gebhart/patrepeval huggingface dataset:
(Invited) What Can Electrochemistry Learn from Chess? (2018)

Batteries are complex electrochemical devices whose short-term and long-term operational lives are highly dependent on their construction, materials, and use cases. Models have been developed and used to improve the performance of batteries by providing different material design, model based control and model based battery management systems 1,2 . In recent literature, data science techniques have been used to accomplish a variety of tasks related to representing simulated data for control or estimation purposes 2,3,4 . Data science techniques have also been used to approximate optimal solutions to computationally difficult problems, such as the traveling salesman problem 5 . Rather than create a surrogate model to use with a typical optimization scheme, we will examine framing the problem as a parameter ‘correction’ endeavor. By doing so, it may be possible to retain all of the information present in a time series of error and leverage this information to very quickly go from a poor initial guess to a viable solution, after which time iterative optimization schemes can take over. The effectiveness of this approach (both in terms of efficiency and robustness) will be compared with the standard approaches. This method is inspired by DeepChess, a comparative deep neural network structure which plays successfully against world-class chess algorithms 4 . Acknowledgments The authors thank the United States Department of Energy (DOE) for the financial support for this work though the Advanced Research Projects Agency – Energy (ARPA-E) award #DEAR0000275, as well as the Clean Energy Institute (CEI) through the DIRECT program at the University of Washington. Part of the research has been supported by the Assistant Secretary for Energy Efficiency and Renewable Energy, Office of Vehicle Technologies of the U. S. Department of Energy through the Advanced Battery Materials Research (BMR) Program (Battery500 Consortium) References Y. Dai, and V. Srinivasan,. J. Electrochem. Soc., 163, A406 (2016). N. Dawson-Elli, S. B. Lee, M. Pathak, K. Mitra, and V. R. Subramanian, “Data Science Approaches for Electrochemical Engineers: An Introduction through Surrogate Model Development for Lithium-Ion Batteries,” J. Electrochem. Soc., vol. 165, no. 2, pp. A1–A15, Jan. 2018. D. A. C. Beck, J. M. Carothers, V. R. Subramanian, and J. Pfaendtner, “Data science: Accelerating innovation and discovery in chemical engineering,” AIChE J., vol. 62, no. 5, pp. 1402–1416, May 2016. Blake R. Hough, author. Jim Pfaendtner, degree supervisor. 2016 Thesis (Ph. D.)--University of Washington,2016. B. La Maire and V. Mladenov, “Comparison of Neural Networks for Solving the Travelling Salesman Problem,” in 11th Symposium on Neural Network Applications in Electrical Engineering,NEUREL 2012 - Proceedings, 2012. E. David, N. S. Netanyahu, and L. Wolf, “DeepChess: End-to-End Deep Neural Network for Automatic Learning in Chess,” arXiv:1711.09667 [cs, stat], vol. 9887, pp. 88–96, 2016.
Synthesis and Antileukemic Activity of Novel 4‐(3‐(Piperidin‐4‐yl) Propyl)Piperidine Derivatives (2011)

To explore the anticancer effect associated with the piperidine framework, several (substituted phenyl) {4-[3-(piperidin-4-yl)propyl]piperidin-1-yl} methanone derivatives 3(a-i) were synthesized. Variation in the functional group at N-terminal of the piperidine led to a set of compounds bearing amide moiety. Their chemical structures were confirmed by (1) H NMR, IR and mass spectra analysis. Among these, compounds 3a, 3d and 3e were endowed with antiproliferative activity. The most active compound among this series was 3a with nitro and fluoro substitution on the phenyl ring of aryl carboxamide moiety, which inhibited the growth of human leukemia cells (K562 and Reh) at low concentration. Comparison with other derivative (3h) results shown by LDH assay, cell cycle analysis and DNA fragmentation suggested that 3a is more potent to induce apoptosis.
Epithelial‐mesenchymal transition spectrum quantification and its efficacy in deciphering survival and drug responses of cancer patients (2014)

Epithelial-mesenchymal transition (EMT) is a reversible and dynamic process hypothesized to be co-opted by carcinoma during invasion and metastasis. Yet, there is still no quantitative measure to assess the interplay between EMT and cancer progression. Here, we derived a method for universal EMT scoring from cancer-specific transcriptomic EMT signatures of ovarian, breast, bladder, lung, colorectal and gastric cancers. We show that EMT scoring exhibits good correlation with previously published, cancer-specific EMT signatures. This universal and quantitative EMT scoring was used to establish an EMT spectrum across various cancers, with good correlation noted between cell lines and tumours. We show correlations between EMT and poorer disease-free survival in ovarian and colorectal, but not breast, carcinomas, despite previous notions. Importantly, we found distinct responses between epithelial- and mesenchymal-like ovarian cancers to therapeutic regimes administered with or without paclitaxel in vivo and demonstrated that mesenchymal-like tumours do not always show resistance to chemotherapy. EMT scoring is thus a promising, versatile tool for the objective and systematic investigation of EMT roles and dynamics in cancer progression, treatment response and survival.
Machine Learning of Discriminative Gate Locations for Clinical Diagnosis (2019)

High-throughput single-cell cytometry technologies have significantly improved our understanding of cellular phenotypes to support translational research and the clinical diagnosis of hematological and immunological diseases. However, subjective and ad hoc manual gating analysis does not adequately handle the increasing volume and heterogeneity of cytometry data for optimal diagnosis. Prior work has shown that machine learning can be applied to classify cytometry samples effectively. However, many of the machine learning classification results are either difficult to interpret without using characteristics of cell populations to make the classification, or suboptimal due to the use of inaccurate cell population characteristics derived from gating boundaries. To date, little has been done to optimize both the gating boundaries and the diagnostic accuracy simultaneously. In this work, we describe a fully discriminative machine learning approach that can simultaneously learn feature representations (e.g., combinations of coordinates of gating boundaries) and classifier parameters for optimizing clinical diagnosis from cytometry measurements. The approach starts from an initial gating position and then refines the position of the gating boundaries by gradient descent until a set of globally-optimized gates across different samples are achieved. The learning procedure is constrained by regularization terms encoding domain knowledge that encourage the algorithm to seek interpretable results. We evaluate the proposed approach using both simulated and real data, producing classification results on par with those generated via human expertise, in terms of both the positions of the gating boundaries and the diagnostic accuracy. © 2019 The Authors. Cytometry Part A published by Wiley Periodicals, Inc. on behalf of International Society for Advancement of Cytometry.
Toward the Synthesis of Yuzurimine-Type Alkaloids: Stereoselective Construction of the Heterocyclic Portions of Deoxyyuzurimine and Macrodaphnine (2019)

The heterocyclic portions of yuzurimine-type alkaloids, such as deoxyyuzurimine and macrodaphnine, were synthesized by using a stereoselective hydroboration-oxidation reaction to install the C20 methyl group, the intramolecular Mitsunobu reaction to construct the E-ring portion, and the intramolecular S<sub>N</sub>2 reaction to construct the F-ring portion as key steps.
Clinical Trial of Oxymorphone in Labour (1964)

The results of 166 assays of urinary gonadotrophins in women with carcinoma of the breast are described. There was a significantly lower excretion of gonadotrophins in women who were unresponsive to hormonal therapy and in " poor " clinical condition. The significance of these findings is briefly discussed.
Army Research Laboratory Ultra‐Wideband Crane SAR: System Overview and Results of Early Ground Penetrating Radar Studies (1995)

PreviousNext No AccessSymposium on the Application of Geophysics to Engineering and Environmental Problems 1995Army Research Laboratory Ultra‐Wideband Crane SAR: System Overview and Results of Early Ground Penetrating Radar StudiesAuthors: Keith A. SturgessLam NguyenMarc ResslerTuan TonT. O. GroschKeith A. SturgessU.S. Army Research Laboratory, 2800 Powder Mill Road, Adelphi,MD 20783‐1197, Lam NguyenU.S. Army Research Laboratory, 2800 Powder Mill Road, Adelphi,MD 20783‐1197, Marc ResslerU.S. Army Research Laboratory, 2800 Powder Mill Road, Adelphi,MD 20783‐1197, Tuan TonU.S. Army Research Laboratory, 2800 Powder Mill Road, Adelphi,MD 20783‐1197, and T. O. GroschLincoln Laboratory, Massachusetts Institute of Technology, P.O. Box 73, Lexington, MA 02173‐9108https://doi.org/10.4133/1.2922167 SectionsAboutPDF/ePub ToolsAdd to favoritesDownload CitationsTrack CitationsPermissions ShareFacebookTwitterLinked InRedditEmail Abstract Introductory paragraph for this paper is available only in the PDF and GZipped PS filesPermalink: https://doi.org/10.4133/1.2922167FiguresReferencesRelatedDetailsCited byResults of a remote sensing experiment using a low frequency ultra-wideband SAR to investigate the phenomenology of landmines Symposium on the Application of Geophysics to Engineering and Environmental Problems 1995ISSN (online):1554-8015Copyright: 1995 Pages: 977 publication data© 1995 Copyright © 1995 The Environmental and Engineering Geophysical SocietyPublisher:Environmental & Engineering Geophysical Society HistoryPublished Online: 30 Sep 2008 CITATION INFORMATION Keith A. Sturgess, Lam Nguyen, Marc Ressler, Tuan Ton, and T. O. Grosch, (1995), "Army Research Laboratory Ultra‐Wideband Crane SAR: System Overview and Results of Early Ground Penetrating Radar Studies," Symposium on the Application of Geophysics to Engineering and Environmental Problems Proceedings : 465-474. https://doi.org/10.4133/1.2922167 Plain-Language Summary PDF DownloadLoading ...
Formulation des dispersions (2003)

Pour le formulateur, les dispersions posent deux types de problèmes. Tout d'abord, ce ne sont jamais des systèmes stables, au sens de la thermodynamique. En effet, les particules solides sont séparées de la phase continue liquide par des interfaces, qui augmentent l'énergie libre de la dispersion par rapport à un système dans lequel tout le solide serait rassemblé en un seul domaine homogène. Il y a donc plusieurs évolutions possibles, par agrégation, mûrissement ou coalescence, que le formulateur doit maîtriser. Ensuite, les dispersions ont des propriétés originales, qui différent des propriétés des phases constituantes. Ces propriétés sont des propriétés mécaniques (écoulement de la dispersion lorsqu'elle est à l'état fluide, résistance mécanique lorsqu'elle est à l'état solide), des propriétés optiques (transparence ou opacité, réflectance ou diffusion de lumière), et des propriétés physico-chimiques (mouillage, adsorption ou adhésion, libération ou capture d'actifs). Le formulateur doit assurer, par son action sur les compositions de la phase dispersée et de la phase continue, que les propriétés d'usagede la dispersion justifient les efforts qu'on a déployés pour la fabriquer.
Super-resolution image synthesis using projections onto convex sets in the frequency domain (2005)

Optical imaging systems are often limited in resolution, not by the imaging optics, but by the light intensity sensors on the image formation plane. When the sensor size is larger than the optical spot size, the effect is to smooth the image with a rectangular convolving kernel with one sample at each non-overlapping kernel position, resulting in aliasing. In some such imaging systems, there is the possibility of collecting multiple images of the same scene. The process of reconstructing a de-aliased high-resolution image from multiple images of this kind is referred to as “super-resolution image reconstruction.” We apply the POCS method to this problem in the frequency domain. Generally, frequency domain methods have been used when component images were related by subpixel shifts only, because rotations of a sampled image do not correspond to a simple operation in the frequency domain. This algorithm is structured to accommodate rotations of the source relative to the imaging device, which we believe helps in producing a well-conditioned image synthesis problem. A finely sampled test image is repeatedly resampled to align with each observed image. Once aligned, the test and observed images are readily related in the frequency domain and a projection operation is defined.
Assembly of the Tripartite and RNA Condensates of the Respiratory Syncytial Virus Factory Proteins In Vitro: Role of the Transcription Antiterminator M2-1 (2023)

A wide variety of viruses replicate in liquid-like viral factories. Non-segmented negative stranded RNA viruses share a nucleoprotein (N) and a phosphoprotein (P) that together emerge as the main drivers of liquid-liquid phase separation. The respiratory syncytial virus includes the transcription antiterminator M<sub>2-1</sub>, which binds RNA and maximizes RNA transcriptase processivity. We recapitulate the assembly mechanism of condensates of the three proteins and the role played by RNA. M<sub>2-1</sub> displays a strong propensity for condensation by itself and with RNA through the formation of electrostatically driven protein-RNA coacervates based on the amphiphilic behavior of M<sub>2-1</sub> and finely tuned by stoichiometry. M<sub>2-1</sub> incorporates into tripartite condensates with N and P, modulating their size through an interplay with P, where M<sub>2-1</sub> is both client and modulator. RNA is incorporated into the tripartite condensates adopting a heterogeneous distribution, reminiscent of the M<sub>2-1</sub>-RNA IBAG granules within the viral factories. Ionic strength dependence indicates that M<sub>2-1</sub> behaves differently in the protein phase as opposed to the protein-RNA phase, in line with the subcompartmentalization observed in viral factories. This work dissects the biochemical grounds for the formation and fate of the RSV condensates in vitro and provides clues to interrogate the mechanism under the highly complex infection context.
On the Valuation of Federal Loan Guarantees to Corporations (1980)

ABSTRACT Since 1956, Federal Loan Guarantee Programs have expanded to the point where recipients of guarantees represent most segments of the economy. Considerable debate centers on the determination of the magnitude of the liability of the Federal Government that is represented by these programs. This paper illustrates how option pricing techniques may be used to obtain estimates of the purely pecuniary costs of loan guarantees, interest saving to the firm on senior and junior debt, and implicit present value profitability indices of projects.
Intelligent Reflecting Surface-Assisted Secret Key Generation With Discrete Phase Shifts in Static Environment (2021)

Physical layer secret key generation is a promising candidate to achieve one-time-pad encryption approach for the wireless communication system. However, in a static environment, the secret key rate is low due to the lack of channel time-variation. To solve this problem, this letter proposes a novel secret key generation scheme assisted by an intelligent reflecting surface with discrete phase shifts. In the scheme, legitimate nodes construct the dynamic time-varying channel by rapidly and randomly switching the phase of IRS elements. Then, channel coefficients are used to generate the secret key. Based on the IRS channel model, we derive the probability distribution of the channel coefficient and the expressions of the secret key rate. Furthermore, we optimize the secret key rate by adjusting the switching time of the IRS phase. Monte Carlo simulation and numerical results show that our proposed scheme can update the secret key in a static environment.
In situ combustion measurements of CO with diode-laser absorption near 23 µm (2000)

In situ measurements of CO concentration were recorded with tunable diode-laser absorption spectroscopy techniques in both the exhaust and the immediate post-flame regions of an atmospheric-pressure flat-flame burner operating on ethylene air. Two room-temperature cw single-mode InGaAsSb/AlGaAsSb diode lasers operating near 2.3 microm were tuned over individual transitions in the CO first overtone band (v' = 2 <-- v" = 0) to record high-resolution absorption line shapes in the exhaust duct [79 cm above the burner, approximately 470 K; R(15) transition at 4311.96 cm(-1)] and the immediate postflame zone [1.5 cm above the burner, 1820-1975 K; R(30) transition at 4343.81 cm(-1)]. The CO concentration was determined from the measured absorption and the gas temperature, which was monitored with type-S thermocouples. For measurements in the exhaust duct, the noise-equivalent absorbance was approximately 3 x 10(-5) (50-kHz detection bandwidth, 50-sweep average, 0.1-s total measurement time), which corresponds to a CO detection limit of 1.5 ppm m at 470 K. Wavelength modulation spectroscopy techniques were used to improve the detection limit in the exhaust to approximately 0.1 ppm m (approximately 500-Hz detection bandwidth, 20-sweep average, 0.4-s total measurement time). For measurements in the immediate postflame zone, the measured CO concentrations in the fuel-rich flames were in good agreement with chemical equilibrium predictions. These experiments demonstrate the utility of diode-laser absorption sensors operating near 2.3 microm for in situ combustion emission monitoring and combustion diagnostics.
Cross Modal Video Representations for Weakly Supervised Active Speaker Localization (2022)

An objective understanding of media depictions, such as inclusive portrayals of how much someone is heard and seen on screen such as in film and television, requires the machines to discern automatically who, when, how, and where someone is talking, and not. Speaker activity can be automatically discerned from the rich multimodal information present in the media content. This is however a challenging problem due to the vast variety and contextual variability in media content, and the lack of labeled data. In this work, we present a cross-modal neural network for learning visual representations, which have implicit information pertaining to the spatial location of a speaker in the visual frames. Avoiding the need for manual annotations for active speakers in visual frames, acquiring of which is very expensive, we present a weakly supervised system for the task of localizing active speakers in movie content. We use the learned cross-modal visual representations, and provide weak supervision from movie subtitles acting as a proxy for voice activity, thus requiring no manual annotations. Furthermore, we propose an audio-assisted post-processing formulation for the task of active speaker detection. We evaluate the performance of the proposed system on three benchmark datasets: i) AVA active speaker dataset, ii) Visual person clustering dataset, and iii) Columbia datset, and demonstrate the effectiveness of the cross-modal embeddings for localizing active speakers in comparison to fully supervised systems.
Automated estimation of contact angle on hydrophobic fibers using a microrobotic platform (2016)

This paper presents an automated computer vision algorithm for estimating contact angles that a droplet of probe liquid forms on hydrophobic fibers. A specially designed microrobotic platform is utilized in manipulating the microscopic fibers, shooting droplets in the scale of tens of nanoliters on the fibers and capturing images of the experiments. The images are then processed with the automated computer vision algorithm. The algorithm is proven to be reliable and repeatable with totally 29 experiments on five different bio-based fiber samples.
Transcriptome-wide mutation discovery in patients in a phase II clinical trial of first-line erlotinib for clinically selected patients with advanced non-small cell lung cancer (2009)

8102 Background: The purpose of this study was to clinically select a population of patients (pts) likely to benefit from erlotinib and to perform extensive genetic profiling of fresh tissue tumour to identify predictive biomarkers. Methods: Treatment was erlotinib 150 mg p.o. daily until disease progression. Eligibility criteria included: stage IIIB/IV NSCLC; no prior chemo; ECOG ≤2; at least 2 of the following 4 criteria: women, never-smokers, Southeast Asian origin, adenocarcinoma and/or BAC. All pts had baseline serum samples and a fresh frozen tumour biopsy. EGFR and KRAS were sequenced using traditional methods to identify known mutations of erlotinib. Transcribed coding regions of all other expressed genes were sequenced to uncover novel mutations and other genetic features. Results: From Sept-06 to Oct-08, 65 pts have been enrolled. Of these 60 have completed at least 8 wks of erlotinib (or progressed before 8 wks). 49F and 11M; 45 never smokers. PS 0/1/2: 10/39/11. 18 Caucasian and 42 Asian. Pathology: 44 ACA; 3 BAC;1 squamous carcinoma; 13 NSCLC NOS. Responses: PR - 21 (35%); SD - 24 (DCR 75%); PD - 10; NE - 5. 85% did not progress at 8 weeks. 19 of 51 (37%) pre-treatment samples had an EGFR mutation. 10 of the 28 pts with response data (24pts still on drug) had a PR and 7 of these had either an LREA deletion or L858R point mutation. 1 of 3 post-treatment samples developed a T790M mutation on erlotinib. 3 of 51 pts have KRAS mutations. Analysis of over 21 Giga basepairs of aligned transcriptome sequencing data from 20 tumour samples has uncovered 1089 putative non-conservative gene mutations of which 15 are seen in multiple tumours: TUBA1C, EPS8L1, ARID4B, RPL22, C20orf52, CCT8, HLA-DRB5, TRIP6, and PLP2 in 4 tumours, C20orf52 and CTSL1 in 5 tumours, and SERF2, TMEM173, and an uncharacterized gene in 6 tumours. Conclusions: Clinical selection of pts enriches the EGFR mutation positive and KRAS mutation negative population and leads to high rates of non-progression. Full tumour RNA analysis identified several recurrent mutations that may describe mechanisms of erlotinib response and resistance. The discovery of novel mutations in multiple pts suggests patterns that may shed light on lung cancer specific behaviour. [Table: see text]
A New Catch-and-release Purification Method Using a Levulinyl Group as a Tag and Its Application to Oligosaccharide Synthesis (2008)

Abstract Products possessing a levulinyl group were selectively isolated from reaction mixtures using a new resin-capture method and a polymer-supported aminooxy group. Successive treatment with NaOH in MeOH readily liberated purified products from the resins. Applications of this method to oligosaccharide syntheses are described.
Image Inpainting Based on Compressed Sensing (2011)

An inpainting method is proposed to restore the image containing some missing patches. Based on the spartity of images, the method translates the problem of image inpainting into image reconstruction in compressed sensing. The inpainting model is solved using the split iteration. Simulated image inpainting results demonstrate the efficiency of the proposed method.