gebhart/patrepeval huggingface dataset:
AC losses in thin superconductors: the integral equation method applied to stacks and windings (2009)

In this paper we present a method for computing transport current ac losses in interacting thin superconductors. The method solves the integral equations for the sheet current density distribution and is specifically developed for those configurations where the symmetry of the current density distributions allows writing the equation in a self-consistent form, without the need for using an auxiliary 2D model to describe the interaction between superconducting tapes. This results in very short computation times and therefore the model can be very useful for optimizing the design of superconducting devices. The method has been tested for different cases of practical applications and the ac loss results have been compared with those obtained with analytical models and with experiments.
Modeling the Effect of Thermal Barrier Coatings on HCCI Engine Combustion Using CFD Simulations with Conjugate Heat Transfer (2019)

&lt;div class="section abstract"&gt;&lt;div class="htmlview paragraph"&gt;Thermal barrier coatings with low conductivity and low heat capacity have been shown to improve the performance of homogeneous charge compression ignition (HCCI) engines. These coatings improve the combustion process by reducing heat transfer during the hot portion of the engine cycle without the penalty thicker coatings typically have on volumetric efficiency. Computational fluid dynamic simulations with conjugate heat transfer between the in-cylinder fluid and solid piston of a single cylinder HCCI engine with exhaust valve rebreathing are carried out to further understand the impacts of these coatings on the combustion process. For the HCCI engine studied with exhaust valve rebreathing, it is shown that simulations needed to be run for multiple engine cycles for the results to converge given how sensitive the rebreathing process is to the residual gas state. The effect of thermal barrier coatings on the piston surface is explored using the properties of Yttria-Stabilized Zirconia (YSZ) and Gadolinium Zirconate (GdZr) top coatings with two different thicknesses. Heat flux measurements from an experimental engine with an all metal piston and YSZ and GdZr thermal barrier coatings are compared to the simulation results and the simulation is found to under predict heat transfer. Reducing the conductivity of the coating advances combustion as does increasing the thickness of the coating.&lt;/div&gt;&lt;/div&gt;
A Novel Metabolite of Antituberculosis Therapy Demonstrates Host Activation of Isoniazid and Formation of the Isoniazid-NAD+Adduct (2011)

One of the most effective and widely used antituberculosis (anti-TB) drugs is isoniazid (INH), a prodrug activated via oxidation that forms an adduct with NAD(+) to inhibit NADH-dependent targets of Mycobacterium tuberculosis, such as enoyl-acyl carrier protein reductase (InhA). The metabolic by-products and potentially toxic intermediates resulting from INH therapy have been identified through a large body of work. However, an INH-NAD adduct or structures related to this adduct have not been identified in specimens from human TB patients or animal models of TB. Analyses by mass spectrometry of urine collected from TB patients in a study conducted by the NIAID-funded Tuberculosis Research Unit identified 4-isonicotinoylnicotinamide (C(12)H(9)N(3)O(2)) as a novel metabolite of INH therapy. This compound was formed by M. tuberculosis strains in a KatG-dependent manner but could also be produced by mice treated with INH independent of an M. tuberculosis infection. Thus, the 4-isonicotinoylnicotinamide observed in human urine samples is likely derived from the degradation of oxidized INH-NAD adducts and provides direct evidence of host INH activation.
Space Sharing Effects on Manycore Systems (2019)

Computing hardware has changed from a single core to a multi-core environment, and programming technique have also shifted from a single thread to multi-threaded model. In a multicore environment where resources are limited, time sharing makes multiple application running simultaneously by using resource efficiently. However, in manycore systems, time sharing technique generates kernel noise and it results in a performance degradation. To solve this problem, this paper proposes a space sharing scheme suitable for manycore systems. Space sharing scheme consists of one core-one thread and one core-one memory, ensuring that threads executed without competing kernel resources. Through experiments, we confirmed that space sharing provides scalability compared to time sharing and reduce kernel noise. In addition, we confirmed its performance through a simple HPC application; Edge-detection. We discover that space sharing can create resource waste for I/O intensive applications, which is rather a performance degradation. This problem should be solved through I/O acceleration later.
Activation of NF-κB-dependent gene expression by silica in lungs of luciferase reporter mice (2002)

Occupational exposure to crystalline silica is associated with the development of pulmonary inflammation and silicosis, yet how silica initiates pulmonary fibrosis and which cell types are involved are unclear. In studies here, we hypothesized that silica particles interact initially with pulmonary epithelial cells and alveolar macrophages (AMs) to cause transcriptional activation of nuclear factor (NF)-kappaB-regulated genes encoding inflammatory cytokines. Exposure of NF-kappaB luciferase reporter mice intratracheally to silica or lipopolysaccharide (LPS), but not the nonfibrogenic particle titanium dioxide (TiO(2)), increased immunoreactivity of luciferase protein in bronchiolar epithelial cells and AMs. Ribonuclease protection assays revealed significant (P < or = 0.05) increases in mRNA levels of inducible nitric oxide synthase, tumor necrosis factor-alpha, macrophage inflammatory protein-2, macrophage chemotactic protein-1 (MCP-1), interferon-gamma, interleukin (IL)-6, and IL-12 in lung homogenates of reporter mice after exposures to silica or LPS. Immunoreactivity of MCP-1 in these animals was localized to AMs and epithelial cells. These data are the first to show activation of NF-kappaB in situ by fibrogenic particles in pulmonary epithelial cells and AMs. Increased expression of NF-kappaB-related inflammatory cytokines by these cell types, which first encounter silica after inhalation, may be critical to the initiation of silica-associated lung diseases, thus providing a rationale for focusing on NF-kappaB in preventive and therapeutic strategies.
Using “Omics” as a Novel Tool to Identify Mitochondrial Dysfunction and Metabolic Dysregulation as Critical Factors in Brain Death Induced Kidney Injury. (2014)

Introduction: To gain better insight into patterns of injury and repair in kidneys from brain dead (BD) donors, we used next generation proteomics and metabolomics to identify the effect of BD on the protein signature of rodent renal samples. Methods: BD was induced in ventilated Fischer rats (250-300g) using a Fogarty balloon catheter inflated in the epidural space (n=6) vs sham controls (n=6). Following BD, ventilation was continued for 4 h. Cortical proteins were extracted using in-solution trypsin digestion and subjected to proteomic analysis using liquid chromatography mass spectrometry (LC-MS/MS). Proteins were identified based on having a >2 peptide sequence homology and analysed using Progenesis and Ingenuity Pathway Analysis (IPA). Samples were prepared for 1H-nuclear magnetic resonance (NMR) spectroscopy metabolomic analysis. Data was analysed as normalised intensity ratios and significantly differentially expressed metabolites determined (p<0.05, Prism 6 Graphpad). Results: Over 1400 proteins were identified, with 43 proteins being differentially expressed between BD and control samples (2 fold up or down regulated, p<0.05). Mitochondrial proteins and proteins concerning small molecule biochemistry and metabolism were the top dysregulated canonical pathways (IPA).Figure: No Caption available.Evaluation of the metabolome revealed significantly increased amounts of lactate (p=0.04) in addition to alterations in other metabolites and intermediaries including increased isoleucine (p=0.002) and decreased AMP (p= 0.004), TMAO (p= 0.015) and aspartate (p=0.015). Creatinine, signifying renal dysfunction, was higher in the BD group in comparison to controls (p=0.009). Conclusion: This study underpins the importance of mitochondrial dysfunction and metabolic disturbances in the aetiology of BD induced kidney injury, suggesting a dependence on anaerobic metabolism of rodent kidneys in the BD state. To prevent kidney injury in the BD donor requires a multifaceted approach targeting protecting against mitochondrial damage and metabolic disturbance.
Gas Chromatographic Column for the Viking 1975 Molecular Analysis Experiment (1975)

A gas chromatographic column has been developed for use in the remote analysis of the martian surface. The column, which utilizes a liquid-modified organic adsorbent (Tenax) as the stationary phase, provides efficient transmission and resolution of nanogram quantities of organic materials in the presence of millionfold excesses of water and carbon dioxide.
Effects of different types of unsymmetrical squaraines on the material properties and Coulomb interactions in organic photovoltaic devices (2018)

A device architecture investigation with varying spacer thickness confirmed that Coulomb interactions exist between the donor phase and electrons in the PC<sub>71</sub>BM phase.
Computing in molecular biology: mapping and interpreting biological information (1991)

Computational challenges for computer scientists in the task of determining the structure of molecules and their components are examined. Problems in sequence analysis, information storage and retrieval and protein structure prediction are summarized. A brief overview of molecular biology provides some context for the problems described.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>
COVID-19 diagnostics in context (2020)

The coronavirus disease 2019 (COVID-19) pandemic has highlighted the need for different types of diagnostics, comparative validation of new tests, faster approval by federal agencies, and rapid production of test kits to meet global demands. In this Perspective, we discuss the utility and challenges of current diagnostics for COVID-19.
Subfemtosecond pulse generation and measurement (2003)

Summary from only given. We report the observation of light-field induced modulation of the width of the kinetic energy distribution of photoelectrons from an atomic gas (krypton) excited by an ultrashort 90eV soft-X-ray pulse in the presence of a 7-fs few cycle light pulse carried at a wavelength of 750 nm.
Size-Selective Growth and Stabilization of Small CdSe Nanoparticles in Aqueous Solution (2009)

Using cysteine and its derivatives as capping molecules, we investigated the influence of the physical structure and chemical nature of capping molecules on the selective growth and stabilization of small CdSe nanoparticles (NPs) in aqueous solution at room temperature. Our investigations revealed specific roles for each functional group of cysteine, and we could correlate this structure and nature of the capping molecules with the size, size restriction, size distribution, and stability of the NPs. For selective growth and stabilization of the NPs in aqueous solution, their capping molecules should have at least one functional group with strong nucleophilicity as well as another free, charged functional group. Capping molecules acting as a monodentate ligand were more effective than those acting as a bidentate ligand for restricting the NPs to a smaller size, whereas the former was less effective than the latter for getting a narrower NP size distribution. Capping molecules with relatively bulky spatial geometry near the ligand-NP interface resulted in the formation of NPs with poor short- and long-term stabilities, whereas those having relatively compact spatial geometry near the interface led to NPs with at least moderate short-term stability. We saw that capping molecules having relatively compact outermost spatial geometry led to NPs with excellent long-term stability, whereas those having relatively bulky outermost spatial geometry produced NPs with at most only moderate long-term stability. Our results clearly showed general trends for the possibility of selective growth of stable semiconductor NPs with particular sizes in aqueous solution.
Differentiation of Boc‐ α,β‐ and β,α‐peptides and a pair of diastereomeric β,α‐dipeptides by positive and negative ion electrospray tandem mass spectrometry (ESI‐MS/MS) (2005)

Positive and negative ion electrospray ionization (ESI) tandem mass spectral study of a new series of hybrid peptides, viz, BocN-alpha,beta-peptides and BocN-beta,alpha-peptides, synthesized from C-linked carbo-beta3-amino acids [Caa (S)] and L-Ala has been carried out. The alpha,beta-peptides have been differentiated from beta,alpha-peptides by the collision-induced dissociation (CID) of [M + H]+ and [M - H]- ions in positive and negative ion ESI-MS respectively. The fragment ion [M + H - C(CH3)3 + H]+ formed from [M + H]+ ions by the loss of 2-methyl-prop-2-ene in alpha,beta-peptides with L-Ala at the N-terminus is insignificant or totally absent for beta,alpha-peptides which have the Caa (S) at N-terminus. The fragment ion [M - H-C(CH3)3OH - HNCO]- formed from [M - H]- of beta,alpha-peptide acids is totally absent for alpha,beta-peptide acids. This has been attributed to the absence of the beta-methylene group in alpha,beta-peptides, and the participation of the beta-methylene group in the loss of HNCO in beta,alpha-peptide acids is confirmed by the deuteration experiments. The CID of [M + H-Boc + H]+ ions of these peptides also produce characteristic fragmentation. In the CID spectra of alpha,beta-peptides, the b(n)+ ions and the resulting y(n)+ ions occur at a mass difference of 243 and 71 Da corresponding to the successive losses of Caa and L-Ala, whereas a mass difference of 71 and 243 Da is observed for beta,alpha-peptides. In contrast to the CID of protonated peptides, the CID of [M - H]- ions of the alpha,beta- and beta,alpha-peptide acids do not give b(n)- ions and show abundant z(n) (-) ions. Further, a pair of diastereomeric dipeptide esters and acids have been distinguished by the CID of [M + H]+ ions. The loss of 2-methyl-prop-2-ene is more pronounced for Boc-NH-Caa(R)-D-Ala-OCH3 (21) and Boc-NH-Caa(R)-D-Ala-OH (23) with Caa (R) at the N-terminus, whereas it is totally absent for Boc-NH-Caa (S)-D-Ala-OCH3 (22) and Boc-NH-Caa(S)-D-Ala-OH (24) peptides, which have Caa (S) at the N-terminus. Thus, on the basis of our previous and present studies, we propose that the CID of [M + H]+ ions provides a simple and useful method for distinguishing the configuration of Caa (S or R) at the N-terminus of BocN-carbo beta,alpha- and beta,beta-dipeptides.
Pilot study of newborn screening for six lysosomal storage diseases using Tandem Mass Spectrometry (2016)

A 6-plex MS/MS assay for 6 lysosomal enzymes can be successfully performed in a NBS laboratory. The analytical ranges (enzyme-dependent assay response for the quality control HIGH sample divided by that for all enzyme-independent processes) for the 6-enzymes with the MS/MS is 5- to 15-fold higher than comparable fluorimetric assays using 4-methylumbelliferyl substrates. The rate of screen positive detection is consistently lower for the MS/MS assay compared to the fluorimetric assay using a digital microfluidics platform.
Colloidal Cutin-Like Substances Cross-Linked to Siderophore Decomposition Products Mobilizing Plutonium from Contaminated Soils (2008)

Relatively recently, inorganic colloids have been invoked to reconcile the apparent contradictions between expectations based on classical dissolved-phase Pu transport and field observations of "enhanced" Pu mobility (Kersting et al. Nature 1999, 397, 56-59). A new paradigm for Pu transport is mobilization and transport via biologically produced ligands. This study for the first time reports a new finding of Pu being transported, at sub-pM concentrations, by a cutin-like natural substance containing siderophore-like moieties and virtually all mobile Pu. Most likely, Pu is complexed by chelating groups derived from siderophores that are covalently bound to a backbone of cutin-derived soil degradation products, thus revealing the history of initial exposure to Pu. Features such as amphiphilicity and small size make this macromolecule an ideal collector for actinides and other metals and a vector for their dispersal. Cross-linking to the hydrophobic domains (e.g., by polysaccharides) gives this macromolecule high mobility and a means of enhancing Pu transport. This finding provides a new mechanism for Pu transport through environmental systems that would not have been predicted by Pu transport models.
Supplementary Table 3 from An Expression Signature as an Aid to the Histologic Classification of Non–Small Cell Lung Cancer (2023)

&lt;p&gt;Validation of the Classifier in FFPE samples&lt;/p&gt;
From barriers to learning in the idea garden: An empirical study (2012)

How can end-user programming environments better help their users overcome programming barriers? We have been investigating an approach called Idea Gardening, which addresses this problem by helping end users to help themselves overcome barriers in the context of “doing”. In this paper, we report on a qualitative empirical study of how effectively an Idea Garden prototype helped end users overcome programming barriers in the CoScripter environment, and the extent to which participants learned after interacting with our features. Our results showed that 9 out of 10 participants who encountered barriers and then used the Idea Garden, overcame their barriers. Further, all 9 went on to demonstrate evidence of having learned the programming concepts, patterns, and strategies relevant to overcoming these barriers.
Comparison of ultrasonic measurements of nulliparous versus multiparous cervices (2011)

Premature remodeling of uterine cervical microstructure plays a large role in preterm birth. Invasive studies confirm that collagen, the major contributor to cervical strength, undergoes rearrangement long before changes associated with pre-delivery remodeling (shortening, softening, dilation) are grossly detectable. However, a lack of noninvasive technology sophisticated enough to interrogate the cervical microstructure makes quantitative assessment of the cervix challenging. Therefore, clinical cervical assessment is subjective. For instance, clinicians can feel a difference in softness between a nulliparous (never had babies) and multiparous (had babies) cervix. Further, they become concerned about preterm birth risk when the cervix feels “too soft” in midgestation. The inability to objectively describe these parameters impedes clinical management; in other words, currently there is no means to answer critical questions such as “how soft is too soft?”. Our preliminary results using quantitative ultrasound (QUS) techniques and shear wave sound speeds (SWS) to objectively describe cervical microstructure and softening suggest that these measurements are sensitive enough to detect differences between the nonpregnant nulliparous and multiparous cervix, and thus are promising for quantitative assessment of the cervix in pregnancy.
Generalisation Error Bounds for Sparse Linear Classifiers (2000)

We provide small sample size bounds on the generalisation error of linear classifiers that are sparse in their dual representation given by the expansion coefficients of the weight vector in terms of the training data. These results theoretically justify algorithms like the Support Vector Machine, the Relevance Vector Machine and K-nearest-neighbour. The bounds are a-posteriori bounds to be evaluated after learning when the attained level of sparsity is known. In a PAC-Bayesian style prior knowledge about the expected sparsity is incorporated into the bounds. The proofs avoid the use of double sample arguments by taking into account the sparsity that leaves unused training points for the evaluation of classifiers. We furthermore give a PAC-Bayesian bound on the average generalisation error over subsets of parameter space that may pave the way combining sparsity in the expansion coefficients and margin in a single bound. Finally, reinterpreting a mistake bound for the classical perceptr...
Predicting Classifier Performance with Limited Training Data: Applications to Computer-Aided Diagnosis in Breast and Prostate Cancer (2015)

Clinical trials increasingly employ medical imaging data in conjunction with supervised classifiers, where the latter require large amounts of training data to accurately model the system. Yet, a classifier selected at the start of the trial based on smaller and more accessible datasets may yield inaccurate and unstable classification performance. In this paper, we aim to address two common concerns in classifier selection for clinical trials: (1) predicting expected classifier performance for large datasets based on error rates calculated from smaller datasets and (2) the selection of appropriate classifiers based on expected performance for larger datasets. We present a framework for comparative evaluation of classifiers using only limited amounts of training data by using random repeated sampling (RRS) in conjunction with a cross-validation sampling strategy. Extrapolated error rates are subsequently validated via comparison with leave-one-out cross-validation performed on a larger dataset. The ability to predict error rates as dataset size increases is demonstrated on both synthetic data as well as three different computational imaging tasks: detecting cancerous image regions in prostate histopathology, differentiating high and low grade cancer in breast histopathology, and detecting cancerous metavoxels in prostate magnetic resonance spectroscopy. For each task, the relationships between 3 distinct classifiers (k-nearest neighbor, naive Bayes, Support Vector Machine) are explored. Further quantitative evaluation in terms of interquartile range (IQR) suggests that our approach consistently yields error rates with lower variability (mean IQRs of 0.0070, 0.0127, and 0.0140) than a traditional RRS approach (mean IQRs of 0.0297, 0.0779, and 0.305) that does not employ cross-validation sampling for all three datasets.
Deep Graph Pose: a semi-supervised deep graphical model for improved animal pose tracking (2020)

Abstract Noninvasive behavioral tracking of animals is crucial for many scientific investigations. Recent transfer learning approaches for behavioral tracking have considerably advanced the state of the art. Typically these methods treat each video frame and each object to be tracked independently. In this work, we improve on these methods (particularly in the regime of few training labels) by leveraging the rich spatiotemporal structures pervasive in behavioral video — specifically, the spatial statistics imposed by physical constraints (e.g., paw to elbow distance), and the temporal statistics imposed by smoothness from frame to frame. We propose a probabilistic graphical model built on top of deep neural networks, Deep Graph Pose (DGP), to leverage these useful spatial and temporal constraints, and develop an efficient structured variational approach to perform inference in this model. The resulting semi-supervised model exploits both labeled and unlabeled frames to achieve significantly more accurate and robust tracking while requiring users to label fewer training frames. In turn, these tracking improvements enhance performance on downstream applications, including robust unsupervised segmentation of behavioral “syllables,” and estimation of interpretable “disentangled” low-dimensional representations of the full behavioral video. Open source code is available at https://github.com/paninski-lab/deepgraphpose .