Miracle-dz/UniFAR-FTUs huggingface dataset:
Noninvasive in vivo human coronary artery lumen and wall imaging using black-blood magnetic resonance imaging.

BACKGROUND High-resolution MRI has the potential to noninvasively image the human coronary artery wall and define the degree and nature of coronary artery disease. Coronary artery imaging by MR has been limited by artifacts related to blood flow and motion and by low spatial resolution. METHODS AND RESULTS We used a noninvasive black-blood (BB) MRI (BB-MR) method, free of motion and blood-flow artifacts, for high-resolution (down to 0.46 mm in-plane resolution and 3-mm slice thickness) imaging of the coronary artery lumen and wall. In vivo BB-MR of both normal and atherosclerotic human coronary arteries was performed in 13 subjects: 8 normal subjects and 5 patients with coronary artery disease. The average coronary wall thickness for each cross-sectional image was 0.75+/-0.17 mm (range, 0.55 to 1.0 mm) in the normal subjects. MR images of coronary arteries in patients with >/=40% stenosis as assessed by x-ray angiography showed localized wall thickness of 4.38+/-0.71 mm (range, 3.30 to 5.73 mm). The difference in maximum wall thickness between the normal subjects and patients was statistically significant (P<0.0001). CONCLUSIONS In vivo high-spatial-resolution BB-MR provides a unique new method to noninvasively image and assess the morphological features of human coronary arteries. This may allow the identification of atherosclerotic disease before it is symptomatic. Further studies are necessary to identify the different plaque components and to assess lesions in asymptomatic patients and their outcomes.
Using predicate abstraction to reduce object-oriented programs for model checking

While it is becoming more common to see model checking applied to software requirements specifications, it is seldom applied to software implementations. The Automated Software Engineering group at NASA Ames is currently investigating the use of model checking for actual source code, with the eventual goal of allowing software developers to augment traditional testing with model checking. Because model checking suffers from the state-explosion problem, one of the main hurdles for program model checking is reducing the size of the program. In this paper we investigate the use of abstraction techniques to reduce the state-space of a real-time operating system kernel written in C++. We show how informal abstraction arguments could be formalized and improved upon within the framework of predicate abstraction, a technique based on abstract interpretation. We introduce some extensions to predicate abstraction that all allow it to be used within the class-instance framework of object-oriented languages. We then demonstrate how these extensions were integrated into an abstraction tool that performs automated predicate abstraction of Java programs.
Mapping Social Networks into P2P Directory Service

This paper presents our approach to use social network information in P2P networks in order to efficiently retrieve relevant information by exploiting existing trust relations of the social network links. The novelty of our work is to demonstrate that only a subset of the whole social network is adequate to build an efficient and reliable service. We use our P2P network, which is an adaptation of virtual ring routing mechanisms originally proposed for ad-hoc networks, to deploy a directory service facilitating search for friends - a common functionality required in online social networks as well. We expect our mechanism can be used in facilitating the deployment of peer-to-peer online social networks. Small scale experiment results, using both artificial as well as real social network graphs, show that with even only small subset of nodes from the whole social network, the approach achieves a high level of query success.
Proposal of flexible robotic arm with thin McKibben actuators mimicking octopus arm structure

An octopus arm has no rigid structure, it is mostly composed of muscles aligned in various directions and the nerves. The muscles are roughly aligned in three directions, and by driving the muscles selectively, the octopus arm can perform multiple functions such as the contracting, bending, torsion and stiffness alteration. This study aims at the development of a new flexible robotic arm using thin McKibben actuators mimicking the muscle structure of an octopus arm. The McKibben actuator is a well-known pneumatic artificial muscle, and we have developed extremely thin McKibben actuators by using a braiding machine. In this paper, configuration of the flexible arm is proposed. The developed mechanism consists of thirty two thin McKibben actuators arranged in three directions, axial, radial and oblique, imitating the muscle structure of an actual octopus arm. The fundamental motion of the flexible arm is investigated experimentally. The proposed mechanism performs bending, contracting, torsion movements and stiffness alteration like an octopus arm.
The average response time in a heavy-traffic srpt queue

Shortest Remaining Processing Time first (SRPT) has long been known to optimize the queue length distribution and the mean response time (a.k.a. flow time, sojourn time). As such, it has been the focus of a wide body of analysis. However, results about the heavy-traffic behavior of SRPT have only recently started to emerge. In this work, we characterize the growth rate of the mean response time under SRPT in the M/GI/1 system under general job size distributions. Our results illustrate the relationship between the job size tail and the heavy traffic growth rate of mean response time. Further, we show that the heavy traffic growth rate can be used to provide an accurate approximation for mean response time outside of heavy traffic.
IQR: an interactive query relaxation system for the empty-answer problem

We present IQR, a system that demonstrates optimization based interactive relaxations for queries that return an empty answer. Given an empty answer, IQR dynamically suggests one relaxation of the original query conditions at a time to the user, based on certain optimization objectives, and the user responds by either accepting or declining the relaxation, until the user arrives at a non-empty answer, or a non-empty answer is impossible to achieve with any further relaxations. The relaxation suggestions hinge on a proba- bilistic framework that takes into account the probability of the user accepting a suggested relaxation, as well as how much that relaxation serves towards the optimization objec- tive. IQR accepts a wide variety of optimization objectives - user centric objectives, such as, minimizing the number of user interactions (i.e., effort) or returning relevant results, as well as seller centric objectives, such as, maximizing profit. IQR offers principled exact and approximate solutions for gen- erating relaxations that are demonstrated using multiple, large real datasets.
E-mail as habitat: an exploration of embedded personal information management

Email has become more like a habitat than an application. It is used for a wide range of tasks such as information management and for coordination and collaboration in organizations. Our research shows that email is the place in which a great deal of work is received and delegated and is a growing portal for access to online publications and information services. It has become the place where PC users spend much if not most of their workdays (the application is always on, and is often the focus of attention). This, and the burgeoning quantities of messages and attachments that email delivers to people each day, has led users to co-opt it as a personal information management (PIM) tool. In fact this simply follows from what we have found to be a common tendency of knowledge workers, which is toembed personal information management directly into their favorite workspaces .
Robust Navigation Using GPS and INS: Comparing the Kalman Estimator and the Particle Estimator

The robustness of navigation systems based on a Global Satellite Navigation System (GNSS) is crucial and can be achieved in many ways, e.g. by using smart antennas (adaptive beamforming antennas or switched beam antennas) or complementing the GNSS with a jamming resistent sensor system. In order to investigate this latter method, a comparison has been performed between a relatively new type of state estimator, called the Particle method based on a linear Kalman Estimator (KE) when both are applied to the problem of combining information from a GNSS with an Inertial Navigation System (INS). This report is a detailed description of this comparison. The comparison of the two estimators regards essentially their robustness towards different types of un­ modeled errors in the three acceleration measurements. These errors consist of different combinations of white noise components and constant components (biases). KE uses a continuous linear error model. The task for the KE is to estimate the errors of the INS solution by using the difference between external measurements of velocity and position (from e.g. GPS) and the velocity and position as calculated by the INS. As the PE does not require linear system equations, it uses a nonlinear full state discrete model. The same external measurements are used as for the KE.english
Home-based SVM protocols for SMP clusters: Design and performance

As small-scale shared memory multiprocessors proliferate in the market, it is very attractive to construct large-scale systems by connecting smaller multiprocessors together in software using efficient commodity, network interfaces and networks. Using a shared virtual memory (SVM) layer for this purpose preserves the attractive shared memory programming abstraction across nodes. In this paper: We describe home-based SVM protocols that support symmetric multiprocessor (SMP) nodes, taking advantage of the intra-node hardware cache coherence and synchronization mechanisms. Our protocols take no special advantage of the network interface and network except as a fast communication link, and as such are very portable. We present the key design tradeoffs, discuss our choices, and describe key data structures that enable us to implement these choices quite simply. We present an implementation on a network of 4-way Intel PentiumPro SMPs interconnected with Myrinet, and provide performance results. We explore the advantages of SMP nodes over uniprocessor nodes with this protocol, as well as other performance tradeoffs, through both real implementation and simulation as appropriate, since both have important roles to play. We find one approach to deliver good parallel performance on many real applications (at least at the scale we examine) and to improve performance over SVM across uniprocessor nodes.
PLGA-Loaded Gold-Nanoparticles Precipitated with Quercetin Downregulate HDAC-Akt Activities Controlling Proliferation and Activate p53-ROS Crosstalk to Induce Apoptosis in Hepatocarcinoma Cells

Controlled release of medications remains the most convenient way to deliver drugs. In this study, we precipitated gold nanoparticles with quercetin. We loaded gold-quercetin into poly(DL-lactide-co-glycolide) nanoparticles (NQ) and tested the biological activity of NQ on HepG2 hepatocarcinoma cells to acquire the sustained release property. We determined by circular dichroism spectroscopy that NQ effectively caused conformational changes in DNA and modulated different proteins related to epigenetic modifications and c ell cycle control. The mitochondrial membrane potential (MMP), reactive oxygen species (ROS), cell cycle, apoptosis, DNA damage, and caspase 3 activity were analyzed by flow cytometry, and the expression profiles of different anti- and pro-apoptotic as well as epigenetic signals were studied by immunoblotting. A cytotoxicity assay indicated that NQ preferentially killed cancer cells, compared to normal cells. NQ interacted with HepG2 cell DNA and reduced histone deacetylases to control cell proliferation and arrest the cell cycle at the sub-G stage. Activities of cell cycle-related proteins, such as p21WAF, cdk1, and pAkt, were modulated. NQ induced apoptosis in HepG2 cells by activating p53-ROS crosstalk and induces epigenetic modifications leading to inhibited proliferation and cell cycle arrest.
Transaction-Data Analysis of Marked Durations and Their Implications for Market Microstructure

We propose an Autoregressive Conditional Marked Duration (ACMD) model for the analysis of irregularly spaced transaction data. Based on the Autoregressive Conditional Duration (ACD) model, the ACMD model assigns marks to characterize events such as tick movements and trade directions (buy/sell). Applying the ACMD model to tick movements, we study the influence of trade frequency, direction and size on price dynamics, volatility and the permanent and transitory price impacts of trade. We also apply the ACMD model to analyze trade-direction data and estimate the probability of informed trading (PIN). We find that trade frequency has a critical role in price dynamics while the contribution of volume to price impacts, volatility, and the probability of informed trading is marginal.
Cantor versus Harley: optimization and analysis of explicit formulae for hyperelliptic curve cryptosystems

Hyperelliptic curves (HEC) look promising for cryptographic applications, because of their short operand size compared to other public-key schemes. The operand sizes seem well suited for small processor architectures, where memory and speed are constrained. However, the group operation has been believed to be too complex and, thus, HEC have not been used in this context so far. In recent years, a lot of effort has been made to speed up group operation of genus-2 HEC. In this paper, we increase the efficiency of the genus-2 and genus-3 hyperelliptic curve cryptosystems (HECC). For certain genus-3 curves, we can gain almost 80 percent performance for a group doubling. This work not only improves Gaudry and Harley's algorithm, but also improves the original algorithm introduced by Cantor [1987]. Contrary to common belief, we show that it is also practical for certain curves to use Cantor's algorithm to obtain the highest efficiency for the group operation. In addition, we introduce a general reduction method for polynomials according to Karatsuba. We implemented our most efficient group operations on Pentium and ARM microprocessors.
Towards a taxonomy for security threats on the web ecosystem

The aim of this paper is to present a taxonomy for security threats on the Web ecosystem. We proposes a classification model based on 21 vectors divided into 8 distinct security threats, making use of levels of abstraction and criteria for discrimination which consider propagation and similarity in vulnerabilities. We also propose to estimate the risk factor and impacts on assets, considering data breaches, human aspects and service reliability. In addition, we validate the taxonomic model proposed through the catalogues of attacks facing the public. Thus, it was possible to observe its applicability for most of the attacks which appear before the public.
Multiobjective evolutionary community detection for dynamic networks

A multiobjective genetic algorithm for detecting communities in dynamic networks, i.e., networks that evolve over time, is proposed. The approach leverages on the concept of evolutionary clustering, assuming that abrupt changes of community structure in short time periods are not desirable. The algorithm correctly detects communities and it is shown to be very competitive w.r. t. some state-of-the-art methods.
Reducing distraction of smartwatch users with deep learning

Smartwatches are overloaded with various notifications from smartphones. Users are largely distracted, while they may benefit from these relayed notification. To reduce smartwatch user's distraction, we propose an intelligent notification delivery system that relays only important notifications to the smartwatch. We claim that important notifications should be handled within a certain time and they are involved in launching mobile applications. To build model, we collect 6491 notifications and sensor data from three users. A mobile application has been developed to unobtrusively monitor relevant data Then, we implemented a binary classifier which identifies important notifications using deep learning and 8 features are extracted from sensor data. Our classifier shows that an important notification can be predicted with 61% - 90% and 51% - 99% of precision and recall.
A faster circular binary segmentation algorithm for the analysis of array CGH data

MOTIVATION Array CGH technologies enable the simultaneous measurement of DNA copy number for thousands of sites on a genome. We developed the circular binary segmentation (CBS) algorithm to divide the genome into regions of equal copy number. The algorithm tests for change-points using a maximal t-statistic with a permutation reference distribution to obtain the corresponding P-value. The number of computations required for the maximal test statistic is O(N2), where N is the number of markers. This makes the full permutation approach computationally prohibitive for the newer arrays that contain tens of thousands markers and highlights the need for a faster algorithm. RESULTS We present a hybrid approach to obtain the P-value of the test statistic in linear time. We also introduce a rule for stopping early when there is strong evidence for the presence of a change. We show through simulations that the hybrid approach provides a substantial gain in speed with only a negligible loss in accuracy and that the stopping rule further increases speed. We also present the analyses of array CGH data from breast cancer cell lines to show the impact of the new approaches on the analysis of real data. AVAILABILITY An R version of the CBS algorithm has been implemented in the "DNAcopy" package of the Bioconductor project. The proposed hybrid method for the P-value is available in version 1.2. 1 or higher and the stopping rule for declaring a change early is available in version 1.5. 1 or higher.
Enabling Large-Scale Pervasive Logic Verification through Multi-Algorithmic Formal Reasoning

Pervasive logic is a broad term applied to the variety of logic present in hardware designs, yet not a part of their primary functionality. Examples of pervasive logic include initialization and self-test logic. Because pervasive logic is intertwined with the functionality of chips, the verification of such logic tends to require very deep sequential analysis of very large slices of the design. For this reason, pervasive logic verification has hitherto been a task for which formal algorithms were not considered applicable. In this paper, we discuss several pervasive logic verification tasks for which we have found the proper combination of algorithms to enable formal analysis. We describe the nature of these verification tasks, and the testbenches used in the verification process. We furthermore discuss the types of algorithms needed to solve these verification tasks, and the type of tuning we performed on these algorithms to enable this analysis
Multivariate regression analysis for estimating the channel capacity of small MIMO antennas regarding correlation, power imbalance, and SNR

A simple and efficient method of the evaluation of MIMO channel capacity has been proposed. First, the channel capacity of a half wavelength dipole array antenna was calculated using a Monte Carlo method by changing incident wave SNR, power difference between two elements, and correlation coefficient. Using the calculated results, a polynomial function of estimating the channel capacity was given by the multivariate regression analysis. Effectiveness of the developed function was verified by comparing the channel capacity estimated by the developed function and that calculated by the Monte Carlo method using a MIMO array antenna mounted on a mobile terminal close to the human body. Finally, GUI software has been developed, so that simple and efficient calculation of the MIMO channel capacity can be performed without a large amount of computer and human resources.
Semi-automatic generation of UML models from natural language requirements

Going from requirements analysis to design phase is considered as one of the most complex and difficult activities in software development. Errors caused during this activity can be quite expensive to fix in later phases of software development. One main reason for such potential problems is due to the specification of software requirements in Natural Language format. To overcome some of these defects we have proposed a technique, which aims to provide semi- automated assistance for developers to generate UML models from normalized natural language requirements using Natural Language Processing techniques. This technique initially focuses on generating use-case diagram and analysis class model (conceptual model) followed by collaboration model generation for each use-case. Then it generates a consolidated design class model from which code model can also be generated. It also provides requirement traceability both at design and code levels by using Key-Word-In-Context and Concept Location techniques respectively to identify inconsistencies in requirements. Finally, this technique generates XML Metadata Interchange (XMI) files for visualizing generated models in any UML modeling tool having XMI import feature. This paper is an extension to our existing work by enhancing its complete usage with the help of Qualification Verification System as a case study.
Coordinating Social Communication in Human-Robot Task Collaborations

ix Chapter 1: Introduction 1 1.1 Overview . 1 1.1.1 Human-Robot Task Collaboration . 1 1.1.2 Approach to Coordinating Social Communication . 3 1.2 Contributions . 7 1.3 Outline . 9 Chapter 2: Background and Related Work 10 2.1 Human-Human Collaboration . 10 2.1.1 Perspective-Taking and Theory-of-Mind . 11 2.1.2 Human Activity Modeling and Recognition . 13 2.2 Multi-Robot Coordination and Applicability to the Human-Robot Case 13 2.2.1 Task Classifications . 15 2.3 Human-Robot Collaboration . 18 2.4 Summary . 20 Chapter 3: Planning of Coordinating Social Communication 22 3.1 Human-Robot Task Representation . 25 3.2 Representing and Recognizing Human Activity . 27 3.3 Communication Planning . 31 3.4 Extensions of the Approach . 33 3.5 Summary . 35
Perception and estimation of time.

nouns or of photographs of faces. This difference in roles of the two hemispheres was to be tested by using right-handed and left-handed Ss. The results were negative, but also the hypotheses were weak. Does a recognition task not always involve the dominant hemisphere? By considering large groups of Ss having brain lesions in widely differing areas , and by subjecting them to a test battery (involving manipulation of temporal concepts estimating time periods , sequence of events , judging and producing short and long intervals singly and in pairs), Bruyer & Bontemps­ Devogel (1979) found that by comparison with a control group, the Ss with lesions showed a lower level of performance . The group with frontal lesions showed a marked disability. A final point to indicate, and it is merely a confIrmation, is that there is no relationship between the alpha rhythm and temporal estimations (Adam et al 1971) . However, Coffin & Ganz ( 1 977) found in the estimation of a 5 sec task a high correlation between the estima­ tions and the weighted mean frequency of the EEG close to the alpha fre­