Miracle-dz/UniFAR-FTUs huggingface dataset:
“ Model Theoretic Syntax is not Generative Enumerative Syntax with constraints ” : under what condition ?

The generative conception of grammars relies on the derivation process which, to its turn, depends on a hierarchical representation of syntax. We show in this paper how a fully constraint-based approach, avoiding such restriction, can constitute an alternative to generativity and form the basis of a framework for a model-theoretic conception of grammar.
Process-theoretic supervisor synthesis framework with data

Supervisory control theory deals with automated synthesis of supervisory controllers that coordinate high-level system behavior. We present a process theory with data that subsumes existing extensions of the traditional theory with parameters and data. To this end, we revisit the notion of partial bisimulation, which models controllability of nondeterministic systems, while retaining desirable algebraic properties. We illustrate our framework by presenting a parameterized model of a pipeless plant. At the end, we instantiate a concrete model of the plant and synthesize a nonblocking supervisor for it using the synthesis tool Supremica.
Psychometric Properties of the Brief Persian Version of the Difficulties in Emotion Regulation Scale (The DERS-16)

The Difficulties in Emotion Regulation Scale (DERS) is an established self-reported measure of emotion regulation difficulties. Recently, a brief 16-item version of this scale—the DERS-16—was developed. The goal of the present study was to extend the research on the DERS-16 by evaluating the reliability and validity of the Persian version in a university sample (N = 201). Results demonstrate that the Persian DERS-16 demonstrated excellent internal consistency, good test–retest reliability, and good concurrent validity. Furthermore, confirmatory factor analysis (CFA) supported the proposed factor structure. Thus, the Persian DERS-16 may offer a valid method for the assessment of overall emotion regulation difficulties as well as for the different facets of the construct.
Linear discriminative image processing operator analysis

In this paper, we propose a method to select a discriminative set of image processing operations for Linear Discriminant Analysis (LDA) as an application of the use of generating matrices representing image processing operators acting on images. First we show that generating matrices can be used for formulating LDA with increasing training samples, then analyze them as image processing operators acting on 2D continuous functions for compressing many large generating matrices by using PCA and Hermite decomposition. Then we propose Linear Discriminative Image Processing Operator Analysis, an iterative method for estimating LDA feature space along with a discriminative set of generating matrices. In experiments, we demonstrate that discriminative generating matrices outperform a non-discriminative set on the ORL and FERET datasets.
Supplementary text S 1 : Methods description and relationships between module preservation statistics

Here, we provide additional methodological details regarding the module preservation statistics. In the first section, we describe standard cross-tabulation based module preservation statistics. Specifically, we present three basic crosstabulation based statistics for determining whether modules in a reference data set are preserved in a test data set. These statistics do not assume that a test network is available. Instead, module assignments in both the reference and the test networks are needed. In the second section, we briefly review a hierarchical clustering procedure for module detection. Many methods exist for defining network modules. In this section, we describe the method used in our applications but it is worth repeating that our preservation statistics apply to most alternative module detection procedures. In the third section, we review the definition of signed and unsigned correlation networks. Correlation networks are a special case of general undirected networks in which the adjacency is constructed on the basis of correlations between quantitative variables. In the fourth section, we present module quality statistics that we are implemented in the modulePreservation R function. While our main article focuses on statistics that measure preservation of modules between a reference and a test network, we briefly discuss the application of some of the preservation statistics to the related but distinct task of measuring module quality in a single (reference) network. More precisely, the density and separability statistics can be applied to the reference network without a reference to a test network. The results can then be interpreted as measuring module quality, that is how closely interconnected the nodes of a module are or how well a module is separated from other modules in the network. In the fifth section, we review the notation for the singular value decomposition and for defining a module eigennnode. The section describes conditions when the eigenvector E is an optimal way of representing a correlation module. It also reviews the definition of propVarExpl (the proportion of the variance explained by the eigennode). We derive a relationship between propVarExpl and the module membership measures kME , which will be useful for deriving relationships between preservation statistics. In the sixth section, we investigate relationships between preservation statistics in correlation networks. An advantage of an (unsigned) weighted correlation network is that it allows one to derive simple relationships between network concepts [1, 2]. We characterize correlation modules where simple relationships exist between i) density-based preservation statistics, ii) connectivity based preservation statistics, and iii) separability based preservation statistics. Apart from studying relationships among preservation statistics in correlation networks, we also briefly describe relationships between preservation statistics in general networks. In the seventh section we briefly review the In-Group Proportion method [3].
Mean-shift background image modelling

Background modelling is widely used in computer vision for the detection of foreground objects in a frame sequence. The more accurate the background model, the more correct is the detection of the foreground objects. In this paper, we present an approach to background modelling based on a mean-shift procedure. The mean shift vector convergence properties enable the system to achieve reliable background modelling. In addition, histogram-based computation and the new concept of local basins of attraction allow us to meet the stringent real-time requirements of video processing.
Bohemians, Human Capital, and Regional Economic Growth

An emerging literature on the geography of bohemians argues that a region’s lifestyle and cultural amenities explain, at least partly, the unequal distribution of highly qualified people across space, which in turn, explains geographic disparities in economic growth. However, to date, there has been little or no empirical attempt to identify a causal relation. To identify the causal impact of bohemians on economic growth, we apply an instrumental variable approach using as an exogenous instrument the geographic distribution of bohemians prior to the Industrial Revolution in Germany. This distribution was primary the result of competition for prestige between courts and not of economic prosperity. Accordingly, the instrument is independent of today’s regional economic development. Focusing on the concentration of highly skilled people today that is explained by the proximity to exogenous concentrations of bohemians, the observed local average treatment effect supports the hypothesis of a positive impact of bohemians on regional economic development.
Test Statistics for Prospect and Markowitz Stochastic Dominances with Applications

Levy and Levy (2002, 2004) extend the stochastic dominance (SD) theory for risk averters and risk seekers by developing the prospect SD (PSD) and Markowitz SD (MSD) theory for investors with S‐shaped and reverse S‐shaped (RS‐shaped) utility functions, respectively. Davidson and Duclos (2000) develop SD tests for risk averters whereas Sriboonchitra et al. (2009) modify their statistics to obtain SD tests for risk seekers. In this paper, we extend their work by developing new statistics for both PSD and MSD of the first three orders. These statistics provide a tool to examine the preferences of investors with S‐shaped utility functions proposed by Kahneman and Tversky (1979) in their prospect theory and investors with RS‐shaped investors proposed by Markowitz (1952a). We also derive the limiting distributions of the test statistics to be stochastic processes. In addition, we propose a bootstrap method to decide the critical points of the tests and prove the consistency of the bootstrap tests. To illustrate the applicability of our proposed statistics, we apply them to study the preferences of investors with the corresponding S‐shaped and RS‐shaped utility functions vis‐a‐vis returns on iShares and vis‐a‐vis returns of traditional stocks and Internet stocks before and after the Internet bubble.
Novel Mechanism for Gonadotropin-Releasing Hormone Neuronal Migration Involving Gas6/Ark Signaling to p38 Mitogen-Activated Protein Kinase

ABSTRACT Gonadotropin-releasing hormone (GnRH) is the central regulator of the reproductive axis. Normal sexual maturation depends on the migration of GnRH neurons from the olfactory placode to the hypothalamus during development. Previously, we showed restricted expression of the membrane receptor adhesion-related kinase (Ark) in immortalized cell lines derived from migratory but not postmigratory GnRH neurons. In addition, Ark and GnRH transcripts were detected along the GnRH neuron migratory route in the E13 mouse cribriform plate. In the present study, we examined the role of Ark and its ligand, Gas6 (encoded by growth arrest-specific gene 6), in GnRH neuron migration. Gas6 stimulated lamellipodial extension, membrane ruffling, and chemotaxis of immortalized NLT GnRH neuronal cells via the Ark receptor. Gas6/Ark signaling promoted activation of the Rho family GTPase Rac, and adenoviral-mediated expression of dominant negative N17Rac abolished Gas6/Ark-induced actin cytoskeletal reorganization and migration of GnRH neuronal cells. In addition, p38 MAPK was activated downstream of Ark and Rac, and inhibition of p38 MAPK with either SB203580 or adenoviral dominant negative p38α also blocked Gas6/Ark-mediated migration. Finally, downstream of Rac and p38 mitogen-activated protein kinase (MAPK), Gas6/Ark signaling promoted activation of MAPK-activated protein kinase 2 and induced phosphorylation of HSP25, a known regulator of cortical actin remodeling. The data are the first to demonstrate a migratory signaling pathway downstream of Ark/Axl family receptors and suggest a previously unidentified role for p38 MAPK in neuronal migration. Furthermore, these studies support a potential role for Ark in the regulation of GnRH neuronal migration.
Content-enriched classifier for web video classification

With the explosive growth of online videos, automatic real-time categorization of Web videos plays a key role for organizing, browsing and retrieving the huge amount of videos on the Web. Previous work shows that, in addition to text features, content features of videos are also useful for Web video classification. Unfortunately, extracting content features is computationally prohibitive for real-time video classification. In this paper we propose a novel video classification framework that is able to exploit both content and text features for video classification while avoiding the expensive computation of extracting content features at classification time. The main idea of our approach is to utilize the content features extracted from training data to enrich the text based semantic kernels, yielding content-enriched semantic kernels. The content-enriched semantic kernels enable to utilize both content and text features for classifying new videos without extracting their content features. The experimental results show that our approach significantly outperforms the state-of-the-art video classification methods.
Asymptotic stability of two-dimensional continuous Roesser models with singularities at the stability boundary

It is shown that the existence of a negative semidefinite solution Q of the Lyapunov equation ATP+AP = Q with a positive definite block diagonal matrix P = PT together with simple additional conditions is sufficient to guarantee asymptotic stability. The stability conditions presented can be used to study a wider range of dynamical systems, including systems with singularities at the stability boundary, which cannot be exponentially stable.
Designing Modular Architectures in the Framework AKIRA ( DRAFT )

AKIRA is an open source framework designed for parallel, asynchronous and distributed computation, on the basis of some general architectural principles which are inspired by modular organization in biological systems. We introduce the motivation behind its design, the components of the framework and some examples of use: 1) a case study in a simple number domain, in which its capabilities such as context sensitiveness are highlighted; 2) an architecture for visual search tasks, in which a goal oriented behavior emerges from the cooperation and competition of many feature-specific modules, organized hierarchically; 3) a schema-based agent architecture, inspired by an ethological model of the praying mantis, including drives, schemas, routines and realizing visual and motor behavior in a realistic simulated environment.
Performance Analysis of Graphene Bilayer Transistors Through Tight-Binding Simulations

A simulation study of a tunable-gap bilayer graphene FET with independent gates is performed with a numerical solver based on the self-consistent solution of the Poisson and Schrodinger equations within the NEGF formalism. The applied vertical field manages to induce an energy gap, but its value is not large enough to suppress band-to-band tunneling and to obtain acceptable I ON /I OFF ratio for CMOS device operation.
Transport in quantum dots from the integrability of the Anderson model

In this work we exploit the integrability of the two-lead Anderson model to compute transport properties of a quantum dot, in and out of equilibrium. Our method combines the properties of integrable scattering together with a Landauer-Buttiker formalism. Although we use integrability, the nature of the problem is such that our results are not generically exact, but must only be considered as excellent approximations which nonetheless are valid all the way through crossover regimes. The key to our approach is to identify the excitations that correspond to scattering states and then to compute their associated scattering amplitudes. We are able to do so both in and out of equilibrium. In equilibrium and at zero temperature, we reproduce the Friedel sum rule for an arbitrary magnetic field. At finite temperature, we study the linear response conductance at the symmetric point of the Anderson model, and reproduce Costi et al.'s numerical renormalization group computation of this quantity. We then explore the out-of-equilibrium conductance for a near-symmetric Anderson model, and arrive at quantitative expressions for the differential conductance, both in and out of a magnetic field. We find the expected splitting of the differential conductance peak into two in a finite magnetic field, $H$. We determine the width, height, and position of these peaks. In particular we find for H >> T_k, the Kondo temperature, the differential conductance has maxima of e^2/h occuring for a bias V close to but smaller than H. The nature of our construction of scattering states suggests that our results for the differential magneto-conductance are not merely approximate but become exact in the large field limit.
Detection and Quantitation of Myocardial Infarction In Vivo Using Transmission Computed Tomography

In vivo studies were performed on 28 dogs to evaluate the usefulness of transmission computed tomography (CT) in the detection and quantitation of experimentally induced myocardial infarction. Intravenously administered contrast material was required to define the internal structure of the heart and to differentiate normal from infarcted tissue. Transmural infarcts with homogeneous central regions were visualized as areas of diminished contrast enhancement compared with the normal myocardium. All transmural infarcts of at least 24 hours' duration showed a surrounding border zone of patchy necrosis that was variable in size and had high CT numbers due to slow washout of the contrast material from this region. Infarct area determined from the images for individual slices correlated well (r = 0.976) with that calculated using pathology. The technique is very sensitive and can detect infarction within a papillary muscle. Nontransmural or patchy infarcts show up as areas of diffuse contrast enhancement without a central core of diminished enhancement. The distribution of the contrast material is similar to that of technetium-99m pyrophosphate in the border zone of the infarct in infusion studies, but in bolus studies it behaves more like thallium-201.
The importance of ultraviolet and near-infrared sensitivity for visual discrimination in two species of lacertid lizards

Male and female Lacertid lizards often display conspicuous coloration that is involved in intraspecific communication. However, visual systems of Lacertidae have rarely been studied and the spectral sensitivity of their retinal photoreceptors remains unknown. Here, we characterise the spectral sensitivity of two Lacertid species from contrasting habitats: the wall lizard Podarcis muralis and the common lizard Zootoca vivipara. Both species possess a pure-cone retina with one spectral class of double cones and four spectral classes of single cones. The two species differ in the spectral sensitivity of the LWS cones, the relative abundance of UVS single cones (potentially more abundant in Z. vivipara) and the coloration of oil droplets. Wall lizards have pure vitamin A1-based photopigments, whereas common lizards possess mixed vitamin A1 and A2 photopigments, extending spectral sensitivity into the near infrared, which is a rare feature in terrestrial vertebrates. We found that spectral sensitivity in the UV and near infrared improves discrimination of small variations in throat coloration among Z. vivipara. Thus, retinal specialisations optimise chromatic resolution in common lizards, indicating that the visual system and visual signals might co-evolve.
SLA Based Profit Optimization in Multi-tier Systems

Nowadays, large service centers provide computational capacity to many customers by sharing a pool of IT resources. The service providers and their customers negotiate utility based service level agreement (SLA) to determine the costs and penalties on the base of the achieved performance level. The system is often based on a multi-tier architecture to service requests. The service provider would like to maximize the SLA revenues, while minimizing its operating costs. The system we consider is based on a centralized network dispatcher which controls the allocation of applications to servers, the request volumes at various servers and the scheduling policy at each server. The dispatcher can also decide to turn ON or OFF servers depending on the system load. This paper designs a resource allocation scheduler for such multi-tier environments so as to maximize the profits associated with multiple class SLAs. The overall problem is NP-hard. We develop heuristic solutions by implementing a local-search algorithm. Results are presented to demonstrate the benefits of our approach
Identify user variants based on user behavior on social media

In social media, users are allowed to express their opinions by commenting on an item or rating an item with scores. The collection of user reviews would generate a positive or negative influence to the media audience. Some malicious users may create multiple variant accounts on the same social media so as to influence or manipulate public opinions for business or criminal purposes. To maintain good social environment, it is necessary to find those fake users. In this paper, we investigate the user variants identification problem using both user behavior and item related information. We study the characteristics of user behaviors on social media and introduce two concepts visibility and distingushibility to preliminarily quantify whether a fake user can be identified. To better understand user intention and characteristics, we profile a user with apparent and implicit features, which are extracted from three aspects: User Generated Contents (UGC), user behavior context and item information. Based on these features, we propose the user Variants Identification Problem (VIP) and an identification algorithm, which finds the top-k similar variants in a social media. We evaluate our methods against two real datasets MovieLens and Amazon and make comparison on the effectiveness against different features in identifying user variants.
Overlap Among Major Web Search Engines

Our paper examined the overlap among results retrieved by three major Web search engines for a large set of more than 10,316 queries. Previous smaller studies have discussed the lack of overlap in results returned by Web search engines for the same queries. Our large-scale study measured the overlap of first page results (both non-sponsored and sponsored) across three major Web search engines - Google, Ask Jeeves and Yahoo - using a large number of randomly selected Dogpile.com queries submitted within a 24 hour - 36 hour period. We then compared the results to results retrieved for the same queries from the meta-search engine Dogpile.com. The percent of total results unique to only one of the three major Web search engines was 85%. 12% of total search results were found on two of the three Web search engines, and 3% of results were found across all three Web search engines. This small level of overlap reflects major differences in Web search engines retrieval and ranking results. Results point to the value of meta-search engines in Web retrieval to overcome the biases of individual search engines
Journalistic Views on Hard and Soft News: Cross-Validating a Popular Concept in a Factorial Survey

Despite the popularity of the concept of hard and soft news, researchers regularly criticize the vague definitions and inconsistent conceptualizations. Following claims for standardization of concept in journalism research, this article aims to cross-validate the most recent understanding of the concept. We conducted a factorial survey with newspaper journalists to probe the question as to which of the theoretically assumed dimensions of the concept are referred to by journalists to distinguish hard from soft news. We find the dimensions “topic,” “relevance,” “framing,” and “opinion” to exert influence on journalists’ understanding of the concept.
Sub‐National Institutional Contingencies, Network Positions, and IJV Partner Selection

The differences in sub‐national institutions within large and complex emerging economies have been increasingly noted. Drawing on social network theory and the institution‐based view, we argue that two network structural attributes of domestic firms – centrality and structural holes – have distinctive values in different sub‐national regions where institutional contexts differ widely. In addition, these sub‐national institutional contingencies influence the attractiveness of different network attributes to foreign entrants seeking international joint venture (IJV) partners. Specifically, in regions where the degree of marketization is high, centrally positioned domestic firms are more likely to be selected by foreign entrants as IJV partners. In regions where the degree of marketization is low, domestic broker firms are more attractive IJV partners. Results from the electrical and information technology industries in 18 provinces in China largely support our hypotheses.