gebhart/patrepeval huggingface dataset:
Context-Aware Systems for Sequential Item Recommendation (2018)

Quizlet is the most popular online learning tool in the United States, and is used by over 2/3 of high school students, and 1/2 of college students. With more than 95% of Quizlet users reporting improved grades as a result, the platform has become the de-facto tool used in millions of classrooms. In this paper, we explore the task of recommending suitable content for a student to study, given their prior interests, as well as what their peers are studying. We propose a novel approach, i.e. Neural Educational Recommendation Engine (NERE), to recommend educational content by leveraging student behaviors rather than ratings. We have found that this approach better captures social factors that are more aligned with learning. NERE is based on a recurrent neural network that includes collaborative and content-based approaches for recommendation, and takes into account any particular student's speed, mastery, and experience to recommend the appropriate task. We train NERE by jointly learning the user embeddings and content embeddings, and attempt to predict the content embedding for the final timestamp. We also develop a confidence estimator for our neural network, which is a crucial requirement for productionizing this model. We apply NERE to Quizlet's proprietary dataset, and present our results. We achieved an R^2 score of 0.81 in the content embedding space, and a recall score of 54% on our 100 nearest neighbors. This vastly exceeds the recall@100 score of 12% that a standard matrix-factorization approach provides. We conclude with a discussion on how NERE will be deployed, and position our work as one of the first educational recommender systems for the K-12 space.
Clofazimine for Treatment of Mycobacterium abscessus Infections in Children (2017)

the 6 months following the quality assurance intervention were included. Sputum samples were processed at the Texas Department of State and Health Services (DSHS) Laboratory.
Acute physical-activity related increases in interoceptive ability are not enhanced with simultaneous interoceptive attention (2022)

Interoception, the sense of the internal body, is proposed to support self-regulation, and consequently influence mental health. Researchers have therefore shown interest in improving the ability to accurately monitor internal signals (i.e., interoceptive accuracy, IAcc). Research suggests that cardiac IAcc is modifiable by both manipulations of interoceptive attention (guided attention towards the internal body), and interoceptive exposure (strategically inducing somatic signals e.g., via physical activity). Whilst successful in isolation, it is unclear whether a combined approach (i.e., directing attention towards the internal body when signals are more salient) could elicit greater benefits. In a 2 × 2 within-subject design, 48 healthy adults (M<sub>age</sub> = 25.98 ± 4.73 years, 50% female) completed four 20-min conditions varying in both attentional focus (interoceptive vs exteroceptive) and physical activity (active vs rest), with cardiac IAcc measured immediately after. Results revealed a main effect for physical activity (p < 0.001), however, there was no effect for attentional focus (p = 0.397), and no interaction effect (p = 0.797). Differential analyses showed that a higher sporting background increased sensitivity to physical activity-related increases in cardiac IAcc (p = 0.031). Findings indicate that (irrespective of attentional focus) moderate-vigorous physical activity-based interventions have the potential to increase cardiac IAcc, with certain individuals potentially benefiting more.
The Nanolithography Toolbox (2016)

This article introduces in archival form the Nanolithography Toolbox, a platform-independent software package for scripted lithography pattern layout generation. The Center for Nanoscale Science and Technology (CNST) at the National Institute of Standards and Technology (NIST) developed the Nanolithography Toolbox to help users of the CNST NanoFab design devices with complex curves and aggressive critical dimensions. Using parameterized shapes as building blocks, the Nanolithography Toolbox allows users to rapidly design and layout nanoscale devices of arbitrary complexity through scripting and programming. The Toolbox offers many parameterized shapes, including structure libraries for micro- and nanoelectromechanical systems (MEMS and NEMS) and nanophotonic devices. Furthermore, the Toolbox allows users to precisely define the number of vertices for each shape or create vectorized shapes using Bezier curves. Parameterized control allows users to design smooth curves with complex shapes. The Toolbox is applicable to a broad range of design tasks in the fabrication of microscale and nanoscale devices.
Compensation for temperature dependence of Faraday effect in diamagnetic materials: application to optical fibre sensors (1991)

The temperature dependence of the Faraday effect in a diamagnetic material can be compensated for by varying the polarisation state of the light entering the material as a function of temperature. We demonstrate that this can be done automatically by exploiting the temperature dependence of a linear retarder (waveplate).
Unsupervised multimodal feature learning for semantic image segmentation (2013)

In this paper, we address the semantic segmentation problem using single-layer networks. This network is used for unsupervised feature learning for the available RGB image and the depth image. A significant contribution of the proposed approach is that the dictionary is selected from the existing samples using the L <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2, 1</sub> optimization. Such a dictionary can capture more meaningful representative samples and exploit intrinsic correlation between features from different modalities. The experimental results on the public NYU dataset show that this strategy dramatically improves the classification performance, compared with existing dictionary learning approach. In addition, we perform experimental verification using the practical robot platforms and show promising results.
Recognition of Mutiple Tachyarrhythmias by Rate‐Independent Means Using a Small Microcomputer (1991)

New implantable devices are now available that can offer different therapies for different arrhythmias but they need a method of discriminating between these rhythms. Heart rate analysis is predominantly used to discern between sinus rhythm (SR) and pathological tachycardias but this may be of limited value when the rates of the rhythms are similar. An enhanced form of Gradient Pattern Detection (GPD) has been developed using an 8-bit microcomputer that can distinguish between SR and up to three other arrhythmias in real time. This is a method based on electrogram morphology where each rhythm's specific electrogram is classified by a sequence of gradient 'zones'. The microprocessor of the computer is of similar processing power to ones used in current pacemakers. Five patients with multiple arrhythmias were studied. Four had ventricular tachycardia (VT) and one had three conduction patterns during supraventricular tachycardia (SVT). Bipolar endocardial right ventricular electrograms were recorded during SR and tachycardia in all patients. The computer would first 'learn' about each different rhythm by a semi-automatic means. Once all the rhythms were learned the program would enter the GPD analysis phase. The computer would output a series of real-time rhythm specific marker codes onto a chart recorder as it recognized each rhythm. Sixteen different arrhythmias (13 VT, 3 SVT) were examined for this study. All rhythms (including SR) were distinguished from each other except in the case of one patient with six VTs where two VTs had identical shapes and therefore could not be detected apart. The method would be a useful addition to heart rate analysis for future generations of microprocessor assisted pacemakers.
Combining Static and Dynamic Analyses to Reverse-Engineer Scenario Diagrams (2013)

This paper discusses a step towards reverse engineering source code to produce UML sequence diagrams, with the aim to aid program comprehension and other activities (e.g., verification). Specifically, our objective being to obtain a lightweight instrumentation and therefore disturb the software behaviour as little as possible in order to eventually produce accurate sequence diagrams. To achieve this, we combine static and dynamic analyses of a Java software, reducing information we collect at runtime (lightweight instrumentation) and compensating for the reduced runtime information with information obtained statically from source code. Static and dynamic information are represented as models and UML diagram generation becomes a model transformation problem. Our validation against a previous, correct approach shows that we indeed reduce the execution overhead inherent to dynamic analysis, while still producing useful diagrams.
Removing foreground objects by using depth information from multi-view images (2007)

In this paper, we present a novel method for removing foreground objects in multi-view images. Unlike the conventional methods, which locate the foreground objects interactive way, we intend to develop an automated system. The proposed algorithm consists of two modules: 1) object detection and removal, and 2) detected foreground filling stage. The depth information of multi-view images is a critical cue adopted in this algorithm. By multi-view images, it is not meant a multi-camera equipped system. We use only one digital camera and take photos by hand. Although it may cause bad matching result, it is sufficient to detect and remove the foreground object by using coarse depth information. The experimental results indicate that the proposed algorithm provides an effective tool, which can be used in applications for digital camera, photo-realistic scene generation, digital cinema and so on.
Multi-Octave Performance of Single-Ended Microwave Solid-State Amplifiers (1984)

The computed performances of multi-stage single-ended GaAs MESFET amplifiers are compared when employing one and the same transistor type. The circuit principles studied are of the reflective match the Iossy match, the feedback, the distributed, and the active-match amplifier variety. It was found that the gain characteristics of the single-stage modules using either passive or active matching do not conclusively identify the optimum circuit type in the band of interest (2-18 GHz). For the case of multistage devices, however, the gain and the VSWR performance clearly favor the distributed amplifier principle. In addition to the data reported in the literature, the paper discusses recent experimental results obtained from a 3-17.5-GHz reflective match module, a two-stage 2-18-GHz and a four-stage 0.5-18.5-GHz feedback amplifier, as well as a two-stage 2-20-GHz and a four-stage 2-18-GHz distributed amplifier.
The Paradox of Silence in the Arts and Religion (1995)

Through paradoxical silences, some artists convey their anguish over heaven's unresponsiveness in the face of evil. But in religion silence often conveys God's presence and sorrow.
Anabaena sp. strain PCC 7120 ntcA gene required for growth on nitrate and heterocyst development (1994)

The Anabaena sp. strain PCC 7120 ntcA (bifA) gene encodes a sequence-specific DNA-binding protein, NtcA (BifA, VF1) that interacts with the upstream region of several genes, including glnA, xisA, rbcL, and nifH. We have constructed a ntcA null mutant by interrupting the gene with an omega Spr-Smr cassette. The ntcA mutant was not able to grow with nitrate or atmospheric dinitrogen as the sole nitrogen source but could be grown on medium containing ammonium. The ntcA mutant was unable to form heterocysts and did not rearrange the nifD or fdxN elements after induction on a medium lacking combined nitrogen. Northern (RNA) analysis of ntcA in the wild-type strain during nitrogen stepdown showed a peak of ntcA message at an early stage (12 h) of heterocyst induction. Complementation of the ntcA mutant with a DNA fragment containing the ntcA gene and 251 bp of upstream sequence on a shuttle vector restored a wild-type phenotype; however, a similar construction containing 87 bp of upstream sequence only partially restored the phenotype. Northern analysis of RNA samples isolated from ammonium-grown cultures of the ntcA mutant showed reduced amounts of glnA message and the absence of a 1.7-kb transcript. In the wild type, the 1.7-kb transcript represents the majority of glnA transcripts after nitrogen stepdown. The ntcA mutant showed a normal pattern of rbcLS messages under these growth conditions.
Bit-cooperative coded modulation (2013)

A new coded modulation technique, termed bit-cooperative coded modulation (BCCM), is proposed in this paper. By introducing a pseudo-random sequence at the transmitter to systematic low-density parity-check (LDPC) codes, the receiver enjoys the benefits of increased minimum Euclidean distance and the Hamming distance when applying this side-information at the receiver. In particular, we propose a new constellation mapping principle to take advantage of the side information. Our analysis indicates that the side information makes the regular LDPC code irregular, with irregularity specified by the check node degree distribution, which allows the density evolution approach to be used to design and optimize the regular LDPC code for the BCCM. We then analytically derive the constellation constrained capacity for the BCCM. The performance of the LDPC-coded BCCM on AWGN channels and Rayleigh fading channels is analyzed using the density evolution and extensive simulations.
Molecular weight effect on line-edge roughness (2003)

The effect of molecular weight (Mw) on line-edge roughness (LER) in ZEP resists, which are positive-tone electron-beam resists, was investigated by changing the size of the aggregates in resist films and the latent-image contrast. The LER was estimated by directly observing the pattern sidewall. It was clarified that the LER for low-Mw resist is larger than that for high-Mw resist and also that the LER for low-Mw resist is independent of the latent image contrast. On the other hand, the LER for high-Mw resist increases rapidly with decreasing contrast. These results can be explained by the relationship between the size of aggregates and the width of the transition zone between low- and high-dose regions. This strongly suggests that low-Mw resists are not necessarily advantageous in reducing LER.
Customer Life Time Value Model Framework Using Gradient Boost Trees with RANSAC Response Regularization (2018)

For many years, Customer lifetime value has been a mainstay concept in direct response marketing and has been increasingly considered. This paper presents a mathematical model framework for determination of customer lifetime value. The proposed multi-layer framework is based on a systematic theoretical taxonomy and on assumptions grounded in customer behavior. CLV, a recent marketing paradigm, pursues long-term relationship with profitable customers. It can be a starting point to understand relationship management and measure the true value of customers to be deployed toward the targeted customers and profitable customers, to foster customers' full profit potential. Corporate success depends on an organization ' ability to build and maintain loyal and valued customer relationships. In this paper, we propose a framework for analyzing customer value and segmenting customers based on their value. We also conducted an in-depth data analysis to find each member's behavior and important attributes which plays a significant role in calculating CLV in multiple revenue bands. From the experimental validation, we concluded that our proposed framework works much better in predicting customer's life time value in terms of revenue compared to other methods in past literature.
Solid‐Phase Synthesis (2006)

Abstract ChemInform is a weekly Abstracting Service, delivering concise information at a glance that was extracted from about 200 leading journals. To access a ChemInform Abstract, please click on HTML or PDF.
Learning How to Propagate Messages in Graph Neural Networks (2021)

This paper studies the problem of learning message propagation strategies for graph neural networks (GNNs). One of the challenges for graph neural networks is that of defining the propagation strategy. For instance, the choices of propagation steps are often specialized to a single graph and are not personalized to different nodes. To compensate for this, in this paper, we present learning to propagate, a general learning framework that not only learns the GNN parameters for prediction but more importantly, can explicitly learn the interpretable and personalized propagate strategies for different nodes and various types of graphs. We introduce the optimal propagation steps as latent variables to help find the maximum-likelihood estimation of the GNN parameters in a variational Expectation- Maximization (VEM) framework. Extensive experiments on various types of graph benchmarks demonstrate that our proposed frame- work can significantly achieve better performance compared with the state-of-the-art methods, and can effectively learn personalized and interpretable propagate strategies of messages in GNNs.
Vegetable Oil Blends after Frying and Sample Stored in Different Storage Packs (2011)

The work done in the reporting quarter concerns the micronutrient analysis of the blend in fresh oil samples and in samples stored under different storage conditions in various types of containers and as well as before and after frying. Conjugated dienes, p-anisidine value, specific gravity, copper and iron content of the oil samples under different conditions were also estimated, and the oxidative stability of the oils was determined. In particular the retention pattern of micronutrients, conjugated dienes and p-anisidine values in the blend under various storage conditions in different packs was studied.
Overcoming Soluble Target Interference in An Anti-Therapeutic Antibody Screening Assay For An Antibody–Drug Conjugate Therapeutic (2012)

The assay development and validation results showed that the addition of wheat germ agglutinin eliminates the interference from circulating CA125 without impacting the ability to detect ATA.
Cryoprocesses for Macromolecule Separation (2015)

AbstractThe success of plasma exchange in the treatment of autoimmune disease states has stimulated the development of various techniques to overcome the disadvantages of exchange and to provide for a more optimum therapy. Membrane filtration techniques, at present, offer the most promise to make such therapies available on a large scale. Cryofiltration, in particular, has within the past several years been applied clinically. The procedure has been shown to be safe. Replacement plasma products are not required. Serologic and clinical parameter improvements in the treatment of rheumatoid arthritis patients as well as patients with other autoimmune diseases have been shown.
유아 가정 수학문해 환경 척도 개발 및 타당화 연구 (2013)

본 연구는 유아의 수학적 경험을 제공하는 가정환경의 질을 측정하기 위한 유아 가정 수학무해 환경 척도를 개발하고 그 타당성을 검증하는데 목적이 있다. 본 연구대상은 유치원과 어린이집을 다니는 유아의 학부모 710명이었으며，수집된 자료는 ``내용타당도， 문항양호도，탐색적 요인분석，상관계수，문항 내적 합치도를 사용하여 개발된 척도의 타당도와 신뢰도를 검 승하였다. 유아 가정 수학문해 환경 척도의 타당도 건승을 위해 탐색적 요인 분석을 한 결과 ``수학 놀잇감 「및 활동자료``. ``유아의 일상생활``. ``유아의 수학학습활동``. ``부모의 참여 및 지원`` 의 4요인으로 추출되었으며，유아 가정 수학문해 환경 척도의 총점과 각 하위요인 간 상관；1수 도. 60-.80로 양호한 깃으로 나타났다. 또한 신뢰도 검증을 위한 Cronbach α 계수도. 83로 비교 석 높게 나타났다. 따라서 본 유아 가정 수학분해 환경 척도는 타당도와 신뢰도가 적합한 검사도구라 볼 수 있다．
Solving the correspondence problem using a Hopfield network (1994)

This paper proposes a Hopfield network to solve the correspondence problem in computer vision. The correspondence problem is that of identifying features in two images that are projections of the same entity in the 3D world. In this paper, correspondence is established between the edge points in the two images. The problem is first formulated as an optimization problem where an energy function is to be minimized. The optimization problem is then solved using a Hopfield network. The technique can also be considered as a constraint satisfaction process, where the nodes are the hypotheses (possible correspondences), and the links between them are the constraints. The weights of these links are derived by making some assumptions about the objects being imaged. Once started, the network converges rapidly to a good solution. The approach presented here is much simpler, and more elegant compared to the other techniques proposed in the literature. It is also easier to design and implement, and is more suitable for parallel implementation. The efficacy of this approach is demonstrated with experimental results on stereo images.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>
A versatile colour system capable of fruit sorting and accurate object classification (2003)

A colour system that can be used for high speed colour classification of fruit in an automatic sorting environment is proposed. The hue, saturation, and intensity (HSI) colour system derived from the red, green, blue system can be represented in various forms. Specifically it is the 'hue' part of the colour system that makes the HSI system so versatile. It is shown that pixels containing the H-I features can be classified using cluster analysis. Supervised and unsupervised classification has applications in colour segmentation and area measurements.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>
Arf Numerical Semigroups with Multiplicity 8 (2023)

In this study, we present a description of Arf numerical semigroups with multiplicity eight and given conductor.
A Randomized Trial of Vitamin E Supplementation and Cognitive Function in Women (2006)

Long-term use of vitamin E supplements did not provide cognitive benefits among generally healthy older women.
Oxidation of a metabolite of indomethacin (Desmethyldeschlorobenzoylindomethacin) to reactive intermediates by activated neutrophils, hypochlorous acid, and the myeloperoxidase system. (1998)

The use of indomethacin is associated with a relatively high incidence of adverse reactions such as agranulocytosis. Many other drugs associated with agranulocytosis are metabolized to reactive metabolites by activated neutrophils. Therefore, we studied the oxidation of indomethacin and its metabolites by activated neutrophils, myeloperoxidase (MPO) (the major oxidizing enzyme in neutrophils), and HOCl (the major oxidant produced by activated neutrophils). No oxidation of indomethacin by activated neutrophils was observed. However, desmethyldeschlorobenzoylindomethacin (DMBI), a major metabolite of indomethacin, was oxidized to a reactive iminoquinone that could be trapped with glutathione (GSH) or N-acetylcysteine (NAC) to form conjugates, with MH+ ions at m/z 511 and 367, respectively. No metabolism was detected in neutrophils that had not been activated, and the oxidation was inhibited by azide (which inhibits MPO) and by catalase (which catalyzes the breakdown of H2O2). In reactions with HOCl, the same reactive intermediate was formed; its mass spectrum, with a MH+ ion at m/z 204, was obtained by using a flow system in which the reactants were fed into a mixing chamber and the products flowed directly into the mass spectrometer. The same GSH and NAC conjugates were also observed when DMBI was oxidized by HOCl or by the MPO system, followed by addition of GSH or NAC. NMR data for the NAC conjugate indicated that the sulfur was substituted in the 4-position on the aromatic ring. The reactive intermediate generated from DMBI by activated neutrophils may be responsible for indomethacin-induced agranulocytosis.