Miracle-dz/UniFAR-FTUs huggingface dataset:
Assessing baroreflex gain from spontaneous variability in conscious dogs: role of causality and respiration.

A double exogenous autoregressive (XXAR) causal parametric model was used to estimate the baroreflex gain (alpha(XXAR)) from spontaneous R-R interval and systolic arterial pressure (SAP) variabilities in conscious dogs. This model takes into account 1) effects of current and past SAP variations on the R-R interval (i.e., baroreflex-mediated influences), 2) specific perturbations affecting R-R interval independently of baroreflex circuit (e.g., rhythmic neural inputs modulating R-R interval independently of SAP at frequencies slower than respiration), and 3) influences of respiration-related sources acting independently of baroreflex pathway (e.g., rhythmic neural inputs modulating R-R interval independently of SAP at respiratory rate, including the effect of stimulation of low-pressure receptors). Under control conditions, alpha(XXAR) = 14.7 +/- 7.2 ms/mmHg. It decreases after nitroglycerine infusion and coronary artery occlusion, even though the decrease is significant only after nitroglycerine, and it is completely abolished by total arterial baroreceptor denervation. Moreover, alpha(XXAR) is comparable to or significantly smaller than (depending on the experimental condition) the baroreflex gains derived from sequence, power spectrum [at low frequency (LF) and high frequency (HF)], and cross-spectrum (at LF and HF) analyses and from less complex causal parametric models, thus demonstrating that simpler estimates may be biased by the contemporaneous presence of regulatory mechanisms other than baroreflex mechanisms.
FORMATED NAVIGATION OF MOBILE ROBOTS USING DISTRIBUTED LEADER-FOLLOWER CONTROL

Abstract This paper presents a formated navigation based on the leader-follower approach. In this approach, the control law of the follower robot includes the states of the leader robot. This is a drawback for implementing the control laws on real mobile robots. To overcome this drawback, this paper proposes a new follower's control law, called the self-made follower input, in which the state of the leader robot is estimated by the relative equation between the leader and the follower robots in the discrete-time domain. On the other hand, a control law of the leader robot is designed with a chained system to track a given reference path. The effectiveness of the proposed techniques is demonstrated in numerical simulation.
Phase 1 Safety and Immunogenicity Evaluation of ADMVA, a Multigenic, Modified Vaccinia Ankara-HIV-1 B'/C Candidate Vaccine

Background We conducted a Phase I dose-escalation trial of ADMVA, a Clade-B'/C-based HIV-1 candidate vaccine expressing env, gag, pol, nef, and tat in a modified vaccinia Ankara viral vector. Sequences were derived from a prevalent circulating HIV-1 recombinant form in Yunnan, China, an area of high HIV incidence. The objective was to evaluate the safety and immunogenicity of ADMVA in human volunteers. Methodology/Principal Findings ADMVA or placebo was administered intramuscularly at months 0, 1 and 6 to 50 healthy adult volunteers not at high risk for HIV-1. In each dosage group [1×107 (low), 5×107 (mid), or 2.5×108 pfu (high)] volunteers were randomized in a 3∶1 ratio to receive ADMVA or placebo in a double-blinded design. Subjects were followed for local and systemic reactogenicity, adverse events including cardiac adverse events, and clinical laboratory parameters. Study follow up was 18 months. Humoral immunogenicity was evaluated by anti-gp120 binding ELISA, immunoflourescent staining, and HIV-1 neutralization. Cellular immunogenicity was assessed by a validated IFNγ ELISpot assay and intracellular cytokine staining. Anti-vaccinia binding titers were measured by ELISA. ADMVA was generally well-tolerated, with no vaccine-related serious adverse events or cardiac adverse events. Local or systemic reactogenicity events were reported by 77% and 78% of volunteers, respectively. The majority of events were of mild intensity. The IFNγ ELISpot response rate to any HIV antigen was 0/12 (0%) in the placebo group, 3/12 (25%) in the low dosage group, 6/12 (50%) in the mid dosage group, and 8/13 (62%) in the high dosage group. Responses were often multigenic and occasionally persisted up to one year post vaccination. Antibodies to gp120 were detected in 0/12 (0%), 8/13 (62%), 6/12 (50%) and 10/13 (77%) in the placebo, low, mid, and high dosage groups, respectively. Antibodies persisted up to 12 months after vaccination, with a trend toward agreement with the ability to neutralize HIV-1 SF162 in vitro. Two volunteers mounted antibodies that were able to neutralize clade-matched viruses. Conclusions/Significance ADMVA was well-tolerated and elicited durable humoral and cellular immune responses. Trial Registration Clinicaltrials.gov NCT00252148
Intervention Policy and Mean Reversion in Exchange Rate Target Zones: The Swedish Case

The intervention policy of the Swedish central bank is studied using daily intervention data for the late 1980s. In contrast to the first generation of target zone models, the authors find that the interventions occur all over the exchange rate band and almost every day. Based on this evidence, they estimate an exchange rate target zone model with intramarginal interventions. The results go a long way towards explaining the well-established hump-shaped exchange rate distribution and lack of nonlinearities. Copyright 1994 by The editors of the Scandinavian Journal of Economics.
On path cover problems with positive and negative constraints for graph-based multitarget tracking

One way to formulate a graph-based target tracking problem is to have vertices representing measurements and/or tracklets and arcs representing allowable associations. Then a solution as a set of tracks is simply a vertex-disjoint path cover of the graph. Under certain (path independence) conditions, the tracking problem can be transformed into one of finding the maximum-weight vertex-disjoint path cover of a directed acyclic graph, which can be efficiently solved using maximum-weight bipartite matching or minimum cost network flow algorithms. However, attribute information often leads to path dependence; in such a case we are interested in an associated graph theoretic problem: Find the maximum-weight vertex-disjoint path cover under “positive” and/or “negative” constraints, where a positive constraint requires, and a negative constraint prohibits, a given pair of vertices to be on the same path. In our previous paper, the case of a single positive constraint (formerly called “same-track constraint”) was considered, and an efficient algorithm to obtain the optimal solution was presented for the special case of a trellis graph. In this paper, we first present a greedy algorithm for multiple positive constraints for a general graph, based on a known algorithm for finding vertex-disjoint paths. We then consider a single negative constraint, and present a search algorithm for a general graph, and an efficient algorithm for a trellis graph.
Spark-based large-scale matrix inversion for big data processing

Matrix inversion is a fundamental operation to solve linear equations for many computational applications. However, it is a challenging task to invert large-scale matrices of extremely high order (several thousands), which are common in most of web-scale systems like social networks and recommendation systems. In this paper, we present a LU decomposition based block-recursive algorithm for large-scale matrix inversion, and its well-designed implementation with optimized data structure, reduction of space complexity and effective matrix multiplication on the Spark parallel computing platform. The experimental evaluation results show that the proposed algorithm is efficient to invert large-scale matrices on a cluster composed of commodity servers and scalable to invert even larger matrices. The proposed algorithm and implementation will be a solid base to build a high-performance linear algebra library on Spark for big data processing.
The Real Interest Rate Spread as a Monetary Policy Indicator

This paper employs a consumption-based capital asset pricing model to derive the generalised Fisher equation, in order to estimate the natural rate of interest and corresponding real interest rate spread for the US. Analysis reveals not only is the estimated real interest rate spread a useful measure of the degree of looseness/tightness in the Federal Reserve’s monetary policy stance, but also the variable contributes substantially to an understanding of the evolution of US inflation over the period 1960-2005.
CUKNN: A parallel implementation of K-nearest neighbor on CUDA-enabled GPU

Recent development in Graphics Processing Units (GPUs) has enabled inexpensive high performance computing for general-purpose applications. Due to GPU's tremendous computing capability, it has emerged as the co-processor of the CPU to achieve a high overall throughput. CUDA programming model provides the programmers adequate C language like APIs to better exploit the parallel power of the GPU. K-nearest neighbor is a widely used classification technique and has significant applications in various domains. The computational-intensive nature of KNN requires a high performance implementation. In this paper, we present a CUDA-based parallel implementation of KNN, CUKNN, using CUDA multi-thread model. Various CUDA optimization techniques are applied to maximize the utilization of the GPU. CUKNN outperforms significantly and achieve up to 15.2X speedup. It also shows good scalability when varying the dimension of the training dataset and the number of records in training dataset.
EVOLUTION OF MASSIVE PROTOSTARS WITH HIGH ACCRETION RATES

Formation of massive stars by accretion requires a high accretion rate of 10^{-4} M_{\odot }\, {\rm yr^{-1}}$? > to overcome the radiation pressure barrier of the forming stars. Here, we study evolution of protostars accreting at such high rates by solving the structure of the central star and the inner accreting envelope simultaneously. The protostellar evolution is followed starting from small initial cores until their arrival at the stage of the Zero-Age Main-Sequence (ZAMS) stars. An emphasis is put on evolutionary features different from those with a low accretion rate of , which is presumed in the standard scenario for low-mass star formation. With the high accretion rate of , the protostellar radius becomes very large and exceeds 100 R☉. Unlike the cases of low accretion rates, deuterium burning hardly affects the evolution, and the protostar remains radiative even after its ignition. It is not until the stellar mass reaches ≃40 M☉ that hydrogen burning begins and the protostar reaches the ZAMS phase, and this ZAMS arrival mass increases with the accretion rate. These features are similar to those of the first star formation in the universe, where high accretion rates are also expected, rather than to the present-day low-mass star formation. At a very high accretion rate of >3 × 10−3 M☉ yr-1, the total luminosity of the protostar becomes so high that the resultant radiation pressure inhibits the growth of the protostars under steady accretion before reaching the ZAMS stage. Therefore, the evolution under the critical accretion rate 3 × 10−3 M☉ yr-1 gives the upper mass limit of possible pre-main sequence stars at ≃60 M☉. The upper mass limit of MS stars is also set by the radiation pressure onto the dusty envelope under the same accretion rate at ≃250 M☉. We also propose that the central source enshrouded in the Orion KL/BN nebula has effective temperature and luminosity consistent with our model and is a possible candidate for such protostars growing under the high accretion rate.
Semi-Fragile Watermark Based on Adaptive Quantization for Image Content Authentication

A novel semi-fragile watermark scheme for image authentication is proposed in this paper. New scheme extracts the image content features from the low frequency domain to generate watermarks, inserts obtained feature into the image by modulating the wavelet domain, and the watermark generation and embedment are disposed in the image. To enhance the robustness and invisibility, the adaptive quantization is used, and quantization step is calculated according to the local image characteristics. The integrity authentication and tamper detection are implemented by comparing the extracted watermark and the extracted content feature. Experimental result shows that the proposed scheme is robust to common image processing (such as JPEG compression, noise-adding, filtering), but malicious changes of the image will result in alarms of the watermark detection. In addition, proposed scheme can detect the exact locations-the illegal modified blocks.
Reversible Multiparty Sessions with Checkpoints

Reversible interactions model different scenarios, like biochemical systems and human as well as automatic negotiations. We abstract interactions via multiparty sessions enriched with named checkpoints. Computations can either go forward or roll back to some checkpoints, where possibly different choices may be taken. In this way communications can be undone and different conversations may be tried. Interactions are typed with global types, which control also rollbacks. Typeability of session participants in agreement with global types ensures session fidelity and progress of reversible communications.
Anaphora Resolution – What Helps in German

Although anaphora resolution has been a very active research area throughout the last decades, there exist only a few studies that focus on German anaphora. Strube and Hahn (1999) present a system for anaphora resolution for German based on an extension of Centering Theory. Müller et al. (2002) and Kouchnir (2003) use co-training and boosting, respectively. Hinrichs et al. (2005) employ a hybrid approach combining a rule-based morphological pre-filter with a memory-based resolution module. With the exception of Schiehlen (2004), who gives a comprehensive survey of important factors for German anaphora resolution, these approaches assume essentially the same core set of features for German that the linguistic literature has come to agree upon for English.
Provenance-based Reconciliation In Conflicting Data

Data fusion is the process of resolving conflicting data from multiple data sources. As the data sources are inherently heterogenous, there is a need for an expert to resolve the conflicting data. Traditional approach requires the expert to resolve a considerable amount of conflicts in order to acquire a high quality dataset. In this project, we consider how to acquire a high quality dataset while maintaining the expert effort minimal. At first, we achieve this goal by building a model which leverages the provenance of the data in reconciling conflicting data. Secondly, we improve our model by taking the dependency between data sources into account. In the end, we empirically show that our solution can significantly reduce the user effort while it can obtain a high quality dataset in comparison with traditional method.
The histone demethylase PHF8 is a molecular safeguard of the IFNγ response

Abstract A precise immune response is essential for cellular homeostasis and animal survival. The paramount importance of its control is reflected by the fact that its non-specific activation leads to inflammatory events that ultimately contribute to the appearance of many chronic diseases. However, the molecular mechanisms preventing non-specific activation and allowing a quick response upon signal activation are not yet fully understood. In this paper we uncover a new function of PHF8 blocking signal independent activation of immune gene promoters. Affinity purifications coupled with mass spectrometry analysis identified SIN3A and HDAC1 corepressors as new PHF8 interacting partners. Further molecular analysis demonstrated that prior to interferon gamma (IFNγ) stimulation, PHF8 is bound to a subset of IFNγ-responsive promoters. Through the association with HDAC1 and SIN3A, PHF8 keeps the promoters in a silent state, maintaining low levels of H4K20me1. Upon IFNγ treatment, PHF8 is phosphorylated by ERK2 and evicted from the promoters, correlating with an increase in H4K20me1 and transcriptional activation. Our data strongly indicate that in addition to its well-characterized function as a coactivator, PHF8 safeguards transcription to allow an accurate immune response.
A sensor fusion algorithm for an integrated angular position estimation with inertial measurement units

This work presents an orientation tracking system for 6D inertial measurements units. The system was modeled with MathWorks Simulink and experimentally tested with the Cube Demo board by SensorDynamics, used to simulate a 3D gyro and a 3D accelerometer. Quaternions were used to represent the angular position and an Extended Kaiman filter was used for the sensor fusion algorithm. The goal was to obtain an integrated system that could be easily integrated within the logic of the new 6D sensor family produced by SensorDynamics. We propose a Kaiman filter simplification for a fixed point arithmetic implementation to reduce the system complexity with negligible performance degradation.
Planar fully depleted silicon technology to design competitive SOC at 28 nm and beyond

This document considers the challenges to obtain competitive silicon technology for the upcoming generation of SystemOn-Chip ICs. It suggests planar fully depleted technology deserves serious interest. After outlining some implementation choices, a number of circuit-level benchmark results as well as some important design aspects are presented. It is found that this technology combines high performance, power efficiency and cost-effectiveness, which makes it a very attractive candidate to serve the needs of mobile and consumer multimedia SOCs starting at the 28nm node and scalable down to 14nm.
Challenges and Opportunities for Context-Aware Retrieval on Mobile Devices

The development of wireless computer networks and powerful mobile computing devices is creating opportunities to introduce mobile information retrieval applications. Information retrieval has traditionally concentrated on desk-based computing systems. Mobile users are in a different environment which requires careful analysis of their information needs and the HCI issues of mobile computing devices. The availability of user context information in mobile environments can assist the satisfaction of user information needs, but also provides exciting new opportunities for information access applications. Exploiting context information to best advantage requires the analysis of existing information retrieval methods and development of novel techniques. Evaluating standard information retrieval systems has been the focus of much work, extending existing evaluation frameworks to mobile and context-aware retrieval applications will be an important component of establishing the effectiveness of new techniques for general and task specific context-aware applica-
The Signal Peptide of Mouse Mammary Tumor Virus-Env: A Phosphoprotein Tumor Modulator

Mouse mammary tumor virus (MMTV) is associated primarily with mammary carcinomas and lymphomas. The signal peptide of the MMTV envelope precursor is uniquely targeted to nucleoli of cells that harbor the virus, where it can function as a nuclear export factor for intron-containing transcripts. Antibodies to this signal peptide, which we refer to as p14, were previously shown to label nucleoli in a subset of human breast cancers. To look for additional cellular functions of p14, different mutants were ectopically expressed in the MCF-7 human breast cancer cell line. This approach identified motifs responsible for its nucleolar targeting, nucleocytoplasmic shuttling, target protein (B23, nucleophosmin) binding, and phosphorylation at serine 18 and 65 both in situ and in vitro. To test the role of these phosphorylation sites, we carried out in vivo tumorigenesis studies in severe combined immunodeficient mice. The findings show that the p14-Ser65Ala mutation is associated with impaired tumorigenicity, whereas the p14-Ser18Ala mutation is associated with enhanced tumorigenicity. Microarray analysis suggests that phosphorylation at serine 18 or at serine 65 is associated with transcriptional regulation of the L5 nucleolar ribosomal protein (a p14 target) and the Erb-B signal transduction pathway. Taken together, these results show that the phosphorylation status of p14 determines whether it functions as a pro-oncogenic or antioncogenic modulator. Mol Cancer Res; 10(8); 1077–86. ©2012 AACR.
Automatic Detection and Removal of Conformance Faults in Feature Models

Building a feature model for an existing SPL can improve the automatic analysis of the SPL and reduce the effort in maintenance. However, developing a feature model can be error prone, and checking that it correctly identifies each actual product of the SPL may be unfeasible due to the huge number of possible configurations. We apply mutation analysis and propose a method to detect and remove conformance faults by selecting special configurations that distinguish a feature model from its mutants. We propose a technique that, by iterating this process, is able to repair a faulty model. We devise several variations of a simple hill climbing algorithm for automatic fault removal and we compare them by a series of experiments on three different sets of feature models. We find that our technique is able to improve the conformance of around 90% of the models and find the correct model in around 40% of the cases.
A large area force sensor for smart skin applications

This paper presents the construction and theory of operation of a large area, flexible, tactile sensor and its applications. The sensing mechanism is based on the novel contact piezoresistive effect. Furthermore, the sensor's resolution, size and shape can be easily tailored to the applications' requirements. This versatility facilitates the use of the sensor in smart applications where tactile information is used to create system intelligence. Future improvements in the tactile sensing arena are discussed along with the potential benefits of using polymer electronics.
Software defined framework for multi-cell Cognitive Radio Networks

Network virtualization is a promising technology that enables the deployment of multiple virtual networks over a single physical network. These virtual networks are allowed to share the set of available resources in order to provide different services to their intended users. Although many projects are studying different aspects of network virtualization, the field of wireless network virtualization is not well investigated. In this work, we propose a dynamic cognitive radio virtualization framework in which several virtual networks are built over a set of physical nodes managed and controlled by a Base Station (BS). This framework is proposed to virtualize Cognitive Radio Networks (CRNs) in order to reduce the control overhead on the BS side by delegating some of its responsibilities to the node side. The proposed framework is applied to a network with multiple overlapping cells. To cope with the self-coexistence problem, we use a resource allocation algorithm to distribute the available channels over the overlapping cells based on their traffic loads with the goal of avoiding harmful interference, enhancing blocking rates and increasing throughput.