gebhart/patrepeval huggingface dataset:
Glycosulfopeptides modeled on P‐selectin glycoprotein ligand‐1 inhibit P‐selectin‐dependent leukocyte rolling in vivo (2002)

Leukocytic inflammation can be limited by inhibiting selectin-dependent leukocyte rolling. In spite of intensive efforts to develop small molecule selectin inhibitors with defined structure-activity profiles, inhibition of P-selectin-dependent leukocyte rolling in vivo by such a compound has yet to be described. We recently reported that glycosulfopeptides (GSP), modeled on the high affinity selectin ligand PSGL-1, inhibit leukocyte binding to P-selectin in vitro. Here, we have used intravital microscopy to investigate whether GSP can inhibit P-selectin-dependent leukocyte rolling in vivo. Surgical preparation of the mouse cremaster muscle for intravital microscopy induced P-selectin-dependent leukocyte rolling. Baseline rolling was recorded for 1 min followed by i.v. injection of GSP. 2-GSP-6 and 4-GSP-6 substantially reversed P-selectin-dependent leukocyte rolling, whereas control GSP, which are not fully glycosylated, did not. Inhibition of leukocyte rolling by 2- and 4-GSP-6 lasted 2-4 min. Clearance studies with 125I-labeled 4-GSP-6 demonstrated rapid reduction in its circulating levels concurrent with accumulation in urine. These data represent the first demonstration that a precisely defined structure based on a natural P-selectin ligand can inhibit P-selectin-dependent leukocyte rolling in vivo.
The microfluidic post-array device: high throughput production of single emulsion drops (2013)

We present a microfluidic device that enables high throughput production of relatively monodisperse emulsion drops while controlling the average size. The device consists of a two-dimensional array of regularly-spaced posts. Large drops of a highly polydisperse crude emulsion are input into the device and are successively split by the posts, ultimately yielding a finer emulsion consisting of smaller, and much more monodisperse drops. The size distribution of the resultant emulsion depends only weakly on the viscosities of the input fluids and allows fluids of very high viscosities to be used. The average size and polydispersity of the drops depend strongly on the device geometry enabling both control and optimization. We use this device to produce drops of a highly viscous monomer solution and subsequently solidify them into polymeric microparticles. The production rate of these devices is similar to that achieved by membrane emulsification techniques, yet the control over the drop size is superior; thus these post-array microfluidic devices are potentially useful for industrial applications.
Self designing pattern recognition system employing multistage classification (2004)

Recently, pattern recognition/classification has received a considerable attention in diverse engineering fields such as biomedical imaging, speaker identification, fingerprint recognition, etc. In most of these applications, it is desirable to maintain the classification accuracy in the presence of corrupted and/or incomplete data. The quality of a given classification technique is measured by the computational complexity, execution time of algorithms, and the number of patterns that can be classified correctly despite any distortion. Some classification techniques that are introduced in the literature are described in Chapter one. In this dissertation, a pattern recognition approach that can be designed to have evolutionary learning by developing the features and selecting the criteria that are best suited for the recognition problem under consideration is proposed. Chapter two presents some of the features used in developing the set of criteria employed by the system to recognize different types of signals. It also presents some of the preprocessing techniques used by the system. The system operates in two modes, namely, the learning (training) mode, and the running mode. In the learning mode, the original and preprocessed signals are projected into different transform domains. The technique automatically tests many criteria over the range of parameters for each criterion. A large number of criteria are developed from the features extracted from these domains. The optimum set of criteria, satisfying specific conditions, is selected. This set of criteria is employed by the system to recognize the original or noisy signals in the running mode. The modes of operation and the classification structures employed by the system are described in details in Chapter three. The proposed pattern recognition system is capable of recognizing an enormously large number of patterns by virtue of the fact that it analyzes the signal in different domains and explores the distinguishing characteristics in each of these domains. In other words, this approach uses available information and extracts more characteristics from the signals, for classification purposes, by projecting the signal in different domains. Some experimental results are given in Chapter four showing the effect of using mathematical transforms in conjunction with preprocessing techniques on the classification accuracy. A comparison between some of the classification approaches, in terms of classification rate in case of distortion, is also given. A sample of experimental implementations is presented in chapter 5 and chapter 6 to illustrate the performance of the proposed pattern recognition system. Preliminary results given confirm the superior performance of the proposed technique relative to the single transform neural network and multi-input neural network approaches for image classification in the presence of additive noise.
Zoom camera based on variable-focus liquid lenses (2006)

A zoom camera was constructed based on two adjustable lenses. The strongly varying lens shapes make an achromatic design complicated. Special liquids are required to prevent chromatic aberrations for all zoom levels and object positions
Few-mode multicore fibers for long-haul transmission line (2016)

Few-mode multicore fibers (FM-MCFs) that enable dense space-division multiplexing (DSDM) have the potential to drastically improve the fiber capacity. In designing the FM-MCFs, several issues that originate from multicore fibers and few-mode fibers must be considered. In this paper, these design issues such as inter-core crosstalk (IC-XT) and dispersion mode delay (DMD) are discussed. A three-mode 12-core fiber with low-DMD low-IC-XT achieves long-haul DSDM transmission over 500 km. The design concept, fiber design, and characteristics of the fabricated three-mode 12-core fiber are also described.
Polarization Diversity Transmitter and Optical Nonlinearity Mitigation using Polarization-Time Coding (2006)

Polarization diversity transmitter is proposed to realize polarization-insensitive coherent detection using polarization-time coding. It can significantly reduce cross-phase-modulation- induced polarization scattering in wavelength-division multiplexing systems. Polarization-time coding is analogous to space-time coding in wireless communications.
Cost minimization of multi-tiered e-business infrastructure with end-to-end delay guarantees (2004)

E-Business has become a cost effective solution for many traditional businesses and a critical component of many companies to such a degree that guaranteeing the performance and availability is vital. The design and development of e-business infrastructure should meet a twofold challenge. On one hand, it must meet customer expectations in terms of quality of service (QoS). On the other hand, companies have to control IT costs to stay competitive. It is therefore crucial to understand the tradeoff between costs and service levels so as to enable the determination of the most cost-effective architecture and system.
Coupling Point Cloud Completion and Surface Connectivity Relation Inference for 3D Modeling of Indoor Building Environments (2018)

Due to occlusions and limited measurement ranges, three-dimensional (3D) sensors are often not able to obtain complete point clouds. Completing missing data and obtaining spatial relations of different building components in such incomplete point clouds are important for several applications, for example, 3D modeling for all objects in indoor building environments. This paper presents a framework that recovers missing points and estimates connectivity relations between planar and nonplanar surfaces to obtain complete and high-quality 3D models. Given multiple depth frames and their sensor poses, a truncated signed distance function (TSDF) octree is constructed to fuse the depth frames and estimate the visibility labels of octree voxels. A normal-based region growing method is utilized to detect planar and nonplanar surfaces from the octree point cloud. Based on the surfaces and the visibility labels, missing points are completed by estimating the connectivity relations between pairs of the surfaces and by filling individual planar surfaces. Experimental results demonstrate that the proposed method can correctly identify at least 78% of the connectivity relations between the detected surfaces, and 87% of added points are correct and help to generate high-quality 3D models compared to the ground truth model.
The plasma concentration of N‐terminal proatrial natriuretic factor anf (1‐98) is related to prognosis in severe heart failure (1994)

Due to its longer halflife, the N-terminal of ANF prohormone, ANF(1-98), has plasma concentrations that exceed those of ANF itself by a factor of 10 or more. It is also less prone to rapid changes secondary to hemodynamic alterations. To evaluate the prognostic significance of ANF(1-98) plasma levels in severe heart failure (NYHA IV), the peptide was measured by radioimmunoassay in plasma samples from patients randomized to additional treatment with enalapril (n = 78) or placebo (n = 61) (CONSENSUS study). In the placebo group there was a positive relation between mortality after 6 months and baseline ANF(1-98) level. Because of a reduced mortality, especially among patients with high ANF(1-98) levels, there was no such relation in the patients treated with enalapril. For both groups there was a positive relationship between increase in ANF(1-98) after 6 weeks of treatment and mortality, while a decrease signaled a favorable prognosis. It is concluded that the magnitude and changes of plasma ANF(1-98) provide information on prognosis and therapeutic effects with respect to mortality in patients with severe heart failure. Plasma ANF(1-98) may serve as a useful clinical biochemical parameter in the treatment of heart failure.
An Ultra High Temperature Positive Photoresist (1985)

This paper discusses the functional performance features of a new positive photoresist designated as ULTRAMAC' PR78T that can be subjected to temperatures up to 220°C. without any changes in the critical dimensions (CD's). No deep UV stabilization, intermediate post bakes, or other stabilization techniques are required to achieve high temperature thermal stability (220°C.). This high temperature positive photoresist is based on a diazo-coupled alkali soluble resin. The resolution and photospeed of this resist, ULTRAMAC' PR78T, are shown to be in the order of 1 micron using a 1.5 microns resist film thickness at 44 mJ/cm<sup>2</sup>. This resist also has submicron capabilities using step-and-repeat exposure equipment (10:1) utilizing monochromatic 436 nanometer light. ULTRAMAC' PR78T resist shows optimum sensitivity in the 300 - 500 nanometer UV spectral range. In contact or projection exposure equipment, resolution in the order of 1 micron can be achieved using a 1 micron resist film with exposure energies of about 35 mJ/cm<sup>2</sup>. For steppers using monochromatic light at 436 nanometers, typical exposure energies are in the order of 160 to 180 mJ/cm<sup>2</sup>, using either metal-ion-free or buffered metal based developers. Contrast (gamma) curves are shown for both metal-ion-free developer, ULTRAMAC' MF72A, and buffered metal containing developer, ULTRAMAC" D71A. High current ion implant data is also presented, showing no resist degradation. Anisotropic plasma/RIE etching selectivity data is also shown on SiO<sub>2</sub> and aluminum alloy substrates.
Advanced MEMS Process for Wafer Level Hermetic Encapsulation of MEMS Devices Using SOI Cap Wafers With Vertical Feedthroughs (2015)

This paper reports a novel and inherently simple fabrication process, so-called advanced MEMS (aMEMS) process, that is developed for high-yield and reliable manufacturing of wafer-level hermetic encapsulated MEMS devices. The process enables lead transfer using vertical feedthroughs formed on an Silicon-On-Insulator (SOI) wafer without requiring any complex via-refill or trench-refill processes. It requires only seven masks to fabricate the hermetically capped sensors with an experimentally verified process yield of above 80%. Hermetic encapsulation is achieved by Au-Si eutectic bonding at 400 °C, and the pressure inside the encapsulated cavity has been characterized to be as low as 1 mTorr with successfully activated thin-film getters. The pressure inside the encapsulated cavity can also be adjusted in the range of 1 mTorr-5 Torr by various combinations of outgassing and gettering options in order to satisfy the requirements of different applications. The package pressure is being monitored for the selected chips and is observed to be stable below 10 mTorr since their fabrication about 10 months ago. The shear strengths of several packages are measured to be as high as 30 MPa with average shear strength of 22 MPa, indicating a mechanically strong bonding. The robustness of the packages is tested by thermal cycling between 100 °C and 25 °C, and absolutely no degradation is observed in the hermeticity and the package pressure. The package pressure is also verified to remain unchanged after storing the packages at a high storage temperature of 150 °C for 24 h. Furthermore, the packaged chips are observed to withstand a high temperature shock test performed at 300 °C for 5 min, at the end of which the characteristics of the encapsulated sensor indicates that the package still remains hermetic (no detectable leaks) and also the package pressure remains constant at ~20 mTorr.
KNITIT (2018)

Highly specified digital control tools for the customization of knitted fabrics is an existing technology, widely used industrially by trained knitters. Some fabrication challenges inhibit the extent of use of digital customization for knitted products on a mass scale, specifically when complex multiple structured knits are involved. This is due, in part, to physical changes that occur in the overall fabric dimensions, when stitch combinations with different physical attributes are combined within the same fabric. Existing computational tools fail to assist in the simulation and prediction of these overall deformations and the industry as a whole relies on the expertise of highly trained individuals. The outline shape of the fabric is of specific importance as it is commonly preconfigured to a specific shape and dimension that must be reproducible. In this work, we propose a computational parametric tool for digitally designing and industrially producing knitted fabrics, creating a direct link between design and manufacturability. The tool includes an integrated physical simulation component for estimating the fabric deformation. It allows users to visualize and control compensations in the fabric structure, to better match between the initial graphic intent of the design and the actual physical knitted fabric outcome. Our approach aims to reduce the number of iteration cycles for knitting material samples, especially when knitting highly varied designs.
Low-Chrome/Chrome Free Refractories for Slagging Gasifiers (2007)

Gasifiers are containment vessels used to react carbon-containing materials with oxygen and water, producing syngas (CO and H2) that is used in chemical and power production. It is also a potential source of H2 in a future hydrogen economy. Air cooled slagging gasifiers are one type of gasifier, operating at temperatures from 1275-1575º C and at pressures of 400 psi or higher. They typically use coal or petroleum coke as the carbon source, materials which contain ash impurities that liquefy at the gasification temperatures, producing liquid slag in quantities of 100 or more tons/day, depending on the carbon fed rate and the percent ash present in the feedstock. The molten slag is corrosive to refractory linings, causing chemical dissolution and spalling. The refractory lining is composed of chrome oxide, alumina, and zirconia; and is replaced every 3-24 months. Gasifier users would like greater on-line availability and reliability of gasifier liners, something that has impacted gasifier acceptance by industry. Research is underway at NETL to improve refractory service life and to develop a no-chrome or low-chrome oxide alternative refractory liner. Over 250 samples of no- or low-chrome oxide compositions have been evaluated for slag interactions by cup testing; with potential candidates for further studies including those with ZrO2, Al2O3, and MgO materials. The development of improved liner materials is necessary if technologies such as IGCC and DOE’s Near Zero Emissions Advanced Fossil Fuel Power Plant are to be successful and move forward in the marketplace.
Introduction (2017)

Security and privacy are increasingly important concerns for the consumer as personal information processing moves from secure servers to a growing set of mobile devices such as smart phones, PDAs, medical devices, and other embedded portable devices. The storage of data is moving from hard disks on our personal computers to more centralized servers (i.e., cloud) which require secure and efficient management of sensitive data. The mathematical strength of cryptographic algorithms that are used to protect information is no longer the weakest link: it is the implementation that is more vulnerable to malicious attacks.
An improved time-recursive lattice structure for low-latency IFFT architecture in DMT transmitter (2002)

In this paper, we propose an improved parallel lattice structure to implement IFFT module in the transmitter of Discrete Multitone (DMT) system. By exploiting the symmetric/anti-symmetric properties of the input symbols, we add a new pre-processing scheme to previous work. By doing so, the iteration number can be halved from 2N to N (N is 256 in DMT). As a result, the clock rate of the IFFT lattice module can be lowered under the same input symbol rate. In addition, the internal registers are also reduced from 4N-4 to 2N-2, and multiplexers in post-processing circuits are all eliminated compared with the previous design. Hence, the proposed method can save more power consumption and further reduce the hardware complexity of the IFFT module. The proposed architecture is regular, modular, and free of global routing. Thus, it is very suitable for VLSI implementation.
Weakly-Supervised Spatial Context Networks (2019)

We explore the power of spatial context as a self-supervisory signal for learning visual representations. In particular, we propose spatial context networks that learn to predict a representation of one image patch from another image patch, within the same image, conditioned on their real-valued relative spatial offset. Unlike auto-encoders, that aim to encode and reconstruct original image patches, our network aims to encode and reconstruct intermediate representations of the spatially offset patches. As such, the network learns a spatially conditioned contextual representation. By testing performance with various patch selection mechanisms we show that focusing on object-centric patches is important, and that using object proposal as a patch selection mechanism leads to the highest improvement in performance. Further, unlike auto-encoders, context encoders [21], or other forms of unsupervised feature learning, we illustrate that contextual supervision (with pre-trained model initialization) can improve on existing pre-trained model performance. We build our spatial context networks on top of standard VGG_19 and CNN_M architectures and, among other things, show that we can achieve improvements (with no additional explicit supervision) over the original ImageNet pre-trained VGG_19 and CNN_M models in object categorization and detection on VOC2007.
Integration of Bridge Damage Detection Concepts and Components Volume I: Strain-Based Damage Detection (2013)

In this work, a previously-developed structural health monitoring (SHM) system was advanced toward a ready-for-implementation system. Improvements were made with respect to automated data reduction/analysis, data acquisition hardware, sensor types, and communication network architecture. The statistical damage-detection tool, control-chart-based damage-detection methodologies, were further investigated and advanced. For the validation of the damage-detection approaches, strain data were obtained from a sacrificial specimen attached to the previously-utilized US 30 Bridge over the South Skunk River (in Ames, Iowa), which had simulated damage,. To provide for an enhanced ability to detect changes in the behavior of the structural system, various control chart rules were evaluated. False indications and true indications were studied to compare the damage detection ability in regard to each methodology and each control chart rule. An autonomous software program called Bridge Engineering Center Assessment Software (BECAS) was developed to control all aspects of the damage detection processes. BECAS requires no user intervention after initial configuration and training.
Efficacy Assessment of a New Fungicide, Miravis Ace, for Control of Fusarium Head Blight in Wheat (2020)

Fusarium head blight (FHB) is a serious disease of wheat and barley that leads to significant economic losses and deteriorated grain quality because of the associated mycotoxins. Genetic resistance and use of fungicides are the methods used to control FHB. However, in weather conditions conducive for FHB epidemics, higher levels of genetic resistance as well as greater efficacy of fungicides are required to adequately control this disease. Due to the extensive use of a single mode of action for management of FHB, there is a need to diversify fungicides used to lower the risk of resistance development in pathogen populations. In this 2-year study, we evaluated the performance of a new fungicide, Miravis Ace (a proprietary mix of pydiflumetofen and propiconazole active ingredients produced by Syngenta) for controlling FHB. It is a mix of succinate dehydrogenase inhibitor and demethylation inhibitor fungicides and can add diversity to the fungicide toolkit for FHB management. The level of control of FHB and deoxynivalenol (DON) achieved by spraying Miravis Ace at anthesis (Feekes growth stage 10.5.1) was found to be equivalent to that provided by the currently recommended products for managing FHB and reducing DON in wheat and barley.