gebhart/patrepeval huggingface dataset:
Molecular Engineering of Somatostatin Analogue with Minimal Dipeptide Motif Induces the Formation of Functional Nanoparticles (2016)

Abstract Functionalized nanoparticles decorated with functional biological entities serve as preferred vehicles for numerous theranostic applications. Here we offer an alternative strategy in which the targeting moieties also act as building blocks for the formation of functional nanoassemblies. Diphenylalanine, a small, highly potent self‐assembling module, was incorporated with a somatostatin analogue, a modified hormone which preferentially binds to cancer cells. The co‐assembly of the engineered hormone together with the structurally diverse diphenylalanine derivative allowed the formation of bioactive homogenous spherical nanostructures. Significant internalization capacity of the loaded co‐assembled nanospheres into cancer cells in vitro, as well as selective in vivo accumulation in tumors, were demonstrated. These findings present a new method for the molecular engineering of bioactive peptide molecules by minor modifications with a remarkably potent association motif.
Compensating for Parasitic Voltage Drops in Resistive Memory Arrays (2017)

Parasitic resistances cause devices in a resistive memory array to experience different read/write voltages depending on the device location, resulting in uneven writes and larger leakage currents. We present a new method to compensate for this by adding extra series resistance to the drivers to equalize the parasitic resistance seen by all the devices. This allows for uniform writes, enabling multi-level cells with greater numbers of distinguishable levels, and reduced write power, enabling larger arrays.
Instant Active Positioning with One LEO Satellite (1999)

ABSTRACT: Autonomous position determination in the Globalstar satellite communication system is discussed. The two-way communication between a user terminal on the earth's surface and a single low earth orbit (LEO) satellite makes it possible to derive range and range-rate and determine the user terminal position instantly. Expected accuracy is presented, and a simple direct solution is given.
DeepQSM - Using Deep Learning to Solve the Dipole Inversion for MRI Susceptibility Mapping (2018)

Quantitative susceptibility mapping (QSM) aims to extract the magnetic susceptibility of tissue from magnetic resonance imaging (MRI) phase measurements. The mapping of magnetic susceptibility in vivo has gained broad interest in several fields of science and medicine because it yields relevant information on biological tissue properties, predominantly myelin, iron and calcium. Thereby, QSM can also reveal pathological changes of these key components in devastating diseases such as Parkinson’s disease, Multiple Sclerosis, or hepatic iron overload. As QSM requires the solution of an ill-posed field-to-source-inversion, current techniques utilize manual optimization of regularization parameters to balance between smoothing, artifacts and quantification accuracy. We trained a fully convolutional deep neural network - DeepQSM - to invert the magnetic dipole kernel convolution. This network is capable of solving the ill-posed field-to-source inversion on real-world in vivo MRI phase data without the need for manual parameter tuning, which proves that this network has generalized the underlying mathematical principle of the dipole inversion. We demonstrate that DeepQSM’s susceptibility maps enable identification of deep brain substructures that are not visible in MRI phase data and provide information on their respective magnetic tissue properties. We illustrate DeepQSM’s clinical relevance in a patient with multiple sclerosis showing its sensitivity to white matter lesions. In summary, DeepQSM can be used to determine the composition of myelin sheets of nerve fibers in the brain, and to assess quantitative information on iron homeostasis and its dysregulation, and will subsequently contribute to a better understanding of these biological processes in health and disease.
Development of Ni‐Based DS Superalloy with Excellent Oxidation Resistance and LCF Properties for Power‐Generation Gas Turbines (2012)

This chapter contains sections titled: Introduction Experimental Procedure Experimental Results Discussion Conclusions Acknowledgments
Scanning Electrospray Microscopy with Nanopipets (2015)

Electrospray from nanopipets is used to realize scanning electrospray microscopy (SESM). This technique provides an ambient, noncontact method to investigate surface topography with distance dependence of electrospray current as feedback for imaging. SESM approach curves, line scans, and images are reported. Salt deposition on the sample surface from SESM is also characterized.
Detection and estimation with compressive measurements (2006)

The recently introduced theory of compressed sensing enables the reconstruction of sparse or\ncompressible signals from a small set of nonadaptive, linear measurements. If properly chosen,\nthe number of measurements can be much smaller than the number of Nyquist rate samples.\nInterestingly, it has been shown that random projections are a satisfactory measurement scheme.\nThis has inspired the design of physical systems that directly implement similar measurement\nschemes. However, despite the intense focus on the reconstruction of signals, many (if not most)\nsignal processing problems do not require a full reconstruction of the signal { we are often\ninterested only in solving some sort of detection problem or in the estimation of some function\nof the data. In this report, we show that the compressed sensing framework is useful for a\nwide range of statistical inference tasks. In particular, we demonstrate how to solve a variety of\nsignal detection and estimation problems given the measurements without ever reconstructing\nthe signals themselves. We provide theoretical bounds along with experimental results.
Pilot's Automated Weather Support System (PAWSS) concepts (1991)

The FAA and NASA are investigating concepts for providing automated support to pilots in obtaining and using weather information. The pilot's Automated Weather Support System (PAWSS) activity is using computer technology to assist the pilot in acquiring and displaying weather information in the cockpit, and to assist in assessing and applying weather data in flight management and en route support. The PAWSS concepts include data link communications with a short update cycle of new weather data, color-coded map depictions with alpha-numeric data available for backup and detailed data presentation, automated monitoring of weather trends with alerting for hazardous conditions, and expert system technology applications in weather data assessments and flight management applications.
Calcium determination in serum with stable alkaline Arsenazo III and triglyceride clearing (1993)

Abstract We describe an analytical procedure for determining serum calcium, using the ligand Arsenazo III in an aqueous alkaline medium. The choice of pH for the proposed technique differs from current procedures, which are for the most part carried out in a slightly acidic medium. An acidic medium avoids interference from magnesium, but is spectrophotometrically suboptimal for this pH-dependent reaction: the molar absorptivity of the Arsenazo III complex with calcium at acid pH is 13,787 L mol-1 cm-1, about one-half of that at a more optimal alkaline pH (26,574 L mol-1 cm-1). We have included a clearing technique in the reagent to avoid spectral aberrations from hypertriglyceridemic samples. alpha-Cyclodextrin absorbs the nonesterified fatty acids liberated from triglycerides by a microbial lipase. This modification may also be helpful for binding nonesterified fatty acids, which are known to interfere with calcium procedures by forming calcium soaps and thus preventing the reaction with intended ligands. The use of 8-hydroxyquinoline sulfonate as the magnesium-masking agent facilitates the use of alkaline pH. The less-water-soluble alternative, 8-hydroxyquinoline, commonly used as a precipitating agent for several methods, is difficult to solubilize in the alkaline reagent and tends to precipitate when complexed to magnesium. Finally, the use of alkaline pH results in a prolonged (&gt; or = 6 weeks) shelf life for the reagent.
Resistive DAC in 65nm CMOS (2011)

The successive-approximation (SA) algorithm is traditionally used for low-bandwidth applications because it requires n clock cycles or more to obtain n-bit resolution. However, the use of modern nanometer CMOS technologies and special design solutions overcome the speed limit, enabling conversion rates in the hundreds of MHz with very low power consumptions [1]. This design uses the successive-approximation method to obtain 8b up to 400MS/s with very low power using a 1.2V supply. Key features of the architecture are a resistive DAC and a 2b-per-cycle conversion with interpolated sampling front-ends and shift registers. A cross-coupled bootstrapping network is also implemented to allevi-ate the signal-dependent clock feed-through. The very compact layout leads to a silicon area of 0.024 mm2. Converting more than one bit per cycle in SA schemes requires using multiple reference voltages that scale along the conversion cycle. Since this need leads to complex and multiple capacitor-based DACs [2], this design uses a Kelvin
Quantifying Therapeutic and Diagnostic Efficacy in 2D Microvascular Images (2009)

VESGEN is a newly automated, user-interactive program that maps and quantifies the effects of vascular therapeutics and regulators on microvascular form and function. VESGEN analyzes two-dimensional, black and white vascular images by measuring important vessel morphology parameters. This software guides the user through each required step of the analysis process via a concise graphical user interface (GUI). Primary applications of the VESGEN code are 2D vascular images acquired as clinical diagnostic images of the human retina and as experimental studies of the effects of vascular regulators and therapeutics on vessel remodeling.
Collusion-Resistant Processing of SQL Range Predicates (2018)

Prior solutions for securely handling SQL range predicates in outsourced Cloud-resident databases have primarily focused on passive attacks in the Honest-but-Curious adversarial model, where the server is only permitted to observe the encrypted query processing. We consider here a significantly more powerful adversary, wherein the server can launch an active attack by clandestinely issuing specific range queries via collusion with a few compromised clients. The security requirement in this environment is that data values from a plaintext domain of size N should not be leaked to within an interval of size $$H$$ . Unfortunately, all prior encryption schemes for range predicate evaluation are easily breached with only $$O(\log _2\psi )$$ range queries, where $$\psi = N{/}H$$ . To address this lacuna, we present SPLIT, a new encryption scheme where the adversary requires exponentially more— $${\mathbf{O}}(\psi )$$ —range queries to breach the interval constraint and can therefore be easily detected by standard auditing mechanisms. The novel aspect of SPLIT is that each value appearing in a range-sensitive column is first segmented into two parts. These segmented parts are then independently encrypted using a layered composition of a secure block cipher with the order-preserving encryption and prefix-preserving encryption schemes, and the resulting ciphertexts are stored in separate tables. At query processing time, range predicates are rewritten into an equivalent set of table-specific sub-range predicates, and the disjoint union of their results forms the query answer. A detailed evaluation of SPLIT on benchmark database queries indicates that its execution times are well within a factor of two of the corresponding plaintext times, testifying its efficiency in resisting active adversaries.
Prestressed Concrete Girder with Multistage Prestressing Concept (2003)

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Oxidative modification of a cephalosporin C acylase from Pseudomonas strain N176 and site-directed mutagenesis of the gene (1996)

A cephalosporanic acid acylase from Pseudomonas strain N176 catalyzes hydrolysis of both glutarylcephalosporanic acid and cephalosporin C to 7-amino-cephalosporanic acid. Chemical modification of the enzyme with acidic hydrogen peroxide was performed to investigate residues which play important roles in enzymatic activity. The activity of the enzyme was reduced to 76% of the original by oxidation. From protein chemical analysis combined with site-directed point mutagenesis, modification of Met-164 was found to correspond to the reduction in activity. To study the effect of Met-164 on the enzymatic character, we prepared mutant acylases in which Met-164 was replaced with several other amino acids and obtained the following data: (i) there existed a trend of mutation to noncharged hydrophilic residues, resulting in an increase of activity against glutarylcephalosporanic acid; (ii) the mutation of Met-164 to Gly and Ala resulted in the lowering of both Km values and the optimal pHs against glutarylcephalosporanic acid; (iii) the mutation to Leu enhanced cephalosporin C acylase activity; and (iv) the mutation to Gln improved the k(cat) value for glutarylcephalosporanic acid. In particular, the mutation to Gln resulted in a high rate of conversion of glutarylcephalosporanic acid to 7-amino-cephalosporanic acid under conditions similar to those of a bioreactor system. These results may indicate that Met-164 is located in or near the cephalosporin compound binding pocket on the enzyme.
In Situ Time-Resolved Observation of the Development of Intracrystalline Mesoporosity in USY Zeolite (2016)

The development of intracrystalline mesoporosity within zeolites has been a long-standing goal in catalysis as it greatly contributes to alleviating the diffusion limitations of these widely used microporous materials. The combination of in situ synchrotron X-ray diffraction and liquid-cell transmission electron microscopy enabled the first in situ observation of the development of intracrystalline mesoporosity in zeolites and provided structural and kinetic information on the changes produced in zeolites to accommodate the mesoporosity. The interpretation of the time-resolved diffractograms together with computational simulations evidenced the formation of short-range hexagonally ordered mesoporosity within the zeolite framework, and the in situ electron microscopy studies allowed the direct observation of structural changes in the zeolite during the process. The evidence for the templating and protective role of the surfactant and the rearrangement of the zeolite crystal to accommodate intracrystalline mesoporosity opens new and exciting opportunities for the production of tailored hierarchical zeolites.
Tunable magnetic regenerator alloys with a giant magnetocaloric effect for magnetic refrigeration from ∼20 to ∼290 K (1997)

A giant magnetocaloric effect (ΔSmag) has been discovered in the Gd5(SixGe1−x)4 pseudobinary alloys, where x⩽0.5. For the temperature range between ∼50 and ∼280 K it exceeds the reversible (with respect to alternating magnetic field) ΔSmag for any known magnetic refrigerant material at the corresponding Curie temperature by a factor of 2–10. The two most striking features of this alloy system are: (1) the first order phase transformation, which brings about the large ΔSmag in Gd5(SixGe1−x)4, is reversible with respect to alternating magnetic field, i.e., the giant magnetocaloric effect can be utilized in an active magnetic regenerator magnetic refrigerator; and (2) the ordering temperature is tunable from ∼30 to ∼276 K by adjusting the Si:Ge ratio without losing the giant magnetic entropy change.
Development of precise energy spectrum measurement technique for high-power pulsed X-ray sources for industrial use (2015)

It is difficult to obtain an accurate energy spectrum by measurement for X-rays which are produced by linear accelerators because so many photons are emitted within a very short period and the photons have energies in a wide range. In order to solve the problem, we developed a new technique utilizing the Bayesian estimation method combined with attenuation curve measurement using a step-shaped attenuation material. We experimentally confirmed the validity of the presented technique for an X-ray computed tomography (CT) system. By using the accurate energy information of emitted X-rays obtained by the developed technique, the quality of non-destructive inspection images can be expected to be improved for industrial X-ray radiography, X-ray CT and so on, using high-power X-ray sources.
Applications of Adaptive Learning Controller to Synthetic Aperture Radar. (1985)

Abstract : In this study the application of Artificial Intelligence methods to Synthetic Aperture Radars (SARs) is investigated. It was shown that the neuron-like Adaptive Learning Controller (ALC), operating in the extremizing mode suggested by Klopf, can be used successfully in the motion compensation system of a SAR. Keywords include: Adaptive control; Artificial intelligence; Synthetic aperture radar; Autofocus; and Learning networks.
Low-power design methodology for an on-chip bus with adaptive bandwidth capability (2003)

This paper describes a low-power design methodology for a bus architecture based on hybrid current/voltage mode signaling for deep sub-micrometer on-chip interconnects that achieves high data transmission rates while minimizing the number of repeaters by nearly 1/3. The technique uses low-impedance current-mode sensing to increase the data throughput and minimizes the static power dissipation inherent to current-mode signaling by adaptively changing the interconnection bandwidth given a change in input signal activity. Since bandwidth is related to power dissipation, the adaptive bus attains energy efficient data transmission by expending minimum power required to support the bus signal activity.The design method is based on statistical analysis of address streams extracted for typical benchmark programs using a microprocessor time-based simulator in combination with circuit-level power analysis. Simulation results indicate improvements in power dissipation of up to 65% and 40% over current and voltage mode signaling schemes, respectively.
Online mobile user speed estimation: Performance and tradeoff considerations (2017)

This paper presents an online algorithm for mobile user speed estimation in 3GPP Long Term Evolution (LTE)/LTE-Advanced (LTE-A) networks. The proposed method leverages on uplink (UL) sounding reference signal (SRS) power measurements performed at the base station, also known as eNodeB (eNB), and remains effective even under large sampling period. Extensive performance evaluation of the proposed algorithm is carried out using field traces from realistic environment. The online solution is proven highly efficient in terms of computational requirement, estimation delay, and accuracy. In particular, we show that the proposed algorithm can allow for the first speed estimation to be obtained after 10 seconds and with an average speed underestimation error of 14 kmph. After the first speed acquisition, subsequent speed estimations can be obtained much faster (e.g., each second) with limited implementation cost and still provide high accuracy.
Seven Different Assays of Hyaluronan Compared for Clinical Utility (1992)

To compare six assays of hyaluronan (hyaluronic acid; HYA) in serum, developed in different laboratories, we analyzed 10 samples from each of three groups: healthy persons, patients with primary biliary cirrhosis, and patients with rheumatoid arthritis. All the assays are based on the use of affinity proteins specific for HYA, prepared from cartilage or brain tissue, and are analogous to RIA or enzyme immunoassay techniques. The assay results were of the same magnitude. Although statistical analysis indicated that the methods in some cases deviated significantly from one another, this variation was less than the physiological variation in the healthy population. Therefore, the results of clinical investigations in which the various methods have been used are comparable. The analyses have high specificity and sensitivity for primary biliary cirrhosis but are somewhat less suitable for detecting rheumatoid arthritis. A seventh laboratory, which obtained antibodies to HYA, used these in an RIA to analyze a separate series of serum specimens. Results were in agreement with those obtained by one of the other assays.
Effects of cations, anions and H<sup>+</sup> concentration of acidic ionic liquids on the valorization of polysaccharides into furfural (2017)

The valorization of hemicellulose into valuable chemicals, such as C5 sugars and furfural, in a one-pot fashion.
Assessment of image registration accuracy in three‐dimensional transrectal ultrasound guided prostate biopsy (2010)

Our results compare favorably with a clinical need for a TRE of less than 2.5 mm, and suggest that image-based registration is superior to surface-based registration for 3D TRUS-guided prostate biopsies, since it does not require segmentation.
Investigation on self-absorption reduction in laser-induced breakdown spectroscopy assisted with spatially selective laser-stimulated absorption (2018)

We proposed spatially selective laser-stimulated absorption (SS-LSA) to reduce self-absorption in laser-induced breakdown spectroscopy (LIBS).
Multichannel image compression by bijection mappings onto zero-trees (2002)

A new approach to multispectral image compression is introduced where the intra- and cross-band correlations are jointly exploited in a surprisingly simple yet very effective manner. The proposed compression algorithm maps the multispectral image set into a virtual 2-dimensional array and applies a scalar image coding algorithm to the virtual array. Thus, the spatial correlation and the spectral correlation of the multispectral data set are jointly exploited. Based on the statistical characteristics of the multispectral data, the bijection mapping is optimized to minimize the distortion introduced by the compression algorithm. At high compression rates, the new algorithm outperforms traditional compression algorithms whenever the cross-band correlation is high and it yields comparable performance at low compression rates.
Dynamic Network Selection using Kernels (2007)

We present a new algorithm for vertical handover and dynamic network selection, based on a combination of multi- attribute utility theory, kernel learning and stochastic gradient descent. We show that this new method is able to improve network selection in a non-stationary mobile environment. Furthermore, since the kernel employed is based on the utility functions for attributes such as Availability, Quality and Cost, the kernel regression in fact gives interpretable results. We present simulation results that demonstrate our algorithm being able to dynamically learn utilities and efficiently select networks.