Miracle-dz/UniFAR-FTUs huggingface dataset:
Surgical Endovascular Neuroradiology in the 21st Century: What Lies Ahead?

FEW COULD HAVE imagined the tremendous growth of endovascular surgery over the past 40 years. Endovascular therapy has greatly enhanced the care of the patient in neurosurgery, spine surgery, and head and neck surgery. Progress in technology and techniques continue to push forward the boundaries of what is deemed “treatable,” assuming acceptable risk. This article will briefly review the current state of endovascular surgery and speculate about what its role will be in the near and far future. Endovascular therapy provides a minimally invasive approach to the central nervous system and other systems via natural and, at times, highly selective pathways. Maximizing the accessibility of these routes to highly specific regions of the central nervous system provides an elegant and minimalist approach to treating diseases of the central nervous system with almost no “footprints” of ever having accessed the region. In the future, safe, efficient and intelligent delivery systems that may enhance or alter the tissue's response may result in successful treatment of cerebrovascular diseases, as well as other diseases of the craniospinal axis. The growth of nanotechnology, metallurgy, synthetic polymers, imaging, and training will all combine to help grow the technology and the science that is surgical endovascular neuroradiology.
AnCora-UPF: A Multi-Level Annotation of Spanish

There is an increasing need for the annotation of multiple types of linguistic information that are rather different in their nature, e.g., word order, morphological features, syntactic and semantic relations, etc. Quite frequently, their annotation is combined in a single structure, which not only results in inadequate annotations of treebanks and consequent low-quality applications trained on them, but also is deficient from a theoretical (linguistic) perspective. We present a new corpus of Spanish annotated on four independent levels, morphology, surface-syntax, deep-syntax and semantics, as well as the methodology that allows for obtaining it with fewer cost while maintaining a high inter-annotator agreement.
APPLYING GENETIC ALGORITHMS TO QUEUING NETWORK DESIGN

This study evaluates the efficacy of using the continuous genetic algorithm (GA) to solve complex queuing network problems. Queuing network design involves random processes and decisions that are subject to a cost constraint. Therefore, we run a simulation program to determine the fitness of each solution in the population. The GA produces good results compared to alternative methods, without the need for restrictive assumptions.
Human TCR-αβ+ CD4− CD8− T Cells Can Derive from CD8+ T Cells and Display an Inflammatory Effector Phenotype1

The origin and function of human double negative (DN) TCR-αβ+ T cells is unknown. They are thought to contribute to the pathogenesis of systemic lupus erythematosus because they expand and accumulate in inflamed organs. In this study, we provide evidence that human TCR-αβ+ CD4− CD8− DN T cells can derive from activated CD8+ T cells. Freshly isolated TCR-αβ+ DN T cells display a distinct gene expression and cytokine production profile. DN cells isolated from peripheral blood as well as DN cells derived in vitro from CD8+ T cells produce a defined array of proinflammatory mediators that includes IL-1β, IL-17, IFN-γ, CXCL3, and CXCL2. These results indicate that, upon activation, CD8+ T cells have the capacity to acquire a distinct phenotype that grants them inflammatory capacity.
VALIDATION OF NEPTUNE _ CFD 1 . 0 . 8 FOR ADIABATIC BUBBLY FLOW AND BOILING FLOW

The NEPTUNE_CFD code, which is based on an Eulerian two-fluid model, is mainly focused on Nuclear Reactor Safety applications involving two-p hase flows, like Pressurized Thermal Shock and Departure from Nucleate Boiling (DNB). Since the ma turity of two-phase CFD has not reached yet the same level as single phase CFD, an important work o f model development and thorough validation is needed. Many of these applications involve bubbly a nd boiling flows, and therefore it is essential to validate the software on such configurations. In pa rticular, this is crucial for applications to flow in PWR fuel assemblies, including studies related to D NB. Four experiments were selected for the validation. The Liu and Bankoff experiment (1993) a nd the Bel F'Dhila experiment (1991) for adiabatic air-water bubbly flow. The DEBORA (Manon, 2000) and the ASU (Hasan, 1990) facilities for boiling flows. A key feature of this work is th at all these computations were performed with a single standard version (1.0.8) of NEPTUNE_CFD, and with a single and consistent set of models. Comparisons with experimental data show that NEPTUN E_CFD has captured experimental profiles with reasonable accuracy for dynamical quantities a nd void fraction. Improvement must be done for the prediction of the bubbles size distribution.
A new structural approach in system identification with generalized analysis-by-synthesis for robust speech coding

In this paper, we apply a new structural approach to generalized analysis-by-synthesis (GAbS) for system identification as a preprocessor of a low-bit-rate speech coder. In our approach, the coder-decoder (CODEC) system is separately estimated and then applied to modify the current input signal. This is different from that originally proposed where the CODEC system is sequentially estimated and then applied to the next input signal. The proposed estimation scheme is compared to the conventional method in terms of the signal modification approach under the various noise data and in several SNR conditions, and shows better performance.
Imaging device, and an imaging system

PROBLEM TO BE SOLVED: To provide an image pickup device which is compact and can photograph a stereoscopic image easily, and an image pickup system.SOLUTION: The image pickup device includes a plurality of image pickup elements each having a transparent substrate and a photodetector disposed on one face of the transparent substrate and having a transparency, the plurality of image pickup elements being placed one on top of another so that the transparent substrate and the photodetector are alternately superposed on each other. Each of the plurality of image pickup elements has a focal distance differing from each other, and the thickness of each photodetector is set so that the light-receiving amount of each photodetector included in the plurality of image pickup elements is equalized.
EXPLORING THE FUZZY NATURE OF TECHNICAL PATTERNS OF U . S STOCK MARKET

Technical analysis has been a part of financial practice for many decades. One of the most challenging areas in technical analysis is the automatic detection of technical patterns that are similar in the eyes of expert investors. In this paper, we propose a fuzzy logic based approach for technical analysis. By introducing the inter & intra fuzzification into an automatic pattern detection and analysis process, we incorporate human cognitive uncertainty into the technical analysis domain. Using a random sample of U. S. stocks, we find that our approach is able to detect subtle differences within a clearly defined pattern template. Our results suggest that such subtle differences could be a source of controversy surrounding technical analysis. Comparing with existing visual technical pattern analysis approaches, our fuzzy logic based approach offers superior precision in detecting and interpreting the technical patterns.
Self-Esteem and In-Group Bias Among Members of a Religious Social Category

Abstract In a sample of New Zealand university students, the author extended earlier research into the relationship between self-esteem and intergroup discrimination. He found no support for the hypothesis that social-category members (i.e., Christians) experience an elevation in the domain of self-esteem (i.e., religious self-esteem) judged as more relevant to the in-group after evaluations favoring the in-group. Regardless of whether the evaluation targets behaved positively or negatively, the respondents in the experimental condition evaluated in-group (Christian) targets more highly than out-group (Atheist) targets. After evaluations favoring the in-group, the respondents did not experience an elevation of religious self-esteem, global self-esteem, or mathematical self-esteem (judged as less relevant to the in-group).
Outage Analysis and Optimization for Time Switching-based Two-Way Relaying with Energy Harvesting Relay Node

Energy harvesting (EH) and network coding (NC) have emerged as two promising technologies for future wireless networks. In this paper, we combine them together in a single system and then present a time switching-based network coding relaying (TSNCR) protocol for the two-way relay system, where an energy constrained relay harvests energy from the transmitted radio frequency (RF) signals from two sources, and then helps the two-way relay information exchange between the two sources with the consumption of the harvested energy. To evaluate the system performance, we derive an explicit expression of the outage probability for the proposed TSNCR protocol. In order to explore the system performance limit, we formulate an optimization problem to minimize the system outage probability. Since the problem is non-convex and cannot be directly solved, we design a genetic algorithm (GA)-based optimization algorithm for it. Numerical results validate our theoretical analysis and show that in such an EH two-way relay system, if NC is applied, the system outage probability can be greatly decreased. Moreover, it is shown that the relay position greatly affects the system performance of TSNCR, where relatively worse outage performance is achieved when the relay is placed in the middle of the two sources. This is the first time to observe such a phenomena in EH two-way relay systems.
Selective concentration of human cancer cells using contactless dielectrophoresis

This work is the first to demonstrate the ability of contactless dielectrophoresis (cDEP) to isolate target cell species from a heterogeneous sample of live cells. Since all cell types have a unique molecular composition, it is expected that their dielectrophoretic (DEP) properties are also unique. cDEP is a technique developed to improve upon traditional and insulator‐based DEP devices by replacing embedded metal electrodes with fluid electrode channels positioned alongside desired trapping locations. Through the placement of the fluid electrode channels and the removal of contact between the electrodes and the sample fluid, cDEP mitigates issues associated with sample/electrode contact. MCF10A, MCF7, and MDA‐MB‐231 human breast cells were used to represent early, intermediate, and late‐staged breast cancer, respectively. Trapping frequency responses of each cell type were distinct, with the largest difference between the cells found at 20 and 30 V. MDA‐MB‐231 cells were successfully isolated from a population containing MCF10A and MCF7 cells at 30 V and 164 kHz. The ability to selectively concentrate cells is the key to development of biological applications using DEP. The isolation of these cells could provide a workbench for clinicians to detect transformed cells at their earliest stage, screen drug therapies prior to patient treatment, increasing the probability of success, and eliminate unsuccessful treatment options.
A computer-based test to raise awareness of disability issues

The purpose of this poster is to share our experience of a staff development tool that has been developed to raise awareness amongst staff about issues that students with disabilities might face. A computer-based test has been created as a training tool to raise awareness among university academic staff of some common experiences faced by people with visual, mobility, hearing and cognitive difficulties when using a computer [1]. The development team is based at Leeds Metropolitan University and is part of a UK centrally-funded "Centre for Excellence in Teaching and Learning" (CETL) [2], in collaboration with the Universities of Durham, Newcastle and Leeds. The Centre is devoted to promoting "Active Learning in Computing" (ALiC) [3] and is the only CETL within the Computer Science academic area. This test simulates experiences of disabled students who use computers and take computer-based tests, and provides advice and guidance to university teaching staff on how they may best cater for the needs of such students. The poster presents the reasons for creating such a tool in such a format, its structure and content.
Depressive symptoms in middle-aged women are more strongly associated with physical health and social support than with socioeconomic factors

The association of socioeconomic factors, health-related factors, and social support with depressive symptoms has been extensively studied. However, most epidemiological studies have focused on a few factors such as marital status, social class, and employment. In this study of middle-aged women we analyzed both univariate and multivariate associations of socioeconomic factors, perceived physical health factors, and social support with self-rated depressive symptoms measured with the Beck Depression Inventory. A nationwide sample (n =1851) of Finnish women aged 48 -50 years was analyzed. Socioeconomic, health-related, and social support factors were all measured with single items. All variables, except level of urbanization, were significantly associated with depressive symptoms in univariate analyses. Multivariate associations were examined with standard multiple regression analyses in three stages: first with the socioeconomic factors, then with socioeconomic and health factors, and finally entering the social support factors into the regression model. In the first model, being either on a sick leave or at home as working status, being divorced, and having low income reached significance. In the second model, being divorced and having poor perceived physical health were the most powerful among the five significant variables. In the last model, explaining 32% of the variance, the most powerful predictors of depressive symptoms were perceived current physical health, satisfaction with received social support, and quality of intimate relationships. For the prevention or intervention of depressive symptoms among middle-aged women in the population subjects with concurrent subjective or objective health problems and poor social support seem to comprise a particularly important target group.
On the quality assessment of advanced e-learning services

Distance learning has been widely researched the past few years, nevertheless the focus has been more on its technological dimension. Designing, developing and supporting a large scale e‐learning application for Higher Education is still a challenging task in many ways. E‐learning is data‐intensive, user‐driven, and has increasing needs for multiculturalism, efficiency, adaptivity and competiveness. Although the complexity of such systems has increased exponentially, the design process still lacks a systematic quality control procedure. In this work we address the increasing need for new methods that maximize usability, and thus end‐user satisfaction. We analyse the technological, managerial and economic factors that affect the design and deployment of a large e‐learning platform with advanced services and propose a set of new metrics for assessing its quality. The metrics are based on the four external quality characteristics (functionality, usability, efficiency and reliability) of the ISO9126 standard for software systems.
Using Wi-Fi/magnetometers for indoor location and personal navigation

New location algorithms using Wi-Fi or/and magnetometer sensors are proposed considering the orientation impact on the measurements. The feasibility of magnetometer alone fingerprint positioning and orientation inference is also assessed with real indoor data. Android smart devices with low cost sensors are used to build up database along with a Gaussian Processes Regression (GPR) model and to collect independent track test to validate results. The corresponding performance of various solutions such as Wi-Fi alone, magnetometer alone and the magnetometer-aided Wi-Fi are compared. The effects of user's orientation on Wi-Fi signal strength, sensed magnetic fields and overall positioning results in real indoor office-like scenarios are also assessed and investigated.
PYMK: friend recommendation at myspace

In recent years Social Networking has enjoyed a significant increase in popularity. The main reason behind this surge in popularity is the social experience associated with connecting content to people and also connecting people with other people. Knowing, seeing, hearing what our friends and like-minded people feel or listen to or upload is an unparalleled experience. Similar to real life, finding good friends is not easy without the help of good recommendations. In this Industry Talk paper we present the MySpace friend recommendation algorithm named People You May Know. We will also comment on both the quality and the effectiveness of the algorithms.
User-Generated Content (UGC) encountered Enterprise-Generated Content (EGC): Quantifying the Impact of EGC on the Propagation of Negative UGC

The impact of user-generated content (UGC), especially negative UGC on enterprises is well recognized. From the perspective of enterprises, different strategies of enterprise-generated content (EGC) have also been adapted to response to the unexpected UGC, but few studies have investigated the influence of such strategies on the UGC propagation. This research examines which strategy on the negative UGC propagation is optimal by proposing EGC-UGC interaction model. It aims to understand the interaction between UGC and EGC in the context of the social network. Using a simulation analysis method to measure the effect of such EGC factors as the first time of issuing EGC, EGC quantity and interactive frequency on the UGC propagation, the study finds that interactive frequency is the most key factor in defending against negative UGC propagation. This research further explores the effect of different strategy combination referring those three factors on the two types of negative UGC propagation based on deviation distance. The results present two optimal strategies for the two types of negative UGC propagation, respectively. Overall, these findings offer some unique implication for UGC management, information diffusion model of competitive information coexisting.
Entropy and Gravity Concepts as New Methodological Indexes to Investigate Technological Convergence: Patent Network-Based Approach

The volatility and uncertainty in the process of technological developments are growing faster than ever due to rapid technological innovations. Such phenomena result in integration among disparate technology fields. At this point, it is a critical research issue to understand the different roles and the propensity of each element technology for technological convergence. In particular, the network-based approach provides a holistic view in terms of technological linkage structures. Furthermore, the development of new indicators based on network visualization can reveal the dynamic patterns among disparate technologies in the process of technological convergence and provide insights for future technological developments. This research attempts to analyze and discover the patterns of the international patent classification codes of the United States Patent and Trademark Office's patent data in printed electronics, which is a representative technology in the technological convergence process. To this end, we apply the physical idea as a new methodological approach to interpret technological convergence. More specifically, the concepts of entropy and gravity are applied to measure the activities among patent citations and the binding forces among heterogeneous technologies during technological convergence. By applying the entropy and gravity indexes, we could distinguish the characteristic role of each technology in printed electronics. At the technological convergence stage, each technology exhibits idiosyncratic dynamics which tend to decrease technological differences and heterogeneity. Furthermore, through nonlinear regression analysis, we have found the decreasing patterns of disparity over a given total period in the evolution of technological convergence. This research has discovered the specific role of each element technology field and has consequently identified the co-evolutionary patterns of technological convergence. These new findings on the evolutionary patterns of technological convergence provide some implications for engineering and technology foresight research, as well as for corporate strategy and technology policy.
Model-based fault detection of gain and offset faults in Doubly Fed Induction Generators

Fault tolerance is gaining interest as a means to increase the reliability and availability of distributed energy systems. In this paper, a voltage-oriented Doubly-Fed Induction Generator is examined. This work applies formerly developped model based sensor fault tolerant control methods to gain and offset faults. For that reason, saturation is modelled. Fault detection is triggered by residuals. Fault isolation determines the faulty sensor. Replacement signals from observers are used to reconfigure the drive and re-enter closed loop control. While model based FDI for these faults is generally possible, it requires the fault to be large enough to be detectable.
Parallel Implicit Adaptive Mesh Refinement Scheme for Body-Fitted Multi-Block Mesh

A parallel implicit adaptive mesh refinement (AMR) algorithm is described for the system of partial-dierenti al equations governing steady two-dimensional compressible gaseous flows. The AMR algorithm uses an upwind finite-volume spatial discretization procedure in conjunction with limited linear solution reconstruction and Riemann-solver based flux functions to solve the governing equations on multi-block mesh composed of structured curvilinear blocks with quadrilateral computational cells. A flexible block-based hierarchical data structure is used to facilitate automatic solution-directed mesh adaptation according to physics-based refinement criteria. A matrix-free inexact Newton method is used to solve the system of nonlinear equations arising from this finite-volume spatial discretization procedure and a preconditioned generalized minimal residual (GMRES) method is used to solve the resulting non-symmetric system of linear equations at each step of the Newton algorithm. Right preconditioning of the linear system is used to improve performance of the Krylov subspace method. An additive Schwarz global preconditioner with variable overlap is used in conjunction with block-fill incomplete lower-upper (BFILU) type preconditioners based on the Jacobian of the first-order upwind scheme for each sub-domain. The Schwarz preconditioning and block-based data structure readily allow ecient and scalable parallel implementations of the implicit AMR approach on distributed-memory multi-processor architectures. Numerical results are described for several flow cases, demonstrating both the eectiveness of the mesh adaptation and algorithm parallel performance. The proposed parallel implicit AMR method allows for anisotropic mesh refinement and appears to be well suited for predicting complex flows with disparate spatial and temporal scales in a reliable and ecient fashion.