gebhart/patrepeval huggingface dataset:
Prediction of pharmacokinetics of CS-023 (RO4908463), a novel parenteral carbapenem antibiotic, in humans using animal data (2006)

The pharmacokinetics of CS-023 (RO4908463, formerly R-115685), a novel parenteral carbapenem antibiotic, in humans was successfully predicted using the data collected from mice, rats, rabbits, and dogs; while inclusion of the monkey data led to a significant underestimation of the total plasma clearance (CL). Double logarithmic plots of CL and distribution volume at the steady-state (Vss) vs. body weight in four animal species were linear with high correlation coefficients; and the predicted CL and Vss values in humans agreed well with the observed values after administration of CS-023 by an intravenous drip infusion for 30 min. The plasma concentration-time profile in humans, which was predicted using a bi-exponential equation fitted to a complex Dedrick plot of the animal data, approximated the observed profile. An underestimation of CL caused by including the monkey data in a prediction is quite likely due to the net tubular reabsorption in monkeys, but not at least in rabbits, dogs, and humans.
Efficient FPGA-based ECDSA Verification Engine for Permissioned Blockchains (2021)

As enterprises embrace blockchain technology, many real-world applications have been developed and deployed using permissioned blockchain platforms (access to network is controlled and given to only nodes with known identities). Such blockchain platforms heavily depend on cryptography to provide a layer of trust within the network, thus verification of cryptographic signatures often becomes the bottleneck. The Elliptic Curve Digital Signature Algorithm (ECDSA) is the most commonly used cryptographic scheme in permissioned blockchains. In this paper, we propose an efficient implementation of ECDSA signature verification on an FPGA, in order to improve the performance of permissioned blockchains that aim to use FPGA-based hardware accelerators. We propose several optimizations for modular arithmetic (e.g., custom multipliers and fast modular reduction) and point arithmetic (e.g., reduced number of point double and addition operations, and optimal width NAF representation). Based on these optimized modular and point arithmetic modules, we propose an ECDSA verification engine that can be used by any application for fast verification of ECDSA signatures. We further optimize our ECDSA verification engine for Hyperledger Fabric (one of the most widely used permissioned blockchain platforms) by moving carefully selected operations to a precomputation block, thus simplifying the critical path of ECDSA signature verification. From our implementation on Xilinx Alveo U250 accelerator board with target frequency of 250MHz, our ECDSA verification engine can perform a single verification in $760μs$ resulting in a throughput of 1,315 verifications per second, which is ~2.5x faster than state-of-the-art FPGA-based implementations. Our Hyperledger Fabric-specific ECDSA engine can perform a single verification in $368μs$ with a throughput of 2,717 verifications per second.
Depression Reduces Accuracy While Parkinsonism Slows Response Time for Processing Positive Feedback in Patients with Parkinson’s Disease with Comorbid Major Depressive Disorder Tested on a Probabilistic Category-Learning Task (2017)

Major depressive disorder (MDD) is the most common non-motor manifestation of Parkinson's disease (PD) affecting 50% of patients. However, little is known about the cognitive correlates of MDD in PD. Using a computer-based cognitive task that dissociates learning from positive and negative feedback, we tested four groups of subjects: (1) patients with PD with comorbid MDD, (2) patients with PD without comorbid MDD, (3) matched patients with MDD alone (without PD), and (4) matched healthy control subjects. Furthermore, we used a mathematical model of decision-making to fit both choice and response time data, allowing us to detect and characterize differences between the groups that are not revealed by cognitive results. The groups did not differ in learning accuracy from negative feedback, but the MDD groups (PD patients with MDD and patients with MDD alone) exhibited a selective impairment in learning accuracy from positive feedback when compared to the non-MDD groups (PD patients without MDD and healthy subjects). However, response time in positive feedback trials in the PD groups (both with and without MDD) was significantly slower than the non-PD groups (MDD and healthy groups). While faster response time usually correlates with poor learning accuracy, it was paradoxical in PD groups, with PD patients with MDD having impaired learning accuracy and PD patients without MDD having intact learning accuracy. Mathematical modeling showed that both MDD groups (PD with MDD and MDD alone) were significantly slower than non-MDD groups in the rate of accumulation of information for stimuli trained by positive feedback, which can lead to lower response accuracy. Conversely, modeling revealed that both PD groups (PD with MDD and PD alone) required more evidence than other groups to make responses, thus leading to slower response times. These results suggest that PD patients with MDD exhibit cognitive profiles with mixed traits characteristic of both MDD and PD, furthering our understanding of both PD and MDD and their often-complex comorbidity. To the best of our knowledge, this is the first study to examine feedback-based learning in PD with MDD while controlling for the effects of PD and MDD.
Autonomous bioluminescent systems: prospects for use in the imaging of living organisms (2019)

Bioluminescent systems are increasingly being used for the development of highly sensitive optical imaging techniques in vivo. However, it is necessary to inject expensive and unstable synthetic substrates (luciferins) before each analysis for most of the systems applied. Autonomous bacterial and fungal bioluminescent systems, that recently have become available for implementation in eukaryotic cells, in our opinion, may be developed into an effective tool in new technologies of bioluminescent imaging.
Investigation of a high-power CO/sub 2/ convection laser. Summary technical report, 17 April 1970-30 January 1972 (1972)

A research investigation was performed to investigate a high-power, closed-cycle CO/sub 2/ cross-beam electric-discharge convection laser (EDCL). In the cross-beam EDCL, the electric discharge is aligned with the flow and laser output power is extracted transverse to the flow. Based upon results of cross-beam EDCLscaling studies, a laser amplifier channel capable of amplifying an optical input of 100 watts to 25 kW was designed and fabricated. Techniques of continuously processing the laser gases were also investigated. The pulse amplification characteristics of the amplifier with a continuously operating discharge were also investigated analytically and experimentally.
ChemInform Abstract: Calothrixins A (I) and B (II), Novel Pentacyclic Metabolites from Calothrix Cyanobacteria with Potent Activity Against Malaria Parasites and Human Cancer Cells (2000)

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.
Respiratory motion estimation from slowly rotating x‐ray projections: Theory and simulation (2005)

Understanding the movement of tumors caused by respiratory motion is very important for conformal radiatherapy. However, respiratory motion is very difficult to study by conventional x-ray CT imaging since object motion causes inconsistent projection views, leading to artifacts in reconstructed images. We propose to estimate the parameters of a nonrigid, free breathing motion model from a set of projection views of the thorax that are acquired using a slowly rotating cone-beam CT scanner. This approach involves deforming a motion-free reference thorax volume according to the estimated parameters and comparing its projections to the corresponding measured projection views. The parameters are optimized by minimizing a regularized squared error cost function. Simulation results with a fan-beam geometry show good agreement between the estimated motion and the true motion, which supports the potential of this approach for estimating four-dimensional (three-dimensional spatial + temporal) respiratory motion.
The role of EDEM2 compared with EDEM1 in ricin transport from the endoplasmic reticulum to the cytosol (2013)

EDEM1 [ER (endoplasmic reticulum)-degradation-enhancing α-mannosidase I-like protein 1] and EDEM2 are crucial regulators of ERAD (ER-associated degradation) that extracts non-native glycoproteins from the calnexin chaperone system. Ricin is a potent plant cytotoxin composed of an A-chain (RTA) connected by a disulfide bond to a cell-binding lectin B-chain (RTB). After endocytic uptake, the toxin is transported retrogradely to the ER, where the enzymatically active RTA is translocated to the cytosol in a similar manner as misfolded ER proteins. This transport is promoted by EDEM1. In the present study we report that EDEM2 is also involved in ricin retrotranslocation out of the ER. However, the role of EDEM1 and EDEM2 in ricin transport to the cytosol seems to differ. EDEM2 promotes ricin retrotranslocation irrespectively of ER translocon accessibility; moreover, co-immunoprecipitation and pull-down studies revealed that more ricin can interact with EDEM2 in comparison with EDEM1. On the other hand, interactions of both lectins with RTA are dependent on the structure of the RTA. Thus our data display a newly discovered role for EDEM2. Moreover, analysis of the involvement of EDEM1 and EDEM2 in ricin retrotranslocation to the cytosol may provide crucial information about general mechanisms of the recognition of ERAD substrates in the ER.
THE EFFECTS OF IMPACT ON THE CORAIDETM VENTRICULAR ASSIST DEVICE (2001)

Controlled drop testing was performed on the CorAideTM ventricular assist device to examine the effects of impact on hydraulic and vibrational performance, magnetic properties, and durability. Signals for acceleration in the X, Y, and Z directions, pump speed, and current were acquired using PowerLab® data acquisition system. In order to assess the effects of impact, three different situations were tested. The first involved dropping a non-operating pump assembly onto a hardwood surface from 3.25 feet. The second and third tests were performed from 4 feet and 15 feet, while the CorAideTM pump was operating in a mock circulatory loop containing blood-analog solution. The boxed pump and mock circulatory loop were dropped onto padding in three different orientations, causing loading in the following directions: radial direction, axial direction towards the secondary impeller, and axial direction towards the primary impeller. The padding thickness was adjusted and the height of 15 feet was selected such that the total impact duration and velocity were comparable with chest accelerations from published automotive test data for survivable crashes. In vitro hydraulic and vibrational performance testing and visual inspection for mechanical defects were completed before and after each test. Magnet strength of the rotating assembly was evaluated prior to the first drop and after the third set of drops. There were no changes in pump performance or magnet strength, and no pump component damage resulted from the testing.Table
Li4Ti5O12 Anode: Structural Design from Material to Electrode and the Construction of Energy Storage Devices (2017)

Spinel Li<sub>4</sub> Ti<sub>5</sub> O<sub>12</sub> , known as a zero-strain material, is capable to be a competent anode material for promising applications in state-of-art electrochemical energy storage devices (EESDs). Compared with commercial graphite, spinel Li<sub>4</sub> Ti<sub>5</sub> O<sub>12</sub> offers a high operating potential of ∼1.55 V vs Li/Li<sup>+</sup> , negligible volume expansion during Li<sup>+</sup> intercalation process and excellent thermal stability, leading to high safety and favorable cyclability. Despite the merits of Li<sub>4</sub> Ti<sub>5</sub> O<sub>12</sub> been presented, there still remains the issue of Li<sub>4</sub> Ti<sub>5</sub> O<sub>12</sub> suffering from poor electronic conductivity, manifesting disadvantageous rate performance. Typically, a material modification process of Li<sub>4</sub> Ti<sub>5</sub> O<sub>12</sub> will be proposed to overcome such an issue. However, the previous reports have made few investigations and achievements to analyze the subsequent processes after a material modification process. In this review, we attempt to put considerable interest in complete device design and assembly process with its material structure design (or modification process), electrode structure design and device construction design. Moreover, we have systematically concluded a series of representative design schemes, which can be divided into three major categories involving: (1) nanostructures design, conductive material coating process and doping process on material level; (2) self-supporting or flexible electrode structure design on electrode level; (3) rational assembling of lithium ion full cell or lithium ion capacitor on device level. We believe that these rational designs can give an advanced performance for Li<sub>4</sub> Ti<sub>5</sub> O<sub>12</sub> -based energy storage device and deliver a deep inspiration.
Adaptive Behavior Cloning Regularization for Stable Offline-to-Online Reinforcement Learning (2022)

Offline reinforcement learning, by learning from a fixed dataset, makes it possible to learn agent behaviors without interacting with the environment. However, depending on the quality of the offline dataset, such pre-trained agents may have limited performance and would further need to be fine-tuned online by interacting with the environment. During online fine-tuning, the performance of the pre-trained agent may collapse quickly due to the sudden distribution shift from offline to online data. While constraints enforced by offline RL methods such as a behaviour cloning loss prevent this to an extent, these constraints also significantly slow down online fine-tuning by forcing the agent to stay close to the behavior policy. We propose to adaptively weigh the behavior cloning loss during online fine-tuning based on the agent's performance and training stability. Moreover, we use a randomized ensemble of Q functions to further increase the sample efficiency of online fine-tuning by performing a large number of learning updates. Experiments show that the proposed method yields state-of-the-art offline-to-online reinforcement learning performance on the popular D4RL benchmark. Code is available: \url{https://github.com/zhaoyi11/adaptive_bc}.
Criticality of Configuration Bits in SRAM-based FPGAs: Predictive Analysis and Experimental Results (2011)

International audience
Sticky and slippery collision avoidance for tele-excavation (2002)

Two new modes of real-time collision avoidance are presented which aid in the effectiveness of remote tele-operation. Sticky collision mode improves system safety by disallowing contact with modelled obstacles. Slippery mode is used do improve the efficiency of the process by reducing the required level of operator skill. Both modes execute in real-time and have been implemented and tested on a remote excavator system. It was found that precise geometries could be excavated using extremely simplified cutting strategies that required very little fine control on the part of the operator, thereby improving the effectiveness of remote tele-excavation.
Une mutation de c-kit dans des mastocytoses systémiques avec « désordres hématologiques » (1996)

Les mastocytoses systemiques forment un groupe heterogene de pathologies caracterisees par une proliferation anormale pluritissulaire (peau, moelle hematopoietique, os, etc.) de cellules mastocytaires [1]. Les cellules mastocytaires normales ou pathologiques expriment le recepteur c-kit (ou kitR) et proliferent apres exposition a son ligand, le facteur [...]
Accurate Retinal Vessel Segmentation via Octave Convolution Neural Network (2019)

Retinal vessel segmentation is a crucial step in diagnosing and screening various diseases, including diabetes, ophthalmologic diseases, and cardiovascular diseases. In this paper, we propose an effective and efficient method for vessel segmentation in color fundus images using encoder-decoder based octave convolution networks. Compared with other convolution networks utilizing standard convolution for feature extraction, the proposed method utilizes octave convolutions and octave transposed convolutions for learning multiple-spatial-frequency features, thus can better capture retinal vasculatures with varying sizes and shapes. To provide the network the capability of learning how to decode multifrequency features, we extend octave convolution and propose a new operation named octave transposed convolution. A novel architecture of convolutional neural network, named as Octave UNet integrating both octave convolutions and octave transposed convolutions is proposed based on the encoder-decoder architecture of UNet, which can generate high resolution vessel segmentation in one single forward feeding without post-processing steps. Comprehensive experimental results demonstrate that the proposed Octave UNet outperforms the baseline UNet achieving better or comparable performance to the state-of-the-art methods with fast processing speed. Specifically, the proposed method achieves 0.9664 / 0.9713 / 0.9759 / 0.9698 accuracy, 0.8374 / 0.8664 / 0.8670 / 0.8076 sensitivity, 0.9790 / 0.9798 / 0.9840 / 0.9831 specificity, 0.8127 / 0.8191 / 0.8313 / 0.7963 F1 score, and 0.9835 / 0.9875 / 0.9905 / 0.9845 Area Under Receiver Operating Characteristic curve, on DRIVE, STARE, CHASE_DB1, and HRF datasets, respectively.
Knowledge management based human capital development improves higher educational institutes' performance (2021)

The purpose of this study is to know whether knowledge management based human capital development improves Higher Educational Institutions Performance. The need of knowledge, creation of knowledge, storage of knowledge and sharing of knowledge have been used as the dimensions of knowledge management. Data is collected by using 5 points Likert scale questionnaire from 221 teachers working in Higher Educational Institutions of Pakistan. The results suggested that knowledge management based human capital development partially improves Higher Educational Institutions Performance. The study also suggests that the creation of knowledge, storage of knowledge and sharing of knowledge improve human capital while the need of knowledge has no influence on human capital. The managerial implication and limitations of this study are also discussed.
Fast is better than free: Revisiting adversarial training (2020)

Adversarial training, a method for learning robust deep networks, is typically assumed to be more expensive than traditional training due to the necessity of constructing adversarial examples via a first-order method like projected gradient decent (PGD). In this paper, we make the surprising discovery that it is possible to train empirically robust models using a much weaker and cheaper adversary, an approach that was previously believed to be ineffective, rendering the method no more costly than standard training in practice. Specifically, we show that adversarial training with the fast gradient sign method (FGSM), when combined with random initialization, is as effective as PGD-based training but has significantly lower cost. Furthermore we show that FGSM adversarial training can be further accelerated by using standard techniques for efficient training of deep networks, allowing us to learn a robust CIFAR10 classifier with 45% robust accuracy to PGD attacks with $\epsilon=8/255$ in 6 minutes, and a robust ImageNet classifier with 43% robust accuracy at $\epsilon=2/255$ in 12 hours, in comparison to past work based on free adversarial training which took 10 and 50 hours to reach the same respective thresholds. Finally, we identify a failure mode referred to as catastrophic overfitting which may have caused previous attempts to use FGSM adversarial training to fail. All code for reproducing the experiments in this paper as well as pretrained model weights are at this https URL.
Coronary Plaque Characteristics and Cut-Off Stenosis for Developing Spasm in Patients with Vasospastic Angina (2020)

Coronary plaque distribution, frequency and cut-off value of percent stenosis for developing vasospasm are uncertain in patients with vasospastic angina (VA). We enrolled 2960 patients who received coronary angiography (CAG) and ergonovine provocation test prospectively in 11 university hospitals in Korea. A total of 1836 patients with VA and 867 without VA were included. Plaque and % stenosis were defined as ≥1% luminal narrowing and mean of each segmental stenosis. Overall frequency of plaque and % diameter stenosis was compared among VA-patients with index coronary spasm positive, those with index arterial spasm negative/other arterial spasm positive (INOP) and non-VA patients. Diameter stenosis associated with the spasm positivity was investigated. Overall plaque frequency and % stenosis were higher in VA patients than non-VA patients. Plaque frequency was 27.6% (243/881) in spasm positive at LAD, 16.4% (157/955) in LAD INOP and 12.6% (109/867) in non-VA with statistic difference (P < 0.001). Same trend for higher rate was observed in LCx and RCA. For % stenosis, 36.6 vs 32.4% (p = 0.010) in LAD, 36.1 vs. 28% (p < 0.001) in LCx and 35.3 vs.30.0% (p = 0.047) in RCA, respectively. Diameter stenosis of LAD with spasm positive vs. LAD INOP vs. non-VA were 38.3%, 34.0%, 32% (P = 0.002) with similar pattern in LCx and RCA. By multivariate logistic regression analysis, coronary stenosis of LAD ≥ 35% or LCx ≥35% or RCA ≥ 40% were independent predictor of developing spasm (OR 2.019, 95% CI 1.315-3.100, P = 0.001). In conclusions, spastic coronary artery had more plaque frequency, higher % stenosis than in non-spastic coronary in VA patients. The spasm related and unrelated coronary in VA patients had more plaque than in matched and unmatched coronary arteries in non-VA patients. Coronary stenosis ≥35% in LAD and LCx was an independent predictor of developing spasm.
JENDL-4.0: A New Library for Nuclear Science and Engineering (2011)

Abstract The fourth version of the Japanese Evaluated Nuclear Data Library has been produced in cooperation with the Japanese Nuclear Data Committee. In the new library, much emphasis is placed on the improvements of fission product and minor actinoid data. Two nuclear model codes were developed in order to evaluate the cross sections of fission products and minor actinoids. Coupled-channel optical model parameters, which can be applied to wide mass and energy regions, were obtained for nuclear model calculations. Thermal cross sections of actinoids were carefully examined by considering experimental data or by the systematics of neighboring nuclei. Most of the fission cross sections were derived from experimental data. A simultaneous evaluation was performed for the fission cross sections of important uranium and plutonium isotopes above 10 keV. New evaluations were performed for the thirty fissionproduct nuclides that had not been contained in the previous library JENDL-3.3. The data for light elements and structural materials were partly reevaluated. Moreover, covariances were estimated mainly for actinoids. The new library was released as JENDL-4.0, and the data can be retrieved from the Web site of the JAEA Nuclear Data Center. KEYWORDS: JENDL-4.0nuclear dataevaluationcross sectionnuclear model calculationexperimental dataactinoidfission productlight elementstructural material