Kip1 was abolished in Skp2-null Eμ-Myc B cells. However, the effect of Skp2 loss on Myc-driven proliferation and lymphomagenesis was surprisingly modest compared with the effects of Cks1 loss. Collectively, these findings suggest that Cks1 targets, in addition to p27Kip1, are critical for Myc-driven proliferation and tumorigenesis. Mol Cancer Res; 8(3); 353–62
Structure and Chemical Inhibition of the RET Tyrosine Kinase Domain*

The RET proto-oncogene encodes a receptor tyrosine kinase for the glial cell line-derived neurotrophic factor family of ligands. Loss-of-function mutations in RET are implicated in Hirschsprung disease, whereas activating mutations in RET are found in human cancers, including familial medullar thyroid carcinoma and multiple endocrine neoplasias 2A and 2B. We report here the biochemical characterization of the human RET tyrosine kinase domain and the structure determination of the non-phosphorylated and phosphorylated forms. Both structures adopt the same active kinase conformation competent to bind ATP and substrate and have a pre-organized activation loop conformation that is independent of phosphorylation status. In agreement with the structural data, enzyme kinetic data show that autophosphorylation produces only a modest increase in activity. Longer forms of RET containing the juxtamembrane domain and C-terminal tail exhibited similar kinetic behavior, implying that there is no cis-inhibitory mechanism within the RET intracellular domain. Our results suggest the existence of alternative inhibitory mechanisms, possibly in trans, for the autoregulation of RET kinase activity. We also present the structures of the RET tyrosine kinase domain bound to two inhibitors, the pyrazolopyrimidine PP1 and the clinically relevant 4-anilinoquinazoline ZD6474. These structures explain why certain multiple endocrine neoplasia 2-associated RET mutants found in patients are resistant to inhibition and form the basis for design of more effective inhibitors.
Maximization of mutual information in a linear noisy network: a detailed study

We consider a linear, one-layer feedforward neural network performing a coding task. The goal of the network is to provide a statistical neural representation that conveys as much information as possible on the input stimuli in noisy conditions. We determine the family of synaptic couplings that maximizes the mutual information between input and output distribution. Optimization is performed under different constraints on the synaptic efficacies. We analyse the dependence of the solutions on input and output noises. This work goes beyond previous studies of the same problem in that: (i) we perform a detailed stability analysis in order to find the global maxima of the mutual information; (ii) we examine the properties of the optimal synaptic configurations under different constraints; (iii) and we do not assume translational invariance of the input data, as it is usually done when inputs are assumed to be visual stimuli.
Fading correlation and analytical performance evaluation of the space-diversity free-space optical communications system

This paper investigates fading correlation in space-diversity free-space optical (FSO) communication systems and its effect on the link performance. We firstly evaluate the fading correlation in multiple-aperture FSO systems using wave-optics simulations. The influence of different system parameters including the link distance and aperture spacing is illustrated under realistic beam propagation conditions. In particular, we show that, at relatively large link distances where the scattering disk is much larger than the receiver aperture size, the fading correlation coefficient is almost independent of the apertures’ diameter and depends only on the apertures’ edge separation. To investigate the impact of fading correlation on the system’s performance, we propose an analytical approach to evaluate the performance of the space-diversity FSO system over a correlated Gamma–Gamma (ΓΓ) fading channel. Our approach is based on approximating the sum of arbitrarily correlated ΓΓ random variables by an α−μ distribution. To validate the accuracy of this method, we evaluate the average bit-error-rate (BER) performance for the case of a multiple-aperture FSO system and compare it with the BER results obtained via Monte Carlo simulations.
An Approach for Geospatial Data Management for Efficient Web Retrieval

The heterogeneous nature of geospatial data makes them almost non-sharable over the web. Geography Markup Language (GML), an XML based data encoding standard, has been proposed by OGC for storing, transporting of geospatial data over the web. With the proliferation of GML in many geospatial application and support from the standard DBMS, the need arises for the efficient storage mechanism of GML data. This paper analyses approaches for XML data storage in traditional DBMS and its extension to GML. We propose an approach for GML storage based on the analysis of the underlying application schema. A semi-automatic mapping mechanism is proposed for the application schema to relational schemas of standard database with the utilization of common concepts for the domain i.e. the ontology of the domain. This enhances the web retrieval of geospatial data by bringing semantics among the data sources.
Power Estimation of Pin

Power dissipation in modern computing systems is a source of concern for hardware designers. Recent research has concentrated a lot of effort in trying to minimize power consumption in processors. However static reduction of power has reached a threshold, which has led to a renewed investigation of runtime techniques. Dynamic binary instrumentation tools are programs which investigate the runtime characteristics of other programs. They are gaining increasing popularity among the software community, since they open up new avenues to perform optimization on programs. DBI tools have been used to study the phases of programs and apply voltage and frequency scaling in order to reduce the power dissipated by the processor. In this paper, we try to evaluate the effect of a industrial strength DBI tool, Pin, on power dissipation, using its various configurations. Our aim is to ascertain which aspects of Pin affect power consumption the most, thereby providing users with a high-level view of the power dissipation caused by the DBI Tool.
Youthful steps towards civic participation: does the internet help?

Book synopsis: A social anxiety currently pervades the political classes of the western world, arising from the perception that young people have become disaffected with liberal democratic politics. Voter turnout among 18-25 year olds continues to be lower than other age groups and they are less likely to join political parties. This is not, however, proof that young people are not interested in politics per se but is evidence that they are becoming politically socialized within a new media environment. This shift poses a significant challenge to politicians who increasingly have to respond to a technologically mediated lifestyle politics that celebrates lifestyle diversity, personal disclosure and celebrity. This book explores alternative approaches for engaging and understanding young people’s political activity and looks at the adoption of information and ICTs as a means to facilitate the active engagement of young people in democratic societies. Young Citizens in a Digital Age presents new research and the first comprehensive analysis of ICTs, citizenship and young people from an international group of leading scholars. It is an important book for students and researchers of citizenship and ICTs within the fields of sociology, politics, social policy and communication studies among others.
Realistic validation of specification for modeling language using Alloy

Authors suggest a resolution to validate metamodels using a formal description language and analyzer Alloy. A MDA meta-hierarchy divides a model into three layers. Therefore this approach is able to validate partial models using Alloy. Validating partial models reduce execution time. For an example of realistic validation, this paper shows application to the specification of an information control system modeling language and results of the validations for the specification.
Investigating the Effects of IT Adoption between Micro-Enterprises from an Ethnic Community in the United States

The present research study aims to discover the effects of IT adoption in micro-enterprises in the Latino community in the United States. While the majority of the IT adoption literature considers large organizations, this study relies on Sen’s Capability Approach and an adaptation of Action Research to support the adoption of IT by micro-enterprises. This “IT therapy” process enables IT to be used by micro-entrepreneurs to grow their businesses. Following an analysis of four Latin American micro-enterprises, this paper presents the most predominant outcomes. An assessment is made of the IT solutions implemented in the participating micro-enterprises. This paper contributes with a better understanding of how IT adoption can enable micro-enterprises in ethnic communities to grow. This has implications for governmental and non-governmental agencies supporting technology implementations in local communities. Future research based on the research findings should investigate communities of local enterprises at underserved areas as they adopt technology.
A Knowledge-Based Multi-Agent Approach for Initial Query Refinement in Information Retrieval

Query refinement is one of the main approaches for overcoming natural language lexical ambiguity and improving the quality of search results in Information Retrieval. In this paper we propose a knowledge–rich personalized approach for iterative query reformulation before sending it to search engines and entropybased approach for refinement quality estimation. The underling hypothesis is that the query reformulation entropy is a valuable characteristic of the refinement quality. We use multi-agent architecture to implement our approach. Experimental results confirm that there is a trend for significant improvement in the quality of search results for large values of entropy.
Exploring Activity Features in Predicting Social Network Evolution

In this paper, we present a novel approach to incorporate the activity features in measuring the influence of member activities on the social network evolution. Convent ional methods analyze social networks and make predictions based on all cumulative members and activities. However, since inactive members do not contribute to the network growth, including them in analysis can lead to less accurate results . Based on this observation, we propose to focus on the active population and explore the influence of member activities. We present a model that can incorporate various activity features and predict the evolution of social activities. At the same time, an algorithm is adopted to select the most influential activity features. The experiments on two different types of social network show that the activity features can predict t he evolution of the social activity accurately and our algorithm is effective to select the most influential features. In addi tion, we find that the most significant activity features to determi ne the network evolution vary among different types of social network. Keywords-Social Activity Evolution, Feature Selection
Quality as the Interface Between Manufacturing and Marketing: A Conceptual Model and An Empirical Study

Even when manufacturing and marketing departments operate at their respective best operating level, it may be suboptimal for the firm as a whole. Their functions can be integrated using quality as the interface. A conceptual model for an integrated approach employing a feedback loop is proposed. The model is analyzed using state-of-the-art scanner data and intrinsic managerial guidelines for global applications are developed.
Extending Urban Air Quality Maps Beyond the Coverage of a Mobile Sensor Network: Data Sources, Methods, and Performance Evaluation

Targeting the problem of generating high-resolution air quality maps for cities, we leverage four different sources of data: (i) in-situ air quality measurements produced by our mobile sensor network deployed on public transportation vehicles, (ii) explanatory air-quality and meteorological variables obtained from two static monitoring stations, (iii) land-use data of the city, and (iv) traffic statistics. We propose two novel approaches for estimating the targeted pollutant level at desired time-location pairs, extending also to areas of the city that are beyond the coverage of our mobile sensor network. The first is a log-linear regression model which is built over a virtual dependency graph based on land-use data. The second is a deep learning framework that automatically captures the dependencies of the data based on autoencoders. We have evaluated the two proposed approaches against three canonical modeling techniques considering metrics of coefficient of determination (R²), root mean square error (RMSE), and the fraction of predictions within a factor of two of observations (FAC2). Using more than 45 million real measurements in the models, the results show consistently superior performance in respect to the canonical techniques.
Natural Language Question Analysis for Querying Biomedical Linked Data

Biomedical knowledge is disseminated in knowledge bases which become increasingly available on the Web. While using biomedical Linked Data is crucial, life-science researchers may have diﬃcul-ties using SPARQL language. Interfaces based on Natural Language question-answering are recognized to be suitable for querying knowledge bases. In this paper, we propose a method for translating natu-ral language questions into SPARQL queries. We use Natural Language Processing tools, semantic resources and the RDF triples description. We designed a four-step method which linguistically and semantically annotates the question, performs an abstraction of the question, then builds a representation of the SPARQL query and ﬁnally generates the query. The method is designed on 50 questions over 3 biomedical knowledge bases used in the task 2 of the QALD-4 challenge framework and evaluated on 27 new questions. It achieves good performance with 0.78 F-measure on the test set. The method for translating questions into SPARQL queries is implemented as a Perl module and is available at http://search.cpan. org/˜thhamon/RDF-NLP-SPARQLQuery/.