Miracle-dz/UniFAR-FTUs huggingface dataset:
Metformin Inhibits Proinflammatory Responses and Nuclear Factor-&kgr;B in Human Vascular Wall Cells

Objective—Metformin may benefit the macrovascular complications of diabetes independently of its conventional hypoglycemic effects. Accumulating evidence suggests that inflammatory processes participate in type 2 diabetes and its atherothrombotic manifestations. Therefore, this study examined the potential action of metformin as an inhibitor of pro-inflammatory responses in human vascular smooth muscle cells (SMCs), macrophages (M&phgr;s), and endothelial cells (ECs). Methods and Results—Metformin dose-dependently inhibited IL-1&bgr;–induced release of the pro-inflammatory cytokines IL-6 and IL-8 in ECs, SMCs, and M&phgr;s. Investigation of potential signaling pathways demonstrated that metformin diminished IL-1&bgr;–induced activation and nuclear translocation of nuclear factor-kappa B (NF-&kgr;B) in SMCs. Furthermore, metformin suppressed IL-1&bgr;–induced activation of the pro-inflammatory phosphokinases Akt, p38, and Erk, but did not affect PI3 kinase (PI3K) activity. To address the significance of the anti-inflammatory effects of a therapeutically relevant plasma concentration of metformin (20 &mgr;mol/L), we conducted experiments in ECs treated with high glucose. Pretreatment with metformin also decreased phosphorylation of Akt and protein kinase C (PKC) in ECs under these conditions. Conclusions—These data suggest that metformin can exert a direct vascular anti-inflammatory effect by inhibiting NF-&kgr;B through blockade of the PI3K–Akt pathway. The novel anti-inflammatory actions of metformin may explain in part the apparent clinical reduction by metformin of cardiovascular events not fully attributable to its hypoglycemic action.
A New Kind of Economics-Computable and Behavioral Economics

This essay is based on my experience of attending the Workshop on Computable Economics hosted by the COBREA of Economics Department at the National University of Ireland, Galway, between March 21-25, 2005. This workshop is absolutely the best one I attended so far. It is small and has a compact schedule. It is really a valuable opportunity to meet several world first-class scholars from economics, mathematics and computer science and discuss with them. The workshop itself is enjoyable, the discussions are deep and sharp, just like Vela said in the workshop: “we are here not for convincing others but for exchanging ideas”. I have learnt a lot from this workshop, not only the knowledge they taught and the ideas they presented but also the way of thinking and the history of thoughts. I have to say I am biased in writing this essay, I’d prefer to write it as my understanding of computable economics and some of my ideas which were inspired by the workshop instead of a simple summary of the lectures.
Security policy specification templates for critical infrastructure services in the cloud

Security policies are an established way for specifying security demands. However, stakeholders are hardly capable of specifying complex machine-readable security policies. Therefore, a user-friendly specification method is necessary, such as refineable natural-language security policy templates. This paper describes how a security expert can elicit security demands from various stakeholders and generalize them as security policy templates. By simply instantiating these templates, policy authors can easily specify their security demands. An examplary application in the context of cloud computing for critical infrastructure IT services is shown.
Inhibition of transglutaminase 2 mitigates transcriptional dysregulation in models of Huntington disease

Caused by a polyglutamine expansion in the huntingtin protein, Huntington's disease leads to striatal degeneration via the transcriptional dysregulation of a number of genes, including those involved in mitochondrial biogenesis. Here we show that transglutaminase 2, which is upregulated in HD, exacerbates transcriptional dysregulation by acting as a selective corepressor of nuclear genes; transglutaminase 2 interacts directly with histone H3 in the nucleus. In a cellular model of HD, transglutaminase inhibition de‐repressed two established regulators of mitochondrial function, PGC‐1α and cytochrome c and reversed susceptibility of human HD cells to the mitochondrial toxin, 3‐nitroproprionic acid; however, protection mediated by transglutaminase inhibition was not associated with improved mitochondrial bioenergetics. A gene microarray analysis indicated that transglutaminase inhibition normalized expression of not only mitochondrial genes but also 40% of genes that are dysregulated in HD striatal neurons, including chaperone and histone genes. Moreover, transglutaminase inhibition attenuated degeneration in a Drosophila model of HD and protected mouse HD striatal neurons from excitotoxicity. Altogether these findings demonstrate that selective TG inhibition broadly corrects transcriptional dysregulation in HD and defines a novel HDAC‐independent epigenetic strategy for treating neurodegeneration.
An Analysis of the Effects of Vancomycin and/or Vancomycin-Resistant Citrobacter freundii Exposure on the Microbial Community Structure in Soil

The occurrence of antibiotics and antibiotic resistance genes in the environment has become a subject of growing concern. The extensive use of vancomycin and other pharmaceuticals may alter the biodiversity of soil microbial communities and select antibiotic-resistant bacteria. Therefore, the purpose of the study was to evaluate the impact of vancomycin and/or vancomycin-resistant Citrobacter freundii on soil microbial communities using the denaturing gradient gel electrophoresis (DGGE) and the phospholipid fatty acid (PLFA) approaches. The experiment had a completely randomized block design with the following treatments: control soil (C), soil with vancomycin (1 mg/kg soil—VA1), soil with vancomycin (10 mg/kg soil—VA10), soil with C. freundii (Cit), soil with vancomycin (1 mg/kg soil) and C. freundii (VA1+Cit), and soil with vancomycin (10 mg/kg soil) and C. freundii (VA10+Cit). A bacterial strain resistant to vancomycin was isolated from raw sewage collected from the municipal sewage treatment plant. The obtained results indicated that the antibiotic and/or the bacterial strain exerted a selective pressure that resulted in qualitative and quantitative changes in the population of soil microorganisms. However, a multivariate analysis showed that the genetic and structural diversity of the soil microbial community was primarily affected by the incubation time and to a lesser extent by the antibiotic and introduced bacteria. DGGE analysis clearly showed that certain species within the bacterial community were sensitive to vancomycin as was evidenced by a decrease in the values of S (richness) and H (Shannon-Wiener) indices. Moreover, a PLFA method-based analysis revealed alterations in the structure of the soil microbial community as indicated by changes in the biomass of the PLFA biomarkers specific for Gram-positive and Gram-negative bacteria as well as fungi. The changes observed in the community of soil microorganisms may decrease the rate of microbial-mediated processes, which can lead to a disturbance in the ecological balance of the soil ecosystem.
A new fast hybrid adaptive grid generation technique for arbitrary two‐dimensional domains

This paper describes a new fast hybrid adaptive grid generation technique for arbitrary two‐dimensional domains. This technique is based on a Cartesian background grid with square elements and quadtree decomposition. A new algorithm is introduced for the distribution of boundary points based on the curvature of the domain boundaries. The quadtree decomposition is governed either by the distribution of the boundary points or by a size function when a solution‐based adaptive grid is desired. The resulting grid is quaddominant and ready for the application of finite element, multi‐grid, or line‐relaxation methods. All the internal angles in the final grid have a lower bound of 45° and an upper bound of 135°. Although our main interest is in grid generation for unsteady flow simulations, the technique presented in this paper can be employed in many other fields. Several application examples are provided to illustrate the main features of this new approach. Copyright © 2010 John Wiley & Sons, Ltd.
Properties of nested sampling

Nested sampling is a simulation method for approximating marginal likelihoods. We establish that nested sampling has an approximation error that vanishes at the standard Monte Carlo rate and that this error is asymptotically Gaussian. It is shown that the asymptotic variance of the nested sampling approximation typically grows linearly with the dimension of the parameter. We discuss the applicability and efficiency of nested sampling in realistic problems, and compare it with two current methods for computing marginal likelihood. Finally, we propose an extension that avoids resorting to Markov chain Monte Carlo simulation to obtain the simulated points. Copyright 2010, Oxford University Press.
On Using Ensemble Methods for Chinese Named Entity Recognition

In sequence labeling tasks, applying different machine learning models and feature sets usually leads to different results. In this paper, we exploit two ensemble methods in order to integrate multiple results generated under different conditions. One method is based on majority vote, while the other is a memory-based approach that integrates maximum entropy and conditional random field classifiers. Our results indicate that the memory-based method can outperform the individual classifiers, but the majority vote method cannot.
Detection of the selected , basic emotions based on face expression using Kinect

Automation of reading emotion from facial expression is a milestone of communication between human and computer. This paper presents an application and way which allows to recognize four (anger, happiness, sadness and surprise) from six basic emotions defined by Paul Ekman. Application “Emotion Detector” use very simple method to recognize it. Thanks to data provided by Kinect, alghorithm (k – nearest neighbors) can classify user emotion in real time.
Pathways to Kindergarten Growth: Synthesizing Theories of the Kindergarten Transition to Support Children's Development

The transition into Kindergarten is a critical time for children’s development— children’s patterns of academic development and engagement with school often start in Kindergarten and persist throughout their academic careers. This is a developmental period that is marked by many changes in children’s lives, and therefore it is not a surprise that many children struggle during this transition. These struggles are more common for children who are living in poverty, and although there have been national initiatives to address opportunity gaps in access to early education, investigations into the effectiveness of these programs in promoting children’s Kindergarten development have shown mixed results. It is therefore essential to identify the types of early education experiences that are effective in supporting children in having a smooth Kindergarten
The first World Atlas of the artificial night sky brightness

ABSTRA C T We present the first World Atlas of the zenith artificial night sky brightness at sea level. Based on radiance-calibrated high-resolution DMSP satellite data and on accurate modelling of light propagation in the atmosphere, it provides a nearly global picture of how mankind is proceeding to envelop itself in a luminous fog. Comparing the Atlas with the United States Department of Energy (DOE) population density data base, we determined the fraction of population who are living under a sky of given brightness. About two-thirds of the World population and 99 per cent of the population in the United States (excluding Alaska and Hawaii) and European Union live in areas where the night sky is above the threshold set for polluted status. Assuming average eye functionality, about one-fifth of the World population, more than two-thirds of the United States population and more than one half of the European Union population have already lost naked eye visibility of the Milky Way. Finally, about onetenth of the World population, more than 40 per cent of the United States population and one sixth of the European Union population no longer view the heavens with the eye adapted to night vision, because of the sky brightness.
Frequency-domain multichannel signal enhancement: Minimum variance vs. minimum correlation

In this paper we compare two optimization criteria that can be used in multichannel signal enhancement. The first criterion, Minimization of the output Variance (MV), is related to conventional adaptive beamforming whereas the second one, minimization of the output cross-correlation (or Symmetric Adaptve Decorrelation - SAD), is related to blind source separation techniques. We develop an implementation-independent comparison framework, where the quality of the MV adaption control is identified with the power of the target. We account for the correlation of the source of finite length. Our analysis shows that SAD is attractive in cases where target and interferer have about the same power level at each sensor. We evidence the fact that SAD requires longer signals, not only to maintain a low source correlation coefficient, but also because SAD learning rules suffer from larger estimation errors.
Synchronous Onset of NGF and TrkA Survival Dependence in Developing Dorsal Root Ganglia

Determinations of dorsal root ganglion (DRG) neuron loss in nerve growth factor (NGF) and neurotrophin-3 (NT-3) null mutant mice have supported the concept that neurons can switch neurotrophin dependence by revealing that many neurons must require both of these factors acting either sequentially or simultaneously during development. The situation is complex, however, in that NT-3(−/−) mutant mice show far greater neuron loss than mice deficient in the NT-3 receptor TrkC, suggesting that NT-3 may support many DRG neurons via actions on the NGF receptor TrkA. To assess the possibility of ligand-receptor cross-talk as a developmental mechanism, we have compared the onset of survival dependence of lumbar DRG neurons on NT-3, TrkC, NGF, and TrkA signaling in mice deficient in these molecules as a result of gene targeting. At embryonic day 11.5 (E11.5), virtually all lumbar DRG cells express TrkC mRNA and many require NT-3 and TrkC signaling for survival. In contrast, although many lumbar DRG cells also express TrkA at E11.5, there is little survival dependence on TrkA signaling. By E13.5, most lumbar DRG cells have downregulated TrkC mRNA. The onset of survival dependence on NGF and TrkA-signaling is concurrent and of equal magnitude at E13.5, demonstrating that NT-3 alone does not support DRG neurons via TrkA, nor can NT-3 compensate for the loss of NGF. We conclude that many murine DRG cells require NT-3 for survival before exhibiting NGF dependence and that NT-3 activation of TrkA is unimportant to these early NT-3 survival-promoting actions. We suggest that the discrepancy in cell loss between NT-3(−/−) and trkC(−/−) mutants is attributable to the ability of NT-3 to support DRG neurons via TrkA in the artificial situation where TrkC is absent.
On the continuous Fermat-Weber problem for a convex polygon using Euclidean distance

We consider the continuous Fermat-Weber problem, where the customers are continuously (uniformly) distributed along the boundary of a convex polygon. We derive the closed-form expression for finding the average distance from a given point to the continuously distributed customers along the boundary. A Weiszfeld-type procedure is proposed for this model, which is shown to be linearly convergent. We also derive a closed-form formula to find the average distance for a given point to the entire convex polygon, assuming a uniform distribution. Since the function is smooth, convex, and explicitly given, the continuous version of the Fermat-Weber problem over a convex polygon can be solved easily by numerical algorithms.
Detecting Objects using Unsupervised Parts-based Attributes ∗

This paper presents a new approach to parts-based object detection. Objects are described using a spatial model based on its constituent parts. Unlike most existing methods, parts are discovered in an unsupervised manner from training images with only object bounding boxes provided. The association between parts is modeled using boosted decision trees that allows arbitrary object-part configurations to be maintained. Experimental results on the challenging VOC 2007 dataset validate our approach.
Evaluación del nivel de aptitud desarrollo de pensamiento computacional en jóvenes de nivel básico secundaria

El término pensamiento computacional (PC) como habilidad que ayuda a resolver problemas, diseñar sistemas y comprender el comportamiento humanopara su aplicación en distintos campos, surge como tal hace doce años, sin embargo diversos de sus componentes tienen una larga historia y han sido abordados por grandes autores de la psicología educativa como Jean Piaget y Lev Vigotsky; a nivel internacional se han realizado estudios relacionados con este tema y la importancia de su inclusión en la educación formal, sin embargo este hecho aún no se logra; aunado a lo anterior también existe un vacío en la medida y evaluación estandarizada de este pensamiento, hecho que ha sido abordado por instituciones que trabajan sus propios métodos de evaluación del PC. EL objetivo planteado fue evaluar el nivel de aptitud desarrollo de pensamiento computacional en jóvenes de nivel básico secundaria que pertenecen al grupo aptitudes sobresalientes (AS) de las unidades de servicio de apoyo a la educación regular (USAER). Los resultados obtenidos muestran un promedio de aciertos del 50%, se visualizaron las áreas para el fortalecimiento del PC en lo que respecta a las habilidades de análisis de situaciones hipotéticas, diseño de los algoritmos para solución de problemas y abstracción de datos. Así mismo se encontró que la madurez y desarrollo cognitivo por grado académico no determina el nivel de desarrollo del PC.
Experimental Research in Urban Spatial Cognition by Using Virtual Reality Technology

This paper presents a VR experiment investigating how people construct the cognitive map in mind, generate spatial memory and respond when exploring the urban environment. 76 participants were recruited to explore the virtual town of Xidi. By analyzing the traces of the participants and the data of subjective feedbacks, the research examines how the space affects people generating spatial memory and producing the corresponding behavior pattern during the exploration. Furthermore, the interaction mechanism between the urban evolution and human behavior is investigated by comparing the participants’ behavior trajectory and the real town spatial structure. Results from this research shed light on the future use of VR technology as an efficient tool in cognitive urban research. 1
Theoretical and Empirical Analysis of a GPU Based Parallel Bayesian Optimization Algorithm

General Purpose computing over Graphical Processing Units (GPGPUs) is a huge shift of paradigm in parallel computing that promises a dramatic increase in performance. But GPGPUs also bring an unprecedented level of complexity in algorithmic design and software development. In this paper we describe the challenges and design choices involved in parallelization of Bayesian Optimization Algorithm (BOA) to solve complex combinatorial optimization problems over nVidia commodity graphics hardware using Compute Unified Device Architecture (CUDA). BOA is a well-known multivariate Estimation of Distribution Algorithm (EDA) that incorporates methods for learning Bayesian Network (BN). It then uses BN to sample new promising solutions. Our implementation is fully compatible with modern commodity GPUs and therefore we call it gBOA (BOA on GPU). In the results section, we show several numerical tests and performance measurements obtained by running gBOA over an nVidia Tesla C1060 GPU. We show that in the best case we can obtain a speedup of up to 13x.
Interacting with Virtual Reality models on mobile devices

This paper discusses alternative approaches for interacting with virtual reality models on mobile devices, based upon work conducted as part of the locus project [6]. First, mobile virtual reality models are discussed within the established realityvirtuality continuum to demonstrate how this new mixed reality paradigm compares with augmented and virtual reality generally. Next, three prototypes are introduced that adopt different interaction paradigms for mobile virtual reality models: interaction can be via the screen only, movement and gestures within the real world environment, or a mixture of these two approaches. Finally this paper describes some potential applications of mobile virtual reality, including navigation, and the display of georeferenced information. The paper concludes by suggesting that interaction via movement and gestures within the may be a more intuitive approach for mobile virtual reality models.
Learning Compact Feature Descriptor and Adaptive Matching Framework for Face Recognition

Dense feature extraction is becoming increasingly popular in face recognition tasks. Systems based on this approach have demonstrated impressive performance in a range of challenging scenarios. However, improvements in discriminative power come at a computational cost and with a risk of over-fitting. In this paper, we propose a new approach to dense feature extraction for face recognition, which consists of two steps. First, an encoding scheme is devised that compresses high-dimensional dense features into a compact representation by maximizing the intrauser correlation. Second, we develop an adaptive feature matching algorithm for effective classification. This matching method, in contrast to the previous methods, constructs and chooses a small subset of training samples for adaptive matching, resulting in further performance gains. Experiments using several challenging face databases, including labeled Faces in the Wild data set, Morph Album 2, CUHK optical-infrared, and FERET, demonstrate that the proposed approach consistently outperforms the current state of the art.
Decay Rate of Coherent Field Oscillation

In recent studies it has become increasingly clear that presence of infinitely many instability bands of the parametric resonance plays crucial roles in the phenomenon of particle production under periodic classical field oscillation. We extend previous works to a general class of models including both the Yukawa and the quartic type of couplings of the classical field to quantum bose fields. Decay rate from the $n-$th band is derived in the small amplitude limit using the functional Schr$\stackrel{. }{{\rm o}}$dinger picture. It is then shown that this analytic result of the decay rate can also be derived as the zero momentum limit of a physical process, $n$ particles that comprise the classical homogeneous field decaying simultaneously into 2 bose particles. The latter approach uses ordinary perturbation theory, hence the former result is a novel resummation of many perturbative amplitudes, which usually becomes complicated for a large $n$ order.