Miracle-dz/UniFAR-FTUs huggingface dataset:
Incorrectly accounting for taste heterogeneity in choice experiments: Does it really matter for welfare measurement?

A range of empirical approaches to representing preference heterogeneity have emerged in choice modelling. Researchers have been able to explore the differences which selection of a particular approach makes to welfare measures in a particular dataset, and indeed have been able to implement a number of tests for which approach best fits a particular set of data. However, the question as to the degree of error in welfare estimation from an inappropriate choice of empirical approach has not been addressed. In this paper, we use Monte Carlo analysis to address this question. Given the high popularity of both the random parameter logit (RPL) and latent class models among choice modellers, we examine the errors in welfare estimates from using the incorrect model to account for taste preference heterogeneity. Our main finding is that using an RPL specification with log-normally distributed preferences seems the best bet.
Virus-Associated Lymphomagenesis

At least 2 billion people are affected by viral infections worldwide. The infections induce a lot of various human diseases and are one of the main causes of human mortality. In particular, they can lead to development of various human cancers. Up to 15-20% of human cancer incidence can be attributed to viruses. Although viral infections are very common in the general population, only few of them result in clinically relevant lesions. Certain associations between virus infections and malignancy are strong and irrefutable, the others are still speculative. The criteria most often used for determining the causality are the consistence of the association, either epidemiologic or at the molecular level, and oncogenicity of viruses or particular viral genes in animal models or cell cultures. Due to some ambiguity of such a determination, it is instructive to consider by specific cases what evidence is generally accepted as sufficient to establish a causal relation between virus and cancer. Lymphomas are one of the best studied cancer types closely associated with a small but definite range of viruses. Numerous data show a close interrelation between lymphomagenesis and infection by such viruses as Kaposi’s sarcoma herpesvirus (KSHV), Epstein-Barr virus (EBV), hepatitis C virus (HCV), human T-cell leukemia virus (HTLV), and human immunodeficiency virus (HIV). For instance, experiments on monkeys artificially infected with viruses and data on anti-cancer effect of specific antiviral preparations strongly suggest the involvement of viruses in lymphoma development. The present review is devoted to the association of different viruses with human lymphomas and to viral genes potentially involved in the neoplastic process. The recognition of virus involvement in lymphomagenesis may facilitate new strategies for cancer therapy, diagnosis and screening and can lead to a reduction in the number of individuals at risk of disease.
In-vivo estimation of the human elbow joint dynamics during passive movements based on the musculo-skeletal kinematics computation

Human upper limb joints dynamics is very important in the fields of humanoid robotics, medical robotics as well as medical research. To make human-like passive movements of the arms when walking humanoid robot arms must have similar dynamics to the human arms, even more if this arm is to be used as a prosthesis. Moreover medical diagnosis of muscle or neuro-motor diseases are based on a visual qualitative estimation of joint passive stiffness. There is a pressing need in human body dynamics characterization and especially in subject specific characterization. In this paper a solution to estimate in-vivo the passive dynamic of the arm joint is proposed. It is based on the use of the musculo-skeletal description of the human body and its kinematics computation. The linear passive joint dynamics: stiffness, viscosity and friction, is then estimated with least squares method. Acquisition of movements both designed for estimation or from medical diagnosis check-up, are achieved with motion capture studio only (no pain, no distress on subject). Experimental results for three valid subject are given
Distributed Modeling in a MapReduce Framework for Data-Driven Traffic Flow Forecasting

With the availability of increasingly more new data sources collected for transportation in recent years, the computational effort for traffic flow forecasting in standalone modes has become increasingly demanding for large-scale networks. Distributed modeling strategies can be utilized to reduce the computational effort. In this paper, we present a MapReduce-based approach to processing distributed data to design a MapReduce framework of a traffic forecasting system, including its system architecture and data-processing algorithms. The work presented here can be applied to many traffic forecasting systems with models requiring a learning process (e.g., the neural network approach). We show that the learning process of the forecasting model under our framework can be accelerated from a computational perspective. Meanwhile, model fusion, which is the key problem of distributed modeling, is explicitly treated in this paper to enhance the capability of the forecasting system in data processing and storage.
Kernel Procrustes

In this work we introduce a new methodology to build a kernel matrix from a collection of kernels. The key idea is to build a unique kernel that eliminates spurious differences between kernels. We propose a method based on the Procrustes problems that uses the alternating projections method to minimize a certain error measure. The resulting kernel will be used for classification purposes using support vector machines (SVMs). The proposed method has been successfully evaluated against alternative kernel combination techniques
A 20‐yr radio light curve for the young supernova remnant G1.9+0.3

The radio source G1.9+0.3 has recently been identified as the youngest known Galactic supernova remnant, with a putative age of� 100 years. We present a radio light curve for G1.9+0.3 based on 25 epochs of observation with the Molonglo Observatory Synthesis Telescope, spanning 20 years from 1988 to 2007. These observations are all at the same frequency (843 MHz) and comparable resolutions (43 00 � 91 00 or 43 00 � 95 00 ) and cover one fifth of the estimated lifetime of the supernova remnant. We find that the flux densit y has increased at a rate of 1:22� 0:24 0:16 per cent yr 1 over the last two decades, suggesting that G1.9+0.3 is undergoing a
Postsynaptic Density Assembly Is Fundamentally Different from Presynaptic Active Zone Assembly

The cellular mechanisms involved in the formation of the glutamatergic postsynaptic density (PSD) are mainly unknown. Previous studies have indicated that PSD assembly may occur in situ by a gradual recruitment of postsynaptic molecules, whereas others have suggested that the PSD may be assembled from modular transport packets assembled elsewhere. Here we used cultured hippocampal neurons and live cell imaging to examine the process by which PSD molecules from different layers of the PSD are recruited to nascent postsynaptic sites. GFP-tagged NR1, the essential subunit of the NMDA receptor, and ProSAP1/Shank2 and ProSAP2/Shank3, scaffolding molecules thought to reside at deeper layers of the PSD, were recruited to new synaptic sites in gradual manner, with no obvious involvement of discernible discrete transport particles. The recruitment kinetics of these three PSD molecules were remarkably similar, which may indicate that PSD assembly rate is governed by a common upstream rate-limiting process. In contrast, the presynaptic active zone (AZ) molecule Bassoon was observed to be recruited to new presynaptic sites by means of a small number of mobile packets, in full agreement with previous studies. These findings indicate that the assembly processes of PSDs and AZs may be fundamentally different.
Opencj: A research Java static compiler based on Open64

As Java becomes more pervasive in the programming landscape even in HPC applications, it is very important to provide optimizing compilers and more efficient runtime systems. To this end, we try to leverage the synergy between static and dynamic optimization to exploit more optimization chances and improve Java runtime performance especially for server applications. This paper presents our first achievement of implementing a Java static compiler Opencj which can perform fully optimization for Java applications. Opencj takes Java source files or class files as inputs and generates machine dependent executable code for Linux/IA32. It is developed based on Open64 with some optimizations implemented for Java. Efficient support for exception handling and virtual method call resolution fulfills the demands which are imposed by the dynamic features of the Java programming language. Due to the same optimizer in Opencj and Open64, the performance gap between Java and C/C++ programs can be evaluated. The evaluation of the scientific SciMark 2.0 benchmark suite shows they have a similar peak performance between its Java and C versions. The evaluation also illustrates that the performance of Opencj is better than GCJ for SPECjvm98 benchmark suite.
Automatic localization of facial landmarks from expressive images of high complexity

The aim of this study was to develop a fully automatic feature-based method for expression-invariant localization of facial landmarks from static facial images. It was a continuation of our earlier work in which we found that lower face expressions deteriorated the feature-based localization of facial landmarks the most. Taking into account the found crucial facial behaviours, the method was improved so that it allowed facial landmarks to be fully automatically located from expressive images of high complexity. Information on local oriented edges was utilized to compose edge maps of the image at several levels of resolution. Landmark candidates which resulted from this step were further verified by matching them against the orientation model. The present novelty came from two last steps of the method which were edge projection that was used to enhance a search for landmark candidates, and structural correction of the found candidates based on a face geometry model. The method was tested on three facial expression databases which represented a wide range of facial appearances in terms of prototypical facial displays and individual facial muscle contractions. To evaluate the localization results, a new performance evaluation measure was introduced that represented a localization result as a rectangular box instead of a conventional point representation. The evaluation of the method by the proposed rectangular and conventional point evaluation measures demonstrated a high overall performance of the method in localization of facial landmarks from images showing complex expressions in upper and lower face.
Application-to-Core Mapping Policies to Reduce Interference in On-Chip Networks

Future many-core processors are likely to concurrently execute a large number of diverse applications. How these applications are mapped to cores largely determines the interference between these applications in critical shared resources such as the network-on-chip. In this paper, we propose applicationto-core mapping policies to reduce the contention in network-on-chip and memory controller resources and hence improve overall system performance. The key ideas of our policies are to: 1) map networklatency-sensitive applications to separate node clusters in the network from network-bandwidth-intensive applications such that the former makes fast progress without heavy interference from the latter, 2) map those applications that benefit more from being closer to the memory controllers close to these resources. Contrary to the conventional wisdom of balancing network or memory load across the network-on-chip and controllers, we observe that it is also important to ensure that applications that are more sensitive to network latency experience little interference from applications that are network-bandwidth-intensive, even at the cost of load imbalance. We evaluate the proposed application-to-core mapping policies on a 60-core system with an 8x8 mesh NoC using a suite of 35 diverse applications. Averaged over 128 randomly generated multiprogrammed workloads, thefinal proposed policy improves system throughput by 16.7% in terms of weighted speedup over a state-of-the-art baseline, while also reducing system unfairness by 22.4% and average interconnect power consumption by 52.3%.
The role of monetary incentives in prediction markets: a time series approach

Prediction markets serve as popular devices to aggregate beliefs and to assess market estimated probabilities. By looking at the interaction between real- and play-money prediction markets, this paper shows that traded volume has a significant positive effect on the probability of real- and play-money market cointegration. This indicates that the information aggregation process, eliminating individual traders'' biases, operates even when not inducing truthful belief revelation with monetary incentives. The study is based on data from four markets covering the 2008 presidential election in the United States of America
Workshop 4: Adaptable and Adaptive Software Using Type Information to Control Framework Reuse 2 Kinds of Reuse

Finding a clear and expressive way to describe how a system can be adapted and to which constraints adaptations should comply is one of the most compelling problems in the development of adaptive software. While currently the possibilities for adaptation are mostly described in an informal way, we show how type information can be used to achieve a more controllable model of modification. We first taxonomise different kinds of reuse and different operations performed through incremental modification and then discuss what constraints should be put on these operations to achieve the distinct kinds of reuse. 1 Background To avoid confusion about terminology we first discuss some related work. [Johnson&Russo91] mention abstract classes and frameworks as the two most important techniques for reuse of design. An abstract class is a class that contains abstract methods. An abstract method has no implementation, only a specification. A template method has an implementation, but uses abstract methods in it. It is not possible to instantiate an abstract class. First, all abstract methods have to be overridden by a concrete method. While an abstract class is a design for a single object, a framework is the design of a set of (abstract) classes that collaborate to carry out a set of responsibilities. The best known way to formally describe the constraints in a framework is through contracts [Helm&al.90] [Holland92]. Contracts specify how abstract classes and frameworks can be refined, specialised and combined. Another related issue is the use of specialisation interfaces [Lamping93]; the interfaces classes want to show their inheriting clients. Specialisation interfaces were introduced to better document classes in a library, based on the idea that a class's inheriting clients should get more, or other information than its message passing clients. Inheritance was traditionally used to describe two kinds of reuse: reuse of behaviour and reuse of code. Later the object-oriented reuse community emphasised reuse of design as another major factor, with abstract classes and frameworks as the most important techniques to achieve it. The distinction between reuse of code and reuse of behaviour is directly related to the distinction between covariance and contravariance made in type systems. In previous work we described a type system for dynamic object extension, that does not strictly impose one of these methods, thus offering the possibility to model both reuse of code and of behaviour [Lucas&al.95] 1. As reuse of behaviour implies substitutabi-lity it requires preservation of …
The Edge Hill Contribution to the INEX Interactive Social Book Search Task

In our contribution we use log-analysis to investigate whether participants in the INEX Interactive Social Book Search are able to use the new multi-stage interface and whether it provides any benefits over the traditional IR baseline interface. Our initial results show that participants are able to successfully use the new multi-stage interface, with no significant learning effects. Additionally, for the open task, the multi-stage interface actually enables the participants to collect more books than when using the baseline interface.
Redeem with privacy (RWP): privacy protecting framework for geo-social commerce

Users are encouraged to check in to commercial places in Geo-social networks (GSNs) by offering discounts on purchase. These promotions are commonly known as deals. When a user checks in, GSNs share the check-in record with the merchant. However, these applications, in most cases, do not explain how the merchants handle check-in histories nor do they take liability for any information misuse in this type of services. In practice, a dishonest merchant may share check-in histories with third parties or use them to track users' location. It may cause privacy breaches like robbery, discovery of sensitive information by combining check-in histories with other data, disclosure of visits to sensitive places, etc. In this work, we investigate privacy issues arising from the deal redemptions in GSNs. We propose a privacy framework, called Redeem with Privacy (RwP), to address the risks. RwP works by releasing only the minimum information necessary to carry out the commerce to the merchants. The framework is also equipped with a recommendation engine that helps users to redeem deals in such a way that their next visit will be less predictable to the merchants. Experimental results show that inference attacks will have low accuracy when users check in using the framework's recommendation.
Area and power efficient VLSI architecture for DCT

The objective of this paper is to design a VLSI based Discrete Cosine Transform (DCT) which is widely used in image and video compression, Video coding systems. This proposed design comprised of Distributed Arithmetic (DA) based VLSI architecture of DCT for reducing the power consumption. The circuit is designed with low power consumption techniques by using low power logical elements which can depend upon the system clock; this technique reduces the glitches and unwanted delays produced in design. The proposed system consists of two modules where the first module is basically the design of 1D Discrete cosine transform for existing method and 1D Discrete Cosine Transform using distributed architecture for proposed method. The simulation is performed on Modelsim6.5a simulator and power consumption can be calculated by using ALTERA power estimation tool.
Sparse coding for histograms of local binary patterns applied for image categorization: Toward a Bag-of-Scenes analysis

In this work1, we propose a novel approach for image categorization, which we will refer to as Bag-of-Scenes (BoS). It is based on the association of Sparse coding (Sc) and pooling techniques applied to histograms of multi-scale Local Binary Patterns (LBP) and its improved variant. This approach can be considered as a 2-layer hierarchical architecture. The first layer, encodes general local patch's structure via histograms of LBP, and the second, encodes the relationships between pre-analyzed LBP-scenes. Our method outperforms SIFT-based approaches using Sc techniques and can be trained efficiently with a simple linear SVM. Our BoS method achieves 87.02%, 87.71% and 79.05% of accuracy for Scene-15, UIUC-Sport and Caltech101 datasets respectively.
Solution structure of stem-loop α of the hepatitis B virus post-transcriptional regulatory element

Chronic hepatitis B virus (HBV) infections may lead to severe diseases like liver cirrhosis or hepatocellular carcinoma (HCC). The HBV post-transcriptional regulatory element (HPRE) facilitates the nuclear export of unspliced viral mRNAs, contains a splicing regulatory element and resides in the 3′-region of all viral transcripts. The HPRE consists of three sub-elements α (nucleotides 1151–1346), β1 (nucleotides 1347–1457) and β2 (nucleotides 1458–1582), which confer together full export competence. Here, we present the NMR solution structure (pdb 2JYM) of the stem-loop α (SLα, nucleotides 1292–1321) located in the sub-element α. The SLα contains a CAGGC pentaloop highly conserved in hepatoviruses, which essentially adopts a CUNG-like tetraloop conformation. Furthermore, the SLα harbours a single bulged G residue flanked by A-helical regions. The structure is highly suggestive of serving two functions in the context of export of unspliced viral RNA: binding sterile alpha motif (SAM-) domain containing proteins and/or preventing the utilization of a 3′-splice site contained within SLα.
The Role of Influenza in the Delay between Low Temperature and Ischemic Heart Disease: Evidence from Simulation and Mortality Data from Japan

Many studies have found that cardiovascular deaths mostly occur within a few days of exposure to heat, whereas cold-related deaths can occur up to 30 days after exposure. We investigated whether influenza infection could explain the delayed cold effects on ischemic heart diseases (IHD) as they can trigger IHD. We hypothesized two pathways between cold exposure and IHD: a direct pathway and an indirect pathway through influenza infection. We created a multi-state model of the pathways and simulated incidence data to examine the observed delayed patterns in cases. We conducted cross-correlation and time series analysis with Japanese daily pneumonia and influenza (P&I) mortality data to help validate our model. Simulations showed the IHD incidence through the direct pathway occurred mostly within 10 days, while IHD through influenza infection peaked at 4–6 days, followed by delayed incidences of up to 20–30 days. In the mortality data from Japan, P&I lagged IHD in cross-correlations. Time series analysis showed strong delayed cold effects in the older population. There was also a strong delay on intense days of influenza which was more noticeable in the older population. Influenza can therefore be a plausible explanation for the delayed association between cold exposure and cardiovascular mortality.
Constructing a Facet-Based and Personalized Just-in-Time Web Information Recommendation Application in a Multi-agent Environment

High precision is vital to the success of just-in-time information retrieval system. This paper attempts to improve it from two aspects: better understanding the user’s current need and providing a highly relevant information source. For the former, an algorithm that can model a user’s need in current context based on his behavior automatically is proposed, and for the latter, a mechanism is provided for the user to choose the information source he need by organizing all Web resources involved in a faceted way. All the algorithms and functions are encapsulated in several agents to constitute a multi-agent just-in-time Web information recommending application that help people write, and all these agent are constructed and managed by a multi-agent system middleware named “MAGE”.