Miracle-dz/UniFAR-FTUs huggingface dataset:
Decomposing Global Cost Functions

Similarly to what has been done with Global Constraints in Constraint Programming, different results have been recently published on Global Cost Functions in weighted CSPs, defining the premises of a Cost Function Programming paradigm. In this paper, in the spirit of Berge-acyclic decompositions of global constraints such as Regular, we explore the possibility of decomposing Global Cost Functions in such a way that enforcing soft local consistencies on the decomposed cost function offers guarantees on the level of consistency enforced on the original global cost function. We show that an extension of Directional Arc Consistency to arbitrary arities and Virtual Arc Consistency offer specific guarantees.We conclude by preliminary experiments on Weighted Regular decompositions that show that decompositions may be very useful to easily integrate global cost functions in existing solvers with good efficiency.
A Study on Energy Consumption and Economic Growth of Three Northeastern Provinces in China

This paper studies the aggregate and structural relationship between energy consumption and economic growth of three northeastern provinces using the grey relational models. Result indicates that there exist distinctive internal economic structure in all three provinces. Whereafter we find that the energy consumption of Jilin has the highest correlation to the economic growth of all three provinces and it's dependence of economic growth on energy consumption is loweast in of all provinces using Grey relatonal analysis. At last we come up some suggestion that the short-term dependence on energy consumption in economic growth of the three northeastern provinces in china should not be ignored.
Electret based energy harvester using a shared si electrode

In this study, an electret based energy harvester with a single silicon structure that shares harvesting counter electrodes and charging grid is demonstrated. The shared electrode provide the batch fabrication process that can avoid the charge leakage from the charged electret. The mass structure supported by the thin Si spring has resonant frequency of 40 Hz. The harvesting demonstration showed the 0.23 µW at 10 Hz, 0.1 G with load resistance of 1 MΩ.
An Equivalent Second Order Model Based on Flow and Speed

Traffic models developed for control include first order LWR model and second order models. The first order model is essentially density dynamics which states the conservation of the number of vehicles in a section of highway. Most second order models are essentially a speed dynamics coupled with the first order density dynamics. There are several second order models but most are for explaining traffic flow. Only a couple of second order models were developed for traffic control purpose. The most popular one is the Payne-Papageorgiou model. Due to point sensor detection limit in highways such as inductive loops, flow estimation is easy and reasonably accurate while density estimation is very difficult. This is the motivation for us to have a look at flow dynamics in place of density. It turns out that flow dynamics of first order cannot be well-defined contrasted to the Cell Transmission Model. However, a flow-speed dynamics can be obtained which is equivalent to the density-speed dynamics of the PaynePapageorgiou model.
A Single Counterexample Leads to Moral Belief Revision

What kind of evidence will lead people to revise their moral beliefs? Moral beliefs are often strongly held convictions, and existing research has shown that morality is rooted in emotion and socialization rather than deliberative reasoning. In addition, more general issues-such as confirmation bias-further impede coherent belief revision. Here, we explored a unique means for inducing belief revision. In two experiments, participants considered a moral dilemma in which an overwhelming majority of people judged that it was inappropriate to take action to maximize utility. Their judgments contradicted a utilitarian principle they otherwise strongly endorsed. Exposure to this scenario led participants to revise their belief in the utilitarian principle, and this revision persisted over several hours. This method provides a new avenue for inducing belief revision.
Improving the Measurement of Disease Activity for Patients with Rheumatoid Arthritis: Validation of an Electronic Version of the Routine Assessment of Patient Index Data 3

Introduction. An electronic Routine Assessment of Patient Index Data 3 (RAPID 3) was incorporated into our electronic health records (EHRs) which did not replicate the visual presentation of the paper version. This study validated the electronic RAPID 3 compared to the paper version. Methods. Rheumatoid arthritis (RA) patients (n = 50) completed both the electronic RAPID 3 online in the week prior to and a paper version on the day of their clinic visit. Results. Paired t-test showed no significant difference (p value = 0.46) between versions. Conclusion. The electronic version of RAPID 3 is valid and can be easily integrated in care of RA patients.
Interleukin 12–dependent Interferon ␥ Production by Cd8 ␣ Ϩ Lymphoid Dendritic Cells

We investigated the role of antigen-presenting cells in early interferon (IFN)-␥ production in normal and recombinase activating gene 2–deficient (Rag-2 ϪրϪ) mice in response to Listeria monocytogenes (LM) infection and interleukin (IL)-12 administration. Levels of serum IFN-␥ in Rag-2 ϪրϪ mice were comparable to those of normal mice upon either LM infection or IL-12 injection. Depletion of natural killer (NK) cells by administration of anti-asialoGM1 antibodies had little effect on IFN-␥ levels in the sera of Rag-2 ϪրϪ mice after LM infection or IL-12 injection. Incubation of splenocytes from NK cell–depleted Rag-2 ϪրϪ mice with LM resulted in the production of IFN-␥ that was completely blocked by addition of anti–IL-12 antibodies. Both dendritic cells (DCs) and monocytes purified from splenocytes were capable of producing IFN-␥ when cultured in the presence of IL-12. Intracellular immunofluorescence analysis confirmed the IFN-␥ production from DCs. It was further shown that IFN-␥ was produced predominantly by CD8 ␣ ϩ lymphoid DCs rather than CD8 ␣ Ϫ myeloid DCs. Collectively, our data indicated that DCs are potent in producing IFN-␥ in response to IL-12 produced by bacterial infection and play an important role in innate immunity and subsequent T helper cell type 1 development in vivo. Key words: recombinase-activating gene 2 knockout mouse • nonobese diabetic-severe combined immunodeficiency disease mouse • ␥ c knockout mouse • natural killer cells • Listeria monocytogenes D endritic cells (DCs) are bone marrow (BM)-derived professional APCs. Peripheral DCs are characterized by high capability for antigen capture and processing, migration to lymphoid organs, and expression of various costimulatory molecules for antigen-specific lymphocyte activation. Cyto-kine secretion by DCs initiates and enhances both innate and acquired immunity (1). Activation of macrophages and DCs by infectious agents leads to secretion of IL-12, which subsequently induces IFN-␥ production by NK cells and directs Th1 development. IFN-␥ , in turn, acts on monocytes to augment IL-12 secretion and to produce nitric oxide that eradicates infected microbes (2, 3). Thus, IL-12 and IFN-␥ comprise a positive feedback system, which is probably required for optimal production of IL-12 in vivo (4, 5). Studies using neutralizing Abs against IFN-␥ and mice deficient for IL-12 or IFN-␥ have confirmed the importance of these cytokines for innate immunity and Th1 development for controlling intracellu-lar pathogens (6–11). It was generally assumed that the only cells producing IFN-␥ in response to IL-12 are NK and T cells. However, recent studies have shown that …
Matching Value and Market Design in Online Advertising Networks: An Empirical Analysis

Advertising networks have recently played an increasingly important role in the online advertising market. Critical to the success of an advertising network are two mechanisms: an allocation mechanism that efficiently matches advertisers with publishers and a pricing scheme that maximally extracts surplus from the matches. In this paper, we quantify the value and investigate the determinants of a successful advertiser-publisher match, using data from Taobao’s advertising network. A counterfactual experiment reveals that the platform’s profit under a decentralized allocation mechanism is close to the profit level when the platform centrally assigns the matching under perfect platform knowledge of matching values. In another counterfactual experiment, we explore the effect of platform technology and revenue model on the strategic choice of the pricing schemes of list price versus generalized second price (GSP) auction pricing. We find that platforms that profit from the advertiser side may have less incentive to adopt GSP auction than platforms that profit from the publisher side.
Copulae as a new tool in financial modelling

The paper presents an overview of financial applications of copulas. Copulas permit to represent joint distribution functions by splitting the marginal behavior, embedded in the marginal distributions, from the dependence, captured by the copula itself. The splitting proves to be very helpful not only in the modelling phase, but also in the estimation or simulation one. Essentially, it provides a straighforward way to extend financial modelling from the usual joint normality assumption to more general joint distributions, even preserving the normality assumption on the marginals. The paper puts into evidence the advantages of the copula representation with respect to the joint distribution one, with special reference to applications in pricing and risk measurement.
Approximate BDD Optimization with Prioritized ε-Preferred Evolutionary Algorithm

Approximate computing has gained high attention in various applications that can benefit from a reduction in costs by lowering the accuracy. In this paper we present an optimization approach for functional approximation of Binary Decision Diagrams (BDDs) which are known for their widespread applications in electronic design automation and formal verification. We propose a three-objective ε-preferred evolutionary algorithm with the first objective set to the BDD size which is given higher priority to the two other objectives set to errors caused by approximation. This is highly demanded by the application to ensure that the minimum size for the approximated BDD is accessible when the error metrics meet certain threshold values. While BDD size minimization is guaranteed by incorporating priority, the use of ε in the proposed approach ensures to guide the search towards desired error values in parallel. Experiments confirm the efficiency of the proposed approach by a size improvement of 64.24% at a fair cost of 3.86% inaccuracy on average.
Window Effect in the Power Spectrum Analysis of a Galaxy Redshift Survey

We investigate the effect of the window function on the multipole power spectrum in two different ways. First, we consider the convolved power spectrum including the window effect, which is obtained by following the familiar (FKP) method developed by Feldman, Kaiser and Peacock. We show how the convolved multipole power spectrum is related to the original power spectrum, using the multipole moments of the window function. Second, we investigate the deconvolved power spectrum, which is obtained by using the Fourier deconvolution theorem. In the second approach, we measure the multipole power spectrum deconvolved from the window effect. We demonstrate how to deal with the window effect in these two approaches, applying them to the Sloan Digital Sky Survey (SDSS) luminous red galaxy (LRG) sample.
Car navigation with route information sharing for improvement of traffic efficiency

This research is intended to increase drivers' utility by reducing traffic congestion. To attain our purpose, we propose a simple route guidance mechanism based on route information sharing (RIS). Drivers using the RIS give planned route details to the route information server, which then sends accumulated traffic information based on those routes to drivers. Multiagent simulation in a lattice network and a radial and ring network confirmed that: i) as the drivers using the RIS increased, the travel time of both the drivers using the RIS and the other drivers decreased; ii) the travel times of drivers using the RIS were substantially shorter than those of drivers using other mechanisms.
Compiler-Directed Power Management for Superscalars

Modern superscalar CPUs contain large complex structures and diverse execution units, consuming wide dynamic power range. Building a power delivery network for the worst-case power consumption is not energy efficient and often is impossible to fit in small systems. Instantaneous power excursions can cause voltage droops. Power management algorithms are too slow to respond to instantaneous events. In this article, we propose a novel compiler-directed framework to address this problem. The framework is validated on a 4th Generation Intel® Core™ processor and with simulator on output trace. Up to 16% performance speedup is measured over baseline for the SPEC CPU2006 benchmarks.
A novel approach to stable IIR digital filter design

In this paper, the problem of designing stable infinite impulse response (IIR) digital filters is discussed. Based on a continuous-time state-space structure and the generalized bilinear transformation, a new parametrization for stable IIR digital filter design is proposed. One of the advantages of this parametrization is that the corresponding stability region is the entire parameter space and hence the design can be carried out using well-established unconstrained optimization methods. Two design examples are presented to demonstrate the performance of the proposed approach and to compare it with an existing one, which show the superior behavior of the filters obtained with the proposed approach to those achieved with the existing one.
FAD, a functional programming language that supports abstract data types

The paper outlines the programming language FAD. FAD is a functional programming system of the kind described by Backus (Backus78]. FAD supports abstract data types, parameterized types, and generic functions. A single scope rule establishes the encapsulation requirements for data type specification and program structuring. Certain syntactic additions improve program readability as compared to pure functional notation.
Molecular Identification, Phylogenetic Status, and Geographic Distribution of Culicoides oxystoma (Diptera: Ceratopogonidae) in Israel

Culicoides oxystoma (Diptera: Ceratopogonidae) is an important vector species, reported mainly from Asia, with high potential to transmit viral diseases affecting livestock. In Japan, many arboviruses have been isolated from C. oxystoma, suggesting it as a key player in the epidemiology of several Culicoides-borne diseases. Over the years, C. oxystoma has also been reported in the Middle East region, including Israel. In this region, however, C. oxystoma cannot be easily distinguished morphologically from its sibling species included in the Culicoides schultzei complex. We therefore used genomic data for species identification and phylogeny resolution. Phylogenetic analyses based on internal transcribed spacer 1 (ITS-1) of ribosomal DNA and the mitochondrial gene encoding cytochrome oxidase subunit I (COI) showed that C. oxystoma from Israel is closely related to C. oxystoma from Japan. Using differential probing PCR, we showed that C. oxystoma is distributed all over the country, especially in Mediterranean climate regions. Culicoides oxystoma is less common or even absent in arid regions, while the other genetic cluster of C. schultzei complex was found only in the east of the country (mostly arid and semiarid regions). The molecular finding of C. oxystoma in wide geographical regions, together with its high proportion in the general Culicoides population and its vectoring potential, imply that it may be an important vector species in the Middle East.
Second Order Online Collaborative Filtering

Collaborative Filtering (CF) is one of the most successful learning techniques in building real-world recommender systems. Traditional CF algorithms are often based on batch machine learning methods which suer from several critical drawbacks, e.g., extremely expensive model retraining cost whenever new samples arrive, unable to capture the latest change of user preferences over time, and high cost and slow reaction to new users or products extension. Such limitations make batch learning based CF methods unsuitable for real-world online applications where data often arrives sequentially and user preferences may change dynamically and rapidly. To address these limitations, we investigate online collaborative ltering techniques for building live recommender systems where the CF model can evolve on-the-y over time. Unlike the regular rst order CF algorithms
Modulation of the Inhibitory Substrate Properties of Oligodendrocytes by Platelet-Derived Growth Factor

Although growth cones typically collapse after encountering O1/galactocerebroside (GalC)-positive oligodendrocytes, the majority of growth cones traversed oligodendrocytes, which were raised for 8–10 d in medium containing 10 ng/ml platelet-derived growth factor (PDGF). Oligodendrocytes raised 8–10 d in control medium caused growth cone collapse as they normally do, but failed to elicit this response after being transferred to PDGF-containing medium for an additional 8–10 d. The opposite was observed when PDGF-treated oligodendrocytes were brought to control medium. Growth cones collapsed when contacting these cells. Oligodendrocytes also lost their collapse-inducing activity when raised in medium conditioned by astrocytes, known to produce PDGF. Antibody IN-1 is directed against neurite growth inhibitors (NI), proteins of 35 and 250 kDa on the surface of O1/GalC-positive oligodendrocytes, which are known to elicit growth cone collapse. IN-1 immunoreactivity was markedly reduced in PDGF-treated oligodendrocytes. However, both PDGF-treated and control oligodendrocytes exhibited myelin-associated glycoprotein, proteolipid protein, and myelin basic protein immunoreactivity. This suggests that PDGF-treatment affects NI expression but does not interfere with the expression of advanced myelin marker proteins. Because NI cause growth cone collapse, the loss of collapse-inducing activity by PDGF-treated oligodendrocytes suggests that PDGF regulates, directly or indirectly, the expression of these proteins.
Appendix to “ Online ` 1-Dictionary Learning with Application to Novel Document Detection ”

2 ‖z− Fx−Gy‖22 , where ρ ∈ R is the Lagrangian multiplier and φ > 0 is a penalty parameter. ADMM utilizes the separability form of (1) and replaces the joint minimization over x and y with two simpler problems. The ADMM first minimizes L over x, then over y, and then applies a proximal minimization step with respect to the Lagrange multiplier ρ. The entire ADMM procedure is summarized in Algorithm 1. The γ > 0 is a constant. The subscript (i) denotes the ith iteration of the ADMM procedure. The ADMM procedure has been proved to converge to the global optimal solution under quite broad conditions [2]. Algorithm 1 : ADMM Update Equations for Solving (1)
MODELING AFM TIP DYNAMICS THROUGH DIFFUSION IN TIME-PERIODIC POTENTIALS

We consider the case of a chemically active AFM tip experiencing a bistable potential near a substrate while being driven by a periodic force of frequency Ω. The average position of such a tip traces a hysteretic loop which encircles an area π (Ω), which can reveal information on the tip-substrate interaction and on tip friction. We model this situation via a Smoluchowski diffusion equation and provide numerical results as well as construct asymptotic expansions for (Ω) in the limits of high and low frequency.
Face Recognition Using Diagonal 2D Linear Discriminant Analysis

Recently, two methods called 2D principle component analysis (2DPCA) and 2D linear discriminant analysis (2DLDA) were proposed to overcome the shortcomings in classical PCA and LDA such as time-consuming and singularity. They were used widely in image representation and recognition. A limitation of 2D methods is that, they only reflect the information between rows of images, while discarding columns information. More recently, a method called diagonal PCA (DiaPCA) was proposed to reserve the correlations between variations of rows and those of columns of images. DiaPCA seeks projection vectors from diagonal face images without image-to-vector transformation. However, DiaPCA does not involve any discrimination features, which are more than desirable in face recognition. In this paper, we propose a method named diagonal 2DLDA (Dia2DLDA) for face recognition. The proposed method projects face image samples by using an optimal projection vectors that derive from the diagonal representation of the image samples. Then, the projected image samples are employed to extract the discrimination features. The method compared with existing 2D schemes on two face databases. Results indicate that the performance of the Dia2DLDA overall better than other methods
Contrast compensation for back-lit and front-lit color face images via fuzzy logic classification and image illumination analysis

Conventional contrast enhancement methods have two shortcomings. First, most of them do not produce satisfactory enhancement results for face images with back-lit or front-lit. Second, most of them need transformation functions and parameters which are specified manually. Thus, this paper proposes an automatic and parameter-free contrast compensation algorithm for color face images. This method includes: RGB color space is transformed to YIQ color space. Fuzzy logic is used to classify the color images into back-lit, normal-lit, and front-lit categories. Image illumination analysis is used to analyze the image distribution. The input image is compensated by piecewise linear based compensation method. Finally, the compensation image is transformed back to RGB color space. This novel compensation method is automatic and parameter-free. Our experiments included back-lit and front-lit images. Experiment results show that the performance of the proposed method is better than other available methods in visual perception measurements.
Comparative study of behavioural tests in the SOD1G93A mouse model of amyotrophic lateral sclerosis

In preclinical trials, a sensitive functional test is required to detect changes in the motor behaviour of the SOD1G93A mouse model of amyotrophic lateral sclerosis (ALS). We evaluated changes in body weight and motor impairment in behavioural tests, such as the rotarod, the hanging-wire test and the treadmill, of transgenic and wild type mice. We found differences in detection of the onset of symptoms and progression of the disease between the different tests assessed. Moreover, the data showed significant gender differences in the motor behaviour of this mouse model. The rotarod and the hanging-wire test were more sensitive to detect early motor impairment. Moreover, the results suggested that the rotarod and hanging-wire became the most accurate tests rather than treadmill to characterise the ALS disease phenotype.