gebhart/patrepeval huggingface dataset:
Autodisplay of Nitrilase from <i>Alcaligenes faecalis</i> in <i>E. coli</i> Yields a Whole Cell Biocatalyst for the Synthesis of Enantiomerically Pure (<i>R</i>)‐Mandelic Acid (2011)

Abstract In the present study, a whole cell biocatalyst for the synthesis of ( R )‐mandelic acid from mandelonitrile was constructed. For this purpose, nitrilase from Alcaligenes faecalis subsp. faecalis ATCC 8750 was displayed on the surface of Escherichia coli by using Autodisplay. Localization of the nitrilase in the cell envelope of E. coli was monitored by SDS‐PAGE and surface exposure was verified by its accessibility to externally added protease. The whole cell biocatalyst converted up to 2.6 m M of ( R )‐mandelic acid under optimum conditions at pH 7.5 and 45 °C within 24 h (1 mL culture, OD 578 =10). By using chiral HPLC, the ee value of the product was determined to be &gt;99 %. The surface displayed nitrilase showed an apparent K m value of 3.6 m M and an apparent V max value of 1 nmol min −1 mL −1 when a bacterial suspension of OD 578 3 was used. Substrate inhibition by benzaldehyde was similar to that of the free enzyme. The whole‐cell biocatalyst retained 55 % of its initial ( R )‐mandelic acid production after 5 cycles of repeated use, and could be stored at −70 °C for 180 d without a substantial loss of activity. In addition the whole cell biocatalyst converted 9.3 m M phenylacetonitrile within 16 h.
Digital In-Line Holographic Microscopy in 4-D (2010)

Digital in-line Holography with spherical waves has been developed into a new microscopy for microfluidic, biological and marine applications, that routinely achieves both lateral and depth resolution at the submicron level in 4-D imaging.
Robust robotic visual servoing for uncertain systems (2021)

The control of robotic manipulators in unstructured environments is a challenging task. Exploiting the camera images for that purpose, known as visual servoing, offers an interesting solution to the problem. Classic visual servoing techniques were the first attempts towards this goal. However, these methods suffered from system’s shortcomings such as ones imposed by the limited camera’s field of view and the robot’s reachability. Numerous approaches were proposed to overcome these limitations. Nevertheless, most of these techniques assumed full knowledge about the system and did not account for uncertainties. Uncertainties in visual servoing systems are introduced by multiple sources such as camera image noise and robot parameters. The lack of knowledge about system’s parameters may lead to reduced accuracy or even total failure. Adaptive techniques were introduced previously to cope with this matter. However, those techniques were usually useful for deterministic uncertainties (e.g., camera calibration errors). Alternately, robust methods were employed to improve the performance of the system under uncertainties. Yet, those methods were usually conservative and more concerned with the stability of the system, rather than its accuracy. This work proposes three steps towards robust and accurate visual servoing. First, the pose estimation algorithm, used in many visual servoing systems, is revised by introducing novel sensor fusion techniques. Multiple fusion algorithms at different levels of estimation are introduced to enhance the accuracy and robustness of the estimation against system uncertainties. Second, a novel uncertainty estimation technique is presented to approximate the level of uncertainties induced by image noise at different levels of the system. A general approach is used for that matter which has applicability over a wide range of controllers. Finally, multiple constraint-aware and robust controllers with improved stability and numerical feasibility are proposed to enhance the performance of the visual servoing systems in presence of uncertainties. The developed uncertainty model is exploited in robust control design. The effectiveness of each proposed technique is verified through numerous simulations and experiments. As it is expected, the proposed methods are capable of handling the uncertainties and enhancing the accuracy, while accounting for system constraints.
Visualizing and Communicating Errors in Rendered Images (2021)

In rendering research and development, it is important to have a formalized way of visualizing and communicating how and where errors occur when rendering with a given algorithm. Such evaluation is often done by comparing the test image to a ground-truth reference image. We present a tool for doing this for both low and high dynamic range images. Our tool is based on a perception-motivated error metric, which computes an error map image. For high dynamic range images, it also computes a visualization of the exposures that may generate large errors.
Papillary Thyroid Carcinoma With Heterotopic Ossification Is a Special Subtype With Extensive Progression (2013)

An immunohistochemical study was conducted of 108 papillary carcinoma cases, including 48 cases with intratumoral heterotopic ossification (IHO). In 48 cases, papillary carcinoma with IHO was accompanied by nodular fibrosis. Cases of papillary carcinoma with IHO or nodular fibrosis showed higher incidences of lymph node metastasis, multifocal lesions, and extrathyroidal invasion than those without IHO and nodular fibrosis. A higher number of stromal myofibroblasts was observed in papillary carcinoma with IHO or nodular fibrosis than in that without fibrosis. Expression of both basic fibroblast growth factor (bFGF) and bone morphogenetic protein (BMP)-2 was the highest in papillary carcinoma with IHO. Papillary carcinoma with IHO showed higher vascular invasion and higher numbers of capillaries expressing nestin, which is associated with high expression of vascular endothelial growth factor (VEGF). Papillary carcinoma with IHO is a unique subtype with extensive progression including frequent lymph node metastasis, multifocality, and invasive behavior. Papillary carcinoma with IHO was correlated with expression of bFGF, BMP-2, and VEGF in the carcinoma cells, leading to neovascularization.
A First-Principles Study of Oxygenates on Co Surfaces in Fischer−Tropsch Synthesis (2008)

Extensive density function theory calculations are performed to study the mechanism of the formation of aldehyde and alcohol on Co surfaces in Fischer−Tropsch synthesis, a challenging issue in heterogeneous catalysis. Three possible pathways for the production of formaldehyde and methanol on flat and stepped Co(0001) surfaces are investigated: (i) CO + 4H → CHO + 3H → CH2O + 2H → CH3O + H → CH3OH; (ii) CO + 4H → COH + 3H → CHOH + 2H → CH2OH + H → CH3OH; and (iii) the coupling reactions of CH2 + O → CH2O and CH3 + OH → CH3OH. It is found that these pathways are generally favored at step sites, and the preferred mechanism is pathway (i) via CHO. Furthermore, the three traditional chain growth mechanisms in Fischer−Tropsch synthesis are semiquantitatively compared and discussed. Our results suggest that the two mechanisms involving oxygenate intermediates (the CO-insertion and hydroxycarbene mechanisms) are less important than the carbene mechanism in the production of long chain hydrocarbons. However, the CO-insertion mechanism may be responsible for the production of long-chain oxygenates.
Toward OAM-selective frequency conversion in a three-mode fiber (2021)

We describe OAM-compatible mode-selective frequency conversion in a few-mode fiber and experimentally demonstrate downconversion of various superpositions of signal modes LP11a and LP11b to the same LP11b mode with conversion efficiency differences &lt;0.8 dB.
MC-CIM: Compute-in-Memory with Monte-Carlo Dropouts for Bayesian Edge Intelligence (2021)

We propose MC-CIM, a compute-in-memory (CIM) framework for robust, yet low power, Bayesian edge intelligence. Deep neural networks (DNN) with deterministic weights cannot express their prediction uncertainties, thereby pose critical risks for applications where the consequences of mispredictions are fatal such as surgical robotics. To address this limitation, Bayesian inference of a DNN has gained attention. Using Bayesian inference, not only the prediction itself, but the prediction confidence can also be extracted for planning risk-aware actions. However, Bayesian inference of a DNN is computationally expensive, ill-suited for real-time and/or edge deployment. An approximation to Bayesian DNN using Monte Carlo Dropout (MC-Dropout) has shown high robustness along with low computational complexity. Enhancing the computational efficiency of the method, we discuss a novel CIM module that can perform in-memory probabilistic dropout in addition to in-memory weight-input scalar product to support the method. We also propose a compute-reuse reformulation of MC-Dropout where each successive instance can utilize the product-sum computations from the previous iteration. Even more, we discuss how the random instances can be optimally ordered to minimize the overall MC-Dropout workload by exploiting combinatorial optimization methods. Application of the proposed CIM-based MC-Dropout execution is discussed for MNIST character recognition and visual odometry (VO) of autonomous drones. The framework reliably gives prediction confidence amidst non-idealities imposed by MC-CIM to a good extent. Proposed MC-CIM with 16x31 SRAM array, 0.85 V supply, 16nm low-standby power (LSTP) technology consumes 27.8 pJ for 30 MC-Dropout instances of probabilistic inference in its most optimal computing and peripheral configuration, saving 43% energy compared to typical execution.
Differential Regulation of the Surface-Exposed and Secreted SslE Lipoprotein in Extraintestinal Pathogenic Escherichia coli (2016)

Extra-intestinal pathogenic Escherichia coli (ExPEC) are responsible for diverse infections including meningitis, sepsis and urinary tract infections. The alarming rise in anti-microbial resistance amongst ExPEC complicates treatment and has highlighted the need for alternative preventive measures. SslE is a lipoprotein secreted by a dedicated type II secretion system in E. coli that was first identified as a potential vaccine candidate using reverse genetics. Although the function and protective efficacy of SslE has been studied, the molecular mechanisms that regulate SslE expression remain to be fully elucidated. Here, we show that while the expression of SslE can be detected in E. coli culture supernatants, different strains express and secrete different amounts of SslE when grown under the same conditions. While the histone-like transcriptional regulator H-NS strongly represses sslE at ambient temperatures, the variation in SslE expression at human physiological temperature suggested a more complex mode of regulation. Using a genetic screen to identify novel regulators of sslE in the high SslE-expressing strain UTI89, we defined a new role for the nucleoid-associated regulator Fis and the ribosome-binding GTPase TypA as positive regulators of sslE transcription. We also showed that Fis-mediated enhancement of sslE transcription is dependent on a putative Fis-binding sequence located upstream of the -35 sequence in the core promoter element, and provide evidence to suggest that Fis may work in complex with H-NS to control SslE expression. Overall, this study has defined a new mechanism for sslE regulation and increases our understanding of this broadly conserved E. coli vaccine antigen.
CMC packing in functional endoscopic sinus surgery: does it affect patient comfort? (2009)

Based on the presented data concerning patient comfort, CMC appears to be an ideal packing material following FESS. However, there is no other study revealing an identical study design focusing on other resorbable packing material. As a consequence, other available resorbable packing material should be investigated to find the ideal packing material following FESS, if packing is required.
A fuzzy logic approach to assembly line balancing (2005)

This paper deals with the use of fuzzy set theory as a viable alternative method for modelling and solving the stochastic assembly line balancing problem. Variability and uncertainty in the assembly line balancing problem has traditionally been modelled through the use of statistical distributions. This may not be feasible in cases where no historical data exists. Fuzzy set theory allows for the consideration of the ambiguity involved in assigning processing and cycle times and the uncertainty contained within such time variables. Two widely used line balancing methods, the COMSOAL and Ranked Positional Weighting Technique, were modified to solve the balancing problem with a fuzzy representation of the time variables. The paper shows that the new fuzzy methods are capable of producing solutions similar to, and in some cases better than, those reached by the traditional methods.
Tuftsin-AZT conjugate: potential macrophage targeting for AIDS therapy (2004)

The IgG-derived immunomodulating peptide tuftsin, Thr-Lys-Pro-Arg, is recognized by specific receptors on phagocytic cells, notably macrophages, and is capable of targeting proteins and peptides to these sites. Aiming to target 3'-azido-3'-deoxythymidine (AZT) to HIV-infected macrophages, a conjugate of AZT with tuftsin was synthesized. The AZT-tuftsin chimera possesses the characteristic capacities of its two components. Thus, like AZT, it inhibits reverse transcriptase activity and HIV-antigen expression, and similarly to tuftsin, it stimulates IL-1 release from mouse macrophages and augments the immunogenic function of the cells. Importantly, the conjugate is not cytotoxic to T-cells. The results suggest that the AZT-tuftsin conjugate might have potential use in AIDS therapy.
Cryogenic micro-calorimeters for mass spectrometry of keV neutral atoms and molecules (2015)

We demonstrate the capability of micro-calorimeters to detect and mass-resolve neutral atoms and molecules at ∼ keV energies, reaching single H-atom resolution.
Development of antisense RNA-mediated quantifiable inhibition for metabolic regulation (2021)

Trans-regulating elements such as noncoding RNAs are crucial in modifying cells, and has shown broad application in synthetic biology, metabolic engineering and RNA therapies. Although effective, titration of the regulatory levels of such elements is less explored. Encouraged by the need of fine-tuning cellular functions, we studied key parameters of the antisense RNA design including oligonucleotide length, targeting region and relative dosage to achieve differentiated inhibition. We determined a 30-nucleotide configuration that renders efficient and robust inhibition. We found that by targeting the core RBS region proportionally, quantifiable inhibition levels can be rationally obtained. A mathematic model was established accordingly with refined energy terms and successfully validated by depicting the inhibition levels for genomic targets. Additionally, we applied this fine-tuning approach for 4-hydroxycoumarin biosynthesis by simultaneous and quantifiable knockdown of multiple targets, resulting in a 3.58-fold increase in titer of the engineered strain comparing to that of the non-regulated. We believe the developed tool is broadly compatible and provides an extra layer of control in modifying living systems.
Power Allocation for Orthogonal Multiple Access Relay Channel Allowing Intra-link Errors (2016)

Power and rate allocation is theoretically analyzed for an orthogonal multiple-access relay channel (MARC), where lossy transmissions are allowed in the source-relay links and the erroneous estimates are forwarded from the relay to the destination. Conventional decode-and-forward (DF) strategy forwards only correctly received estimates and discards the erroneous. However, even the erroneous estimates can be utilized at the destination in order to improve the reliability of the received information sequences sent from source nodes. In this paper, minimum power and maximum rate problems for the MARC system with lossy relaying are formulated and the resulting nonconvex problems are solved via successive convex approximation (SCA). Numerical results show that the system allowing erroneous relaying is superior in terms of the considered objectives compared to the lossless DF.
Rapid determination of the binding affinity and specificity of the mushroom Polyporus squamosus lectin using frontal affinity chromatography coupled to electrospray mass spectrometry (2001)

The binding affinity and specificity of the mushroom Polyporus squamosus lectin has been determined by the recently developed method of frontal affinity chromatography coupled to electrospray mass spectrometry (FAC/MS). A micro-scale affinity column was prepared by immobilizing the lectin ( approximately 25 microg) onto porous glass beads in a tubing column (9.8 microl column volume). The column was then used to screen several oligosaccharide mixtures. The dissociation constants of 22 sialylated or sulfated oligosaccharides were evaluated against the immobilized lectin. The lectin was found to be highly specific for Neu5Acalpha2-6Galbeta1-4Glc/GlcNAc containing oligosaccharides with K(d) values near 10 microM. The FAC/MS assay permits the rapid determination of the dissociation constants of ligands as well as a higher throughput screening of compound mixtures, making it a valuable tool for affinity studies, especially for testing large numbers of compounds.
Memristors in the electrical network of<i>Aloe vera</i>L. (2014)

A memristor is a resistor with memory, which is a non-linear passive two-terminal electrical element relating magnetic flux linkage and electrical charge. Here we found that memristors exist in vivo. The electrostimulation of the Aloe vera by bipolar sinusoidal or triangle periodic waves induce electrical responses with fingerprints of memristors. Uncouplers carbonylcyanide-3-chlorophenylhydrazone and carbonylcyanide-4-trifluoromethoxy-phenyl hydrazone decrease the amplitude of electrical responses at low and high frequencies of bipolar periodic sinusoidal or triangle electrostimulating waves. Memristive behavior of an electrical network in the Aloe vera is linked to the properties of voltage gated ion channels: the K(+) channel blocker TEACl reduces the electric response to a conventional resistor. Our results demonstrate that a voltage gated K(+) channel in the excitable tissue of plants has properties of a memristor. The discovery of memristors in plants creates a new direction in the modeling and understanding of electrical phenomena in plants.
Quality costing of an administrative process (1998)

The purpose of this paper is to describe a methodology for measuring “cost of poor quality” within an administrative process. The methodology provides primarily a process analysis tool, but it can also be used as a quality measurement technique and a platform for activity based costing. The methodology was developed in the Scottish Legal Aid Board ‐ a non‐departmental public body ‐ addressing the key administrative process of invoice payment. An initial pilot study was enlarged into a full evaluation which combined the quantification of “quality costs” using a novel cost model with the identification of process weaknesses as part of the “analysis” phase of a new computer system development. The paper addresses some of the general practical considerations in launching cost of poor quality measurement schemes.
Data Fusion and Filtering Techniques (2017)

This chapter presents two major approaches of data fusion: the least squares (LS) approach and the Bayesian framework. The LS approach is an algorithm that estimates the position of a mobile station (MS) by minimizing the squared error between the actual measurements observed in the wireless channel and the expected measurements resulting from the estimated position. In the Bayesian framework, the position is determined as an estimator that minimizes the mean square error between the actual measurements and the expected measurements. The chapter also provides three major implementations of the Bayesian framework: the Kalman filter (KF), the particle filter (PF) and grid-based methods. The KF is a group of methods that assumes the measurements to be corrupted by white Gaussian noise, the PF is a Monte Carlo type of algorithm that does not constrain the noise component of the Gaussian distribution, and the grid-based methods assume that the state space is discrete and finite.
Blood Freezing to Nearly Absolute Zero Temperature: −272.29°C (1981)

Human erythrocytes were collected in ACD anticoagulant, glycerolized with an equal volume of 8.6 M glycerol, 8 percent glucose, 1 percent fructose, and 0.3 percent Na2 EDTA solution, sealed in glass ampules, and frozen to -272.29 degrees C (0.86 degrees K) in liquid helium under high vacuum. Biological assays performed after thawing and three-stage dialysis to remove the glycerol showed less than 1 percent hemolysis. Intracellular potassium, 2,3 DPG, and ATP were within the normal range.
Identification and structural characterization of novel <i>O</i>‐ and <i>N</i>‐glycoforms in the urine of a Schindler disease patient by Orbitrap mass spectrometry (2015)

Schindler disease is an inherited metabolic disorder caused by the deficient activity of α-N-acetylgalactosaminidase enzyme. An accurate diagnosis requires, besides clinical examination, complex and costly biochemical and molecular genetic tests. In the last years, mass spectrometry (MS) based on nanofluidics and high-resolution instruments has become a successful alternative for disease diagnosis based on the investigation of O-glycopeptides in patient urine. A complex mixture of glycoforms extracted from the urine of a 3-year-old patient was investigated by Orbitrap MS equipped with Nanospray Flex Ion Source in the negative ion mode. For structural characterization of several molecular species, collision-induced dissociation MS<sup>2</sup> -MS<sup>3</sup> was carried out using collision energy values within 20-60 eV range. By our approach, 39 novel species associated to this condition were identified, among which O-glycopeptides, free O-glycans and one structure corresponding to an N-glycan never characterized in the context of Schindler disease. The experiments conducted at a resolution of 60 000 allowed the discrimination and identification of a total number of 69 different species with an average mass accuracy of 9.87 ppm, an in-run reproducibility of almost 100%, an experiment-to-experiment and day-to-day reproducibility of about 95%. This study brings contributions in the diagnosis of Schindler disease through the elucidation of potential biomarker species in urine. Our multistage MS results completed with 39 new glycoforms the inventory of potential biomarker structures associated to Schindler disease. For the first time, an N-glycan was identified and structurally characterized in Schindler patient urine, which opens new research directions in the field. Copyright © 2015 John Wiley & Sons, Ltd.
Biomechanical Evaluation of the Pedicle Screw Insertion Depth Effect on Screw Stability Under Cyclic Loading and Subsequent Pullout (2014)

Although increased screw depth led to increased fixation and decreased loosening, additional purchase of the stiff anterior cortex is essential to reach superior screw-bone construct stability and stiffness.