gebhart/patrepeval huggingface dataset:
Finding Structure with Randomness: Probabilistic Algorithms for Constructing Approximate Matrix Decompositions (2011)

Low-rank matrix approximations, such as the truncated singular value decomposition and the rank-revealing QR decomposition, play a central role in data analysis and scientific computing. This work surveys and extends recent research which demonstrates that randomization offers a powerful tool for performing low-rank matrix approximation. These techniques exploit modern computational architectures more fully than classical methods and open the possibility of dealing with truly massive data sets. This paper presents a modular framework for constructing randomized algorithms that compute partial matrix decompositions. These methods use random sampling to identify a subspace that captures most of the action of a matrix. The input matrix is then compressed—either explicitly or\nimplicitly—to this subspace, and the reduced matrix is manipulated deterministically to obtain the desired low-rank factorization. In many cases, this approach beats its classical competitors in terms of accuracy, robustness, and/or speed. These claims are supported by extensive numerical experiments and a detailed error analysis. The specific benefits of randomized techniques depend on the computational environment. Consider the model problem of finding the k dominant components of the singular value decomposition of an m × n matrix. (i) For a dense input matrix, randomized algorithms require O(mn log(k))\nfloating-point operations (flops) in contrast to O(mnk) for classical algorithms. (ii) For a sparse input matrix, the flop count matches classical Krylov subspace methods, but the randomized approach is more robust and can easily be reorganized to exploit multiprocessor architectures. (iii) For a matrix that is too large to fit in fast memory, the randomized techniques require only a constant number of passes over the data, as opposed to O(k) passes for classical algorithms. In fact, it is sometimes possible to perform matrix approximation with a single pass over the data.
MicroGrid Online Management and Balancing Using Multiobjective Optimization (2007)

This paper presents a generalized formulation to determine the optimal operating strategy and cost optimization scheme as well as the reduction of the emissions for a MicroGrid (MG). Multiobjective (MO) optimization is applied to the environmental/economic problem of the MG. The proposed problem is formulated as a nonlinear constrained MO optimization problem. The model takes into consideration the operation and maintenance costs as well as the emissions NOx, SO <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> , and CO <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> reduction. The MG considered in this paper consists of a wind turbine, a micro turbine , a diesel generator , a photovoltaic array , a fuel cell, and a battery storage. The optimization is aimed at minimizing the operating cost of the system while constraining it to meet the costumer demand and safety of the system. We also added a daily income and outgo from sold and purchased power. The results demonstrate the efficiency of the proposed approach to satisfy the load and to reduce the cost and the emissions in one single run.
Mixed Signal Neurocomputing Based on Floating-gate Memories (2017)

Nervous systems inspired neurocomputing has shown its great advantage in object detection, speech recognition and a lot of other machine-learning technology-driven applications from speed and power efficiency. Among handful neurocomputing implementation approaches, analog nanoelectronic circuits are very appealing because they may far overcome digital circuits of the same functionality in circuit density, speed and energy efficiency. Device density is one of the most essential metrics for designing large-scale neural networks, allowing for high connectivity between neurons. Thanks to the high-density nature of traditional memory applications, building artificial neural networks with hybrid complementary metal oxide semiconductor (CMOS)/memory devices would enable the high parallelism as well as achieve the performance advantages.Synapses, the most numerous elements of neural networks, are efficiently implemented by memory devices. This application, however, imposes a number of requirements, such as the continuous change of the memory resistance state, creating the need for novel engineering approaches. Here we report such engineering approaches for advancedcommercial 180-nm ESF1 and 55-nm ESF3 NOR flash memory, facilitating fabrication and successful test of high performance analog vector-by-matrix multiplication which is the key operation performed at signal propagation through any neuromorphic network. Furthermore, we discuss the recent progress toward neuromorphic computing implementations based on nonvolatile floating-gate devices, in particular the experimental results for a prototype 28×28-binary-input, 10-output, 3-layer neuromorphic network based on arrays of highly optimized embedded nonvolatile floating-gate cells. The fabricated neuromorphic network’s active components, including 101,780 floating-gate cells, have a total area below 1 mm2. The network has shown a 94.7% classification fidelity on the common MNIST benchmark, close to the 96.2% obtained in simulation. The classification of one pattern takes sub-1 μs time and sub-20 nJ energy – both numbers much better than for the best reported digital implementations of the same task. Estimates show that a straightforward optimization of the hardware, and its transfer to the already available 55-nm technology may increase this advantage to more than 100X in speed and 10000X in energy efficiency.As pure analog circuits cannot address the noise accumulation problem, a practical solution would also require inclusion of analog-to-digital and digital-to-analog stages for signal restoration. High energy-efficient and compact data converters are therefore expected to play an important role in future computing platforms. We perform an experimental demonstration of 6-bit digital-to-analog (DAC) and 4-bit analog-to-digital conversion (ADC) operations implemented with a hybrid circuit consisting of Pt/TiO2-x /Pt resistive switching devices (also known as ReRAMs or memristors) and a CMOS operational amplifier (opamp). In particular, ADC is implemented with a Hopfield neural network circuit.
Luminescence Excitation Spectra and Their Exciton Structures of ZnS Phosphors. II. Al and Te Doped Phosphors (1980)

UV emission bands designated Al-SAL and Te-BE due to Al and Te, respectively, in hexagonal ZnS have been investigated at 75 K or with varying temperature with the major focus on exciton structures in the excitation spectra. The concentration and temperature variations of the exciton structures show that the Al-SAL and Te-BE bands are composed of two bands; one is due to bound exciton recombination, and the other results from electron-hole recombination at pairs of shallow donors and isoelectronic centers. In the Te-doped samples, the isoelectronic center responsible is tellurium substituting for sulfur, but that due to Al doping has not been identified yet. Two kinds of edge omission are also observed; one is due to donor-acceptor pairs and is accompanied by a series of peaks with equidistant intervals of 335 cm-1, and the other involves isoelectronic centers.
cDNA microarray analysis of non-selected cases of acute myeloid leukemia demonstrates distinct clustering independent of cytogenetic aberrations and consistent with morphological signs of differentiation (2006)

Acute myeloid leukemia (AML) is a heterogeneous disease with respect to biology and clinical course. Until now the basis for prognostic evaluation and therapeutic decision has been the karyotype, genetic FLT3 abnormalities and the initial chemotherapy response. A question that has emerged is if extensive gene expression analysis may supplement or partly replace current diagnostics. In an attempt to address this question, we performed cDNA microarray analysis on peripheral blood samples of 25 patients with newly diagnosed AML with high blast counts. The patients were randomly selected from a large group of consecutive patients. Leave-one-out crossvalidation (LOOCV) showed with high accuracy that gene expression classifiers could predict if leukaemia samples belonged to the FAB AML-M1 or to the FAB AML-M2 groups. An unsupervised two-dimensional hierarchical cluster analysis generated 3 patient subgroups. Except for an accumulation of samples classified as FAB M1 and M2 in cluster 3, there was no evident relationship between the clusters and the FAB classification. Each subgroup displayed clearly distinguished gene expression patterns validated using real-time quantitative PCR analysis. The identification of specific gene expressions that together constitute regulatory modules must complement cluster analyses in order to achieve an accurate basis for prognosis and prediction.
Fusing optical flow and stereo in a spherical depth panorama using a single-camera folded catadioptric rig (2011)

We present a novel catadioptric-stereo rig consisting of a coaxially-aligned perspective camera and two spherical mirrors with distinct radii in a “folded” configuration. We recover a nearly-spherical dense depth panorama (360°×153°) by fusing depth from optical flow and stereo. We observe that for motion in a horizontal plane, optical flow and stereo generate nearly complementary distributions of depth resolution. While optical flow provides strong depth cues in the periphery and near the poles of the view-sphere, stereo generates reliable depth in a narrow band about the equator. We exploit this principle by modeling the depth resolution of optical flow and stereo in order to fuse them probabilistically in a spherical panorama. To aid the designer in achieving a desired field-of-view and resolution, we derive a linearized model of the rig in terms of three parameters (radii of the two mirrors plus axial separation from their centers). We analyze the error due to the violation of the Single Viewpoint (SVP) constraint and formulate additional constraints on the design to minimize the error. Performance is evaluated through simulation and with a real prototype by computing dense spherical panoramas in cluttered indoor settings.
Ovarian Function in the Cycling Cow: Relationship between Gonadotropin Binding to Theca and Granulosa and Steroidogenesis in Individual Follicles2 (1981)

Thirty-six Angus and Angus crossbred cows were used in a 3 x 2 x 2 factorial experiment designed to determine the effects of stage of the estrous cycle (day 6, 12 or 18), a long term with a single ovary (2 years) and side of previous ovulation or remaining ovary on the development of large ovarian follicles (LF; diameter greater than or equal to 8 mm). Follicular fluid estradiol-17 beta (FFE) concentration, localization of gonadotropin binding sites and granulosa cell condition were determined for each LF by radioimmunoassay, autoradiography and histological examination, respectively. No side differences were noted. However, the sample was biased by the use of equal numbers of left and right side ovulators. Compared to intact controls, one-ovary cows showed 100% compensation of LF development. Eighty-five percent of the LF studied bound follicle stimulating hormone (FSH) in the granulosa and human chorionic gonadotropin (hCG) in the theca. Thirty-eight percent also bound hCG in the granulosa. Both binding patterns were found on all days studied. Atretic follicles had lower (P less than .05) FFE concentrations than healthy follicles (r = -.59). The number of LF per cow increased (P less than .05) from day 6 (1.3) to days 12 (1.8) and 18 (2.1). Conversely, their FFE content per cow decreased (P less than .05) from 109 ng/cow on day 6 to 20 ng on; day 12 and 34 ng on day 18. The data suggested the emergency of two LF classes on day 18, one preovulatory, with exceptionally high FFE levels, the other atretic or becoming atretic, with low FFE levels.
The Internet of Things (2016)

Nowadays, data is created by humans as well as automatically collected by physical things, which embed electronics, software, sensors and network connectivity. Together, these entities constitute the Internet of Things (IoT). The automated analysis of its data can provide insights into previously unknown relationships between things, their environment and their users, facilitating an optimization of their behavior. Especially the real-time analysis of data, embedded into physical systems, can enable new forms of autonomous control. These in turn may lead to more sustainable applications, reducing waste and saving resources IoT's distributed and dynamic nature, resource constraints of sensors and embedded devices as well as the amounts of generated data are challenging even the most advanced automated data analysis methods known today. In particular, the IoT requires a new generation of distributed analysis methods. Many existing surveys have strongly focused on the centralization of data in the cloud and big data analysis, which follows the paradigm of parallel high-performance computing. However, bandwidth and energy can be too limited for the transmission of raw data, or it is prohibited due to privacy constraints. Such communication-constrained scenarios require decentralized analysis algorithms which at least partly work directly on the generating devices. After listing data-driven IoT applications, in contrast to existing surveys, we highlight the differences between cloudbased and decentralized analysis from an algorithmic perspective. We present the opportunities and challenges of research on communication-efficient decentralized analysis algorithms. Here, the focus is on the difficult scenario of vertically partitioned data, which covers common IoT use cases. The comprehensive bibliography aims at providing readers with a good starting point for their own work
A new configuration of single-phase symmetrical PWM AC chopper voltage controller (1999)

With the increased availability of power MOSFETs and insulated gate bipolar transistors, a new generation of simple choppers for AC inductive loads is foreseen. These new power semiconductors ease the use of forced commutations of thyristor switches to improve the supply power factor, even with highly inductive loads. The AC controllers with thyristor technology can be replaced by pulsewidth modulation (PWM) AC chopper controllers which have important advantages. In this paper, a symmetrical PWM AC chopper designed to operate with single-phase inductive loads with a reduced number of controlled switches is described. The operation as a variable voltage source of this converter is evaluated. This includes the conversion characteristics, harmonic generation, harmonic distortion factor, and input power factor. By digital simulation, these characteristics are investigated theoretically, and to correlate the measurements with theory, an experimental setup is presented to confirm the analytical analysis.
Structural effect of avocado/soybean unsaponifiables on joint space loss in osteoarthritis of the hip (2002)

This pilot randomized, double-blind, placebo-controlled trial failed to demonstrate a structural effect of ASU in hip OA. However, in a post-hoc analysis, ASU significantly reduced the progression of joint space loss as compared with placebo in the subgroup of patients with advanced joint space narrowing. These results suggest that ASU could have a structural effect but require confirmation in a larger placebo-controlled study in hip OA.
Petroleum Resins: An Overview (2000)

Tack, as a stickiness property that is measured simply by application of finger pressure, is of significant importance in many conventional and special uses, as well as in industrial products manuf...
Theory for momentum transfer to a surface with a high-power laser (1973)

A model is developed for the momentum transferred to a solid from a laser-supported gaseous detonation wave initiated in air above the surface. One-dimensional gasdynamic analysis is used for the detonation wave moving away from the surface and cylindrical blast-wave theory is employed to partially account for two dimensional effects. Momentum transfer coupling coefficients (impulse/laser energy) are calculated which are functions of the laser energy flux, pulse duration, and the beam and target surface areas. Results are compared with recent experimental data obtained using a high-power CO2 laser.
Introduction: Human Metabolites in Safety Testing (MIST) Issue (2009)

ADVERTISEMENT RETURN TO ISSUEEditorialNEXTIntroduction: Human Metabolites in Safety Testing (MIST) IssueF. Peter GuengerichCite this: Chem. Res. Toxicol. 2009, 22, 2, 237–238Publication Date (Web):February 16, 2009Publication History Received2 January 2009Published online16 February 2009Published inissue 16 February 2009https://pubs.acs.org/doi/10.1021/tx900003khttps://doi.org/10.1021/tx900003keditorialACS PublicationsCopyright © 2009 American Chemical Society. This publication is available under these Terms of Use. Request reuse permissions This publication is free to access through this site. Learn MoreArticle Views4785Altmetric-Citations39LEARN ABOUT THESE METRICSArticle Views are the COUNTER-compliant sum of full text article downloads since November 2008 (both PDF and HTML) across all institutions and individuals. These metrics are regularly updated to reflect usage leading up to the last few days.Citations are the number of other articles citing this article, calculated by Crossref and updated daily. Find more information about Crossref citation counts.The Altmetric Attention Score is a quantitative measure of the attention that a research article has received online. Clicking on the donut icon will load a page at altmetric.com with additional details about the score and the social media presence for the given article. Find more information on the Altmetric Attention Score and how the score is calculated. Share Add toView InAdd Full Text with ReferenceAdd Description ExportRISCitationCitation and abstractCitation and referencesMore Options Share onFacebookTwitterWechatLinked InRedditEmail PDF (48 KB) Get e-AlertscloseSUBJECTS:Metabolism,Pharmaceuticals,Pharmacokinetics,Safety,Testing and assessment Get e-Alerts
Interleukin-11: stimulation in vivo and in vitro by respiratory viruses and induction of airways hyperresponsiveness. (1996)

To address the role of IL-11 in viral airways dysfunction, we determined whether infectious agents that exacerbate asthma stimulate stromal cell IL-11 production, determined whether IL-11 could be detected at sites of viral infection and evaluated the effects of IL-11 on airway physiology. Respiratory syncytial virus (RSV), parainfluenza virus type 3 (PIV3), and rhinovirus (RV) 14 were potent stimulators while cytomegalovirus and adenovirus only weakly stimulated and herpes simplex virus type 2 and bacteria did not stimulate IL-11 elaboration. IL-11 was not detected or barely detected in nasal aspirates from children without, but was detected in aspirates from children with viral upper respiratory tract infections. The levels of IL-11 were highest in patients with clinically detectable wheezing. IL-11 also caused nonspecific airways hyperresponsiveness in BALB/c mice. These studies demonstrate that three major causes of viral-induced asthma, RSV, RV, and PIV, in contrast to other viruses and bacteria, share the ability to induce stromal cell IL-11 production. They also demonstrate that IL-11 can be detected in vivo during viral respiratory infections, that the presence of IL-11 correlates with clinical bronchospasm and that IL-11 is a potent inducer of airways hyperresponsiveness. IL-11 may be an important mediator in viral airways disorders.
Simple, Effective Molecular Strategy for the Design of Fuel Cell Membranes: Combination of Perfluoroalkyl and Sulfonated Phenylene Groups (2016)

Proton-conducting membranes are key materials in polymer electrolyte fuel cells. In addition to high proton conductivity and durability, a membrane must also support good electrocatalytic performance of the catalyst layer at the membrane–electrode interface. We herein propose an effective molecular approach to the design of high-performance proton-conducting membranes designed for fuel cell applications. Our new copolymer (SPAF) is a simple combination of perfluoroalkylene and sulfonated phenylene groups. Because this ionomer membrane exhibits a well-controlled finely phase-separated morphology, based on the distinct hydrophilic–hydrophobic differences along with the polymer chain, it functions well in an operating fuel cell with good durability under practical conditions. The advantages of this ionomer, unlike typical perfluorosulfonic acid ionomers (e.g., Nafion), include easy synthesis and versatility in molecular structure, enabling the fine-tuning of membrane properties.
Neuro-imagerie et état de stress post-traumatique (2003)

Au cours de ces dix dernieres annees, nombreuses sont les publications investiguant la neuro-imagerie dans l'etat de stress post-traumatique (ESPT) tant au niveau de la structure cerebrale qu'au niveau fonctionnel. Si la diminution du volume hippocampal semble etre une constante, son interpretation reste sujette a caution. Par ailleurs, au niveau fonctionnel, l'hyperactivation amygdalienne et la desactivation de certaines structures cognitives superieures comme l'aire de Broca semblent etre specifiques de la cohorte de patients avec ESPT et liees a la condition traumatique. De futures etudes dans le domaine devraient determiner s'il s'agit d'un facteur de risque a developper l'ESPT ou plutot d'une consequence a long terme de l'affection.
Overflow Microfluidic Networks for Open and Closed Cell Cultures on Chip (2010)

Microfluidics have a huge potential in biomedical research, in particular for studying interactions among cell populations that are involved in complex diseases. Here, we present "overflow" microfluidic networks (oMFNs) for depositing, culturing, and studying cell populations, which are plated in a few microliters of cell suspensions in one or several open cell chambers inside the chip and subsequently cultured for several days in vitro (DIV). After the cells have developed their phenotype, the oMFN is closed with a lid bearing microfluidic connections. The salient features of the chips are (1) overflow zones around the cell chambers for drawing excess liquid by capillarity from the chamber during sealing the oMFN with the lid, (2) flow paths from peripheral pumps to cell chambers and between cell chambers for interactive flow control, (3) transparent cell chambers coated with cell adhesion molecules, and (4) the possibility to remove the lid for staining and visualizing the cells after, for example, fixation. Here, we use a two-chamber oMFN to show the activation of purinergic receptors in microglia grown in one chamber, upon release of adenosine triphosphate (ATP) from astrocytes that are grown in another chamber and challenged with glutamate. These data validate oMFNs as being particularly relevant for studying primary cells and dissecting the specific intercellular pathways involved in neurodegenerative and neuroinflammatory brain diseases.