Miracle-dz/UniFAR-FTUs huggingface dataset:
Actin Is a Target of T-Cell Reactivity in Patients with Advanced Carotid Atherosclerotic Plaques

Atherosclerosis is a chronic inflammatory disease of the arterial wall associated with autoimmune reactions. In a previous study, we observed the presence of actin-specific antibodies in sera from patients with carotid atherosclerosis. To extend our previous results we evaluated the possible role of actin as antigenic target of cell-mediated immune reactions in carotid atherosclerosis. Peripheral blood mononuclear cells (PBMC) from 17 patients and 16 healthy subjects were tested by cell proliferation assay and by ELISA for cytokine production. Actin induced a proliferative response in 47% of patients' PBMC samples, with SI ranging from 2.6 to 21.1, and in none of the healthy subjects' samples (patients versus healthy subjects, P = 0.02). The presence of diabetes in patients was significantly associated with proliferative response to actin (P = 0.04). IFN-γ and TNF-α concentrations were higher in PBMC from patients than in those from healthy subjects and in PBMC proliferating to actin than in nonproliferating ones. Our data demonstrate for the first time a role of actin as a target autoantigen of cellular immune reactions in patients with carotid atherosclerosis. The preferential proinflammatory Th1 activation suggests that actin could contribute to endothelial dysfunction, tissue damage, and systemic inflammation in carotid atherosclerosis.
Initiating Organizational Memories using Ontology-based Network Analysis as a Bootstrapping Tool

An important problem for many kinds of knowledge systems is their initial set-up. It is difficult to choose the right information to include in such systems, and the right information is also a prerequisite for maximizing the uptake and relevance. To tackle this problem, most developers adopt heavyweight solutions and rely on a faithful continuous interaction with users to create and improve content. In this paper, we explore the use of an automatic, lightweight ontology-based solution to the bootstrapping problem, in which domain-describing ontologies are analysed to uncover significant yet implicit relationships between instances. We illustrate the approach by using such an analysis to provide content automatically for the initial set-up of an organizational memory.
PAIN OUT: The making of an international acute pain registry

About 240 million patients undergo surgery every year, worldwide. Roughly 50% of these patients report clinically significant pain. Numerous barriers impede provision of adequate management. Lack of evidence about appropriateness and effectiveness of interventions is one. A registry can provide such information, eventually facilitating better management. This paper reports the development and feasibility of PAIN OUT, the first international acute pain registry, established with funds from the European Commission, and presents preliminary analysis to illustrate the nature of investigations that registry data make possible.
Is Local Nitric Oxide Availability Responsible for Myocardial Salvage after Remote Preconditioning?

Background: Remote ischemic preconditioning (RIPC) represents an attractive therapy for myocardial protection, particularly when ischemic events can be anticipated. Although several hypothetic mechanisms have been proposed, no definite molecular pathways have been elucidated. Objective: We evaluated the effect of brachial circulation cuff occlusion on myocardial ischemic tolerance, necrosis, and nitric oxide (NO) in patients with ischemic heart disease undergoing elective percutaneous coronary interventions (PCI). Methods: 46 patients were randomly allocated into two groups: control and RIPC before PCI procedures. Electrocardiographic analysis, serum concentrations of troponin I (cTn-I) were measured at baseline and 24 hours after PCI. A blood sample from the atherosclerotic plaque was drawn to determine nitrate and nitrites. Results: RIPC increased the availability of NO in the stented coronary artery. Control patients presented a small but significant increase in cTn-I, whilst it remained unchanged in preconditioned group. The preconditioning maneuver not only preserved but also enhanced the sum of R waves. Conclusions: RIPC induced an intracoronary increase of NO levels associated with a decrease in myocardial damage (measured as no increase in cTn-I) with electrocardiographic increases in the sum of R waves, suggesting an improved myocardium after elective PCI.
International Conference on Research and Innovation in Information Systems – 2013 ( ICRIIS ’ 13 ) Taxonomies of User Experience ( UX ) Evaluation Methods

User Experiences (UX) and Usability are tightly coupled. They are yardsticks for successful interaction designs. Various methods are available to evaluate UX and usability respectively. Many arguments are presented in order to either distinguish or identify common grounds between the two. These evaluation methods are used in various different contexts and environments, and they fall into different types of taxonomy. Several UX and usability evaluation methods were reviewed and summarized in this paper. The result of analysis and observation indicates that there are correlations and disassociations between UX and Usability. Keywords-User Experience, UX, Usability, User Experience Evaluation Methods, Correlation, Disassociation
Finding Mixed-Memberships in Social Networks

This paper addresses the problem of unsupervised group discovery in social networks. We adopt a nonparametric Bayesian framework that extends previous models to networks where the interacting objects can simultaneously belong to several groups (i.e., mixed membership). For this purpose, a hierarchical nonparametric prior is utilized and inference is performed using Gibbs sampling. The resulting mixed-membership model combines the usual advantages of nonparametric models, such as inference of the total number of groups from the data, and provides a more flexible modeling environment by quantifying the degrees of membership to the various groups. Such models are useful for social information processing because they can capture a user’s multiple interests and hobbies.
A Stable Numerical Scheme for Stochastic Differential Equations with Multiplicative Noise

We introduce a new approach for designing numerical schemes for stochastic differential equations (SDEs). The approach, which we have called the direction and norm decomposition method, proposes to approximate the required solution $X_t$ by integrating the system of coupled SDEs that describes the evolution of the norm of $X_t$ and its projection on the unit sphere. This allows us to develop an explicit scheme for stiff SDEs with multiplicative noise that shows a solid performance in various numerical experiments. Under general conditions, the new integrator preserves the almost sure stability of the solutions for any step-size, as well as the property of being distant from $0$. The scheme also has a linear rate of weak convergence for a general class of SDEs with locally Lipschitz coefficients, and one-half strong order of convergence.
MOT: memory online tracing of Web information system

With advances in World-Wide Web applications and technologies, research on measurement and modeling of Internet and Web-based information systems has become increasingly important This paper focuses on continuously monitoring Web traffic by packet sniffing on high-speed links, which is the foundation of analyzing theoretical models of Web characteristics and evolvement. The author presents MOT, a memory online tracing system of Web traffic. MOT parses all packets in memory directly without involving unnecessary I/0 operations with magnetic disks to enhance the system performance. Event-driven design pattern and several other techniques are adopted in MOT to overcome the difficulties of buffering huge volume of traffic. MOT provides a fast, accurate and safe way to obtain the source data for many Web-related studies.
Incremental Detection of Inconsistencies in Distributed Data

This paper investigates incremental detection of errors in distributed data. Given a distributed database D, a set Σ of conditional functional dependencies (CFDs), the set V of violations of the CFDs in D, and updates ΔD to D, it is to find, with minimum data shipment, changes ΔV to V in response to ΔD. The need for the study is evident since real-life data is often dirty, distributed and frequently updated. It is often prohibitively expensive to recompute the entire set of violations when D is updated. We show that the incremental detection problem is NP-complete for database D that is partitioned either vertically or horizontally, even when Σ and D are fixed. Nevertheless, we show that it is bounded: there exist algorithms to detect errors such that their computational cost and data shipment are both linear in the size of ΔD and ΔV, independent of the size of the database D. We provide such incremental algorithms for vertically partitioned data and horizontally partitioned data, and show that the algorithms are optimal. We further propose optimization techniques for the incremental algorithm over vertical partitions to reduce data shipment. We verify experimentally, using real-life data on Amazon Elastic Compute Cloud (EC2), that our algorithms substantially outperform their batch counterparts.
Biotope of Corsac Fox and Red Fox in Ikh Nart Nature Reserve

Corsac foxes ( Vulpes corsac ) and red foxes ( V. vulpes ) range widely across northern and central Asia, occupying a variety of arid biotopes. In Mongolia, both species live sympatrically throughout most of the country, but few details of their habitat associations exist. We examined the biotope of corsac and red foxes in Ikh Nart Nature Reserve in Dornogobi Aimag, Mongolia, which lies at the confluence of steppe and semi-desert vegetation zones. We evaluated the extent to which both species occur in these two zones and the habitats within them based on locations of scats ( n = 1,967), opportunistic sightings ( n = 219), and captures ( n = 35) collected from August 2004 to August 2007. Corsac and red foxes occurred in both steppe and semi-desert zones and all habitat types in the reserve. However, corsacs occurred more frequently than expected in steppe zone and red foxes occurred more than expected in semi-desert zone. Corsac locations associated positively with steppe habitats, including grass, shrub, and semi-shrub plains, whereas red fox locations fell mainly in drier, more rugged semi-desert habitats, suggesting ecological separation exists between species. As corsac and red foxes appear to be declining in Mongolia, our results suggest that protection efforts in Ikh Nart should focus on steppe habitats for corsacs and semi-desert habitats for red foxes.
An Experimental Platform for Scholarly Article Recommendation

We describe the experimental recommendation platform created in collaboration with the Social Science Research Network (SSRN). This system allows for researchers to test recommendation algorithm on SSRN’s users and quickly collect feedback on the efficacy of their recommendations. We further describe a test run performed using EigenFactor recommends and compare its performance to SSRN’s production recommender.
Architecture for Intelligent Big Data Analysis based on Automatic Service Composition

Big Data contains massive information, which are generating from heterogeneous, autonomous sources with distributed and anonymous platforms. Since, it raises extreme challenge to organizations to store and process these data. Conventional pathway of store and process is happening as collection of manual steps and it is consuming various resources. An automated real-time and online analytical process is the most cognitive solution. Therefore it needs state of the art approach to overcome barriers and concerns currently facing by the Big Data industry. In this paper we proposed a novel architecture to automate data analytics process using Nested Automatic Service Composition (NASC) and CRoss Industry Standard Platform for Data Mining (CRISPDM) as main based technologies of the solution. NASC is well defined scalable technology to automate multidisciplined problems domains. Since CRISP-DM also a well-known data science process which can be used as innovative accumulator of multi-dimensional data sets. CRISP-DM will be mapped with Big Data analytical process and NASC will automate the CRISP-DM process in an intelligent and innovative way.
“Teddies” and the Origin of the Leeuwin Current

Abstract The outflow from the Indonesian seas empties approximately 5–7 Sv of surface warm (and low salinity) Indonesian Throughflow water into the southern Indian Ocean (at roughly 12°S). Using a nonlinear 1½-layer model with a simple geometry consisting of a point source (of anomalous water) situated along a meridional wall on a β plane, the spreading of these waters is examined. An analytical solution is constructed with the aid of the “slowly varying” approach, and process-oriented numerical simulations are performed. It is found that, immediately after emptying into the ocean, the outflow splits into two branches. One branch carries approximately 13% of the source mass flux and forms a chain of high amplitude anticyclonic eddies (lenses) immediately to the west of the source. These eddies drift westward and penetrate into the interior of the Indian Ocean. The second branch carries the remaining 87% of the mass flux via a coastal southward flowing current. Ultimately, this second branch separates from.
Balanced BPF with controllable dual passband performance

In this paper, balanced bandpass filter (BPF) with controllable dual passband performance is presented. Based on the voltage distribution of traditional half-wavelength resonator, the stub-loaded theory with independently controlled differential-mode resonances is presented and applied to design dual-band balanced BPF with independently controlled passband locations. Then, except for the main coupling path, by introducing coupling between the loaded stubs, another coupling path can be obtained to independently control the bandwidth of the first differential-mode passband. To validate the proposed idea, the balanced dual-band BPF is designed and simulated.
A Fast Universal Immobilization of Immunoglobulin G at 4°C for the Development of Array-based Immunoassays

To maintain the antibody activity and enhance performance of array-based immunoassays, protein G was used to allow a shorter duration of immunoglobulin G immobilization at 4°C, with the antibody placed in the appropriate orientation. The multiplexed detection of six pain-related message molecules (PRMMs) was used as examples for the development of array-based immunoassays: substance P, calcitonin gene-related peptide, nerve growth factor, brain-derived neurotrophic factor, tumor necrosis factor-α, and β-endorphin. Protein G- and non-protein G-coated slides were tested. Compared to non-protein G immunoassays, protein G shortened the antibody immobilization time at 4°C from overnight to 2 hours. Only protein G-facilitated immunoassays succeeded in simultaneously detecting all six PRMMs with high specificity. Dose-response curves showed that the limits of detection of the protein G-multiplexed immunoassays for the PRMMs was approximately 164, 167, 120, 60, 80, and 92 pg/ml, respectively. Thus, protein G effectively shortens the duration of antibody immobilization at 4°C, allowing the use of sensitive array-based immunoassays for the simultaneous detection of PRMMs.
An experimental study comparing the relative effectiveness of functional, scan, IDDq and delay-fault testing

This paper describes an experiment in which various semiconductor test methodologies (stuck-fault, functional, delay and IDDq) are applied to an ASIC device. The goal of this project is to provide the data that will enable manufacturers to optimize their application of the various tests. This project was supported through SEMATECH (Project S-121, "Semiconductor Test Method Evaluation ").
Effective 3D object detection and regression using probabilistic segmentation features in CT images

3D object detection and importance regression/ranking are at the core for semantically interpreting 3D medical images of computer aided diagnosis (CAD). In this paper, we propose effective image segmentation features and a novel multiple instance regression method for solving the above challenges. We perform supervised learning based segmentation algorithm on numerous lesion candidates (as 3D VOIs: Volumes Of Interest in CT images) which can be true or false. By assessing the statistical properties in the joint space of segmentation output (e.g., a 3D class-specific probability map or cloud), and original image appearance, 57 descriptive features in six subgroups are derived. The new feature set shows excellent performance on effectively classifying ambiguous positive and negative VOIs, for our CAD system of detecting colonic polyps using CT images. The proposed regression model on our segmentation derived features behaves as a robust object (polyp) size/importance estimator and ranking module with high reliability, which is critical for automatic clinical reporting and cancer staging. Extensive evaluation is executed on a large clinical dataset of 770 CT scans from 12 medical sites for validation, with the best state-of-the-art results.
Forcoa.NET: An interactive tool for exploring the significance of authorship networks in DBLP data

This paper presents an online analysis tool called Forcoa.NET, which is built over the DBLP dataset of publications from the field of computer science. The developed tool is focused on the analysis and visualization of the co-authorship relationship based on the intensity and topic of joint publications. The visualization of co-authorship networks allows to describe the author and his/her current surroundings while still incorporating the historical aspect. The analysis is based on using the forgetting function to hold the information relevant to the selected date. After this analysis, we are capable of computing several measures, which can describe different aspects of user behaviour from the point of view of scientific social network.
SPC03-5: Analog Multi-Tone Signaling for High-Speed Backplane Electrical Links

Implementing a multi-tone (MT) architecture for high-speed backplane electrical links is difficult given the tight power and complexity constraints in this application. This paper proposes an approach that incorporates a baseband (BB) channel and a few passband (PB) channels. In this MT system inter- channel interference (ICI) and inter-symbol interference (ISI) are eliminated through fractionally spaced equalization at the transmitter and feedback equalization at the receiver. The design is modeled as a MIMO system, and optimal equalizer coefficients to minimize the transmit peak voltage are found by casting the optimization as a Second Order Conic (SOC) problem. In addition, for systems that need adaptation, we show how equalizer and power allocation coefficients can be obtained (sub optimally) using Zero Forcing (ZF) optimization. The effect of transmitter and receiver clock jitter are modeled in a way that can be included in both SOC and ZF optimizations, and the performance of this system is compared to more conventional baseband examples. It is shown that this AMT system can be built with complexity/power similar to a comparable performance baseband system, but has the ability to scale to higher bit rates.
Astaxanthin Alleviates Early Brain Injury Following Subarachnoid Hemorrhage in Rats: Possible Involvement of Akt/Bad Signaling

Apoptosis has been proven to play a crucial role in early brain injury pathogenesis and to represent a target for the treatment of subarachnoid hemorrhage (SAH). Previously, we demonstrated that astaxanthin (ATX) administration markedly reduced neuronal apoptosis in the early period after SAH. However, the underlying molecular mechanisms remain obscure. In the present study, we tried to investigate whether ATX administration is associated with the phosphatidylinositol 3-kinase-Akt (PI3K/Akt) pathway, which can play an important role in the signaling of apoptosis. Our results showed that post-SAH treatment with ATX could cause a significant increase of phosphorylated Akt and Bad levels, along with a significant decrease of cleaved caspase-3 levels in the cortex after SAH. In addition to the reduced neuronal apoptosis, treatment with ATX could also significantly reduce secondary brain injury characterized by neurological dysfunction, cerebral edema and blood-brain barrier disruption. In contrast, the PI3K/Akt inhibitor, LY294002, could partially reverse the neuroprotection of ATX in the early period after SAH by downregulating ATX-induced activation of Akt/Bad and upregulating cleaved caspase-3 levels. These results provided the evidence that ATX could attenuate apoptosis in a rat SAH model, potentially, in part, through modulating the Akt/Bad pathway.
Modeling graphic subsystem for M5 simulator

In computer architecture research and design, simulator is a viable alternative for researchers to evaluate the functionality and performance of the future computer systems architecture. The cost and timeline to complete a project tremendously can be reduced with simulators, as it allows a quick quantitative evaluation of the wide range of architectures in computer systems, such as CPU, memory and I/O system. The M5 simulator, is one of the open source computer architecture available. This paper propose a graphic subsystem for the existing M5 simulator to allow research and development activities in the area especially for Graphic Processing Unit (GPU). The GPU model chosen for the M5 simulator is the PCI based Voodoo 3 GPU, manufactured by the 3Dfx Interactive Inc. The functionality of the built GPU model are evaluated by using several software engineering testing methodologies, and the programmability of the model is tested by using the Glide API, the 3D graphics API developed for the Voodoo Graphics 3D accelerator cards.
Key Agreement in Dynamic Peer Groups

As a result of the increased popularity of group-oriented applications and protocols, group communication occurs in many different settings: from network multicasting to application layer tele- and videoconferencing. Regardless of the application environment, security services are necessary to provide communication privacy and integrity. This paper considers the problem of key agreement in dynamic peer groups. (Key agreement, especially in a group setting, is the stepping stone for all other security services.) Dynamic peer groups require not only initial key agreement (IKA) but also auxiliary key agreement (AKA) operations, such as member addition, member deletion, and group fusion. We discuss all group key agreement operations and present a concrete protocol suite, CLIQUES, which offers complete key agreement services. CLIQUES is based on multiparty extensions of the well-known Diffie-Hellman key exchange method. The protocols are efficient and provably secure against passive adversaries.