gebhart/patrepeval huggingface dataset:
80-kb Logic Embedded High-K Charge Trap Transistor-Based Multi-Time-Programmable Memory With No Added Process Complexity (2018)

This paper describes the design and implementation of an 80-kb logic-embedded non-volatile multi-time programmable memory (MTPM) with no added process complexity. Charge trap transistors (CTTs) that exploit charge trapping and de-trapping behavior in high-K dielectric of 32-/22-nm Logic FETs are used as storage elements with logic-compatible programming voltages. A high-gain slew-sense amplifier (SA) is used to efficiently detect the threshold voltage difference (ΔVDIF) between the true and complement FETs in the twin cell. Design-assist techniques including multi-step programming with overwrite protection and block write algorithm are used to enhance the programming efficiency without causing a dielectric breakdown. High-temperature stress results show a projected data retention of 10 years at 125 °C with a signal loss of <;30% that is margined in while programming, by employing a sense margining logic in the SA. Scalability of CTT has been established by the first demonstration of CTT-based MTPM in 14-nm bulk FinFET technology with read cycle time of 40 ns at 0.7-V VDD.
A Mathematical Model for Wideband Ranging (2014)

Wideband ranging is essential for numerous emerging applications that rely on accurate location awareness. The quality of range information, which depends on network intrinsic properties and signal processing techniques, affects the localization accuracy. A popular class of ranging techniques is based on energy detection owing to its low-complexity implementation. This paper establishes a tractable model for the range information as a function of wireless environment, signal features, and energy detection techniques. Such a model serves as a cornerstone for the design and analysis of wideband ranging systems. Based on the proposed model, we develop practical soft-decision and hard-decision algorithms. A case study for ranging and localization systems operating in a wireless environment is presented. Sample-level simulations validate our theoretical results.
Abstract 128: Serum Anti-MAA Antibody Titers are Associated with Acute Myocardial Infarction and MMP-9 (2013)

Introduction Atherosclerotic plaque rupture is the leading cause of acute myocardial infarction (AMI). Malondialdehyde acetaldehyde (MAA) modified proteins have recently been implicated in this process by their ability to initiate inflammatory responses. Matrix metalloproteinase 9 (MMP-9) is increased following AMI and has been associated with the disease due to its ability to degrade the fibrotic cap that forms on some plaques. Objective The purpose of this study was to evaluate the relationship between MMP-9 and anti-MAA antibody isotypes in patients experiencing acute myocardial infarction (AMI). Methods Serum samples from AMI patients (n=10) were collected and tested for the presence of anti-MAA antibody isotypes, peak CK, peak troponin, and MMP-9 levels. Samples were collected at the time of AMI, 24 and 48 hours post event. Data was correlated to determine relationships with antibody isotypes directed against MAA protein antigens. Results MMP-9 increased significantly from the initial presentation at 24 hours post-AMI (p=0.006) and 48 hours post-AMI (p= 0.044). Anti-MAA IgM decreased significantly (p= 0.021) between initial and 24 hours post AMI. A similar significant decrease was observed for anti-MAA IgG (p= 0.006). Anti-MAA IgA levels did not change significantly post-AMI. Significant correlations were demonstrated between peak CK and anti-MAA IgG 24 hours post AMI (r= -0.819, p= 0.013), between peak troponin and anti-MAA IgG 24 hours post AMI (r= -0.860, p= 0.006) and between MMP-9 levels 24 hours post AMI and anti-MAA IgM levels 24 hours post MI ( r= 0.0712, p=0.021). Conclusions The negative correlation of anti-MAA IgG to cardiac enzymes is suggestive that myocardial infarction and tissue necrosis results in the release of the MAA antigen from infarcted myocardium and clearance of anti-MAA antibodies. Additionally, anti-MAA IgM and MMP-9 are positively correlated with each other 24 hours post-AMI, suggesting that anti-MAA IgM titers may correlate to the severity of the AMI and thus CAD. Implications Anti-MAA antibodies might serve as important biomarkers of impending atherosclerotic plaque rupture and subsequent AMI and warrants further investigation in a larger cohort of patients.
Advanced monopole and dipole sonic log data processing — Part 1: Real time (2020)

Real-time open-hole wireline sonic logging data processing becomes a nontrivial task to accurately, automatically, and efficiently evaluate the compressional and shear slowness of a borehole rock formation when human interaction is not possible and the signal processing time is limited to the elapsed time between different transmitter excitations. To address real-time sonic data processing challenges, we have developed self-adaptive, data-driven methods to accurately measure the formation P- and S-wave slowness from monopole and dipole waveforms in all types of formations. These new real-time processing techniques take advantage of the fact that advanced wireline sonic logging tools have wide frequency responses and little to no detectable tool body arrivals. These technology improvements provide an opportunity to implement a first-motion-detection technique that detects the onset of P-waves in the monopole array waveforms. The knowledge of compressional arrival time and corresponding slowness are then used to project an appropriate slowness-time window to identify the monopole refracted S-wave and its slowness based on the range of possible compressional to shear velocity ratio ([Formula: see text]/[Formula: see text]) for earth rock formation. To process the borehole dipole flexural waves, we develop a new, data-driven frequency-domain method that enables the evaluation of the full flexural-wave dispersion response and its corresponding low-frequency shear slowness asymptote. Field data processing results indicate that our methods provide high-quality compressional slowness (delta-T compressional) and shear slowness measurements that are not affected by other borehole modes or dispersion complications in most formation types.
A high speed reconfigurable integrated architecture for DWT (2002)

In this paper, we present an integrated systolic architecture for the discrete wavelet transform (DWT). This architecture is useful for both decomposition (forward DWT) and reconstruction (inverse DWT) of signals. The architecture has been designed based on an efficient systolic algorithm suitable for high speed VLSI implementation. This systolic architecture is unique in the sense that the same architecture is used for forward DWT and inverse DWT by selecting some suitable control signals and this systolic architecture yields 100% utilization unlike many other existing architectures in the literature. The two-dimensional DWT architecture can easily be designed by extending this one-dimensional solution.
Digital Background Correction of Harmonic Distortion in Pipelined ADCs (2006)

Pipelined analog-to-digital converters (ADCs) are sensitive to distortion introduced by the residue amplifiers in their first few stages. Unfortunately, residue amplifier distortion tends to be inversely related to power consumption in practice, so the residue amplifiers usually are the dominant consumers of power in high-resolution pipelined ADCs. This paper presents a background calibration technique that digitally measures and cancels ADC error arising from distortion introduced by the residue amplifiers. It allows the use of higher distortion and, therefore, lower power residue amplifiers in high-accuracy pipelined ADCs, thereby significantly reducing overall power consumption relative to conventional pipelined ADCs
Multi-Language Hypotheses Ranking And Domain Tracking for Open Domain (2015)

Hypothesis ranking (HR) is an approach for improving the accuracy of both domain detection and tracking in multi-domain, multi-turn dialogue systems. This paper presents the results of applying a universal HR model to multiple dialogue systems, each of which are using a different language. It demonstrates that as the set of input features used by HR models are largely language independent a single, universal HR model can be used in place of language specific HR models with only a small loss in accuracy (average absolute gain of +3:55% versus +4:54%), and also such a model can generalise well to new unseen languages, especially related languages (achieving an average absolute gain of +2:8% in domain accuracy on held out locales fr-fr, es-es, it-it; an average of 66% of the gain that could be achieve by training language specific HR models). That the latter is achieved without retraining significantly eases expansion of existing dialogue systems to new locales/languages.
On the construction of LDPC convolutional code ensembles based on permuted circulant unit matrices (2014)

In this paper, a construction methodology for ensembles of Low-Density Parity-Check Convolutional Codes (LDPC-CCs) based on permuted circulant unit matrices is proposed. The proposed method directly generates the syndrome former matrices according to specified code parameters and constraints i.e. code-rate, degree-distribution, constraint length, period and memory, in contrast to the majority of the available methodologies that produce relevant error-correcting codes based on either block ones, protographs or spatially-coupled type of codes. Simulation results show that the constructed ensembles demonstrate advanced error-correcting capability of up to 0.5 dB in terms of frame-error and bit-error rates at the convergence region, when compared to the performance of Forward Error Correction schemes adopted by various wireless standards, with comparable hardware complexity even at short codeword-lengths.
Energetics and stability of pentacene thin films on amorphous and crystalline octadecylsilane modified surfaces (2010)

Charge transport in organic thin film transistors (OTFTs) is directly related to the morphology and growth of the organic semiconductor at the dielectric interface. The most commonly used dielectric interface in OTFT research is alkylsilane-modified silicon oxide (SiO2). In this report, the nucleation, energetics, and stability of pentacene thin films on methyl-terminated surfaces are discussed. The density of the terminal methyl group was found to be an important parameter for controlling the growth of organic semiconductors. Pentacene growth is two-dimensional (2D) on SiO2 dielectrics modified with a crystalline, densely packed octadecylsilane (OTS) monolayer. However, it is primarily three-dimensional (3D) on SiO2 dielectrics modified with an amorphous OTS layer. Beyond a critical OTS density, the interaction between the OTS and pentacene exceeds the pentacene interlayer interaction energy engendering 2D growth which is preferential for high charge carrier mobility. The nucleation density is also much higher on the crystalline OTS compared to the amorphous OTS. The sub-monolayer thin films of pentacene were found to be much more stable on the ordered OTS compared to disordered OTS. Atomic force microscopy (AFM) and Monte Carlo simulations were used to develop a thorough analysis of pentacene film growth and energetics on OTS surfaces.
Genetics a nd Treatment of Dystonia (2009)

Advances in molecular biology have revealed mutations in increasing numbers of genes that cause several forms of primary and secondary dystonia. Studies of the biologic function of these genes using cellular and animal models have led to important insights into the pathophysiology of dystonia. These results, in turn, allow for a more accurate counseling of patients regarding prognosis and progression of the disease. A better understanding of the physiologic function of the mutated genes ultimately holds promise for the identification of novel targets for pharmacologic intervention.
Optimal On The Fly Index Selection in Polynomial Time (2017)

The index selection problem (ISP) is an important problem for accelerating the execution of relational queries, and it has received a lot of attention as a combinatorial knapsack problem in the past. Various solutions to this very hard problem have been provided. In contrast to existing literature, we change the underlying assumptions of the problem definition: we adapt the problem for systems that store relations in memory, and use complex specification languages, e.g., Datalog. In our framework, we decompose complex queries into primitive searches that select tuples in a relation for which an equality predicate holds. A primitive search can be accelerated by an index exhibiting a worst-case run-time complexity of log-linear time in the size of the output result of the primitive search. However, the overheads associated with maintaining indexes are very costly in terms of memory and computing time. In this work, we present an optimal polynomial-time algorithm that finds the minimal set of indexes of a relation for a given set of primitive searches. An index may cover more than one primitive search due to the algebraic properties of the search predicate, which is a conjunction of equalities over the attributes of a relation. The index search space exhibits a exponential complexity in the number of attributes in a relation, and, hence brute-force algorithms searching for solutions in the index domain are infeasible. As a scaffolding for designing a polynomial-time algorithm, we build a partial order on search operations and use a constructive version of Dilworth's theorem. We show a strong relationship between chains of primitive searches (forming a partial order) and indexes. We demonstrate the effectiveness and efficiency of our algorithm for an in-memory Datalog compiler that is able to process relations with billions of entries in memory.
In Vitro Assay for Conversion of Arabitol to Xylitol Using L-arabitol dehydrogenase and L-xylulose reductase from Neurospora crassa (2009)

Xylose reductase (XR) is a key enzyme in D-xylose metabolism, catalyzing the reduction of D-xylose to xylitol. However, the broad substrate spectrum of XR can also reduce L-arabinose to L-arabitol, byproduct, which requires expensive downstream process in industrial xylitol production. Some filamentous fungi have L-arabitol dehydrogenase(LAD) oxidizing L-arabitol to L-xylulose and Lxylulose reductase(LXR) reducing L-xylulose to xylitol. Genes incoding LAD and LXR were isolated from the genomic DNA of Neurospora crassa ATCC10333. Each gene was expressed in Escherichia coli BL21(DE3) using T7 promoter. Expression of LAD and LXR was confirmed by determining enzyme activity in cells grown on the LB media. The activity of LAD and LXR was 600 mU/mg of proteins and 4430 mU/mg of proteins, respectively. In vitro assay was performed for conversion of arabitol to xylitol using crude enzymes(LAD and LXR) and cofactors(NAD and NADPH). Substrates and products were analyzed by HPLC, and consequently, 49% of arabitol was converted to xylitol for two hours of enzyme reaction.
Phytotoxic metabolites of <i>Phomopsis</i><i>convolvulus</i>, a host-specific pathogen of field bindweed (1992)

Phomopsisconvolvulus is a host-specific pathogen which causes leaf spots and anthracnose lesions in the important perennial weed Convolvulusarvensis (field bindweed). Investigation of the metabolites produced by the fungus led to the isolation of the known fungal metabolites ergosterol (1) and ergosterol peroxide (2), in addition to four novel phytotoxins: the phthalides convolvulanic acid A (3), convolvulanic acid B (4), convolvulol (5), and the α-pyrone convolvulopyrone (6). The latter compounds were assigned the structures of 4-carboxy-3-hydroxy-7-methoxy-6-methyl-1(3H)-isobenzofuranone (3), 4-carboxy-7-methoxy-6-methyl-1(3H)-isobenzofuranone (4), 4-(hydroxymethyl)-7-methoxy-6-methyl-1(3H)-isobenzofuranone (5), and 3-[4-methoxy-3-methyl-α-pyron-6-yl]-2-methyl-2-butenoic acid (6) respectively. Strong herbicidal activity against C. arvensis was observed with compounds 3 and 4 at concentrations of 3–5 × 10 −4 M.
Real-Time Well Construction Process Inference through Probabilistic Data Fusion (2018)

Abstract Well construction process automation systems rely on the tracking of the state of the world (equipment, wellbore, process) with a high degree of confidence for safe and efficient operations. Robust state detection algorithms are paramount as they depend on uncertain models and data from imperfect sensors. The proposed solution outlined here is a practical implementation for well construction state inference, focused on bit-rock interaction. Probabilistic mixture models are learned from input sensor data stream, e.g. surface torque and hook load, accounting for noise and suitable priors. These models are then used for online classification of observations related to the underlying state of operations (e.g. on bottom drilling vs off bottom rotating). Multiple classified observables from different types of measurements are subsequently fused into system states using a Bayesian network, giving a robust state detection under uncertainty. The method required drilling mechanics knowledge in the interpretation of the classification as well as the design of the Bayesian network model. The algorithm was applied on real sensor data (hook load and surface torque), for the inference of elementary states of bit-rock interaction (no interaction, bit fully engaged with formation, in transition). The use of streaming input data to continuously learn the mixture model allows the tracking of levels. For instance, hook load is modeled as the mixture of several distributions evolving as the well progresses, correlated to the drill string being in slips, out of slips off bottom, or on bottom rotating. Observations inferred from the mixture models have various levels of confidence. The Bayesian network allows their fusion into a robust system state. The presented Bayesian network backed by mixture model is a fast, adaptive and robust solution to detect system state from drilling time series data with complex temporally correlated patterns. By learning from data and using priors from domain experts, the inference algorithms operate without user tuned thresholds or parameters. The probabilistic Bayesian approach provides a framework for dealing with uncertainty in drilling systems and can be extended in the future with additional observations drawn from new measurements.
An Efficient Coded Multicasting Scheme Preserving the Multiplicative\n Caching Gain (2015)

Coded multicasting has been shown to be a promis- ing approach to\nsignificantly improve the caching performance of content delivery networks with\nmultiple caches downstream of a common multicast link. However, achievable\nschemes proposed to date have been shown to achieve the proved order-optimal\nperformance only in the asymptotic regime in which the number of packets per\nrequested item goes to infinity. In this paper, we first extend the asymptotic\nanalysis of the achievable scheme in [1], [2] to the case of heterogeneous\ncache sizes and demand distributions, providing the best known upper bound on\nthe fundamental limiting performance when the number of packets goes to\ninfinity. We then show that the scheme achieving this upper bound quickly loses\nits multiplicative caching gain for finite content packetization. To overcome\nthis limitation, we design a novel polynomial-time algorithm based on random\ngreedy graph- coloring that, while keeping the same finite content\npacketization, recovers a significant part of the multiplicative caching gain.\nOur results show that the order-optimal coded multicasting schemes proposed to\ndate, while useful in quantifying the fundamental limiting performance, must be\nproperly designed for practical regimes of finite packetization.\n
Synchronous picosecond sonoluminescence (1993)

A strong sound field can (1) trap a bubble of gas at a velocity node, (2) maintain the bubble against diffusion, and (3) at sufficient intensity cause it to emit flashes of light that have intensities over 30 mW and widths less than 50 ps. The flashes are emitted in a clocklike fashion with a jitter that is also less than 50 ps. The spectral intensity of the sonoluminescence (SL) increases into the ultraviolet. The mechanism for this effect is still unknown but light scattering experiments have resolved the bubble motion—radius versus time—on a scale of nanoseconds and indicate that the light is emitted by a supersonic collapse. The emitted intensity is a strong function of ambient temperature and varies by a factor of 200 between 1 and 40 C. Light scattering measurements of temperature-dependent SL therefore provide data that can critically test any proposed theory such as imploding shock waves [C. C. Wu and P. H. Roberts, Phys. Rev. Lett. (May 1993)]. [Work supported by the US DOE Division of Advanced Energy Projects, R. L. is supported by an AT&T fellowship.]
3‐Aminoazetidin‐2‐one Derivatives as <i>N</i>‐Acylethanolamine Acid Amidase (NAAA) Inhibitors Suitable for Systemic Administration (2014)

N-Acylethanolamine acid amidase (NAAA) is a cysteine hydrolase that catalyzes the hydrolysis of endogenous lipid mediators such as palmitoylethanolamide (PEA). PEA has been shown to exert anti-inflammatory and antinociceptive effects in animals by engaging peroxisome proliferator-activated receptor α (PPAR-α). Thus, preventing PEA degradation by inhibiting NAAA may provide a novel approach for the treatment of pain and inflammatory states. Recently, 3-aminooxetan-2-one compounds were identified as a class of highly potent NAAA inhibitors. The utility of these compounds is limited, however, by their low chemical and plasma stabilities. In the present study, we synthesized and tested a series of N-(2-oxoazetidin-3-yl)amides as a novel class of NAAA inhibitors with good potency and improved physicochemical properties, suitable for systemic administration. Moreover, we elucidated the main structural features of 3-aminoazetidin-2-one derivatives that are critical for NAAA inhibition.
Subsequent Generation “Functional Foods”—Production of Candidate Oral Vaccines in Transgenic Plants (1996)

The concept of “Functional Foods” is becoming a commonly used term in discussions of human nutrition. Consumer awareness of natural food constituents and their role in cancer and cardiovascular disease prevention has done much to increase health consciousness with respect to plant products. The Plants and Human Health Program of the Boyce Thompson Institute uses molecular techniques to create transgenic plants with modified food composition; our goal is to devise strategies for production of pharmaceuticals or “nutraceuticals” in plants. Our initial focus has been genes encoding the antigenic proteins of human infectious agents such as hepatitis B and the causal agents of diarrheal disease. Areas of research include; 1) methods to increase production of foreign proteins in transgenic plants, and 2) utilization of engineered edible plant tissues for animal feeding studies. We have found that transgenic foods orally immunize test animals; these findings portend many new and exciting possibilities for plant medicinal chemistry.
FeedWinnower (2010)

Information overload is a growing threat to the productivity of today's knowledge workers, who need to keep track of multiple streams of information from various sources. RSS feed readers are a popular choice for syndicating information streams, but current tools tend to contribute to the overload problem instead of solving it. We introduce FeedWinnower, an enhanced feed aggregator that helps readers to filter feed items by four facets (topic, people, source, and time), thus facilitating feed triage. The combination of the four facets provides a powerful way for users to slice and dice their personal feeds. In addition, we present a formative evaluation of the prototype conducted with 15 knowledge workers in two different organizations.