gebhart/patrepeval huggingface dataset:
Stimulated Raman Scattering in Yttrium, Gadolinium, and Calcium Orthovanadate Crystals with Single and Combined Frequency Shifts under Synchronous Picosecond Pumping for Sub-Picosecond or Multi-Wavelength Generation around 1.2 µm (2020)

Comparative investigation of stimulated Raman scattering (SRS) characteristics in the YVO4, GdVO4, and Ca3(VO4)2 orthovanadate crystals at both low and high frequency anionic group vibrations is presented. It was found that GdVO4 is the most perspective for SRS generation on both the ν1 stretching and ν2 bending modes of internal anionic group vibrations with the strongest SRS pulse shortening under synchronous picosecond pumping. It is as a result of GdVO4‘s widest linewidth (17cm−1) of the homogeneously broadened scheelite-type component of the bending ν2 Raman line that led to the strongest SRS pulse shortening down to the dephasing time of the widest (scheelite-type) Raman mode at the secondary intracavity short-shifted SRS conversion. It allowed us to achieve SRS pulses with sub-picosecond duration under tens-of-picoseconds pumping due to the strongest 42-fold pulse shortening. Using the Ca3(VO4)2 crystal with essentially wider Raman lines (~50cm−1) did not allow us to generate SRS pulses shorter than 1 ps. It can be explained by inhomogeneous broadening of the Raman lines in Ca3(VO4)2 because of its structural disordering. Using the measured SRS pulse duration, the homogeneous broadening of the inhomogeneously broadened bending Raman line of Ca3(VO4)2 was estimated to be ~9cm−1. Among the orthovanadate crystals, the YVO4 crystal with the highest Raman gain and with homogeneously broadened Raman lines allowed us to realize the most efficient SRS lasing and SRS pulse shortening truly down to inverse half-width of the bending Raman line.
Electrically-pumped plasmonic lasers based on low-loss hybrid SPP waveguide (2015)

A low-loss surface plasmonic polariton (SPP) laser is designed as a candidate for the light-source in large-scale integrated (LSI) photonic circuits. Key design parameters of the laser are discussed and optimized to enhance the optical gain and minimize the metallic absorption loss. Performance of the laser is calculated to verify the device feasibility in the designed application.
Crystal Chemistry, Optical–Electronic Properties, and Electronic Structure of Cd 1– x In 2+2 x /3 S 4 Compounds (0 ≤ x ≤ 1), Potential Buffer in CIGS-Based Thin-Film Solar Cells (2018)

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A high-frequency, high-efficiency silicon carbide based phase-shifted full-bridge converter as a core component for a high-density on-board vehicle battery charging system (2013)

This paper presents a phase-shifted full-bridge (PSFB) converter that utilizes silicon carbide (SiC) power devices to achieve a high-density and high-efficiency solution for isolated dc-dc converter applications. Specifically, this converter represents a core technology for a Level 2 on-board vehicle battery charger for applications in electric vehicles (EVs) and plug-in hybrid electric vehicles (PHEVs). The operation of the circuit topology is discussed along with the advantages gained through the use of SiC power devices. Design equations for the power stage components are presented. Expected performance is validated via a hardware prototype, where a peak efficiency of 93.4% is obtained at a switching frequency of 500 kHz. The switching frequency is then reduced to optimize the converter efficiency and an overall peak efficiency of 96.5% is measured at 200 kHz. A peak output power of 6.06 kW results in a volumetric power density of 12.0 kW/L and a gravimetric power density of 9.1 kW/kg.
Laser optoacoustic tomography for the study of femtosecond laser filaments in air (2016)

We propose to use optoacoustic tomography to study the characteristics of femtosecond laser filamentation in air and condensed matter. The high spatial resolution of the proposed system, which consists of an array of broadband megahertz piezoelectric elements, ensures its effectiveness, despite the attenuation of ultrasonic waves in air.
Feasibility Study on Fire-Resistive Engineered Cementitious Composites (2014)

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VENOM: A Vectorized N:M Format for Unleashing the Power of Sparse Tensor Cores (2023)

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ChemInform Abstract: A Strategy for Constructing C‐Sialosides Based on Ireland—Claisen Rearrangement and Application for the Synthesis of a CF2‐Linked Ganglioside GM4 Analogue (2009)

Abstract ChemInform is a weekly Abstracting Service, delivering concise information at a glance that was extracted from about 200 leading journals. To access a ChemInform Abstract of an article which was published elsewhere, please select a “Full Text” option. The original article is trackable via the “References” option.
Discretization errors and free surface stabilization in the finite difference and marker-in-cell method for applied geodynamics: A numerical study (2011)

The finite difference–marker-in-cell (FD-MIC) method is a popular method in thermomechanical modeling in geodynamics. Although no systematic study has investigated the numerical properties of the method, numerous applications have shown its robustness and flexibility for the study of large viscous deformations. The model setups used in geodynamics often involve large smooth variations of viscosity (e.g., temperature-dependent viscosity) as well large discontinuous variations in material properties (e.g., material interfaces). Establishing the numerical properties of the FD-MIC and showing that the scheme is convergent adds relevance to the applications studies that employ this method. In this study, we numerically investigate the discretization errors and order of accuracy of the velocity and pressure solution obtained from the FD-MIC scheme using two-dimensional analytic solutions. We show that, depending on which type of boundary condition is used, the FD-MIC scheme is a second-order accurate in space as long as the viscosity field is constant or smooth (i.e., continuous). With the introduction of a discontinuous viscosity field characterized by a viscosity jump (η*) within the control volume, the scheme becomes first-order accurate. We observed that the transition from second-order to first-order accuracy will occur with only a small increase in the viscosity contrast (η* ≈ 5). We have employed two methods for projecting the material properties from the Lagrangian markers onto the Eulerian nodes. The methods are based on the size of the interpolation volume (4-cell, 1-cell). The use of a more local interpolation scheme (1-cell) decreases the absolute velocity and pressure discretization errors. We also introduce a stabilization algorithm that damps the potential oscillations that may arise from quasi free surface calculations in numerical codes that employ the strong form of the Stokes equations. This correction term is of particular interest for topographic modeling, since the surface of the Earth is generally represented by a free surface. Including the stabilization enables physically meaningful solutions to be obtained from our simulations, even in cases where the time step value exceeds the isostatic relaxation time. We show that including the stabilization algorithm in our FD stencil does not affect the convergence properties of our scheme. In order to verify our approach, we performed time-dependent simulations of free surface Rayleigh-Taylor instability.
WELDON: Weakly Supervised Learning of Deep Convolutional Neural Networks (2016)

In this paper, we introduce a novel framework for WEakly supervised Learning of Deep cOnvolutional neural Networks (WELDON). Our method is dedicated to automatically selecting relevant image regions from weak annotations, e.g. global image labels, and encompasses the following contributions. Firstly, WELDON leverages recent improvements on the Multiple Instance Learning paradigm, i.e. negative evidence scoring and top instance selection. Secondly, the deep CNN is trained to optimize Average Precision, and fine-tuned on the target dataset with efficient computations due to convolutional feature sharing. A thorough experimental validation shows that WELDON outperforms state-of-the-art results on six different datasets.
Light as a Resource, Stressor and Cue in Mediating Diversity-Productivity Relationships in Forests (2022)

In closed-canopy forests, the availability of photosynthetically active light has been a focal point of research, emphasizing the role of light as a resource in limiting carbon assimilation and individual tree growth. However, light shapes the functioning of forest ecosystems through multiple mechanisms. Here, using a series of studies from a network of tree diversity experiments, we explore the multifaceted ways in which light---in terms of both quantity and quality---shapes productivity in mixed-species forests. Spectral reflectance from remote sensing of forest canopies is being increasingly used to detect how tree diversity influences productivity. We demonstrate that airborne imaging spectroscopy captures functionally important differences among canopies related to their structure, chemistry, and underlying biological interactions. Ground-based analyses can show in detail how photosynthetically active light is partitioned among species in mixed-species communities. We show that greater interception of light and greater efficiency of light use, generated by inter- and intra-specific differences, combine to enhance productivity in mixed-species forests. Light may shape forest function not only as a resource but also as a stressor and cue. Plants can perceive light at various wavelengths, use this information to assess their neighborhoods, and subsequently adjust their physiology and allocation. We characterize how light quality---from the ultraviolet to shortwave infrared---varies among and within canopies of differing diversity. We explore how these diversity-light quality relationships arise and connect across levels of biological organization from leaf-level trait expression to forest function. Together these studies lend insight into light-mediated mechanisms that drive relationships between biodiversity and productivity in forest ecosystems---insights that are crucial to predict how biodiversity change will affect future forest function.
Prediction of PM2.5 concentration based on recurrent fuzzy neural network (2017)

The prediction of PM2.5 is difficult because the variation of PM2.5 concentration is a nonlinear dynamic process. Therefore, a recurrent fuzzy neural network prediction method is proposed to predict the PM2.5 concentration in this paper. Firstly, the partial least squares (PLS) algorithm is used to select key input variables as a preprocessing step. Then, a recurrent fuzzy neural network model is established and the gradient descent algorithm with an adaptive learning rate is used to train the neural network. Simulation results show that the recurrent neural network has better prediction performance and higher interpretability than fuzzy neural network (FNN) and radial-basis function (RBF) feed forward neural network.
Information batteries (2021)

Coping with the intermittency of renewable power is a fundamental challenge, with load shifting and grid-scale storage as key responses. We propose Information Batteries (IB), in which energy is stored in the form of information---specifically, the results of completed computational tasks. Information Batteries thus provide storage through speculative load shifting, anticipating computation that will be performed in the future. We take a distributed systems perspective, and evaluate the extent to which an IB storage system can be made practical through augmentation of compiler toolchains, key-value stores, and other important elements in modern hyper-scale compute. In particular, we implement one specific IB prototype by augmenting the Rust compiler to enable transparent function-level precomputation and caching. We evaluate the overheads this imposes, along with macro-level job prediction and power prediction. We also evaluate the space of operation for an IB system, to identify the best case efficiency of any IB system for a given power and compute regime.
Breast Cancer during Pregnancy—Current Paradigms, Paths to Explore (2019)

Breast cancer is the most common form of malignancy in pregnant women. The prevalence of pregnancy-associated breast cancer (PABC) is up to 0.04% of pregnancies and is expected to rise in developed countries. PABC represents a unique clinical scenario which requires a delicate balance of risks and benefits for both maternal and fetal well-being. Currently, there is paucity of data regarding the short- and long-term outcomes of in-utero exposure to anti-neoplastic agents. In general, when possible, treatment for PABC should follow the same guidelines as in non-pregnant patients. Surgery, including sentinel lymph node biopsy, is possible during all trimesters of pregnancy. Radiotherapy is contraindicated during pregnancy, although it might be considered in highly selected patients based on risk-benefit assessment. Evidence supports that administration of chemotherapy may be safe during the second and third trimesters, with cessation of treatment three weeks prior to expected delivery. Currently, hormonal therapy and anti-HER2 agents are contraindicated during pregnancy and should be postponed until after delivery. Prematurity is associated with worse neonatal and long-term outcomes, and thus should be avoided. While current data on the long-term effects of anti-neoplastic treatments are reassuring, grade of evidence is lacking, hence additional large prospective studies with long-term follow-up are essential to rule out any treatment-induced adverse effects.
Effects of nonionic, ionic, and dipolar ionic detergents and EDTA on the Brucella cell envelope (1982)

Cell envelopes prepared from smooth and rough strains of Brucella were characterized on the basis of lipopolysaccharide and protein content. The action of three kinds of detergents on Brucella cell envelopes and Escherichia coli control cell envelopes was examined on the basis of the proteins and lipopolysaccharides that were extracted. As compared with those of E. coli, Brucella cell envelopes were resistant to nonionic detergents. Zwittergents 312 and 316 were most effective in extracting E. coli cell envelopes, and Zwittergent 316 was most effective in extracting Brucella cell envelopes. Sarkosyl extracted proteins but extracted only trace amounts of lipopolysaccharides from cell envelopes of both bacteria. Sodium dodecyl sulfate-polyacrylamide gel electrophoresis analysis of the Sarkosyl-resistant proteins revealed a composition similar to that of the proteins exposed on the surfaces of viable cells, as determined by the lactoperoxidase-125I radioiodination method. EDTA, with either Tris-HCl or Tris-HCl-Triton X-100, did not have detectable effects on Brucella cell envelopes. Ultracentrifugation of purified lipopolysaccharides in detergents and EDTA demonstrate that, in contrast to that of E. coli, Brucella lipopolysaccharide was not stabilized by divalent cations. Sarkosyl was ineffective in dispersing lipopolysaccharides, whereas the action of Zwittergents was related to the length of their alkyl chains.
Screening for overlapping bacterial artificial chromosome clones by PCR analysis with an arbitrary primer (1998)

In this article, we used PCR analysis with arbitrary primers (AP-PCR) to screen for overlapping bacterial artificial chromosome (BAC) clones and assembly of contigs. A rice BAC library with three genome equivalents was used to prepare pooled BAC DNA. Twenty-two arbitrary primers were used to survey the pooled BAC DNAs and individual BAC DNAs. Each primer identified 1-10 loci, and the average was 4.4 loci. There were 1-5 overlapping clones in each locus, and the average was 2.5 clones. A total of 245 BAC clones were identified as overlapping by AP-PCR and the identities were confirmed by DNA-DNA hybridization. The 245 BAC clones were then assembled into 80 contigs and 17 single-clone loci. The results indicated that PCR analysis with arbitrary primers is a powerful tool in screening for overlapping BAC clones with high accuracy and efficiency. The use of AP-PCR analysis should speed up the construction of physical maps of the plant and animal genomes, as well as the rice genome.
Estimating Temperature Rise in Electronic Equipment Cases (1951)

In the design of airborne electronic equipment of minimum size and weight, the ambient temperature rating of components is often limiting. This ambient temperature is the equilibrium temperature inside the case, and may determine either the choice of components or the need for external cooling means. Calculation of equilibrium temperature requires knowledge of the power dissipated in the case and the rate of heat transfer to the surroundings by conduction, convection, and radiation. To avoid often laborious calculation, a series of charts are presented as an aid to estimating temperature rise. Graphical corrections for pressure altitude are given, together with a discussion of the effects of case color, high-speed aircraft skin temprerature, and other variables.
Dos, a Heme-Binding PAS Protein from Escherichia coli, Is a Direct Oxygen Sensor (2000)

A direct sensor of O(2), the Dos protein, has been found in Escherichia coli. Previously, the only biological sensors known to respond to O(2) by direct and reversible binding were the FixL proteins of Rhizobia. A heme-binding region in Dos is 60% homologous to the O(2)-sensing PAS domain of the FixL protein, but the remainder of Dos does not resemble FixL. Specifically, the C-terminal domain of Dos, presumed to be a regulatory partner that couples to its heme-binding domain, is not a histidine kinase but more closely resembles a phosphodiesterase. The absorption spectra of Dos indicate that both axial positions of the heme iron are coordinated to side chains of the protein. Nevertheless, O(2) and CO bind to Dos with K(d) values of 13 and 10 microM, respectively, indicating a strong discrimination against CO binding. Association rate constants for binding of O(2) (3 mM(-)(1) s(-)(1)), CO (1 mM(-)(1) s(-)(1)) and even NO (2 mM(-)(1) s(-)(1)) are extraordinarily low and very similar. Displacement of an endogenous ligand, probably Met 95, from the heme iron in Dos triggers a conformational change that alters the activity of the enzymatic domain. This sensing mechanism differs from that of FixL but resembles that of the CO sensor CooA of Rhodospirillum rubrum. Overall the results provide evidence for a heme-binding subgroup of PAS-domain proteins whose working range, signaling mechanisms, and regulatory partners can vary considerably.
Alcohol intake and the risk of intracerebral hemorrhage in the elderly (2018)

In white people aged 55 years and older, high alcohol intake might exert a causal effect on ICH, with a prominent role in the vascular pathologies underlying deep ICH.
Behavior of Non-metallic Inclusions in a Continuous Casting Tundish with Channel Type Induction Heating (2014)

A generalized three dimensional mathematical model, which adopted the Euler-Lagrange approach, has been developed for the motion of inclusions in a continuous casting tundish with channel type induction heating. The inclusion trajectories were obtained by numerical solution of the motion equation including gravity, buoyancy, drag, lift, added mass, Brownian, electromagnetic pressure and thermophoretic forces. Besides, the collision and coalescence of inclusions and adhesion to the lining solid surfaces were also taken into account. The Brownian, Stokes and turbulent collision were clarified, separately. Then the effect of induction heating power on the inclusion behavior was demonstrated. A reasonable agreement between the experimental observation and numerical results was obtained. The results indicate that the electromagnetic pressure force significantly promotes the removal of inclusions, especially for the bigger inclusion. Although the thermophoretic force goes against the removal of inclusions, its influence is negligibly small. The removal ratio of inclusions in the tundish with induction heating increases from 67.45% to 96.43%, while the power varies from 800 kW to 1200 kW. The collision and coalescence should be included when model the inclusion motion, because it can promote the removal of inclusion. The turbulent and Brownian collision becomes more active with the increasing power, while the Stokes collision is just opposite.
Low-frequency ultrasound radiosensitization and therapy response monitoring of tumors: An in vivo study (2016)

A new framework has been introduced in this paper for tumor radiosensitization and therapy response monitoring using low-frequency ultrasound. Human fibrosarcoma xenografts grown in severe combined immunodeficiency (SCID) mice (n = 108) were treated using ultrasound-stimulated microbubbles at various concentration and exposed to different doses of radiation. Low-frequency ultrasound radiofrequency (RF) data were acquired from tumors prior to and at different times after treatment. Quantitative ultrasound (QUS) techniques were applied to generate spectral parametric maps of tumors. Textural analysis were performed to quantify spatial heterogeneities within QUS parametric maps. A hybrid model was developed using multiple regression analysis to predict extent of histological tumor cell death non-invasively based on QUS spectral and textural biomarkers. Results of immunohistochemistry on excised tumor sections demonstrated increases in cell death with higher concentration of microbubbles and radiation dose. Quantitative ultrasound results indicated changes that paralleled increases in histological cell death. Specifically, the hybrid QUS biomarker demonstrated a good correlation with extent of tumor cell death observed from immunohistochemistry. A linear discriminant analysis applied in conjunction with the receiver operating characteristic (ROC) curve analysis indicated that the hybrid QUS biomarker can classify tumor cell death fractions with an area under the curve of 91.2. The results obtained in this research suggest that low-frequency ultrasound can concurrently be used to enhance radiation therapy and evaluate tumor response to treatment.
Cloning and Characterization of the ∆6 Polyunsaturated Fatty Acid Elongase from the Green Microalga Parietochloris incisa (2009)

The very-long-chain polyunsaturated fatty acid (VLC-PUFA), arachidonic acid (ARA, 20:4omega-6) is a component of neuron tissues such as brain and retina cells and a primary substrate for the biosynthesis of biologically active eicosanoids. The green freshwater microalga Parietochloris incisa (Trebouxiophyceae) has been shown to accumulate an extraordinary high content of ARA-rich triacylglycerols. It was thus interesting to characterize the genes involved in lipid biosynthesis in this alga. We report here the identification of a cDNA encoding for a P. incisa PUFA elongase (PiELO1) and demonstrate that the expression of PiELO1 in yeast Saccharomyces cereviseae confers its elongase activity on C18 6 PUFA. Phylogenetic analysis indicated that PiELO1 is highly similar to functionally characterized 6 PUFA elongase genes from other green algae and lower plants. Quantitative real-time PCR expression studies showed that PiELO1 is upregulated under nitrogen starvation, the condition triggering and enhancing storage oil and ARA accumulation in P. incisa.
Review of "Principles of Artificial Intelligence by Nils J. Nilsson", Tioga Publishing Co. (1980)

Nils Nilsson's new book, (Principles of Artificial Intelligence) (Tioga Publishing Co., 1980) discusses some basic ideas underlying different applications of AI. The book, designed as a text for a senior or first-year graduate course, aims to fill a gap between theory and practice. It succeeds in building a good solid arch outward from the shore of theory, but only a few support beams anchor the bridge to the shore of practice.