Miracle-dz/UniFAR-FTUs huggingface dataset:
Nitroglycerine-Induced Nitrate Tolerance Compromises Propofol Protection of the Endothelial Cells against TNF-α: The Role of PKC-β 2 and NADPH Oxidase

Continuous treatment with organic nitrates causes nitrate tolerance and endothelial dysfunction, which is involved with protein kinase C (PKC) signal pathway and NADPH oxidase activation. We determined whether chronic administration with nitroglycerine compromises the protective effects of propofol against tumor necrosis factor (TNF-) induced toxicity in endothelial cells by PKC-β 2 dependent NADPH oxidase activation. Primary cultured human umbilical vein endothelial cells were either treated or untreated with TNF-α (40 ng/mL) alone or in the presence of the specific PKC-β 2 inhibitor CGP53353 (1 μM)), nitroglycerine (10 μM), propofol (100 μM), propofol plus nitroglycerin, or CGP53353 plus nitroglycerine, respectively, for 24 hours. TNF-α increased the levels of superoxide, Nox (nitrate and nitrite), malondialdehyde, and nitrotyrosine production, accompanied by increased protein expression of p-PKC-β 2, gP91phox, and endothelial cell apoptosis, whereas all these changes were further enhanced by nitroglycerine. CGP53353 and propofol, respectively, reduced TNF-α induced oxidative stress and cell toxicity. CGP53353 completely prevented TNF-α induced oxidative stress and cell toxicity in the presence or absence of nitroglycerine, while the protective effects of propofol were neutralized by nitroglycerine. It is concluded that nitroglycerine comprises the protective effects of propofol against TNF-α stimulation in endothelial cells, primarily through PKC-β 2 dependent NADPH oxidase activation.
Beyond Traditional Kernels: Classification in Two Dissimilarity-Based Representation Spaces

Proximity captures the degree of similarity between examples and is thereby fundamental in learning. Learning from pairwise proximity data usually relies on either kernel methods for specifically designed kernels or the nearest neighbor (NN) rule. Kernel methods are powerful, but often cannot handle arbitrary proximities without necessary corrections. The NN rule can work well in such cases, but suffers from local decisions. The aim of this paper is to provide an indispensable explanation and insights about two simple yet powerful alternatives when neither conventional kernel methods nor the NN rule can perform best. These strategies use two proximity-based representation spaces (RSs) in which accurate classifiers are trained on all training objects and demand comparisons to a small set of prototypes. They can handle all meaningful dissimilarity measures, including non-Euclidean and nonmetric ones. Practical examples illustrate that these RSs can be highly advantageous in supervised learning. Simple classifiers built there tend to outperform the NN rule. Moreover, computational complexity may be controlled. Consequently, these approaches offer an appealing alternative to learn from proximity data for which kernel methods cannot directly be applied, are too costly or impractical, while the NN rule leads to noisy results.
A coalition formation game for transmitter cooperation in OFDMA uplink communications

The SC-FDMA (single-carrier frequency division multiple access) is the access scheme that has been adopted by 3GPP (3rd generation partnership project) for the LTE (long term evolution) uplink. The SC-FDMA is an attractive alternative to OFDMA (orthogonal frequency-division multiple access) especially on the uplink owing to its low peak-to-average power ratio. This fact increases the power efficiency and reduces the cost of the power amplifiers at the mobile terminals. The use of SC-FDMA on the uplink implies that for highly loaded cells the base station allocates a single subcarrier to each user. This results in the limitation of the achievable rate on the uplink. In this work, we propose a coalition game between mobile terminals that allows them to improve their performance by sharing their subcarriers without creating any interference to each other. The proposed scheme allows a fair use of the subcarriers and leads to a significant capacity gain for each user. The cooperation between the nodes is modelled using coalitional game theory. In this game, each coalition tries to maximize its utility in terms of rate. In the absence of cooperation cost, it can be shown that the grand coalition is sum-rate optimal and stable, i.e., the mobile terminals have no incentive to leave the grand coalition.
Whole-brain diffusion histogram and selected tractography in assessing changes in normal aging brain

Poster: "ECR 2010 / C-2468 / Whole-brain diffusion histogram and selected tractography in assessing changes in normal aging brain" by: "M. Onu, A. Roceanu, V. Ferastraoaru, F. Preoteasa, E. Tarta, I. G. Lupescu, E. Rizea, O. Bajenaru; Bucharest/RO"
Standard Interface for data analysis of solvers in multibody dynamics

After more than twenty years spent on the development of simulation models and integration algorithms, there is no convenient way to compare the performance of the many algorithms that solve the Complementarity Problem (CP) in an unbiased manner. The constraint models in multibody systems naturally take the form of CPs and the current methods for the formulations lead to singular CPs which are difficult to solve. Since the underlying models are nonsmooth and nonlinear, mathematical theory supporting the design of simulation methods is sparse. For these reasons, we find that an important tool in the field of physical simulation will be a benchmark database that facilitates the fair comparison of solver algorithms. In any field where theory is limited, sound empirical methods must be used to measure progress and set future research directions. We present an HDF5 database, which provides a standard interface for the capture of data needed to reconstruct the time-stepping subproblem from any open-source physics engine e.g. Bullet, ODE, Gazebo, ChronoEngine etc. Timing data, as well as unilateral and bilateral constraint information is collected at the time-step level. This dataset may then be accessed later to reformulate the subproblem using different dynamics models. Applying different solvers to the CPs provides a comparison of solver performance and error analysis. This standard software interface provides a convenient and fair way to compare the solvers in the different physics engines as well as customized algorithms for multibody systems.
Protocol Data Parts Inclusion in a Formal Passive Testing Approach

Commonly, two main classes of formal testing techniques are applied to check the conformance of protocols and software: active and passive testing (monitoring) techniques. Because of many industrial constraints such as the necessity to achieve implementation black box testing, passive testing techniques become highly relevant in several cases. Besides, most of the passive testing techniques only consider control portions of exchanged packets and ignores data parts. However, since systems become more complex, testing for data constraints and relations between packets is now essential. In this paper we propose a novel approach for defining data oriented invariants and show how they can be tested in a trace set by using logic programming. Experimental results on SIP protocol traces are provided.
Independent Security Testing on Agile Software Development: A Case Study in a Software Company

Agile methodologies are becoming increasingly common on Software Engineering Teams. Unfortunately, their relation with the security activities is complex to approach, even more complex when the Security Team has strong requirements of independence. This paper shows a case study of a software security testing process, based on the Microsoft Software Development Lifecycle for Agile, on a company moving their Software Engineering Teams from waterfall to agile. The results of this case study show a successful synchronization between the tasks of agile Software Engineering Teams and the independent Security Team.
Screening of classical Casimir forces by electrolytes in semi-infinite geometries

We study the electrostatic Casimir effect and related phenomena in the equilibrium statistical mechanics of classical (non-quantum) charged fluids. The prototype model consists of two identical dielectric slabs in empty space (the pure Casimir effect) or in the presence of an electrolyte between the slabs. In the latter case, it is generally believed that the long-ranged Casimir force due to thermal fluctuations in the slabs is screened by the electrolyte into some residual short-ranged force. The screening mechanism is based on a 'separation hypothesis': thermal fluctuations of the electrostatic field in the slabs can be treated separately from the pure image effects of the 'inert' slabs on the electrolyte particles. In this paper, by using a phenomenological approach under certain conditions, the separation hypothesis is shown to be valid. The phenomenology is tested on a microscopic model in which the conducting slabs and the electrolyte are modelled by symmetric Coulomb gases of point-like charges with different particle fugacities. The model is solved in the high-temperature Debye–Huckel limit (in two and three dimensions) and at the free-fermion point of the Thirring representation of the two-dimensional Coulomb gas. The Debye–Huckel theory of a Coulomb gas between dielectric walls is also solved.
High-Performance Geospatial Analytics in HyPerSpace

In the past few years, massive amounts of location-based data has been captured. Numerous datasets containing user location information are readily available to the public. Analyzing such datasets can lead to fascinating insights into the mobility patterns and behaviors of users. Moreover, in recent times a number of geospatial data-driven companies like Uber, Lyft, and Foursquare have emerged. Real-time analysis of geospatial data is essential and enables an emerging class of applications. Database support for geospatial operations is turning into a necessity instead of a distinct feature provided by only a few databases. Even though a lot of database systems provide geospatial support nowadays, queries often do not consider the most current database state. Geospatial queries are inherently slow given the fact that some of these queries require a couple of geometric computations. Disk-based database systems that do support geospatial datatypes and queries, provide rich features and functions, but they fall behind when performance is considered: specifically if real-time analysis of the latest transactional state is a requirement. In this demonstration, we present HyPerSpace, an extension to the high-performance main-memory database system HyPer developed at the Technical University of Munich, capable of processing geospatial queries with sub-second latencies.
Antiplatelet efficacy of XV459, a novel nonpeptide platelet GPIIb/IIIa antagonist: comparative platelet binding profiles with c7E3.

Recent advances in the development of i.v. platelet glycoprotein alphaIIb/beta3 integrin (GPIIb/IIIa) antagonists led to the development of either a class of small-molecular-weight antagonists with a short to ultra-short duration of antiplatelet effects (Integrelin, Tirofiban, DMP728) or a very long-acting antagonist (ReoPro). Thus the present study was undertaken to characterize the antiplatelet efficacy of a small-molecule GPIIb/IIIa antagonist, DMP754/XV459, and to determine its platelet GPIIb/IIIa receptor binding profiles. DMP754, upon its conversion with esterases to its free acid form XV459, and XV459 itself, demonstrated high potency (IC50 = 0.030-0.060 microM) in inhibiting human platelet aggregation induced by ADP (100 microM), thrombin receptor agonist peptide (10 microM) or collagen (20 microgram/ml) in citrate or heparin. Maximal platelet aggregation inhibition was achieved at 50 to >/=80% receptor occupancy, depending on the agonist used. Both XV459 and c7E3 bind with high affinity to either activated human platelets (Kd = 0.0008 and 0.0091 microM, respectively) or unactivated human platelets (Kd = 0.0025 and 0.0092 microM, respectively). XV459 demonstrated tight association with human, baboon and (to a lesser extent) canine platelets (t1/2 of dissociation = 7 +/- 0, 8 +/- 1 and 1.4 +/- 0.1 minutes, respectively). Both c7E3 and XV459 associate tightly with slower dissociation rates to unactivated human platelets. XV459 represents a potent antiplatelet agent in inhibiting platelet aggregation along with offering high affinity and a relatively slow dissociation rate from human platelet GPIIb/IIIa receptors that might allow for once-a-day p.o. dosage.
Circadian System and Melatonin Hormone: Risk Factors for Complications during Pregnancy

Pregnancy is a complex and well-regulated temporal event in which several steps are finely orchestrated including implantation, decidualization, placentation, and partum and any temporary alteration has serious effects on fetal and maternal health. Interestingly, alterations of circadian rhythms (i.e., shiftwork) have been correlated with increased risk of preterm delivery, intrauterine growth restriction, and preeclampsia. In the last few years evidence is accumulating that the placenta may have a functional circadian system and express the clock genes Bmal1, Per1-2, and Clock. On the other hand, there is evidence that the human placenta synthesizes melatonin, hormone involved in the regulation of the circadian system in other tissues. Moreover, is unknown the role of this local production of melatonin and whether this production have a circadian pattern. Available information indicates that melatonin induces in placenta the expression of antioxidant enzymes catalase and superoxide dismutase, prevents the injury produced by oxidative stress, and inhibits the expression of vascular endothelial growth factor (VEGF) a gene that in other tissues is controlled by clock genes. In this review we aim to analyze available information regarding clock genes and clock genes controlled genes such as VEGF and the possible role of melatonin synthesis in the placenta.
Multi-antenna-based transmission strategy in 5 GHz unlicensed band

Spectrum sharing technology has received a lot of attention as a promising solution for the problem on the shortage of spectrum resources due to mobile traffic increase. For the purpose of coexistence without harmful interference to incumbent services, secondary users (SUs) in spectrum sharing systems should adjust their transmission power while complying with regulatory requirements. In this paper, we develop the transmission strategies for multiple-antenna-based SU devices in 5GHz unlicensed band where a radar system is allocated as a primary user. We analyze the achievable throughput and bit error performances for the SU receiver using zero-forcing linear processing under imperfect channel estimation. Given the analytic results, we propose the dynamic transmission strategy on determination of the optimal number of active transmit antennas according to the restricted maximum transmission power corresponding to the received radar signal strength.
Strategies for Language Model Web-Data Collection

This paper presents an analysis of the use of textual information collected from the Internet via a search engine for the purpose of building domain specific language models. A framework to analyse the effect of search query formulation on the resulting Web-data language model performance in an evaluation is developed. The framework gives rise to improved methods of selecting n-gram search engine queries, which return documents that make better domain specific language models
Image segmentation with active contours based on selective visual attention

Telemedicine is growing and there is an increased demand for faster image processing and transmitting diagnostic medical images. Identifying and extracting the region of interest (ROI) accurately is an important step before coding and compressing the image data for efficient transmission or storage. The usual approach to extract ROI is to apply contour segmentation method. Chan-Vese active contour model [1] is a well-known image segmentation technique based on Mumford-Shah level set methods. Selective visual attention is a fundamental component of perceptual representation in a visual system. It influences the identification of a stimulus from those that operate after perception is complete. The Saliency Toolbox [2] is a collection of Matlab functions and scripts for computing the saliency map for an image, for determining the extent of a proto-object, and for serially scanning the image with the focus of visual attention. The implementation of the toolbox is extension of the saliency map-based model of bottom-up attention [3], by a process of inferring the extent of a proto-object at the attended location from the maps that are used to compute the saliency map. In this paper, we focus on extracting ROI by segmentation based on visual attended locations. Chan-Vese active contour model is used for image segmentation and attended locations are determined by SaliencyToolbox. Finally, we successfully segmented two attended locations of a medical image.
Understanding novice errors and error paths in Object-oriented programming through log analysis

What difficulties do beginners face when learning object-oriented programming? How are these reflected in the code they write? In the context of a new introductory programming course based on “inverted curriculum” ideas, and taking advantage of our ability to instrument the compiler, we obtained interaction logs from two different groups of students across two unrelated universities. We developed a methodology for analysing these logs to identify students’ intentions, with the goal of providing contextual feedback in an Intelligent Tutoring System.
ASAP: Automatic Smoothing for Attention Prioritization in Streaming Time Series Visualization

Time series visualization of streaming telemetry (i.e., charting of key metrics such as server load over time) is increasingly prevalent in recent application deployments. Existing systems simply plot the raw data streams as they arrive, potentially obscuring large-scale deviations due to local variance and noise. We propose an alternative: to better prioritize attention in time series exploration and monitoring visualizations, smooth the time series as much as possible to remove noise while still retaining large-scale structure. We develop a new technique for automatically smoothing streaming time series that adaptively optimizes this trade-off between noise reduction (i.e., variance) and outlier retention (i.e., kurtosis). We introduce metrics to quantitatively assess the quality of the choice of smoothing parameter and provide an efficient streaming analytics operator, ASAP, that optimizes these metrics by combining techniques from stream processing, user interface design, and signal processing via a novel autocorrelation-based pruning strategy and pixel-aware preaggregation. We demonstrate that ASAP is able to improve users’ accuracy in identifying significant deviations in time series by up to 38.4% while reducing response times by up to 44.3%. Moreover, ASAP delivers these results several orders of magnitude faster than alternative optimization strategies.
Ambient aerosol sampling using the Aerodyne Aerosol Mass Spectrometer

The Aerodyne Aerosol Mass Spectrometer (AMS) has been designed to measure size-resolved mass distributions and total mass loadings of volatile and semivolatile chemical species in/on submicron particles. This paper describes the application of this instrument to ambient aerosol sampling. The AMS uses an aerodynamic lens to focus the particles into a narrow beam, a roughened cartridge heater to vaporize them under high vacuum, and a quadrupole mass spectrometer to analyze the vaporized molecules. Particle size is measured via particle time-of-flight. The AMS is operated in two modes: (1) a continuous mass spectrum mode without size information; and (2) a size distribution measurement mode for selected m/z settings of the quadrupole. Single particles can also be detected and sized if they have enough mass of a chemical component. The AMS was deployed at a ground sampling site near downtown Atlanta during August 1999, as part of the Environmental Protection Agency/Southern Oxidant Study Particulate Matter “Supersite” experiment, and at a suburban location in the Boston area during September 1999. The major observed components of the aerosol at both sites were sulfate and organics with a minor fraction of nitrate, consistent with prior studies and colocated instruments. Different aerosol chemical components often had different size distributions and time evolutions. More than half of the sulfate mass was contained in 2% of the ambient particles in one of the sampling periods. Trends in mass concentrations of sulfate and nitrate measured with the AMS in Atlanta compare well with those measured with ion chromatography-based instruments. A marked diurnal cycle was observed for aerosol nitrate in Atlanta. A simple model fit is used to illustrate the integration of data from several chemical components measured by the AMS together with data from other particle instruments into a coherent representation of the ambient aerosol.
Beyond thinking in common categories: Predicting obstacle vulnerability using large random codebooks

Obstacle detection for advanced driver assistance systems has focused on building detectors for only a few number of object categories so far, such as pedestrians and cars. However, vulnerable obstacles of other categories are often dismissed, such as wheel-chairs and baby strollers. In our work, we try to tackle this limitation by presenting an approach which is able to predict the vulnerability of an arbitrary obstacle independently from its category. This allows for using models not specifically tuned for category recognition. To classify the vulnerability, we apply a generic category-free approach based on large random bag-of-visual-words representations (BoW), where we make use of both the intensity image as well as a given disparity map. In experimental results, we achieve a classification accuracy of over 80% for predicting one of four vulnerability levels for each of the 10000 obstacle hypotheses detected in a challenging dataset of real urban street scenes. Vulnerability prediction in general and our working algorithm in particular, pave the way to more advanced reasoning in autonomous driving, emergency route planning, as well as reducing the false-positive rate of obstacle warning systems.
Contour detection based on SUSAN principle and surround suppression

A contour edge detector combing SUSAN principle and surround suppression is proposed in this paper. Specifically, the operator follows the flow of the Canny edge detector. Firstly, the edge gradient information and modified SUSAN principle are utilized to classify contour edge points and texture edge points approximately. Secondly, surround suppression is applied on the texture edges to suppress them. Finally, contour map is constructed through two hysteresis thresholding procedures. Performance comparison with three other detectors is made and experimental results show that our contour detector performs better.