Miracle-dz/UniFAR-FTUs huggingface dataset:
Avoidance Binge Eating and Weight Control : The Role of Experiential

Two thirds of the adults in the United States are overweight or obese. Binge eating is a barrier to treatment adherence and sustained weight loss, and can be seen as a form of experiential avoidance. The current study analyzed the impact of binge eating on weight reduction in a previously published study of a 1-day acceptance and commitment therapy (ACT) workshop (N = 83) and the psychological processes accounting for the binge-eating results. ACT participants reported less binge eating, which in turn significantly mediated changes in weight. Mediation analyses also showed that reductions in binge eating were mediated by changes in experiential avoidance. The study suggests that ACT and its targeted processes of change may be particularly relevant to binge eating, and that targeting binging is a possible pathway for improving weight management.
Resources for the Detection of Conventionalized Metaphors in Four Languages

This paper describes a suite of tools for extracting conventionalized metaphors in English, Spanish, Farsi, and Russian. The method depends on three significant resources for each language: a corpus of conventionalized metaphors, a table of conventionalized conceptual metaphors (CCM table), and a set of extraction rules. Conventionalized metaphors are things like “escape from poverty” and “burden of taxation”. For each metaphor, the CCM table contains the metaphorical source domain word (such as “escape”) the target domain word (such as “poverty”) and the grammatical construction in which they can be found. The extraction rules operate on the output of a dependency parser and identify the grammatical configurations (such as a verb with a prepositional phrase complement) that are likely to contain conventional metaphors. We present results on detection rates for conventional metaphors and analysis of the similarity and differences of source domains for conventional metaphors in the four languages.
The Lost South Gobi Microcontinent: Protolith Studies of Metamorphic Tectonites and Implications for the Evolution of Continental Crust in Southeastern Mongolia

The Central Asian Orogenic Belt, or Altaids, is an amalgamation of volcanic arcs and microcontinent blocks that records a complex late Precambrian–Mesozoic accretionary history. Although microcontinents cored by Precambrian basement are proposed to play an integral role in the accretion process, a lack of isotopic data hampers volume estimates of newly produced arc-derived versus old-cratonic crust in southeastern Mongolia. This study investigates metamorphic tectonites in southern Mongolia that have been mapped as Precambrian in age, largely on the basis of their high metamorphic grade and high strain. Here we present results from microstructural analyses and U-Pb zircon geochronology on samples from Tavan Har (44.05° N, 109.55° E) and the Yagan-Onch Hayrhan metamorphic core complex (41.89° N, 104.24° E). Our results show no compelling evidence for Precambrian basement in southeastern Mongolia. Rather, the protoliths to all tectonites examined are Paleozoic–Mesozoic age rocks, formed during Devonian–Carboniferous arc magmatism and subsequent Permian–Triassic orogenesis during collision of the South Mongolia arc with the northern margin of China. These results yield important insights into the Paleozoic accretionary history of southern Mongolia, including the genesis of metamorphic and igneous basement during the Paleozoic, as well as implications for subsequent intracontinental reactivation.
Using Kinect for real-time emotion recognition via facial expressions

Emotion recognition via facial expressions (ERFE) has attracted a great deal of interest with recent advances in artificial intelligence and pattern recognition. Most studies are based on 2D images, and their performance is usually computationally expensive. In this paper, we propose a real-time emotion recognition approach based on both 2D and 3D facial expression features captured by Kinect sensors. To capture the deformation of the 3D mesh during facial expression, we combine the features of animation units (AUs) and feature point positions (FPPs) tracked by Kinect. A fusion algorithm based on improved emotional profiles (IEPs) and maximum confidence is proposed to recognize emotions with these real-time facial expression features. Experiments on both an emotion dataset and a real-time video show the superior performance of our method.
Lexicalised Configuration Grammars

This paper introduces Lexicalised Configuration Grammars (lcgs), a new declarative framework for natural language syntax. lcg is powerful enough to encode a large number of existing grammar formalisms, facilitating their comparison from the perspective of graph configuration (Debusmann et al., 2005). Once a formalism has been encoded as an lcg, the framework oers various means to increase its expressivity in a controlled manner. Trading expressive power for computational complexity, this makes it possible to model syntactic phenomena in novel ways. Parsing algorithms for lcgs lend themselves to a combination of chartbased and constraint-based processing techniques, allowing both to bring in their strengths.
Software Engineering Metrics: What Do They Measure and How Do We Know?

Construct validity is about the question, how we know that we're measuring the attribute that we think we're measuring? This is discussed in formal, theoretical ways in the computing literature (in terms of the representational theory of measurement) but rarely in simpler ways that foster application by practitioners. Construct validity starts with a thorough analysis of the construct, the attribute we are attempting to measure. In the IEEE Standard 1061, direct measures need not be validated. "Direct" measurement of an attribute involves a metric that depends only on the value of the attribute, but few or no software engineering attributes or tasks are so simple that measures of them can be direct. Thus, all metrics should be validated. The paper continues with a framework for evaluating proposed metrics, and applies it to two uses of bug counts. Bug counts capture only a small part of the meaning of the attributes they are being used to measure. Multidimensional analyses of attributes appear promising as a means of capturing the quality of the attribute in question. Analysis fragments run throughout the paper, illustrating the breakdown of an attribute or task of interest into sub-attributes for grouped study.
A Novel Route to Fabricate High-Performance 3D Printed Continuous Fiber-Reinforced Thermosetting Polymer Composites

Recently, 3D printing of fiber-reinforced composites has gained significant research attention. However, commercial utilization is limited by the low fiber content and poor fiber–resin interface. Herein, a novel 3D printing process to fabricate continuous fiber-reinforced thermosetting polymer composites (CFRTPCs) is proposed. In brief, the proposed process is based on the viscosity–temperature characteristics of the thermosetting epoxy resin (E-20). First, the desired 3D printing filament was prepared by impregnating a 3K carbon fiber with a thermosetting matrix at 130 °C. The adhesion and support required during printing were then provided by melting the resin into a viscous state in the heating head and rapidly cooling after pulling out from the printing nozzle. Finally, a powder compression post-curing method was used to accomplish the cross-linking reaction and shape preservation. Furthermore, the 3D-printed CFRTPCs exhibited a tensile strength and tensile modulus of 1476.11 MPa and 100.28 GPa, respectively, a flexural strength and flexural modulus of 858.05 MPa and 71.95 GPa, respectively, and an interlaminar shear strength of 48.75 MPa. Owing to its high performance and low concentration of defects, the proposed printing technique shows promise in further utilization and industrialization of 3D printing for different applications.
N-myc and Noncoding RNAs in Neuroblastoma

Neuroblastoma is a pediatric tumor of the sympathetic nervous system. Amplification and overexpression of the MYCN proto-oncogene occurs in approximately 20% of neuroblastomas and is associated with advanced stage disease, rapid tumor progression, and poor prognosis. MYCN encodes the transcriptional regulator N-myc, which has been shown to both up- and downregulate many target genes involved in cell cycle, DNA damage, differentiation, and apoptosis in neuroblastoma. During the last years, it has become clear that N-myc also modulates the expression of several classes of noncoding RNAs, in particular microRNAs. MicroRNAs are the most widely studied noncoding RNA molecules in neuroblastoma. They function as negative regulators of gene expression at the posttranscriptional level in diverse cellular processes. Aberrant regulation of miRNA expression has been implicated in the pathogenesis of neuroblastoma. While the N-myc protein is established as an important regulator of several miRNAs involved in neuroblastoma tumorigenesis, tumor suppressor miRNAs have also been documented to repress MYCN expression and inhibit cell proliferation of MYCN-amplified neuroblastoma cells. It is now becoming increasingly evident that N-myc also regulates the expression of long noncoding RNAs such as T-UCRs and ncRAN. This review summarizes the current knowledge about the interplay between N-myc and noncoding RNAs in neuroblastoma and how this contributes to neuroblastoma tumorigenesis. Mol Cancer Res; 10(10); 1243–53. ©2012 AACR.
GNU Scientific Library - Reference Manual, Third Edition, for GSL Version 1.12

Mark Galassi Los Alamos National Laboratory Jim Davies Department of Computer Science, Georgia Institute of Technology James Theiler Astrophysics and Radiation Measurements Group, Los Alamos National Laboratory Brian Gough Network Theory Limited Gerard Jungman Theoretical Astrophysics Group, Los Alamos National Laboratory Patrick Alken Department of Physics, University of Colorado at Boulder Michael Booth Department of Physics and Astronomy, The Johns Hopkins University Fabrice Rossi University of Paris-Dauphine
Th1, Th2, Th17 and Regulatory T Cell Pattern in Psoriatic Patients: Modulation of Cytokines and Gene Targets Induced by Etanercept Treatment and Correlation with Clinical Response

Background: Psoriasis is sustained by pro-inflammatory CD4+ T helper cells mainly belonging to the Th1, Th17 and Th22 lineage. Objective: To identify whether treatment with the anti-tumour-necrosis-factor antagonist etanercept is able to induce significant modulations in transcription factor and cytokine mRNA gene expressions related to the different T cell immune response polarization (Th1, Th2, Th17 and regulatory T cells, Treg) and to correlate them with clinical response. Methods: The study population included 19 psoriasis patients treated with etanercept and 19 healthy subjects. Blood samples were collected at baseline and every 4 weeks during treatment. Taqman quantitative real-time polymerase chain reaction was applied to analyse the expression of: Stat-4, T-bet, IL-12p35 and IFN-γ (Th1-related); GATA-3, IL-4 (Th2-related); Stat-3, RORγt, IL-23p19 (Th17-related); Foxp3, IL-2 (Treg-related). Flow cytometry was applied to analyse CD4+CD25+brightFoxp3+ cells in peripheral blood. Results: Upregulation of Th1 and Th17 and downregulation of Treg subsets was found at baseline. The response to etanercept could be associated with a significant reversal of the Th1/Th17 activation, and a concomitant upregulation of Th2 and Treg subsets. Conclusion: Our data may contribute to a better understanding of the mechanisms underlying the achievement of clinical response in psoriasis and could be helpful for the identification of early predictive markers of response.
Optimization-based synthesis of stochastic biocircuits with statistical specifications

Model-guided design has become a standard approach to engineering biomolecular circuits in current synthetic biology. However, the stochastic nature of biomolecular reactions is often overlooked in the design process. As a result, cell-cell heterogeneity causes unexpected deviation of biocircuit behaviors from model predictions and requires additional iterations of design-build-test cycles. To enhance the design process of stochastic biocircuits, this paper presents a computational framework to systematically specify the level of intrinsic noise using well-defined metrics of statistics and design highly heterogeneous biocircuits based on the specifications. Specifically, we use descriptive statistics of population distributions as an intuitive specification language of stochastic biocircuits and develop an optimization based computational tool that explores parameter configurations satisfying design requirements. Sensitivity analysis methods are also developed to ensure the robustness of a biocircuit design. These design tools are formulated using convex optimization programs to enable efficient and rigorous quantification of the statistics without approximation, and thus, they are amenable to the synthesis of stochastic biocircuits that require high reliability. We demonstrate these features by designing a stochastic negative feedback biocircuit that satisfies multiple statistical constraints. In particular, we use a rigorously quantified parameter map of feasible design space to perform in-depth study of noise propagation and regulation in negative feedback pathways.
Skin color detection using multiple cues

In this paper, we present a novel space transformation to describe the skin and non-skin attributes, and build a new non-linear skin color classifier combining the spatial and probabilistic distributions of pixels. To weaken the illumination effect on images, we introduce a new gamma correction (GC) method. Experimental results show that our approach has good performance in skin color detection.
Parallelism in Inheritance Hierarchies with Exceptions

In a recent paper, Etherington & Reiter formalized a simple version of semantic networks with exceptions in terms of Reiter's Default Logic. With this approach they were able to formally characterize the correctness of an inference algorithm in terms of Default Logic, and exhibited an algorithm that was correct in this sense. Finally, they concluded that massively parallel architectures for semantic networks, such as NETL apparently cannot implement this algorithm. In this paper, we present a different massively parallel architecture for the simplified semantic networks outlined in their paper which appears to avoid the objections to NETL. We also present some results of simulations in this framework of the examples presented in Etherington and Reiter.
HSP90 gene expression induced by aspirin is associated with damage remission in a chicken myocardial cell culture exposed to heat stress

Abstract To understand the potential protection of heat shock protein 90 (HSP90) induced by aspirin against heat stress damage in chicken myocardial cells, enzyme activities related to stress damage, cytopathological changes, the expression and distribution of HSP90, and HSP90 mRNA levels in the myocardial cells exposed to heat stress (42°C) for different durations with or without aspirin administration (1 mg/ml, 2 h prior) in vitro were investigated. Significant increase of enzyme levels in the supernatant of heat-stressed myocardial cells and cellular lesions characterised by acute degeneration, karyopyknosis and karyorrhexis were observed, compared to non-treated cells. However, the lesions of cells treated with aspirin were milder, characterised by earlier recovery of enzyme levels to the control levels and no obvious heat stress-related cellular necrosis. Stronger positive signals in the cytoplasm and longer retention of HSP90 signal in nuclei were observed in aspirin-treated myocardial cells than those of only heat-stressed cells. HSP90 level in the aspirin-treated myocardial cells was 11.1-fold higher than that in non-treated cells, and remained at a high level at the early stage of heat stress, whereas it was just 4.1-fold higher in only heat-stressed cells and returned rapidly to a low level. Overexpression of HSP90 mRNA in aspirin-treated cells was observed throughout the experiment, whereas HSP90 mRNA decreased significantly only in heat-stressed cells. The early higher HSP90 expression induced by aspirin during heat stress was accompanied by decreased heat stress damage, suggesting that aspirin might play an important role in preventing myocardial cells from heat stress damage in vitro.
Multi-Layer Skeleton Fitting for Online Human Motion Capture

This paper describes a new approach to fitting a kinematic model to human motion data which is a component of a marker-free optical human motion capture system. Efficient vision-based feature tracking and volume reconstruction by shapefrom-silhouette are applied to raw image data obtained from several synchronized cameras in realtime. The combination of both sources of information enables the application of a new method for fitting a sophisticated multi-layer humanoid skeleton. We present results with real video data that demonstrate that our system runs at 1-2 fps.
Complex interactions between cis-regulatory modules in native conformation are critical for Drosophila snail expression

It has been shown in several organisms that multiple cis-regulatory modules (CRMs) of a gene locus can be active concurrently to support similar spatiotemporal expression. To understand the functional importance of such seemingly redundant CRMs, we examined two CRMs from the Drosophila snail gene locus, which are both active in the ventral region of pre-gastrulation embryos. By performing a deletion series in a ∼25 kb DNA rescue construct using BAC recombineering and site-directed transgenesis, we demonstrate that the two CRMs are not redundant. The distal CRM is absolutely required for viability, whereas the proximal CRM is required only under extreme conditions such as high temperature. Consistent with their distinct requirements, the CRMs support distinct expression patterns: the proximal CRM exhibits an expanded expression domain relative to endogenous snail, whereas the distal CRM exhibits almost complete overlap with snail except at the anterior-most pole. We further show that the distal CRM normally limits the increased expression domain of the proximal CRM and that the proximal CRM serves as a `damper' for the expression levels driven by the distal CRM. Thus, the two CRMs interact in cis in a non-additive fashion and these interactions may be important for fine-tuning the domains and levels of gene expression.
Re-establishing network connectivity in post-disaster scenarios through mobile cognitive radio networks

Network interoperability and self-organization constitute important communication requirements in disaster recovery scenarios. Here, the original communication infrastructure might be partially or completely damaged, and the whole network might be partitioned into segments (called islands in the following) that might operate on different frequencies/wireless technologies. In this paper, we investigate techniques to maximally re-establish the connectivity among heterogeneous islands through the utilization of specialized repairing units called Stem Nodes (SNs). A SN combines spectrum reconfigurability (offered by the Software Defined Radio technology) with self-positioning and dynamic routing functionalities, and thus it is able to replace damaged components of the original infrastructure. Moreover, sets of SNs can self-organize into multi-hop mesh structures connecting heterogeneous islands. We study the problem of determining the optimal deployment of SNs so that the number of connected devices of the original network is maximized. Given the NP-hardness of the problem, we propose approximated solutions with reduced computational complexity. We then compare the centralized solution with a distributed algorithm (based on virtual springs approach) that enables SNs to explore the environment in both space/frequency domains, and to self-organize into virtual mesh structures. Simulation results confirm the effectiveness of the distributed algorithm to maximally re-establish the network connectivity even on large-scale scenarios.
Systems Modeling at Multiple Levels of Regulation: Linking Systems and Genetic Networks to Spatially Explicit Plant Populations

Selection and adaptation of individuals to their underlying environments are highly dynamical processes, encompassing interactions between the individual and its seasonally changing environment, synergistic or antagonistic interactions between individuals and interactions amongst the regulatory genes within the individual. Plants are useful organisms to study within systems modeling because their sedentary nature simplifies interactions between individuals and the environment, and many important plant processes such as germination or flowering are dependent on annual cycles which can be disrupted by climate behavior. Sedentism makes plants relevant candidates for spatially explicit modeling that is tied in with dynamical environments. We propose that in order to fully understand the complexities behind plant adaptation, a system that couples aspects from systems biology with population and landscape genetics is required. A suitable system could be represented by spatially explicit individual-based models where the virtual individuals are located within time-variable heterogeneous environments and contain mutable regulatory gene networks. These networks could directly interact with the environment, and should provide a useful approach to studying plant adaptation.
Error bounds and error indicators for conforming , nonconforming and mixed elements

We introduce a simple construction for the computation of er ror bounds in the energy norm for finite element solutions of an elliptic problem . Therefore, we describe a simple method for the interpolation of a mixed approximati on nto a conforming pair for primal and dual solutions. The error bound is extend ed to weakly nonlinear problems and eigenvalue problems. We use the local contr ibutions of the error bounds as an error indicator for an adaptive multigrid metho d. The application of the error bound is discussed for a modified Emden problem and t he performance of the indicator is demonstrated by examples for the Poisson eq uation using the lowest order Raviart-Thomas elements and BDM elements and for plan ar elasticity using the Stenberg stabilization of the BDM elements. AMS Subject Classification: 65N30
Ontology-Based Query Expansion Widget for Information Retrieval

In this paper we present an ontology-based query expansion widget which utilizes the ontologies published in the ONKI Ontology Service. The widget can be integrated into a web page, e.g. a search system of a museum catalogue, enhancing the page by providing a query expansion functionality. We have tested the system with general, domainspecific and spatio-temporal ontologies.