gebhart/patrepeval huggingface dataset:
Protease-Activated Receptor 1 Contributes to Angiotensin II-Induced Cardiovascular Remodeling and Inflammation (2020)

Angiotensin II (Ang II) plays an important role in cardiovascular disease. It also leads to the activation of coagulation. The coagulation protease thrombin induces cellular responses by activating protease activated receptor 1 (PAR-1). We investigated if PAR-1 contributes to Ang II-induced cardiovascular remodeling and inflammation.
Compensation for core loss of adaptive flux observer-based field-oriented induction motor drives (2003)

The authors present a method of improving the characteristics of flux-observer-based field-oriented induction motor drives by considering core losses. Two kinds of adaptive flux observers of induction motors have been proposed. One adaptive scheme identifies stator and rotor resistances which vary with the motor temperature. The other one identifies the motor speed for eliminating rotational transducers. These adaptive flux observers were derived from an induction motor model which neglects core losses. In the present work, the influence of the core losses on the adaptive flux observers and field-oriented induction motor drives is investigated, and a compensation method is proposed. In order to compensate for this influence, a novel flux observer taking the core loss into account approximately is proposed. The validity of the proposed method has been verified by simulation.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>
Coherence-Factor-Based Rough Surface Clutter Suppression for Forward-Looking GPR Imaging (2020)

We present an enhanced imaging procedure for suppression of the rough surface clutter arising in forward-looking ground-penetrating radar (FL-GPR) applications. The procedure is based on a matched filtering formulation of microwave tomographic imaging, and employs coherence factor (CF) for clutter suppression. After tomographic reconstruction, the CF is first applied to generate a “coherence map” of the region in front of the FL-GPR system illuminated by the transmitting antennas. A pixel-by-pixel multiplication of the tomographic image with the coherence map is then performed to generate the clutter-suppressed image. The effectiveness of the CF approach is demonstrated both qualitatively and quantitatively using electromagnetic modeled data of metallic and plastic shallow-buried targets.
Outcome of acute hypoxaemic respiratory failure: insights from the LUNG SAFE Study (2020)

More than one-third of patients receiving mechanical ventilation have hypoxaemia and new infiltrates with a hospital mortality of 38.6%. Survival is dependent on the degree of pulmonary involvement whether or not ARDS criteria are reached.
Electron Transfer Chains and Oxidative Phosphorylation (1976)

Book Review| December 01 1976 Electron Transfer Chains and Oxidative Phosphorylation Electron Transfer Chains and Oxidative Phosphorylation. E. QUAGLIARIELLO, S. PAPA, E. PALMIERI, E. C. SLATER, N. SILIPRANDI. North-HollandAmsterdam and Oxford, and American Elsevier, New York 1975 pp. 452, $35.95 P. E. LINNETT P. E. LINNETT Search for other works by this author on: This Site PubMed Google Scholar Biochem Soc Trans (1976) 4 (6): 1181. https://doi.org/10.1042/bst0041181 Views Icon Views Article contents Figures & tables Video Audio Supplementary Data Peer Review Share Icon Share Facebook Twitter LinkedIn MailTo Cite Icon Cite Get Permissions Citation P. E. LINNETT; Electron Transfer Chains and Oxidative Phosphorylation. Biochem Soc Trans 1 December 1976; 4 (6): 1181. doi: https://doi.org/10.1042/bst0041181 Download citation file: Ris (Zotero) Reference Manager EasyBib Bookends Mendeley Papers EndNote RefWorks BibTex toolbar search Search Dropdown Menu toolbar search search input Search input auto suggest filter your search All ContentAll JournalsBiochemical Society Transactions Search Advanced Search This content is only available as a PDF. © 1976 Biochemical Society1976 Article PDF first page preview Close Modal You do not currently have access to this content.
Supplementary Figure 6 from Mitochondrially Targeted p53 Has Tumor Suppressor Activities <i>In vivo</i> (2023)

Supplementary Figure 6 from Mitochondrially Targeted p53 Has Tumor Suppressor Activities &lt;i&gt;In vivo&lt;/i&gt;
Attenuating the Impact of Integrity Attacks on Real-Time Pricing in Smart Grids (2014)

The vulnerability of false data injection attacks on real-time electricity pricing for the power grid market has been recently explored. Previous work has focused on the impact caused by attackers that compromise pricing signals and send false prices to a subset of consumers. In this paper we extend previous work by considering a more powerful and general adversary model, a new analysis method based on sensitivity functions, and by proposing several countermeasures that can mitigate the negative impact of these attacks. Countermeasures include adding a low-pass filter to the pricing signals, selecting the time interval between price updates, selecting parameters of the controller, designing robust control algorithms, and by detecting anomalies in the behavior of the system.
Estimation of Piezoresistive Errors for High-G Measurement by Thermal Accelerometer (2018)

The piezoresistive response of thermal is presented in this paper. One of the prime application is the measurement of acceleration for magnitude of a couple of thousand G. The thermal accelerometer is composed of one heater resistor and two detectors. By thermoresistive effect the detectors measure a difference of temperature proportional to the acceleration. Nevertheless, for these values of acceleration, simulations show a large displacement of these resistors. The consequences of this deformation is variation of resistance by piezoresistive effect. These variations create errors of measurements. Nanoindentation experiments allow to estimate the average gauge factor, k=2,65, for our samples. Finite element analysis has been performed, in order to estimate the deflection in function of the acceleration for different values of shock amplitude. Finally, the piezoresistive contribution is three orders less of magnitude than the difference of temperature between the two detectors.
Diversity-multiplexing-delay tradeoffs in MIMO multihop networks with ARQ (2010)

The tradeoff between diversity, multiplexing, and delay in multihop MIMO relay networks with ARQ is studied, where the random delay is caused by queueing and ARQ retransmission. This leads to an optimal ARQ allocation problem with a per-hop delay or end-to-end delay constraint. The optimal ARQ allocation has to trade off between the ARQ error that the receiver fails to decode in the allocated maximum ARQ rounds and the packet loss due to queueing delay. These two probability of errors are characterized using the diversity-multiplexing-delay tradeoff (DMDT) (without queueing) and the tail probability of random delay derived using large deviation techniques, respectively. Then the optimal ARQ allocation problem can be formulated as a convex optimization problem. We show that the optimal ARQ allocation should balance each link performance as well as avoid significant queue delay, which is also demonstrated by numerical examples.
Synthesis and Oxygen Reduction Reaction Activity of Atomic and Nanoparticle Gold on Thiol-Functionalized Multiwall Carbon Nanotubes (2011)

We demonstrated the self-assembly of atomic Au on thiol-functionalized multiwall carbon nanotubes through covalent bonding and the formation of Au nanoparticles (NPs) upon a subsequent thermal treatment. Au NPs of 3.4 nm were found to exhibit higher ORR activity than that of 1.9 nm, which can be attributed to removal of thiols from Au NP surfaces. This hypothesis is supported by decreasing intrinsic ORR activity with increasing alkanethiol-coverage on polycrystalline-Au. The understanding on top of the novel synthetic route has led to the development of Au NPs less than 5 nm with the highest ORR activity reported to date.
A taxonomy on intrusion alert aggregation techniques (2014)

As security threats advance in a drastic way, most of the organizations apply various intrusion detection systems (IDSs) to optimize detection and to provide comprehensive view of intrusion activities. But IDS produces huge number of duplicated alerts information that overwhelm security operator. Alert aggregation addresses this issue by reducing, fusing and clustering the alerts. Techniques from a different scope of disciplines have been proposed by researchers for different aspects of aggregation. In this paper we present a comprehensive review on proposed alert aggregation techniques. Our main contribution is to classify the literature based on the techniques applied to aggregate the alerts.
Reproducible and Accurate Algorithms for Numerical Linear Algebra (2016)

International audience
Synthesis, stereochemistry and reactions of selenoxanthen-10-io(alkoxalyl alkoxycarbonyl)methanides and related compounds. (1984)

Selenoxanthene 10-oxides (5a-d) reacted with methyl propiolate, dimethyl and diethyl acetylenedicarboxylates to afford selenoxanthen-10-io [formyl (or alkoxalyl) alkoxycarbonyl]-methanides (6a-i). The 9-isopropyl derivative gave only trans-ylides and the 9-phenyl congener formed cis-and trans-ylides. The stereochemistry is discussed on the basis of the nuclear magnetic resonance spectral data. Reduction of the selenoxanthenium ylides with sodium borohydride afforded the ylide lactones (16a-c) and the ylide alcohols (17a-f). The product ratio depended on the solvent used.
Unbiased Teacher for Semi-Supervised Object Detection (2021)

Semi-supervised learning, i.e., training networks with both labeled and unlabeled data, has made significant progress recently. However, existing works have primarily focused on image classification tasks and neglected object detection which requires more annotation effort. In this work, we revisit the Semi-Supervised Object Detection (SS-OD) and identify the pseudo-labeling bias issue in SS-OD. To address this, we introduce Unbiased Teacher, a simple yet effective approach that jointly trains a student and a gradually progressing teacher in a mutually-beneficial manner. Together with a class-balance loss to downweight overly confident pseudo-labels, Unbiased Teacher consistently improved state-of-the-art methods by significant margins on COCO-standard, COCO-additional, and VOC datasets. Specifically, Unbiased Teacher achieves 6.8 absolute mAP improvements against state-of-the-art method when using 1% of labeled data on MS-COCO, achieves around 10 mAP improvements against the supervised baseline when using only 0.5, 1, 2% of labeled data on MS-COCO.
The Oxford Companion to Beer (2011)

Over 1,100 entries1st Place Winner of the 2012 Gourmand Award for Best in the World in the Beer category.The first major reference work to investigate the history and vast scope of beer, The Oxford Companion to Beer features more than 1,100 A-Z entries written by 166 of the world's most prominent beer experts. Attractively illustrated with over 140 images, the work covers everything from the agricultural makeup of various beers to the technical elements of the brewing process, local effects of brewing on regions around the world, and the social and political implications of sharing a beer. Entries not only define terms such as
Exceeding the Nonlinear Shannon-Limit in Coherent Optical Communications\n by MIMO Machine Learning (2018)

The nonlinear Shannon capacity limit has been identified as the fundamental barrier to the maximum rate of transmitted information in optical communications. In long-haul high-bandwidth optical networks, this limit is mainly attributed to deterministic Kerr-induced fiber nonlinearities and from the interaction of amplified spontaneous emission noise from cascaded optical amplifiers with fiber nonlinearity: the stochastic parametric noise amplification. Unlike earlier impractical approaches that compensate solely deterministic nonlinearities, here we demonstrate a novel electronic-based deep neural network with multiple-inputs and outputs (MIMO) that tackles the interplay of deterministic and stochastic nonlinearity manifestation in coherent optical signals. Our demonstration shows that MIMO deep learning can compensate nonlinear inter-carrier crosstalk effects even in the presence of frequency stochastic variations, which has hitherto been considered impossible. Our solution significantly outperforms conventional machine learning and gold-standard nonlinear equalizers without sacrificing computational complexity, leading to record-breaking transmission performance for up to 40 Gbit/sec high-spectral-efficient optical signals.
Interprotein interactions are responsible for the confined diffusion of a G-protein-coupled receptor at the cell surface (2003)

The monitoring of the movements of membrane proteins (or lipids) by single-particle tracking enables one to obtain reliable insights into the complex dynamic organization of the plasma membrane constituents. Using this technique, we investigated the diffusional behaviour of a G-protein-coupled receptor. The trajectories of the receptors revealed a diffusion mode combining a short-term rapid confined diffusion with a long-term slow diffusion. A detailed statistical analysis shows that the receptors have a diffusion confined to a domain which itself diffuses, the confinement being due to long-range attractive inter-protein interactions. The existing models of the dynamic organization of the cell membrane cannot explain our results. We propose a theoretical Brownian model of interacting proteins that is consistent with the experimental observations and accounts for the variations found as a function of the domain size of the short-term and long-term diffusion coefficients.
Optimizing the MapReduce framework on Intel Xeon Phi coprocessor (2013)

MapReduce has become one of the most popular framework for building big-data applications. It was originally designed for distributed-computing, and has been extended to various hardware architectures, e.g., multi-core CPUs, GPUs and FPGAs. In this work, we develop the first MapReduce framework on the recently released Intel Xeon Phi coprocessor. We utilize advanced features of the Xeon Phi to achieve high performance. In order to take advantage of the SIMD vector processing units, we propose a vectorization friendly technique to assist the auto-vectorization as well as develop SIMD hash computation algorithms. Furthermore, we utilize MIMD hyper-threading to pipeline the map and reduce phases to improve the resource utilization. We also eliminate multiple local arrays but use low cost atomic operations on the global array for some applications, which can improve the thread scalability and data locality. We conduct comprehensive experiments to compare our optimized MapReduce framework with a state-of-the-art multi-core based MapReduce framework (Phoenix++). By evaluating six real-world applications, the experimental results show that our optimized framework is 1.2X to 38X faster than Phoenix++ for various applications on the Xeon Phi.
Dual radiofrequency drive quantum voltage standard with nanovolt resolution based on a closed-loop refrigeration cycle (2012)

We have developed a programmable Josephson voltage standard that can produce voltages up to 20 V with a resolution of better than 0.1 µV over the whole voltage range and better than 1 nV for voltages up to 10 mV. The standard has two superconductor–normal metal–superconductor junction arrays connected in series and driven by two radiofrequency oscillators. The cryogenic part of the standard is based on a cryocooler. The new standard agrees with the primary quantum voltage standard maintained at the National Measurement Institute, Australia, within 10 nV and forms the basis of an automated calibration system for digital multimeters and voltage references.
Mice with altered serotonin 2C receptor RNA editing display characteristics of Prader–Willi syndrome (2020)

RNA transcripts encoding the 2C-subtype of serotonin (5HT2C) receptor undergo up to five adenosine-to-inosine editing events to encode twenty-four protein isoforms. To examine the effects of altered 5HT2C editing in vivo, we generated mutant mice solely expressing the fully-edited (VGV) isoform of the receptor. Mutant animals present phenotypic characteristics of Prader-Willi Syndrome (PWS) including a failure to thrive, decreased somatic growth, neonatal muscular hypotonia, and reduced food consumption followed by post-weaning hyperphagia. Though previous studies have identified alterations in both 5HT2C receptor expression and 5HT2C-mediated behaviors in both PWS patients and mouse models of this disorder, to our knowledge the 5HT2C gene is the first locus outside the PWS imprinted region in which mutations can phenocopy numerous aspects of this syndrome. These results not only strengthen the link between the molecular etiology of PWS and altered 5HT2C expression, but also demonstrate the importance of normal patterns of 5HT2C RNA editing in vivo.
Stochastic Gradient Based Extreme Learning Machines For Online Learning\n of Advanced Combustion Engines (2015)

In this article, a stochastic gradient based online learning algorithm for\nExtreme Learning Machines (ELM) is developed (SG-ELM). A stability criterion\nbased on Lyapunov approach is used to prove both asymptotic stability of\nestimation error and stability in the estimated parameters suitable for\nidentification of nonlinear dynamic systems. The developed algorithm not only\nguarantees stability, but also reduces the computational demand compared to the\nOS-ELM approach based on recursive least squares. In order to demonstrate the\neffectiveness of the algorithm on a real-world scenario, an advanced combustion\nengine identification problem is considered. The algorithm is applied to two\ncase studies: An online regression learning for system identification of a\nHomogeneous Charge Compression Ignition (HCCI) Engine and an online\nclassification learning (with class imbalance) for identifying the dynamic\noperating envelope of the HCCI Engine. The results indicate that the accuracy\nof the proposed SG-ELM is comparable to that of the state-of-the-art but adds\nstability and a reduction in computational effort.\n
Relationship between locomotive syndrome and frailty in rheumatoid arthritis patients by locomotive syndrome stage (2021)

As LS worsens in RA patients, the likelihood of developing physical frailty increases. RA patients with a low LS stage can still develop frailty, and suppressing disease activity may not be sufficient to prevent frailty. These findings highlight the need to screen for frailty in RA patients and consider appropriate interventions based on each patient's condition, focusing on nonphysical factors.
Adaptive estimation of state of charge for lithium-ion batteries (2013)

State of charge (SoC) estimation is a fundamental challenge in designing battery management systems. An adaptive SoC estimator, named as the AdaptSoC, is developed in this paper. It is able to estimate the SoC when the model parameters are unknown, through joint SoC and parameter estimation. Design of the AdaptSoC builds up on (1) a reduced complexity battery model that is developed from the well-known single particle model (SPM) and, (2) joint local observability/identifiability analysis of the SoC and the unknown model parameters. Shown to be strongly observable, the SoC is estimated jointly with the parameters by the AdaptSoC using the iterated extended Kalman filter (IEKF). Simulation and experimental results exhibit the effectiveness of the AdaptSoC.
Crystal structure of 9,9-diethyl-9H-fluorene-2,4,7-tricarbaldehyde (2021)

The title compound, C<sub>20</sub>H<sub>18</sub>O<sub>3</sub>, crystallizes in the space group <i>P</i>2<sub>1</sub>/<i>c</i> with one mol-ecule in the asymmetric unit of the cell. The fluorene skeleton is nearly planar and the crystal structure is composed of mol-ecular layers extending parallel to the (302) plane. Within a layer, one formyl oxygen atom participates in the formation of a C<sub>arene</sub>-H⋯O bond, which is responsible for the formation of an inversion symmetric supra-molecular motif of graph set <i>R</i> <sub>2</sub> <sup>2</sup>(10). A second oxygen atom is involved in an intra-molecular C<sub>arene</sub>-H⋯O hydrogen bond and is further connected with a formyl hydrogen atom of an adjacent mol-ecule. A Hirshfeld surface analysis indicated that the most important contributions to the overall surface are from H⋯H (46.9%), O⋯H (27.9%) and C⋯H (17.8%) inter-actions.
SUN-LB74 Radiofrequency Echographic Multi-Spectrometry (REMS) for the Assessment of Bone Strength and Fracture Risk Prediction (2020)

Abstract Introduction Fragility bone fractures impact patient’s quality of life and worldwide healthcare systems: accurate technologies and device are required in order to early diagnose and monitor the effect of osteoporosis on a mass-population basis. Several studied have analysed the pros and cons of the numerous technologies available nowadays for the diagnosis and monitoring of bone health, highlighting the need of further tools able to better define and estimate bone strength and to predict the risk of fracture [1]. Objectives The aim is to assess the state of the art about Radiofrequency Echographic Multi-Spectrometry (REMS). Methods A review of the available literature was performed, considering full papers, reviews and abstracts on REMS published before January 31th 2020. Results REMS has been recently presented by an ESCEO consensus paper as a valuable technology for osteoporosis diagnosis and fracture risk estimation [1]. It is based on the automatic processing of the raw unfiltered signals obtained with an ultrasound scan, thus overcoming the main drawback of dual-energy X-ray absorptiometry (DXA) and computed tomography (CT)-based technologies [2]. Moreover, REMS scans are performed at axial skeleton reference sites, i.e. lumbar spine [3] and femoral neck [4], differently from quantitative ultrasound (QUS) technology, which is usually applied to peripheral sites [3]. Clinical performance has been confirmed by a multicentre clinical trial enrolling over 1900 Caucasian women, demonstrating a high correlation between bone mineral density (BMD) estimated by REMS and DXA. In addition, high performance in terms of precision and intra- and inter-operator repeatability of REMS have been assessed [6]. Prospective studies have demonstrated the predictive ability of incident fragility fractures [7] and the high concordance with DXA in terms of measured BMD in patients with rheumatoid arthritis and pre/post-menopause [8, 9]. Conclusions REMS is an innovative approach for the early diagnosis, short-term monitoring of osteoporosis and risk fracture prediction. The available data envisaged for further applications in paediatric patients, pregnant women and patients at risk of secondary osteoporosis (e.g., diabetic, nephropathic, oncological patients). The EchoS system, a device implementing the REMS technology, has recently received the approval from the U.S. Food and Drug Administration (FDA). References 1. Diez-Perez et al. Aging Clin Exp Res 2019;31(10):1375–89 2. Iwaszkiewicz &amp; Leszczyński. Forum Reumatol 2019;5(2):81–8 3. Hans &amp; Baim. J Clin Densitom 2017;20(3):322-3 4. Conversano et al. Ultrasound Med Biol 2015;41:281–300 5. Casciaro et al. Ultrasound Med Biol 2016;42:1337–56 6. Di Paola et al. Osteoporos Int 2018;30:391–402 7. Adami et al. Ann Rheum Dis, vol.78, supp.2, 2019, p.A928 8. Bojincă et al. Exp Ther Med 2019;18(3):1661-68 9. Kirilova et al. Clin Cases Miner Bone Metab 2019; 16(1):14-17
Stabilization of biped dynamic walking using gyroscopic couple (2002)

This paper presents a new strategy for dynamic walking machine where a gyroscope mounted on top of the biped is processed to achieve balancing both in the coronal and sagittal planes. A gait is devised and simulation results are provided to show the feasibility of proposed balancing method.