Miracle-dz/UniFAR-FTUs huggingface dataset:
MacrophagesProinflammatory Pathways in Monocytes and Essential Mediator of CD40-Activated TNF Receptor-Associated Factor 6 Is an

The interaction between CD40 and its ligand, CD154, has been shown to play a role in the onset and maintenance of inﬂammatory disease. Contributing to this process is the ability of CD40 to signal monocyte and macrophage inﬂammatory cytokine production. We have shown that this event is dependent on Src family tyrosine kinase activity and the subsequent activation of ERK1/2. To address the role of TNFR-associated factor (TRAF) family members in facilitating this signaling pathway, we transfected a CD40-deﬁcient macrophage cell line with wild-type human CD40, or with CD40 containing disrupted TRAF binding sites. Ligation of either wild-type CD40, or a CD40 mutant unable to bind TRAF2/3/5, resulted in the stimulation of inﬂammatory cytokine production. However, ligation of a CD40 mutant lacking a functional TRAF6 binding site did not initiate inﬂammatory cytokine production, and this mutant was found to be defective in CD40-mediated activation of ERK1/2, as well as I (cid:1) B kinase (IKK) and NF- (cid:1) B. Likewise, introduction of a dominant-negative TRAF6 into a wild-type (CD40 (cid:2) ) macrophage cell line resulted in abro-gation of CD40-mediated induction of inﬂammatory cytokine synthesis. Finally, treatment of monocytes with a cell-permeable peptide corresponding to the TRAF6-binding motif of CD40 inhibited CD40 activation of ERK1/2, IKK, and inﬂammatory cytokine production. These data demonstrate that TRAF6 acts as a critical adapter of both the Src/ERK1/2 and IKK/NF- (cid:1) B proinﬂammatory signaling pathways in monocytes and macrophages.
Crowd Video Classification Using Convolutional Neural Networks

Deep learning tools such as the convolutional neural network (CNN) are extensively used for image analysis and interpretation tasks but they become relatively expensive to use for a corresponding analysis in videos by requiring memory provision for the additional temporal information. Crowd video analysis is one of the subareas in video analysis that has recently gained notoriety. In this paper we have shown that a 2D CNN can be used to classify videos by using 3-channel image map input for each video computed using spatial and temporal information and this reduces space and time complexity over a classical 3D CNN usually used for video analysis. We test the model developed with the state-of-the-art method of [1] using their proposed dataset, and without any additional processing steps, improve upon their reported accuracy.
TrustLite: a security architecture for tiny embedded devices

Embedded systems are increasingly pervasive, interdependent and in many cases critical to our every day life and safety. Tiny devices that cannot afford sophisticated hardware security mechanisms are embedded in complex control infrastructures, medical support systems and entertainment products [51]. As such devices are increasingly subject to attacks, new hardware protection mechanisms are needed to provide the required resilience and dependency at low cost. In this work, we present the TrustLite security architecture for flexible, hardware-enforced isolation of software modules. We describe mechanisms for secure exception handling and communication between protected modules, enabling seamless interoperability with untrusted operating systems and tasks. TrustLite scales from providing a simple protected firmware runtime to advanced functionality such as attestation and trusted execution of userspace tasks. Our FPGA prototype shows that these capabilities are achievable even on low-cost embedded systems.
Differences in the audio-visual detection of word prominence from Japanese and English speakers

We have previously shown that for English speakers information on the mouth shape of a speaker is a powerful feature for the machine based discrimination of prominent from nonprominent words. In this paper we extend our analysis to data from Japanese speakers. We compare the discrimination performance of the different acoustic and visual features we extract for the two languages. This comparison shows a much wider variability in discrimination scores for the different speakers and the different features in the English dataset than in the Japanese dataset. Despite previous hints that visual speech and word prominence perception by Japanese listeners can yield inferior performance compared to English listeners we see that our discrimination scores are high and very similar for the English and Japanese speakers which indicates that at least the speakers signal prominence with a similar level of consistency in both languages.
Multiple Eph Receptors and B-Class Ephrins Regulate Midline Crossing of Corpus Callosum Fibers in the Developing Mouse Forebrain

Agenesis of the corpus callosum (CC) is a rare birth defect that occurs in isolated conditions and in combination with other developmental cerebral abnormalities. Recent identification of families of growth and guidance molecules has generated interest in the mechanisms that regulate callosal growth. One family, ephrins and Eph receptors, has been implicated in mediating midline pathfinding decisions; however, the complexity of these interactions has yet to be unraveled. Our studies shed light on which B-class ephrins and Eph receptors function to regulate CC midline growth and how these molecules interact with important guideposts during development. We show that multiple Eph receptors (B1, B2, B3, and A4) and B-class ephrins (B1, B2, and B3) are present and function in developing forebrain callosal fibers based on both spatial and temporal expression patterns and analysis of gene-targeted knock-out mice. Defects are most pronounced in the combination double knock-out mice, suggesting that compensatory mechanisms exist for several of these family members. Furthermore, these CC defects range from mild hypoplasia to complete agenesis and Probst's bundle formation. Further analysis revealed that Probst's bundle formation may reflect aberrant glial formations and/or altered sensitivity of CC axons to other guidance cues. Our results support a significant role for ephrins and Eph receptors in CC development and may provide insight to possible mechanisms involved in axon midline crossing and human disorder.
Overview of SLL's proposal in response to NIST's call for new global IdM/CKM designs without public keys

In this paper we outline (apparently) the first globally scalable, post quantum secure, symmetric method of Identity Management (IdM) and Cryptographic Key Management (CKM) that is secure against a collusion of up to m-1 participating service providers. Our proposal is made in response to the U.S. National Institute of Standards and Technology (NIST) 2009 call [4] for new high-availability IdM/CKM designs that do NOT use public key technologies. Our efficiently realisable proposal addresses this and many other requirements identified by NIST managers.
NTT-NAIST SMT systems for IWSLT 2013

This paper presents NTT-NAIST SMT systems for EnglishGerman and German-English MT tasks of the IWSLT 2013 evaluation campaign. The systems are based on generalized minimum Bayes risk system combination of three SMT systems: forest-to-string, hierarchical phrase-based, phrasebased with pre-ordering. Individual SMT systems include data selection for domain adaptation, rescoring using recurrent neural net language models, interpolated language models, and compound word splitting (only for German-English).
Probabilistic Forecast Calibration Using ECMWF and GFS Ensemble Reforecasts. Part I: Two-Meter Temperatures

Abstract Recently, the European Centre for Medium-Range Weather Forecasts (ECMWF) produced a reforecast dataset for a 2005 version of their ensemble forecast system. The dataset consisted of 15-member reforecasts conducted for the 20-yr period 1982–2001, with reforecasts computed once weekly from 1 September to 1 December. This dataset was less robust than the daily reforecast dataset produced for the National Centers for Environmental Prediction (NCEP) Global Forecast System (GFS), but it utilized a much higher-resolution, more recent model. This manuscript considers the calibration of 2-m temperature forecasts using these reforecast datasets as well as samples of the last 30 days of training data. Nonhomogeneous Gaussian regression was used to calibrate forecasts at stations distributed across much of North America. Significant observations included the following: (i) although the “raw” GFS forecasts (probabilities estimated from ensemble relative frequency) were commonly unskillful as measured in conti.
Measurement and Prediction of the Thermomechanical Response of Shape Memory Alloy Hybrid Composite Beams

An experimental and numerical investigation into the static and dynamic responses of shape memory alloy hybrid composite (SMAHC) beams is performed to provide quantitative validation of a recently commercialized numerical analysis/design tool for SMAHC structures. The SMAHC beam specimens consist of a composite matrix with embedded pre-strained SMA actuators, which act against the mechanical boundaries of the structure when thermally activated to adaptively stiffen the structure. Numerical results are produced from the numerical model as implemented into the commercial finite element code ABAQUS. A rigorous experimental investigation is undertaken to acquire high fidelity measurements including infrared thermography and projection moiré interferometry for full-field temperature and displacement measurements, respectively. High fidelity numerical results are also obtained from the numerical model and include measured parameters, such as geometric imperfection and thermal load. Excellent agreement is achieved between the predicted and measured results of the static and dynamic thermomechanical response, thereby providing quantitative validation of the numerical tool.
'New' Views on the Optimum Currency Area Theory: What is Emu Telling Us?

This paper surveys the optimum currency area (OCA) literature. It is organised into four phases: the 'pioneering phase' which put forward the OCA theory and its properties, the 'reconciliation phase' when its diverse facets were combined, the 'reassessment phase' that led to the 'new OCA theory' and the 'empirical phase' during which the theory was subject to due empirical scrutiny. We make systematic reference to the European economic and monetary union (EMU) to which the OCA theory has been most frequently applied. All pioneering contributions are still relevant. Several early weaknesses have now been amended. Meanwhile, the balance of judgements has shifted in favour of currency unions. They are now deemed to generate fewer costs in terms of the loss of autonomy of domestic macroeconomic policies, and there is greater emphasis on the benefits. Looking ahead we are confronted with two distinct paradigms -- specialisation versus endogeneity of OCA. JEL Classification: E42, F15, F33, F41
Genome Sequence of Lactobacillus sunkii Strain CG_D

ABSTRACT Lactobacillus sunkii CG_D is a rod-shaped, Gram-positive, and heterofermentative lactic acid bacterium. The draft genome of L. sunkii strain CG_D comprises 2,794,637 bp with an average G+C content of 42.03%. The genome harbors 2,662 predicted protein-encoding, and 71 RNA genes.
The Role of Fulbright Program in Building Positive Perception and Ally Image of the U.S. Among Pakistani Scholars

This study was aimed at exploring the role of Fulbright program in building perception about U.S. and Americans among Pakistani Fulbright scholars. While a host of theory and research had been growing on contact theory (Allport, 1954; Pettigrew & Tropp, 2008), application of contact hypothesis to cultural exchange programs based on foreign policy intended to develop peace and affective ties between nations has been limited. Specifically, this research gap was filled by this study that focused on the impact of direct contact on perception and image of the U.S. in the context of the U.S. and Pakistan Fulbright program. Pakistani Fulbright scholars (81 men, 67 women; Mean age = 23 years; Range = 21-29 years), with low-contact and high-contact were compared with respect to their perceptions of a prototypical American and the United States as an international entity. Compared to participants with low-contact (n = 52), participants with high-contact (n = 96) had developed a higher positive perception of a prototypical American. Furthermore, compared to participants with low-contact, those with high-contact perceived the U.S. significantly more as an ally and less as an imperialist-enemy nation. Participation was controlled through selection for the Fulbright program and no previous visits to the U.S. Discussion has focused on possibilities for foreign policy and peace related implications of the Fulbright program.
How Massive Are BALQSO Winds

We are involved in a program to derive properties of broad absorption line (BAL) winds in quasars using combined UV and X-ray observations. A major obstacle is large uncertainties in the derived BAL column densities because of partial coverage of the background light source. In this preliminary report, we circumnavigate those uncertainties by making a simple assumption -- that the relative metal abundances are roughly solar. In this case, the PV 1118,1128 multiplet should have at least 500 times lower optical depth than CIV 1549,1551. Nonetheless, a PV BAL is present in at least half of the well-measured BALQSOs we studied. We conclude that the strong lines of abundant species like CIV are typically very optically thick. The total BAL column densities are N_H > 10^22 cm^-2 (for solar overall metallicity), and they might be comparable to the X-ray absorbers, of order 10^23 cm^-2, if the BAL gas is sufficiently ionized. If the column densities in outflowing BAL gas are, in fact, as large as the X-ray absorbers, it would present a serious challenge to models of radiatively-driven BAL winds.
MeV-mass dark matter and primordial nucleosynthesis

The annihilation of new dark matter candidates with masses $m_X$ in the MeV range may account for the galactic positrons that are required to explain the 511 keV $\gamma$-ray flux from the galactic bulge. We study the impact of MeV-mass thermal relic particles on the primordial synthesis of $^2$H, $^4$He, and $^7$Li. If the new particles are in thermal equilibrium with neutrinos during the nucleosynthesis epoch they increase the helium mass fraction for $m_X\alt 10$ MeV and are thus disfavored. If they couple primarily to the electromagnetic plasma they can have the opposite effect of lowering both helium and deuterium. For $m_X=4$--10 MeV they can even improve the overall agreement between the predicted and observed $^2$H and $^4$He abundances.
A Hybrid Approach to Extracting Disorder Mentions from Clinical Notes

Crucial information on a patient’s physical or mental conditions is provided by mentions of disorders, such as disease, syndrome, injury, and abnormality. Identifying disorder mentions is one of the most significant steps in clinical text analysis. However, there are many surface forms of the same concept documented in clinical notes. Some are even recorded disjointedly, briefly, or intuitively. Such difficulties have challenged the information extraction systems that focus on identifying explicit mentions. In this study, we proposed a hybrid approach to disorder extraction, which leverages supervised machine learning, rule-based annotation, and an unsupervised NLP system. To identify different surface forms, we exploited rich features, especially the semantic, syntactic, and sequential features, for better capturing implicit relationships among words. We evaluated our method on the CLEF 2013 eHealth dataset. The experiments showed that our hybrid approach achieves a 0.776 F-score under strict evaluation standards, outperforming any participating systems in the Challenge.
A novel Ant algorithm for permutation flow shop problem

A new ant algorithm for the permutation flow shop problem is presented, which embraces two new features. One is a different yet outstanding pheromone structure, in which an ant is permitted to select more than one jobs at each step when constructing a complete travel sequence. The other is a new heuristic to guide the search. Experiments shows that a considerable improvement of performance can be obtained, and the reason behind is presented.
Classification Method Incorporating Decision Tree with Particle Swarm Optimization

This study attempts to develop a new method that could be used to handle the problem of finding the cut point or interval of continuous-valued attribute in decision tree, and to reach the following objectives: 1. The decision tree algorithm can handle the data that combines both the nominal attribute and continuous-valued attribute. 2. The decision tree algorithm has less nodes and branches in the situation that accuracy of prediction has no obvious change. 3. The decision tree algorithm can generate better rules with multi-interval division of attribute.
A Robust Synchronization Method for Centralized Microgrids

Microgrids represent one of the best candidates to redesign the architecture of the future distribution network. Such a model, in fact, is promising to be able to properly manage a larger penetration of distributed energy resources while improving the local production and utilization of energy. On the other hand, the control of a microgrid is quite challenging since the system has to be particularly reliable and flexible due to the required multiple and concurrent tasks to be performed. In this scenario, this paper proposes a novel solution that is able to synchronize the phase and the frequency of all of the devices connected to the microgrid through the combined use of different phase-locked loops and the 1 pulse per second signal, provided by a Global Positioning System device. Extensive experimental tests, performed also in critical operating conditions of the grid, have confirmed the effectiveness of the proposed method.
Automatic tracking of the aorta in cardiovascular MR images using deformable models

Presents a new algorithm for the robust and accurate tracking of the aorta in cardiovascular magnetic resonance (MR) images. First, a rough estimate of the location and diameter of the aorta is obtained by applying a multiscale medial-response function using the available a priori knowledge. Then, this estimate is refined using an energy-minimizing deformable model which the authors define in a Markov-random-field (MRF) framework. In this context, the authors propose a global minimization technique based on stochastic relaxation. Simulated annealing (SA), which is shown to be superior to other minimization techniques, for minimizing the energy of the deformable model. The authors have evaluated the performance and robustness of the algorithm on clinical compliance studies in cardiovascular MR images. The segmentation and tracking has been successfully tested in spin-echo MR images of the aorta. The results show the ability of the algorithm to produce not only accurate, but also very reliable results in clinical routine applications.
Evaluation of P2P-Based Internet Measurement System on Loss Tolerance to Measurement Results

Network tomography enables network operators to detect and mitigate congestion by inferring internal states from multiple end-to-end active performance measurements. In previous studies, we proposed a novel architecture to develop P2P-based measurement system that scales with the nationwide Internet. One of the key features is low-overhead data management method where measurement results are piggybacked onto measurements themselves. However this feature leads to the loss of measurement results, which may cause inference accuracy to decline. In this paper, we estimate the proposed architecture from the viewpoint of tolerance to packet losses. Our simulation results show that the architecture can infer congested segments with satisfactory accuracy even if 1% of links in a network are congested
On the Spectral Characteristics of Ad Hoc Networks and their Mobility Properties

Random geometric graphs have proven to be extremely useful in modeling static wireless ad-hoc and sensor networks. The study of these graphs and their spectral properties is a very active field with many interesting applications. In this work, we study the spectral properties of these graphs and in particular we prove the lack of spectral gap in random geometric graphs under a wide range of cases. We also present some results on the spectral properties of generalized weighted versions of these graphs. We later focus on mobile geometric graphs or dynamic Boolean models as were introduced by van den Berg, Meester, and White in 1997. These mobile models have been used to model mobile ad-hoc and sensor networks. Our results are aimed at understanding the dynamics of message spreading in a real-world dynamical network. We simulate a message spreading process and present some results related to the total propagation time under different scenarios. We call total propagation time the time it takes for a certain message to reach all the nodes in the network. This message could be a packet, a virus, a rumor in a social network, or something more general. In particular, we study how the metric, the mobility properties, the presence or absence of obstacles and finally the propagation characteristics affect the dynamics of the message spreading.
Road detection and classification in urban environments using conditional random field models

Understanding the road scene structure is essential and important for perceiving the driving situation in intelligent transportation systems (ITS). In this paper, we aim at analyzing the road scene structure by classifying the pixels to three different types, including road surface, lane markings, and non-road objects. Instead of detecting these three objects separately in traditional approaches, we integrate different ad hoc methods under the conditional random field framework. Three feature functions based on three cues including smoothness, color and lane marking segmentation, are used for pixel classification. Besides, an optimization algorithm using graph cuts is applied to find the solutions efficiently. Experiments on the data sets demonstrate high classification accuracy on objects in the road scene
KBS-HYPERBOOK - An Open Hyperbook System for Education

Educators are currently investing much effort into the conversion of their textbooks and lectures into hypertext documents. Within our K BS Virtual Classroom project, we have recently developed a data-base oriented method for systematically designing such hyperbooks. However, converting theoretical material into a hyp erbook is only the first step towards a modern, project-oriented, computer-supported learni ng environment. To realise such an environment, the static course materials (regardless wh ether they are printed textbooks or hyperbooks) should be replaced by an open hypermedia inf ormation system, to which both the educators and the students contribute. In this spirit we have redesigned our hyperbook modeling technique to make it suitable for both capturing th eoretical lecture material and providing a structure for the student projects.