gebhart/patrepeval huggingface dataset:
Block Adjustment of High-Resolution Satellite Images Described by Rational Polynomials (2003)

model provides a rigorous, accurate method to block adjust This paper describes how to block adjust high-resolution Ikonos data outside of the ground stations. satellite imagery described by Rational Polynomial Coefficient This publication of a technique for block adjusting Ikonos (RPC) camera models and illustrates the method with an Ikonos images described by RPC data is motivated by a desire to satisfy example. By incorporating a priori constraints into the the needs of those users who would like to perform their own adjustment model, multiple independent images can be block adjustment, and to ensure that Ikonos images are proadjusted with or without ground control. The RPC block cessed in such way as to consistently achieve the highest possiadjustment model presented in this paper is directly related ble accuracy. In developing the adjustment model described to geometric properties of the physical camera model. Multiple here, the authors had access to the complete description of physical camera model parameters having the same net effect Ikonos imaging geometry, familiarity with all of the satellite on the object-image relationship are replaced by a single maneuvering modes, the resources of extensive test ranges and adjustment parameter. Consequently, the proposed method is imagery with which to test and validate, and the experience numerically more stable than the traditional adjustment of gained calibrating, testing, and troubleshooting Ikonos metric exterior and interior orientation parameters. This method is projects. generally applicable to any photogrammetric camera with a narrow field of view, calibrated, stable interior orientation, and Physical Camera Models accurate a priori exterior orientation data. As demonstrated Owing to the dynamic nature of satellite image collection, phoin the paper, for Ikonos satellite imagery, the RPC block togrammetric processing of satellite imagery is more compliadjustment achieves the same accuracy as the ground station cated than is aerial frame camera processing. Aerial cameras block adjustment with the full physical camera model. acquire the entire image at an instant of time with a unique exposure station and orientation. High-resolution pushbroom Background satellite cameras, including Ikonos, use linear sensor arrays
Distinguishing dose, focus, and blur for lithography characterization and control (2007)

We derive a physical model to describe the dependence of pattern dimensions on dose, defocus and blur. The coefficients of our model are constants of a given lithographic process. Model inversion applied to dimensional measurements then determines effective dose, defocus and blur for wafers patterned with the same process. In practice, our approach entails the measurement of proximate grating targets of differing dose and focus sensitivity. In our embodiment, the measured attribute of one target is exclusively sensitive to dose, whereas the measured attributes of a second target are distinctly sensitive to defocus and blur. On step-and-scan exposure tools, z-blur is varied in a controlled manner by adjusting the across slit tilt of the image plane. The effects of z-blur and x,y-blur are shown to be equivalent. Furthermore, the exposure slit width is shown to determine the tilt response of the grating attributes. Thus, the response of the measured attributes can be characterized by a conventional focus-exposure matrix (FEM), over which the exposure tool settings are intentionally changed. The model coefficients are determined by a fit to the measured FEM response. The model then fully defines the response for wafers processed under "fixed" dose, focus and blur conditions. Model inversion applied to measurements from the same targets on all such wafers enables the simultaneous determination of effective dose and focus/tilt (DaFT) at each measurement site.
Reactive Polymer Coatings for Biological Applications (2008)

The design of biologically active surfaces offers a new dimension to the development of advanced materials for biomedical and microfluidic applications. Our approach to creating these surfaces is via the fabrication of vapor-based reactive polymer coatings, which provide sophisticated functional groups for the immobilization of biological ligands. Chemical vapor deposition (CVD) polymerization has been used to prepare a wide spectrum of functionalized poly(p-xylylenes). The applicability of a few of these reactive surfaces as stable platforms for biomimetic modifications is discussed in this review.
Graphene plasmonics for terahertz photonics (2016)

Graphene plasmonics has the potential to revolutionize terahertz technology — the last great underdeveloped frequency band of electromagnetic waves. We describe here recent research on large-area tunable graphene plasmonic materials and devices for use in terahertz detectors, modulators, and filters.
A 1V 0.25uW inverter-stacking amplifier with 1.07 noise efficiency factor (2017)

This paper presents a highly power efficient amplifier. By stacking inverters and splitting the capacitor feedback network, the proposed amplifier achieves 6-time current reuse, thereby significantly boosting gm and lowering noise but without increasing power. A novel biasing scheme is devised to ensure robust operation under 1V supply. A prototype in 180nm CMOS has 5.5uV rms noise within 10kHz BW while consuming only 0.25uW, leading to a noise efficiency factor (NEF) of 1.07, which is the best among reported amplifiers.
Design of a new series of potent and selective beta-3 adrenergic receptor (β3-AdrR) antagonists for the treatment of acute decompensated heart failure (2022)

The design of a new series of β3-Adrenergic receptor (β3-AdrR) antagonists is described. The use of a spiro building block in the core of the molecule provided novel compounds with reduced aromaticity and antagonist activity at the human β3-AdrR. A shortening of this core and exploration of a series of sulfonamide derivatives produced compounds with good selectivity over β1-AdrR and β2-AdrR. Alternative substitutions on the terminal aromatic rings produced compounds with further improvements in selectivity, particularly with respect to β2-AdrR. Finally, the incorporation of heteroatoms into the fused aromatic ring provided significant improvements in solubility. One compound from the series was shown to antagonize the effect of an exogenously administered β3-AdrR agonist on left ventricular pressure in the rat, making this a series of high interest for further Lead Optimization.
Fast echo cancellation in a voice-processing system (1992)

An efficient adaptive echo cancellation scheme where near-end hybrid echoes are considered the dominant factor in poor DTMF detection and speech recognition in the presence of outbound speech is described. The incorporation of distinct and separate adapt and cancel filters is crucial in attaining significant echo reduction. The adapt filter performs nonreal-time identification of the echo transfer function with buffered transmit and receive data that meet specific criteria. The adaptation implementation is controlled by what has been termed cycle steal; after the required functions have been performed, the remaining real time is utilized for adaptation. After each convergence interval, a windowed set of coefficients is passed from the adapt filter to the cancel filter. The cancel filter performs echo cancellation in real time with the defined coefficients and produces dramatic improvements in measured DTMF detection performance.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>
The primary structure of a fungal chitin deacetylase reveals the function for two bacterial gene products. (1993)

Chitin deacetylase (EC 3.5.1.41) hydrolyzes the N-acetamido groups of N-acetyl-D-glucosamine residues in chitin. A cDNA to the Mucor rouxii mRNA encoding chitin deacetylase was isolated, characterized, and sequenced. Protein sequence comparisons revealed significant similarities of the fungal chitin deacetylase to rhizobial nodB proteins and to an uncharacterized protein encoded by a Bacillus stearothermophilus open reading frame. These data suggest the functional homology of these evolutionarily distant proteins. NodB is a chitooligosaccharide deacetylase essential for the biosynthesis of the bacterial nodulation signals, termed Nod factors. The observed similarity of chitin deacetylase to the B. stearothermophilus gene product suggests that this gene encodes a polysaccharide deacetylase.
An Analysis of Persistent Memory Use with WHISPER (2017)

Emerging non-volatile memory (NVM) technologies promise durability with read and write latencies comparable to volatile memory (DRAM). We define Persistent Memory (PM) as NVM accessed with byte addressability at low latency via normal memory instructions. Persistent-memory applications ensure the consistency of persistent data by inserting ordering points between writes to PM allowing the construction of higher-level transaction mechanisms. An epoch is a set of writes to PM between ordering points.
V2O3 Anode Catalyst for Solid Oxide Fuel Cell using H2S-containing Hydrogen (2008)

A new vanadium oxide based anode catalyst V2O3-YSZ was developed for the purpose of direct use of hydrogen sulfide-containing hydrogen in solid oxide fuel cell systems. H2S-containing hydrogen (H2 balanced with 5000 ppmv H2S) and air were used as anode and cathode feed gas, respectively. The V2O3-YSZ catalyst showed good catalytic activity for conversion of H2S-containing hydrogen in the SOFC systems. Current density over 450 mA/cm2 at 0.5 V and maximum power density of 160 mW/cm2 (at 400 mA/cm2) were obtained at 900åC. Conductivity tests showed that the V2O3 catalyst had good electronic conductivity in hydrogen atmosphere. XRD and XPS analysis showed that the new catalyst was stable in the environment of H2S-rich hydrogen, and this was confirmed experimentally in fuel cell tests.
Managing the attractive magnetic force between an untethered magnetically actuated tool and a rotating permanent magnet (2013)

Untethered magnetic devices, such as magnetic microrobots and magnetically actuated capsule endoscopes, stand to significantly impact the field of minimally invasive medicine. These devices, which we refer to as magnetically actuated tools (MATs), are often controlled using electromagnets, which can be expensive to scale clinically. Due to their potential for low-cost and high strength, permanent magnets are being considered for MAT actuation. Great care must be taken for in vivo medical applications, however, as systems using single permanent magnets typically generate an attractive force, which may cause trauma if uncontrolled. In this paper, we present techniques for managing the attractive magnetic force. We find that in the case of rotating MATs actuated using a single rotating permanent magnet (RPM), for which magnetic torque is the primary form of actuation, the attractive magnetic force can be substantially reduced in magnitude and the time-averaged attractive component eliminated when operating the MAT such that magnetic torque is maximized. We provide experimental demonstration that validates and illustrates the force management strategies presented.
Improvement of the specific infectivity of the rubella virus (RUB) infectious clone: determinants of cytopathogenicity induced by RUB map to the nonstructural proteins (1997)

A plasmid, Robo102, which contains a cDNA copy of the rubella virus (RUB) genomic RNA from which infectious transcripts can be synthesized in vitro, was recently developed (C. Y. Wang, G. Dominguez, and T. K. Frey, J. Virol. 68:3550-3557, 1994). To increase the specific infectivity of Robo102 transcripts (approximately 5 plaques/10 microg of transcripts), a modified reverse transcription-PCR method was used to amplify nearly 90% of the RUB genome in three fragments, which were then used to replace the corresponding fragments in Robo102. Replacement of a fragment covering nucleotides (nt) 5352 to 9759 of the RUB genome yielded a construct, Robo202, which produced highly infectious transcripts (10(4) plaques/microg), indicating the presence of an unrecognized deleterious mutation (or mutations) in this region of the Robo102 cDNA. Robo102 was based on the w-Therien strain of RUB, which forms opaque plaques in Vero cells, while the PCR replacement fragments were generated from a variant, f-Therien, which produces clear plaques in Vero cells. Although Robo202 contains over 4,000 nt from f-Therien, Robo202 virus produces opaque plaques. However, when the other two PCR fragments amplified from f-Therien (nt 1 to 1723 and nt 2800 to 5352) were introduced into Robo202, the resulting construct, Robo302, yielded transcripts that produced a virus that formed clear plaques. This indicates that the determinants of plaque morphology map to the regions of the genome covered by these two fragments, both of which are in the nonstructural open reading frame. Generation of Robo202/302 chimeras indicated that the most 5' terminal fragment (nt. 1 to 1723) had the greatest effect on plaque morphology. The plaque morphology was correlated with the ability of the viruses to kill infected cells. The only difference at the molecular level detected among the viruses was that the more cytopathic viruses produced more nonstructural proteins than did the less cytopathic viruses. This finding, as well as the mapping of the genetic determinants to the region of the genome encoding these proteins, indicates that the nonstructural proteins can mediate cell killing.
Joint Demosaicing and Denoising via Learned Nonparametric Random Fields (2014)

We introduce a machine learning approach to demosaicing, the reconstruction of color images from incomplete color filter array samples. There are two challenges to overcome by a demosaicing method: 1) it needs to model and respect the statistics of natural images in order to reconstruct natural looking images and 2) it should be able to perform well in the presence of noise. To facilitate an objective assessment of current methods, we introduce a public ground truth data set of natural images suitable for research in image demosaicing and denoising. We then use this large data set to develop a machine learning approach to demosaicing. Our proposed method addresses both demosaicing challenges by learning a statistical model of images and noise from hundreds of natural images. The resulting model performs simultaneous demosaicing and denoising. We show that the machine learning approach has a number of benefits: 1) the model is trained to directly optimize a user-specified performance measure such as peak signal-to-noise ratio (PSNR) or structural similarity; 2) we can handle novel color filter array layouts by retraining the model on such layouts; and 3) it outperforms the previous state-of-the-art, in some setups by 0.7-dB PSNR, faithfully reconstructing edges, textures, and smooth areas. Our results demonstrate that in demosaicing and related imaging applications, discriminatively trained machine learning models have the potential for peak performance at comparatively low engineering effort.
Skp2 Contains a Novel Cyclin A Binding Domain That Directly Protects Cyclin A from Inhibition by p27Kip1 (2006)

Skp2 is well known as the F-box protein of the SCF(Skp2) x Roc1 complex targeting p27 for ubiquitylation. Skp2 also forms complexes with cyclin A, which is particularly abundant in cancer cells due to frequent Skp2 overexpression, but the mechanism and significance of this interaction remain unknown. Here, we report that Skp2-cyclin A interaction is mediated by novel interaction sequences on both Skp2 and cyclin A, distinguishing it from the well known RXL-hydrophobic patch interaction between cyclins and cyclin-binding proteins. Furthermore, a short peptide derived from the mapped cyclin A binding sequences of Skp2 can block Skp2-cyclin A interaction but not p27-cyclin A interaction, whereas a previously identified RXL peptide can block p27-cyclin A interaction but not Skp2-cyclin A interaction. Functionally, Skp2-cyclin A interaction is separable from Skp2 ability to mediate p27 ubiquitylation. Rather, Skp2-cyclin A interaction serves to directly protect cyclin A-Cdk2 from inhibition by p27 through competitive binding. Finally, we show that disruption of cyclin A binding with point mutations in the cyclin A binding domain of Skp2 compromises the ability of overexpressed Skp2 to counter cell cycle arrest by a p53/p21-mediated cell cycle checkpoint without affecting its ability to cause degradation of cellular p27 and p21. These findings reveal a new functional mechanism of Skp2 and a new regulatory mechanism of cyclin A.
Analysis of plasma biomarker and tumor genetic alterations from a phase II trial of lenvatinib in patients with advanced endometrial cancer. (2013)

5591 Background: Lenvatinib is an oral receptor tyrosine kinase inhibitor targeting VEGFR1-3, FGFR1-4, RET, KIT, and PDGFRβ. A phase 2 study in patients with advanced endometrial cancer following 1 or 2 prior platinum-based treatments was performed and is presented in a separate abstract. Here we report potential predictive markers of clinical benefit. Methods: Pre- and post-treatment plasma samples collected from 122 of 133 treated subjects were analyzed for 50 circulating cytokine and angiogenic factors (CAFs) using ELISA and multiplex assay platforms; 107 archival tumor tissues obtained from 133 enrolled subjects were analyzed for gene mutation (mut) (81 samples) and gene expression profiling (GEP) (64 samples). For GEP analysis, the NanoString nCounter platform was used to measure the expression level of approximately 300 genes identified preclinically as relevant. Correlation with clinical outcome measures including maximal tumor shrinkage (MTS), objective response rate (ORR), PFS, and OS was performed. Results: Clinical correlation identified baseline levels of 7 CAFs related to angiogenesis (Ang-2, IL-8, HGF, VEGFA, PlGF, Tie-2, and TNFa) that associated with survival. Only baseline levels of Ang-2 associated with greater MTS (R=0.36 [Spearman], P<0.001), ORR (61% vs 18%), mPFS (9.5 vs 3.7 mos), and mOS (23 vs 8.9 mos) as determined using a defined cut-off value for baseline Ang-2. In gene mut analysis, no significant correlations were observed among the genes tested. Mut in PIK3CA showed a trend toward shorter OS (p = 0.085). In GEP analysis, expression levels of approximately 90 genes correlated with clinical outcome. Combination of GEP and CAF signatures identified signaling pathways, including Ang-2, that associated with OS. Clinical and preclinical GEP analysis identified overlapping gene signatures involving MAPK and PI3K signaling pathways that contributed to lenvatinib resistance. Conclusions: Baseline circulating Ang-2 levels may potentially predict outcomes in patients with advanced endometrial cancer and require further examination. This may provide a basis for stratification of patients in future clinical trials. Clinical trial information: NCT01111461.
Abstract 1217: Spatio-temporal modeling of the tumor microenvironment for prediction of patient-specific response to chemotherapy (2022)

Abstract Tumor heterogeneity, understood as the intrinsic (e.g., mutations, dysregulation, metabolic reprogramming) and extrinsic (e.g., nutrient/drug perfusion, interactions with surrounding tissues and the tumor microenvironment (TME)) to the cells that constitute the tumor, drives the variability of response to neoadjuvant chemotherapy. SimBioSys has developed TumorScope, a platform capable of capturing the chemical and biophysical interactions within the tumor and with the surrounding tissue by integrating these factors into a virtual tumor model. TumorScope makes individualized predictions of the response of each patient’s tumor to NACT. It utilizes three-dimensional biophysical simulations that model the dynamic tumor microenvironment (TME). The platform allows modelling of nutrient transport and drug behavior through perfusion and predicts when and where different regions of the tumor grow and die, and how that translates to overall response to treatment. TumorScope also incorporates multi-omics data, imaging data, pathology, and patient characteristics to simulate tumor biology of individual patient tumors. We have validated our approach in breast cancer by comparing TumorScope simulations against actual tumor response to neoadjuvant chemotherapy in over 400 patients. Simulations were initialized using each patient’s pretreatment MRI and pathology data and run from the beginning of therapy to the specified surgical date. The simulated tumor volumetric percent response (calculated as the ratio of change in tumor volume to initial volume) at the time of surgery was then compared with actual tumor volumetric percent response extracted from presurgical MRIs. Moreover, using TumorScope as a decision support system, we predicted patient response to multiple chemotherapies. For patients with event free survival data available we performed a Cox proportional hazard analysis. Using SimBioSys TumorScope we predicted a pre-surgical tumor volumetric response with a median error of 0.03% and median absolute deviation of 8.2%. For patients with available EFS data, we found a significant difference associated with having a final simulated volume greater than 0.01 cc. The SimBioSys TumorScope accurately predicts patient specific responses to NACT using only standard-of-care pre-treatment diagnostic data. These predictions can support decision making and enable the selection of less-toxic regimens for patients in which a robust response is predicted, and more aggressive treatments or alternative treatment strategies when response is likely to be poor. Citation Format: John A. Cole, Joseph R. Peterson, Tyler M. Earnest, Michael J. Hallock, Daniel Cook, Eduardo Braun, Anu Antony, Lance Munn, John Pfeiffer, Tushar Pandey. Spatio-temporal modeling of the tumor microenvironment for prediction of patient-specific response to chemotherapy [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 1217.
Global models with parametric offsets as applied to cardiac motion recovery (1996)

We introduce a new solid shape model formulation that includes built-in offsets from a base global component (e.g. an ellipsoid) which are functions of the global component's parameters. The offsets provide two features. First, they help to form an expected model shape which facilitates appropriate model data correspondences. Second, they scale with the base global model to maintain the expected shape even in the presence of large global deformations. We apply this model formulation to the recovery of 3-D cardiac motion from a volunteer dataset of tagged-MR images. The model instance is a variation of the hybrid volumetric ventriculoid (HVV), a deformable thick-walled ellipsoid model resembling the left ventricle (LV) of the heart. A unique aspect of of implementation is the employment of constant volume constraints when recovering the cardiac motion. In addition, we present a novel geodesic-like prismoidal tessellation of the model which provides for more stable fits.
Quantum random bit generation by stimulated Raman scattering (2012)

We introduce a quantum random number generator based on the phase measurement of Stokes light generated by amplification of zero-point vacuum fluctuations using stimulated Raman scattering in bulk diamond.