gebhart/patrepeval huggingface dataset:
Direct Medium-Chain Carboxylic Acid Oil Separation from a Bioreactor by an Electrodialysis/Phase Separation Cell (2020)

Medium-chain carboxylic acids (MCCAs) are valuable platform chemicals and can be produced from waste biomass sources or syngas fermentation effluent through microbial chain elongation. We have previously demonstrated successful approaches to separate >90% purity oil with different MCCAs (MCCA oil) by integrating the anaerobic bioprocess with membrane-based liquid-liquid extraction (pertraction) and membrane electrolysis. However, two-compartment membrane electrolysis unit without pertraction was not able to separate MCCA oil. Therefore, we developed a five-compartment electrodialysis/phase separation cell (ED/PS). First, we tested an ED/PS cell <i>in series</i> with pertraction and achieved a maximum MCCA-oil flux of 1.7 × 10<sup>3</sup> g d<sup>-1</sup> per projected area (m<sup>2</sup>) (19 mL oil d<sup>-1</sup>) and MCCA-oil transfer efficiency [100% × moles MCCA-oil moles electrons<sup>-1</sup>] of 74% at 15 A m<sup>-2</sup>. This extraction system at 15 A m<sup>-2</sup> demonstrated a ∼10 times lower electric-power consumption (1.1 kWh kg<sup>-1</sup> MCCA oil) than membrane electrolysis in series with pertraction (9.9 kWh kg<sup>-1</sup> MCCA oil). Second, we evaluated our ED/PS as a stand-alone unit when integrated with the anaerobic bioprocess and demonstrated that we can selectively extract and separate MCCA oil directly from chain-elongating bioreactor broth with just an abiotic electrochemical cell. However, the electric-power consumption increased considerably due to the lower MCCA concentrations in the bioreactor broth compared to the pertraction broth.
ChemInform Abstract: Desymmetrization Reactions: A Convenient Synthesis of Aromatic Diamide Diamines. (2001)

Abstract ChemInform is a weekly Abstracting Service, delivering concise information at a glance that was extracted from about 100 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.
Ascorbic Acid and 4‐Hexylresorcinol Effects on Pear PPO and PPO Catalyzed Browning Reaction (2007)

The effects of ascorbic acid (AA) and 4-hexylresorcinol (4-HR) on pear polyphenoloxidase (PPO) activity and stability have been investigated in vitro. AA does not interact directly with PPO but prevents browning by reducing oxidized substrates. The 4-HR exerts a dual role on PPO. If no substrates are present, it interacts preferably with the deoxy form of PPO inactivating it. If substrates and 4-HR are both present they compete for the catalytic site. The 4-HR behaves then as a canonical enzyme inhibitor, binding to the met form of PPO. Simultaneous addition of 4-HR and AA has synergistic inhibition or inactivatory effects depending on the presence or the absence of PPO substrates.
Detection of NH 2 Radical in Ammonia Radio-Frequency Plasmas by Laser-Induced Resonance Fluorescence (2001)

By means of one photon absorption laser-induced resonance fluorescence at 599.5 nm the relative concentrations of the amidogen (NH2) radical in the ammonia (NH3) radio-frequency (rf) plasma source were measured under different discharge pressures and rf powers. The time dependence of the fluorescence which comes from the radiation 101-211 of the P-branches of the Σ vibronic sub-bands can be described by a single-exponential decay. The decay time of NH2(A2A1) Σ (0, 9, 0) rovibronic state was determined. The spatial dependence of the NH2 density in the discharge tube was measured.
Adaptive Cardiac Resynchronization Therapy Device Based on Spiking Neurons Architecture and Reinforcement Learning Scheme (2007)

Spiking neural network (NN) architecture that uses Hebbian learning and reinforcement-learning schemes for adapting the synaptic weights is implemented in silicon and performs dynamic optimization according to hemodynamic sensor for a cardiac resynchronization therapy (CRT) device. The spiking NN architecture dynamically changes the atrioventricular (AV) delay and interventricular (VV) interval parameters according to the information provided by the intracardiac electrograms (IEGMs) and hemodynamic sensors. The spiking NN coprocessor performs the adaptive part and is controlled by a deterministic algorithm master controller. The simulated cardiac output obtained with the adaptive CRT device is 30% higher than with a nonadaptive CRT device and is likely to provide improvement in the quality of life for patients with congestive heart failure. The spiking NN architecture shows synaptic plasticity acquired during the learning process. The synaptic plasticity is manifested by a dynamic learning rate parameter that correlates patterns of hemodynamic sensor with the system outputs, i.e., the optimal AV and VV pacing intervals.
Chemical and biological assessment of metal organic frameworks (MOFs) in pulmonary cells and in an acute in vivo model: relevance to pulmonary arterial hypertension therapy (2017)

Pulmonary arterial hypertension (PAH) is a progressive and debilitating condition. Despite promoting vasodilation, current drugs have a therapeutic window within which they are limited by systemic side effects. Nanomedicine uses nanoparticles to improve drug delivery and/or reduce side effects. We hypothesize that this approach could be used to deliver PAH drugs avoiding the systemic circulation. Here we report the use of iron metal organic framework (MOF) MIL-89 and PEGylated MIL-89 (MIL-89 PEG) as suitable carriers for PAH drugs. We assessed their effects on viability and inflammatory responses in a wide range of lung cells including endothelial cells grown from blood of donors with/without PAH. Both MOFs conformed to the predicted structures with MIL-89 PEG being more stable at room temperature. At concentrations up to 10 or 30 µg/mL, toxicity was only seen in pulmonary artery smooth muscle cells where both MOFs reduced cell viability and CXCL8 release. In endothelial cells from both control donors and PAH patients, both preparations inhibited the release of CXCL8 and endothelin-1 and in macrophages inhibited inducible nitric oxide synthase activity. Finally, MIL-89 was well-tolerated and accumulated in the rat lungs when given in vivo. Thus, the prototypes MIL-89 and MIL-89 PEG with core capacity suitable to accommodate PAH drugs are relatively non-toxic and may have the added advantage of being anti-inflammatory and reducing the release of endothelin-1. These data are consistent with the idea that these materials may not only be useful as drug carriers in PAH but also offer some therapeutic benefit in their own right.
Comparison of Urine Albumin-to-Creatinine Ratio (ACR) Between ACR Strip Test and Quantitative Test in Prediabetes and Diabetes (2016)

The ACR strip test showed high sensitivity, specificity, and negative predictive value, suggesting that the test can be used to screen for albuminuria in cases of prediabetes and diabetes.
Integrating aligned nanorod array onto optical fibers for SERS probes (2006)

The use of fiber optics can greatly reduce device size while maintaining the sensitivity. Recently, nanostructures, especially metallic nanoparticles, have been incorporated into fiber optical sensors to obtain high sensitivity and specificity. Here, we propose a new way to integrate aligned nanorods onto optical fibers using a modified oblique angle deposition (OAD) technique. By rotating the optical fiber with a proper tilting angle, aligned nanorods from materials such as metals, semiconductors and metal oxides have been successfully deposited. With a slight modification, multilayer film/nanorod and nanorod/nanorod structures have also been demonstrated. This method has the advantage to coat aligned nanorods on optical fibers at low temperature, and is particularly promising for preparing nanostructured fiber optical probes for sensor applications. We also demonstrate that the optical fiber with its tip coated with Ag nanorod arrays can act as a Surface Enhance Raman Scattering (SERS) sensor.
1.5 μm ingaasp fabry‐perot cavity‐type laser amplifiers (1987)

Abstract To understand the small‐signal gain, signal‐gain saturation and noise characteristics of 1.5 μm InGaAsP Fabry‐Perot cavity‐type laser amplifiers, two types of laser amplifiers having different thickness of the active layers were tested. It was found that the larger the gain coefficient (i.e., the larger the injected carrier density), the higher the gain and saturation output of the amplifiers, and the lower the noise level. Stern's gain calculation method was applied to materials for the 1.5‐μm region. It was found theoretically that these characteristics are due to the dependence of the carrier lifetime on the injected carrier density and the dependence of the saturation intensity and the population inversion parameter of the gain coefficient, by using the material parameters taking account of the Auger effect and the structure parameters of the device. The feature of the 1.5‐μm amplifiers is that the reduction of the carrier lifetime with the increase of the carrier density becomes more significant due to the Auger recombination process. It is important for improving the saturation output by positively utilizing this phenomenon to design the amplifier structure so that the amplifiers can be operated in a high‐gain region.
Electrocardiogram ST Analysis During Labor (2015)

The use of ST analysis during labor as an adjunct to the standard cardiotocography does not improve perinatal outcomes or decrease cesarean delivery.
Turbo decoding for wireless systems with imperfect channel estimates (2000)

A new metric for turbo decoding on Rayleigh fading channels with noisy channel estimates is derived. By including the error variance of the channel estimate in the decoder metric derivation, we calculate the correct channel reliability factor for this case. Simulations show that the signal-to-noise ratio gain of using this new metric, compared to ignoring the uncertainty of the channel estimate, may be as large as 1 dB at a bit error probability of 10/sup -3/. This gain is obtained without any complexity increase.
Two new inflammatory markers associated with Disease Activity Score‐28 in patients with rheumatoid arthritis: neutrophil‐lymphocyte ratio and platelet‐lymphocyte ratio (2015)

The present study showed us that NLR and PLR were two new inflammatory markers which could be used to assess disease activity in patients with RA.
Screening of patients with maternally transmitted diabetes for mitochondrial gene mutations in the tRNALeu(UUR) region (1997)

To investigate the prevalence and clinical characteristics of diabetes mellitus caused by mitochondrial gene mutations in the tRNA[Leu(UUR)] region, a known 'hot spot' for pathogenic mutations, we screened 440 diabetic patients with diabetic mothers for 11 mitochondrial gene mutations reported in mitochondrial neuromuscular disorders; nucleotide pairs (np) 3250, 3251, 3252, 3254, 3256, 3260, 3271, 3291, 3302 and 3303 in addition to an A to G transition at np 3243. The dot-blot hybridization method using 32P-labelled sequence-specific oligonucleotides as probes was used. One subject carrying a T to C transition at np 3271 and seven carrying the A to G transition at np 3243 were identified, while none of the other diabetic patients screened had these mutations in the tRNA[Leu(UUR)] region. The patient with the 3271 mutation, a 39-year-old male, had excellent glycaemic control with diet alone and had neither hearing impairment nor symptoms suggesting mitochondrial myopathy, encephalopathy, lactic acidosis and stroke-like episodes (MELAS). Thus, among patients with maternally transmitted diabetes, the prevalence of the 3271 mutation was approximately one-seventh that of the 3243 mutation, and other mutations are even more rare in the mitochondrial tRNA[Leu(UUR)] region.
Evaluation of amorphous diamond-like carbon-nitrogen films as wear protective coatings on thin film media and thin film head sliders (1997)

As the magnetic data storage industry strives to achieve ultra-high recording densities requiring fly heights of less than one microinch, the tribology of the head-disk interface (HDI) is a limiting factor in disk drive design. Amorphous diamond-like-carbon (DLC) films have been the materials of choice for wear-protective coatings. Various amorphous DLC type coatings have been developed. The earliest DLC material was DC magnetron sputtered pure carbon films. Recent developments have produced C:H (hydrogenated-carbon) and C:N (carbon-nitrogen) films with greater wear-resistance than pure C film. Our intent is to describe and evaluate the wear-resistance performance of amorphous C:N films as wear-protective overcoats on thin film media and thin film sliders. Both C:H and C:N films have demonstrated superiority over DC magnetron sputtered pure carbon films. The bond character, microhardness, surface roughness features, and the physical nature of initial wear damage influence wear-resistance performance significantly. A recent report of nano-indentor measurements and wear-resistance performance confirmed the superiority of RF diode and DC magnetron Facing Target Sputtering (FTS) of thin C:N coatings over other DLC films.
Analog vs. digital: a comparison of circuit implementations for low-power matched filters (1996)

The matched filter or correlator block of a spread-spectrum communication system occupies a place in the receiver that just follows the analog RF-to-baseband or RF-to-IF downconversion circuitry and just precedes the digital data-decoding circuitry. A matched filter may, therefore, be implemented via either digital or analog circuit techniques. This paper analyzes and compares a digital and an analog implementation of a programmable parallel matched filter using power efficiency-as a function of signal integrity, filter size, operating frequency, and technology scaling-as the primary metric of comparison. A methodology is presented and results are given that indicate wherein the multidimensional design space the digital circuit is more power-efficient than the analog one, and vice versa.
Learning to Repeat: Fine Grained Action Repetition for Deep Reinforcement Learning (2017)

Reinforcement Learning algorithms can learn complex behavioral patterns for sequential decision making tasks wherein an agent interacts with an environment and acquires feedback in the form of rewards sampled from it. Traditionally, such algorithms make decisions, i.e., select actions to execute, at every single time step of the agent-environment interactions. In this paper, we propose a novel framework, Fine Grained Action Repetition (FiGAR), which enables the agent to decide the action as well as the time scale of repeating it. FiGAR can be used for improving any Deep Reinforcement Learning algorithm which maintains an explicit policy estimate by enabling temporal abstractions in the action space. We empirically demonstrate the efficacy of our framework by showing performance improvements on top of three policy search algorithms in different domains: Asynchronous Advantage Actor Critic in the Atari 2600 domain, Trust Region Policy Optimization in Mujoco domain and Deep Deterministic Policy Gradients in the TORCS car racing domain.
RANDOM NEURAL NETWORK LEARNING HEURISTICS (2017)

The random neural network (RNN) is a probabilitsic queueing theory-based model for artificial neural networks, and it requires the use of optimization algorithms for training. Commonly used gradient descent learning algorithms may reside in local minima, evolutionary algorithms can be also used to avoid local minima. Other techniques such as artificial bee colony (ABC), particle swarm optimization (PSO), and differential evolution algorithms also perform well in finding the global minimum but they converge slowly. The sequential quadratic programming (SQP) optimization algorithm can find the optimum neural network weights, but can also get stuck in local minima. We propose to overcome the shortcomings of these various approaches by using hybridized ABC/PSO and SQP. The resulting algorithm is shown to compare favorably with other known techniques for training the RNN. The results show that hybrid ABC learning with SQP outperforms other training algorithms in terms of mean-squared error and normalized root-mean-squared error.
Representing inferential uncertainty in deep neural networks through sampling (2017)

As deep neural networks (DNNs) are applied to increasingly challenging problems, they will need to be able to represent their own uncertainty. Modelling uncertainty is one of the key features of Bayesian methods. Bayesian DNNs that use dropout-based variational distributions and scale to complex tasks have recently been proposed. We evaluate Bayesian DNNs trained with Bernoulli or Gaussian multiplicative masking of either the units (dropout) or the weights (dropconnect). We compare these Bayesian DNNs ability to represent their uncertainty about their outputs through sampling during inference. We tested the calibration of these Bayesian fully connected and convolutional DNNs on two visual inference tasks (MNIST and CIFAR-10). By adding different levels of Gaussian noise to the test images, we assessed how these DNNs represented their uncertainty about regions of input space not covered by the training set. These Bayesian DNNs represented their own uncertainty more accurately than traditional DNNs with a softmax output. We find that sampling of weights, whether Gaussian or Bernoulli, led to more accurate representation of uncertainty compared to sampling of units. However, sampling units using either Gaussian or Bernoulli dropout led to increased convolutional neural network (CNN) classification accuracy. Based on these findings we use both Bernoulli dropout and Gaussian dropconnect concurrently, which approximates the use of a spike-and-slab variational distribution. We find that networks with spike-and-slab sampling combine the advantages of the other methods: they classify with high accuracy and robustly represent the uncertainty of their classifications for all tested architectures.
Interaction of MeV ions with pre-existing damage in Si: A new ion beam annealing mechanism (1989)

A new ion beam annealing phenomenon which occurs during room-temperature irradiation of Si is discussed. The interaction of high-energy ions with different damage morphologies is shown to depend on the detailed nature of the damage. This interaction leads to annealing when the damage consists only of simple types of defects, while irradiation of more complex damage morphologies can result in additional damage growth. A model is proposed which qualitatively accounts for the phenomenon.
Multiple kernel interpolation for inverting non-linear dimensionality reduction and dimension estimation (2014)

The problem of stably inverting a non-linear dimensionality reduction map has applications in data visualization and machine learning, besides being of theoretical interest. In this paper, we propose a meshfree interpolation method for obtaining such inverse maps using a non-negative linear combination of multiple interpolants. We show that the proposed scheme can improve upon the approximation power of its individual constituent kernels, and discuss the conditions under which its parameters can be uniquely estimated. We also provide an approach for estimating the intrinsic dimensionality (ID) of manifolds using the proposed inverse map. Experiments using multiple kernel interpolation for reconstruction of novel test data and ID estimation show an improved or similar performance compared to existing techniques.
Optimising the Integration of Terrain Referenced Navigation with INS and GPS (2005)

The benefits of integrated INS/GPS systems are well known. However, the knowledge required to jam GPS is becoming public and the hardware to achieve this is basic. When GPS data are unavailable and a low grade INS is used, navigation accuracy quickly degrades to an unacceptable level. The addition of one or more terrain referenced navigation (TRN) systems to an integrated INS/GPS navigation system enables the INS to be calibrated during GPS outages, increasing the robustness of the overall navigation solution. TRN techniques are compared and integration architectures are reviewed. For the initial studies of INS/GPS/TRN integration, radar altimeter based terrain contour navigation (TCN) with a batch processing algorithm is used in conjunction with a centralised integration filter. Four different approaches for using these TCN fixes to calibrate the INS are compared. These are a best fix method, a weighted fix method using a probabilistic data association filter (PDAF) and single and multi-hypothesis versions of the Iterative Gaussian Mixture Approximation of the Posterior (IGMAP) method. Simulation results are presented showing that the single hypothesis IGMAP technique offers the best balance between accuracy, robustness and processing efficiency.
From molecular copper complexes to composite electrocatalytic materials for selective reduction of CO<sub>2</sub> to formic acid (2015)

The development of new energy storage technologies is central to solving the challenges facing the widespread use of renewable energies.
Conformational dynamics of SARS-CoV-2 trimeric spike glycoprotein in complex with receptor ACE2 revealed by cryo-EM (2020)

The recent outbreaks of SARS-CoV-2 pose a global health emergency. The SARS-CoV-2 trimeric spike (S) glycoprotein interacts with the human ACE2 receptor to mediate viral entry into host cells. We report the cryo-EM structures of a tightly closed SARS-CoV-2 S trimer with packed fusion peptide and an ACE2-bound S trimer at 2.7- and 3.8-Å resolution, respectively. Accompanying ACE2 binding to the up receptor-binding domain (RBD), the associated ACE2-RBD exhibits continuous swing motions. Notably, the SARS-CoV-2 S trimer appears much more sensitive to the ACE2 receptor than the SARS-CoV S trimer regarding receptor-triggered transformation from the closed prefusion state to the fusion-prone open state, potentially contributing to the superior infectivity of SARS-CoV-2. We defined the RBD T470-T478 loop and Y505 as viral determinants for specific recognition of SARS-CoV-2 RBD by ACE2. Our findings depict the mechanism of ACE2-induced S trimer conformational transitions from the ground prefusion state toward the postfusion state, facilitating development of anti-SARS-CoV-2 vaccines and therapeutics.
Three-dimensional structure of p21H-ras and its implications. (1992)

The three-dimensional structure of the H-ras oncogene product p21 has been determined in both its active, GTP-bound and its inactive, GDP-bound forms. This has supplied a wealth of information on the mode of binding of guanine nucleotides, on the mechanism of the GTPase reaction and on the conformational change of the protein which accompanies GTP hydrolysis. The structural analysis has also given clues to the interaction of p21 with the regulatory proteins GAP (GTPase Activating Protein) and nucleotide exchange factor. The three-dimensional structures of oncogenic mutants of p21 have also been determined and can nicely explain different biochemical and biological behaviour of these mutant proteins.