gebhart/patrepeval huggingface dataset:
Thermoelectric properties of Zn-doped Ca5In2Sb6 (2013)

The Zintl compound Ca5Al2Sb6 is a promising thermoelectric material with exceptionally low lattice thermal conductivity resulting from its complex crystal structure. In common with the Al analogue, Ca5In2Sb6 is naturally an intrinsic semiconductor with a low p-type carrier concentration. Here, we improve the thermoelectric properties of Ca5In2Sb6 by substituting Zn(2+) on the In(3+) site. With increasing Zn substitution, the Ca5In(2-x)Zn(x)Sb6 system exhibits increased p-type carrier concentration and a resulting transition from non-degenerate to degenerate semiconducting behavior. A single parabolic band model was used to estimate an effective mass in Ca5In2Sb6 of m* = 2m(e), which is comparable to the Al analogue, in good agreement with density functional calculations. Doping with Zn enables rational optimization of the electronic transport properties and increased zT in accordance with a single parabolic band model. The maximum figure of merit obtained in optimally Zn-doped Ca5In2Sb6 is 0.7 at 1000 K. While undoped Ca5In2Sb6 has both improved electronic mobility and reduced lattice thermal conductivity relative to Ca5Al2Sb6, these benefits did not dramatically improve the Zn-doped samples, leading to only a modest increase in zT relative to optimally doped Ca5Al2Sb6.
Removal of Non-process Elements from Hardwood Chips Prior to Kraft Cooking (2005)

The major part of the intake of non-process elements (NPE's) to the pulp mill is via the wood chips. Some of the problems associated with NPE's are e.g. precipitation of sparingly soluble calcium salts in the fibre line and in the recovery department. In order to investigate the possibilities of reducing the intake of NPE's via hardwood chips to the pulp mill, laboratory studies on the acidic leaching of birch and eucalyptus chips were carried out. The results showed that potassium, magnesium and manganese were removed from both wood species at similar rates. The removal of calcium was however significantly slower from eucalyptus than from birch. Removal of NPE's from birch wood chips prior to cooking resulted in a higher rate of delignification, a higher unbleached brightness and a higher viscosity. In the case of eucalyptus, acidic leaching had no effect on the rate of delignification. The positive effect of acidic leaching of birch chips was found to be due to a lower content of calcium in the cooking stage.
Doppler time-of-flight imaging (2015)

Over the last few years, depth cameras have become increasingly popular for a range of applications, including human-computer interaction and gaming, augmented reality, machine vision, and medical imaging. Many of the commercially-available devices use the time-of-flight principle, where active illumination is temporally coded and analyzed on the camera to estimate a per-pixel depth map of the scene. In this paper, we propose a fundamentally new imaging modality for all time-of-flight (ToF) cameras: per-pixel velocity measurement. The proposed technique exploits the Doppler effect of objects in motion, which shifts the temporal frequency of the illumination before it reaches the camera. Using carefully coded illumination and modulation frequencies of the ToF camera, object velocities directly map to measured pixel intensities. We show that a slight modification of our imaging system allows for color, depth, and velocity information to be captured simultaneously. Combining the optical flow computed on the RGB frames with the measured metric axial velocity allows us to further estimate the full 3D metric velocity field of the scene. We believe that the proposed technique has applications in many computer graphics and vision problems, for example motion tracking, segmentation, recognition, and motion deblurring.
Deep inverse reinforcement learning by logistic regression (2016)

This study proposes model-free deep inverse reinforcement learning to find nonlinear reward function structures. It is based on our previous method that exploits the fact that the log of the ratio between an optimal state transition and a baseline one is given by a part of reward and the difference of the value functions under linearly solvable Markov decision processes and reward and value functions are estimated by logistic regression. However, reward is assumed to be a linear function whose basis functions are prepared in advance. To overcome this limitation, we employ deep neural network frameworks to implement logistic regression. Simulation results show our method is comparable to model-based previous methods with less computing effort in the Objectworld benchmark. In addition, we show the optimal policy, which is trained with the shaping reward using the estimated reward and value functions, outperforms the policies that are used to collect data in the game of Reversi.
A Review of Two Industrial Deployments of Multi-criteria Decision-making Systems at General Electric (2007)

Two industrial deployments of multi-criteria decision-making systems at General Electric are reviewed from the perspective of their multi-criteria decision-making component similarities and differences. The motivation is to present a framework for multi-criteria decision-making system development and deployment. The first deployment is a financial portfolio management system that integrates hybrid multi-objective optimization and interactive Pareto frontier decision-making techniques to optimally allocate financial assets while considering multiple measures of return and risk, and numerous regulatory constraints. The second deployment is a power plant management system that integrates predictive modeling based on neural networks, optimization based on multi-objective evolutionary algorithms, and automated decision-making based on Pareto frontier techniques. The integrated approach, embedded in a real-time plant optimization and control software environment dynamically optimizes emissions and efficiency while simultaneously meeting load demands and other operational constraints in a complex real-world power plant
PRK-based scheduling for predictable link reliability in wireless networked sensing and control (2013)

Despite decades of research on interference-oriented channel access scheduling, most existing literature are either based on the physical interference model or the protocol interference model, neither of which is a good foundation for distributed interference control in the presence of uncertainties [2]. To address the issue, Che et al. [2] have identified the physical-ratio-K (PRK) interference model that integrates the protocol model's locality with the physical model's high-fidelity. Given a transmission from a node S to another node R, a concurrent transmitter C is regarded as not interfering with the reception at R in the PRK model if and only if P(C, R) < P(S,R)/KS,R,TS,R, where P(C, R) and P(S, R) is the strength of signals reaching R from C and S respectively, KS,R,TS,R is the minimum real number chosen such that, in the presence of interference from all concurrent transmitters, the probability for R to successfully receive packets from S is no less than the minimum link reliability TS,R required by applications (e.g., control algorithms).
Fermented Oyster Extract Prevents Ovariectomy-Induced Bone Loss and Suppresses Osteoclastogenesis (2019)

There is growing interest in bioactive substances from marine organisms for their potential use against diverse human diseases. Osteoporosis is a skeletal disorder associated with bone loss primarily occurring through enhanced osteoclast differentiation and resorption. Recently, we reported the anti-osteoclastogenic activity of fermented Pacific oyster (<i>Crassostrea gigas</i>) extract (FO) in vitro. The present study focused on investigating the anti-osteoporotic efficacy of FO in bone loss prevention in an experimental animal model of osteoporosis and elucidating the mechanism underlying its effects. Oral administration of FO significantly decreased ovariectomy-induced osteoclast formation and prevented bone loss, with reduced serum levels of bone turnover biomarkers including osteocalcin and C-terminal telopeptide fragment of type I collagen C-terminus (CTX). FO significantly suppressed receptor activator of nuclear factor-κB ligand (RANKL)-induced differentiation of bone marrow-derived macrophages (BMMs) into osteoclasts and attenuated the induction of osteoclast-specific genes required for osteoclastogenesis and bone resorption. Furthermore, FO inhibited RANKL-mediated IκBα and p65 phosphorylation in BMMs. Taken together, these results demonstrate that FO effectively suppresses osteoclastogenesis in vivo and in vitro, and that FO can be considered as a potential therapeutic option for the treatment of osteoporosis and osteoclast-mediated skeletal diseases.
Temperature-dependent magnetic properties of (Y,Sm,Lu,Tm,Ca)3(Fe,Ge)5O12 epitaxial garnet films (1979)

Thulium has been substituted for yttrium in melts for the growth of (Y,Sm,Lu,Ca)3(Fe,Ge)5O12 epitaxial garnet films for the purpose of reducing the magnitude of the temperature coefficient αbc of the bubble collapse field. As an extension of previous substitutions [J. E. Davies, G. Galli, and J. C. Suits, J. Appl. Phys. 49, 1859 (1978)] of Tm for Lu to smaller bubble diameters, growth conditions were adjusted to produce films of nearly identical thickness (1.40 μm) and characteristic length (0.222 μm at 25°C) for Tm substitutions up to 0.25 atoms in the formula unit. This substitution was found to decrease the magnitude of αbc as measured at 50°C by approximately 0.04%/°C⋅Tm atom. Anisotropy remains nearly constant with Tm substitution.
Heterologous expression of Saccharomyces cerevisiae MPR1 gene confers tolerance to ethanol and l-azetidine-2-carboxylic acid in Hansenula polymorpha (2009)

Hansenula polymorpha is a naturally xylose-fermenting yeast; however, both its ethanol yield from xylose and ethanol resistance have to be improved before this organism can be used for industrial high-temperature simultaneous saccharification and fermentation of lignocellulosic materials. In the current research, we checked if the expression of the Saccharomyces cerevisiae MPR1 gene encoding N-acetyltransferase can increase the ethanol tolerance of H. polymorpha. The S. cerevisiae MPR1 gene was cloned in the H. polymorpha expression vector under the control of the H. polymorpha strong constitutive promoter of the glyceraldehyde-3-phosphate dehydrogenase gene (GAPDH). H. polymorpha recombinant strains harboring 1-3 copies of the S. cerevisiae MPR1 gene showed enhanced tolerance to L: -azetidine-2-carboxylic acid and ethanol. The obtained results suggest that the expression of the S. cerevisiae MPR1 gene in H. polymorpha can be a useful approach in the construction of H. polymorpha strains with improved ethanol resistance.
Abstract 1048: Homogenous, bioluminescent and HTS formatted assay for quantization of ADP production in kinase and ATPase reactions (2010)

Abstract Because of its versatility (all types of substrates), robustness (Z’&gt;0.8), rapid performance, and its ease of use, the luminescence based Kinase GloTM assays platform have gained wide acceptance in many drug screening programs for protein kinase inhibitors. We have attempted to extend our strategy by now monitoring ADP product formation in the kinase reaction. The new assay we developed (ADP Glo) maintains all the positive features of Kinase GloTM such as universality, and applicability to all kinds of kinase substrates regardless of their nature with no prior modification (peptides, protein, polymer, lipids, and sugars) but In stead of measuring ATP depletion, it monitors ADP production. It detects ADP at early stages of enzyme reactions with very high signal to background (SB) ratio. It can be run at a wide range of ATP concentrations (low micromolar to millimolar), is sensitive to low ADP concentrations (0.1 pmol), and it can be carried out in high density plate formats. This assay is robust and homogenous, and does not require antibodies or custom synthesized substrates. It is ideal to search for optimal substrates in a collection of peptides, proteins, or lipids in a single assay format, and to screen for ATP competitive and Non competitive inhibitors. Because of the high dynamic range and more importantly, the high SB values even at low % ATP to ADP conversion, the assay allows the use of low amounts of enzyme during high-throughput screening. Evaluation of this assay in a screen of a large chemical library showed minimal false hits attesting to the quality of this system. The ADP-GloTM assay is applicable to all types of kinases, ATPases, multidrug resistant proteins such as MDR1-Pgp, helicases, topoisomerases, and heat shock proteins and as well as many other ADP producing enzyme reactions. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 101st Annual Meeting of the American Association for Cancer Research; 2010 Apr 17-21; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2010;70(8 Suppl):Abstract nr 1048.
A positive systems model of TCP-like congestion control: asymptotic results (2006)

We study communication networks that employ drop-tail queueing and Additive-Increase Multiplicative-Decrease (AIMD) congestion control algorithms. It is shown that the theory of nonnegative matrices may be employed to model such networks. In particular, important network properties, such as: 1) fairness; 2) rate of convergence; and 3) throughput, can be characterized by certain nonnegative matrices. We demonstrate that these results can be used to develop tools for analyzing the behavior of AIMD communication networks. The accuracy of the models is demonstrated by several NS studies
Inhibition of secreted frizzled-related protein 5 improves glucose metabolism (2014)

Elucidating the role of secreted frizzled-related protein 5 (SFRP5) in metabolism and obesity has been complicated by contradictory findings when knockout mice were used to determine metabolic phenotypes. By overexpressing SFRP5 in obese, prediabetic mice we consistently observed elevated hyperglycemia and glucose intolerance, supporting SFRP5 as a negative regulator of glucose metabolism. Accordingly, Sfrp5 mRNA expression analysis of both epididymal and subcutaneous adipose depots of mice indicated a correlation with obesity. Thus, we generated a monoclonal antibody (mAb) against SFRP5 to ascertain the effect of SFRP5 inhibition in vivo. Congruent with SFRP5 overexpression worsening blood glucose levels and glucose intolerance, anti-SFRP5 mAb therapy improved these phenotypes in vivo. The results from both the overexpression and mAb inhibition studies suggest a role for SFRP5 in glucose metabolism and pancreatic β-cell function and thus establish the use of an anti-SFRP5 mAb as a potential approach to treat type 2 diabetes.
First Direct Body Fat Content Measurement during Pregnancy Using Fourier Transform Near-Infrared Spectroscopy (2014)

Currently, there are no direct and reliable methods to measure the body fat content of women during pregnancy. Estimates of fat accretion can significantly affect calculations of energy requirements. We report here the first direct measurement of determining the body fat content of two women during pregnancy using the Fourier transform near-infrared spectroscopy (FT-NIR) method. Fourier transform near-infrared spectroscopy was shown to provide comparable results to dual-energy X-ray absorptiometry and magnetic resonance imaging. These latter methods, even though very reliable to measure body fat levels, cannot be used to measure the body fat of women during pregnancy because of health concerns, while FT-NIR poses no health risk. The FT-NIR results showed the percent body fat remained relatively constant throughout pregnancy, but fat mass and fat free mass increased. Fat mass followed an S curve with a maximum increase between 15 to 25 weeks of gestation that was only detected by repeated measurements using the FT-NIR technique. These results demonstrate the value of the FT-NIR method to directly measure the fat content of pregnant women in minutes instead of relying on indirect calculations or taking measurements before and after pregnancy to track gestational fat mass accretion.
Ultrathin gradient nonlinear metasurface with a giant nonlinear response (2016)

Gradient metasurfaces have recently been demonstrated to provide control of the phase of scattered fields over subwavelength scales, enabling a broad range of linear optical components in a flat, ultrathin, integrable platform. Additionally, the development of nonlinear metasurfaces has disrupted conventional nonlinear optical device design by relaxing phase matching constraints, reducing size and dimensionality, and providing record values of localized nonlinear responses. However, extending the ???flat optics??? paradigm to the nonlinear case faces important challenges, since we are required to simultaneously achieve efficient frequency conversion and sub-diffractive phase control. Here, we experimentally demonstrate continuous phase control of the giant nonlinear second harmonic optical response from metasurfaces tied to intersubband transitions in semiconductor multi-quantum wells, establishing an exciting path toward realizing the vision of flat, nonlinear optics.
Supraparticle Nanoassemblies with Enzymes (2019)

Supraparticles are micelle-like self-limited assemblies from inorganic nanoparticles (NPs), whose size and morphology are determined by the equilibrium between short-range attraction and long-range repulsion forces. They can be spontaneously assembled from a variety of nanoscale components that are, in the majority of cases, the same NPs. Hybrid supraparticles made from inorganic and biological components are possible but hardly known. We report here the self-assembly of hybrid bioinorganic supraparticles, prepared from iron disulfide, cadmium telluride, and zinc oxide NPs as well as protease, cytochrome c, and formate dehydrogenase, in which the protein content can exceed that of NPs by 3:1. The resulting bioinorganic supraparticles are 70–150 nm in diameter and have a narrow size distribution. Five different permutations of inorganic and biological components indicate the generality of the observed phenomena. Coarse-grained molecular dynamics simulations confirmed that the formation of supraparticles depends on the interplay between attraction strengths and electrostatic repulsion. Enzymatic activity of the native protein is retained and is completely recovered from the assemblies, which suggests that the supraparticles can be utilized for encapsulation of biomolecules.
SCAN: Structure Correcting Adversarial Network for Organ Segmentation in Chest X-rays (2017)

Chest X-ray (CXR) is one of the most commonly prescribed medical imaging procedures, often with over 2-10x more scans than other imaging modalities such as MRI, CT scan, and PET scans. These voluminous CXR scans place significant workloads on radiologists and medical practitioners. Organ segmentation is a crucial step to obtain effective computer-aided detection on CXR. In this work, we propose Structure Correcting Adversarial Network (SCAN) to segment lung fields and the heart in CXR images. SCAN incorporates a critic network to impose on the convolutional segmentation network the structural regularities emerging from human physiology. During training, the critic network learns to discriminate between the ground truth organ annotations from the masks synthesized by the segmentation network. Through this adversarial process the critic network learns the higher order structures and guides the segmentation model to achieve realistic segmentation outcomes. Extensive experiments show that our method produces highly accurate and natural segmentation. Using only very limited training data available, our model reaches human-level performance without relying on any existing trained model or dataset. Our method also generalizes well to CXR images from a different patient population and disease profiles, surpassing the current state-of-the-art.
Development of chiral smectic C materials for multiplexed display applications (1988)

Abstract The practice is well established, of formulating ferroelectric liquid crystal mixtures by use of a laterally polar chiral dopant dissolved in a wide temperature range liquid crystal host having a tilted smectic phase. This approach is valuable as it allows molecular engineering of each component of the mixture in order to optimise its properties: the chiral dopant for example need not possess any liquid crystal phase in its own right. Work has previously been described in which laterally fluorinated esters of structure I are used to formulate a smectic C base mixture, which is then doped with naphthalene esters of 2-octanol (11) to impart ferroelectric properties.
Field and Current Control of the Electrical Conductivity of an Artificial 2D Honeycomb Lattice (2019)

The conductivity of a neodymium-based artificial honeycomb lattice undergoes dramatic changes upon application of magnetic fields and currents. These changes are attributed to a redistribution of magnetic charges that are formed at the vertices of the honeycomb due to the nonvanishing net flux of magnetization from adjacent magnetic elements. It is suggested that the application of a large magnetic field or a current causes a transition from a disordered state, in which magnetic charges are distributed at random, to an ordered state, in which they are regularly arranged on the sites of two interpenetrating triangular Wigner crystals. The field and current tuning of electrical properties are highly desirable functionalities for spintronics applications. Consequently, a new spintronics research platform can be envisaged using artificial magnetic honeycomb lattices.
Stochastic finite-state models for spoken language machine translation (2000)

Stochastic finite-state models are efficiently learnable from data, effective for decoding and are associated with a calculus for composing models which allows for tight integration of constraints from various levels of language processing. In this paper, we present a method for stochastic finite-state machine translation that is trained automatically from pairs of source and target utterances. We use this method to develop models for English-Japanese and Japanese-English translation. We have embedded the Japanese-English translation system in a call routing task of unconstrained speech utterances. We evaluate the efficacy of the translation system in the context of this application.
A Practical Price Optimization Approach for Omnichannel Retailing (2019)

Consumers are increasingly navigating across sales channels to maximize the value of their purchase. The existing retail practices of pricing channels either independently or matching competitor prices are unable to achieve the desired profitable coordination between channels. We engaged with three major retailers over two years and developed omnichannel pricing (OCP) solutions in partnership with IBM Commerce to overcome these challenges. We implement an integrated data processing and machine learning framework that enables estimation of location-specific, cross-channel price elasticities and competitive effects. We develop an integrated OCP optimization formulation to profitably coordinate prices for nonperishable products offered across channels and store locations while satisfying practical constraints on volume and price. The resultant optimization formulations for discrete choice demand models are nonconvex and NP-hard, and we prescribe practically efficient mixed-integer programs that can be used to recover (near) optimal solutions. An OCP implementation in two categories for a major retail chain projected a 7% profit lift while preserving the sales volume. This benefit was achieved by lowering online prices and optimally raising and lowering location-specific store prices. This integrated pricing approach allows the retailer to be competitive and preserve market share without aggressively matching the low price of e-tail giants.