gebhart/patrepeval huggingface dataset:
Acquired von Willebrand disease caused by an autoantibody selectively inhibiting the binding of von Willebrand factor to collagen (1994)

An 82-year-old man with a low-grade malignant non-Hodgkin lymphoma and an IgG3 lambda monoclonal gammopathy presented a recently acquired bleeding tendency, characterized by recurrent epistaxis, easy bruising, and episodes of melena, requiring packed red blood cell transfusions. Coagulation studies showed a von Willebrand factor (vWF) defect (Ivy bleeding time, > 15 minutes; vWF antigen [vWF:Ag], 0.08 U/mL; ristocetin cofactor activity [vWF:RCoF], < 0.05 U/mL; collagen binding activity [vWF:CBA], 0.01 U/mL; absence of the high molecular weight multimers of vWF on multimeric analysis). Mixing experiments suggested the presence of an inhibitor directed against the vWF:CBA activity of vWF without significantly inhibiting the FVIII:C, vWF:Ag, and vWF:RCoF activities. The inhibitor was identified as an antibody of the IgM class by immunoabsorption of vWF and inhibitor-vWF complexes from the plasma of the patient. Subsequent immunoprecipitation experiments using recombinant fragments of vWF showed that the inhibitor reacted with both the glycoprotein Ib binding domain (amino acids [aa] 422-826) and the A3 (aa 909-1112) domain of vWF, but not with the A2 (aa 716-908) or D4 (aa 1183-1535) domains. We conclude that the IgM autoantibody inhibits the vWF:CBA activity by reacting with an epitope present on both the glycoprotein Ib and A3 domains of vWF.
Constrained attitude maneuvering of a spacecraft with reaction wheel assembly by Nonlinear Model Predictive Control (2016)

This paper develops a nonlinear model predictive controller for constrained attitude maneuvering of spacecraft actuated by a reaction wheel assembly. In the proposed control algorithm, a Lie group variational integrator is implemented for the prediction of discrete-time dynamics. The model predictive control problem is defined on SO(3) and converted to an optimal control problem over the prediction horizon. The numerical solver for this optimal control problem is implemented. The developed solver utilizes the Indirect Single Shooting Method to find a solution to the necessary conditions for optimality. The control constraints and exclusion zone constraints are handled using a penalty function approach. Simulation results on a spacecraft model are presented.
A Data Quality Ontology for the Secondary Use of EHR Data. (2015)

The secondary use of EHR data for research is expected to improve health outcomes for patients, but the benefits will only be realized if the data in the EHR is of sufficient quality to support these uses. A data quality (DQ) ontology was developed to rigorously define concepts and enable automated computation of data quality measures. The healthcare data quality literature was mined for the important terms used to describe data quality concepts and harmonized into an ontology. Four high-level data quality dimensions ("correctness", "consistency", "completeness" and "currency") categorize 19 lower level measures. The ontology serves as an unambiguous vocabulary, which defines concepts more precisely than natural language; it provides a mechanism to automatically compute data quality measures; and is reusable across domains and use cases. A detailed example is presented to demonstrate its utility. The DQ ontology can make data validation more common and reproducible.
On the Effect of Cooperative Relaying on the Performance of Video Streaming Applications in Cognitive Radio Networks (2011)

The problem of optimal resource allocation to share high-quality multimedia content in cognitive ad hoc networks with cooperative relays is addressed in this paper. Cooperative transmission is a promising technique to increase the capacity of wireless links by exploiting spatial diversity without multiple antennas at each node. However, mainstream research in this field focuses on optimizing physical layer performance measures, with little consideration for application-specific and network-wide performance measures. In this paper, the problem of joint video encoding rate control, power control, relay selection and channel assignment is formulated as a mixed-integer nonlinear problem(MINLP), and a solution algorithm based on a combination of the branch and bound framework and convex relaxation techniques is then proposed. The proposed solution jointly allocates channel, power, video encoding rate, and relay nodes for secondary users to maximize the video quality under the constraints posed by delay-sensitive video applications. Performance evaluation results show that cognitive networks with cooperative relaying can provide considerably higher video quality (in terms of the average peak signal-to-noise ratio (PSNR)) than solutions that do not rely on cooperation or without dynamic spectrum allocation.
Role of inclined threading dislocations in stress relaxation in mismatched layers (2005)

(0001)-oriented epitaxial wurtzite III-nitride layers grown on mismatched substrates have no resolved shear stress on the natural basal and prismatic slip planes; however, strained III-nitride layers may gradually relax. We report on the stress relaxation of Al0.49Ga0.51N layers grown on nominally relaxed Al0.62Ga0.38N buffer layers on sapphire. The reduction in elastic strain of the Al0.49Ga0.51N was enhanced by Si doping which caused an increased surface roughness. Despite the Si doping, the films always sustained step-flow growth. The extent of relaxation of the Al0.49Ga0.51N layer was determined by on-axis ω-2θ scans of (000l) peaks and reciprocal space maps of inclined (off-axis) peaks. Cross-section and plan-view transmission electron microscopy studies showed that the threading dislocations in the Al0.49Ga0.51N layer inclined from the [0001] direction towards ⟨11¯00⟩ directions by ∼15–25°, perpendicular to their Burgers vector (13⟨112¯0⟩). These inclined threading dislocations have a misfit dislocation component and thus provide stress relief. The contribution of the dislocation inclination to the degree of relaxation has been formulated and the energy release has been determined for dislocation inclination in mismatched stressed layers.
Validation of a Convolutional Neural Network Model for Spike Transformation Using a Generalized Linear Model (2020)

Identification of causal relationships of neural activity is one of the most important problems in neuroscience and neural engineering. We show that a novel deep learning approach using a convolutional neural network to model output neural spike activity from input neural spike activity is able to achieve high correlation between the predicted probability of spiking in the output neuron and the true probability of spiking in the output neuron for data generated with a generalized linear model. The convolutional neural network is also able to recover the true model variables (kernels) used to generate the probability of spiking in the output neuron. Based on the convolutional neural network model's validation via a generalized linear model, future work will include validation with non-linear models that use higher-order kernels.
Dynamics of the chemisorption of N2 on W(100): Precursor-mediated and activated dissociation (1990)

The dissociative chemisorption probability of N2 on W(100) is found to proceed by way of two dynamically distinct channels. At low kinetic energies Ei, dissociation proceeds primarily by way of a precursor-mediated process, where the dissociation probability is found to fall with increasing Ei, reflecting the energy dependence of the trapping probability into this state. Dissociation at low energies is also strongly dependent on surface temperature Ts which effects the fraction of trapped species that desorb. For energies above about 0.45 eV, the dissociation probability is found to rise from a minimum of about 0.14 at Ts=800 K to over 0.45 at Ei=5 eV. Over this range we believe that kinetic energy enables the incident molecules to directly overcome a barrier in the reaction coordinate. Throughout the entire range of energies we observe only slight variations of the dissociation probability with the angle of incidence, with no discernible sensitivity for energies below ∼0.5 eV. For energies between 1 and 4 eV, associated with the ‘‘activated’’ channel, we observe a slight preference for non-normal incidence, with a clear preference for normal incidence only for Ei&amp;gt;5 eV. While the ‘‘precursor-mediated’’ channel displays a considerable sensitively to surface temperature, results at high energy are found to be essentially independent of this parameter. Moreover, dissociation by way of the precursor-mediated channel is found to be insensitive to surface coverage, in contrast to a roughly linear decrease in the dissociation probability with surface coverage observed for dissociation via the activated process. In this latter case, we find that the saturation coverage remains approximately constant at about 0.6 atomic monolayers for all conditions, up to the highest incidence energies. This differs from previous observations for the dissociation of O2 and N2 on W(110), where the saturation coverage was found to rise with increasing Ei. Finally we find that the dissociation probability vs kinetic energy curve for the ‘‘direct’’ dissociation case is qualitatively similar to that for the N2/W(110) system, but with a threshold that is ∼0.4 eV lower. We argue that the ‘‘precursor-mediated’’ mechanism does not contribute significantly to dissociative chemisorption in the W(110) case and conclude that the primary difference between N2 dissociation on the W(110) and W(100) surfaces is that the barrier to dissociation is slightly higher in the W(110) case.
Highly Tunable Electrostatic Nanomechanical Resonators (2017)

There has been significant interest toward highly tunable resonators for on-demand frequency selection in modern communication systems. Here, we report highly tunable electrostatically actuated silicon-based nanomechanical resonators. In-plane doubly clamped bridges, slightly curved as shallow arches due to residual stresses are fabricated using standard electron beam lithography and surface nanomachining. The resonators are designed such that the effect of midplane stretching dominates the softening effect of the electrostatic force. This is achieved by controlling the gap-to-thickness ratio and by exploiting the initial curvature of the structure from fabrication. We demonstrate considerable increase in the resonance frequency of nanoresonators with the dc bias voltages up to 108% for 180 nm thick structures with a transduction gap of 1 μm separating them from the driving/sensing electrodes. The experimental results are found in good agreement with those of a nonlinear analytical model based on the Euler-Bernoulli beam theory. As a potential application, we demonstrate a tunable narrow bandpass filter using two electrically coupled nanomechanical arch resonators with varied dc bias voltages.
Apparatus, system, and method for providing fabric-elastomer composites as pneumatic actuators (2023)

Soft pneumatic actuators based on composites consisting of elastomers with embedded sheet or fiber structures (e.g., paper or fabric) that are flexible but not extensible are described. On pneumatic inflation, these actuators move anisotropically, based on the motions accessible by their composite structures. They are inexpensive, simple to fabricate, light in weight, and easy to actuate. This class of structure is versatile: the same principles of design lead to actuators that respond to pressurization with a wide range of motions (bending, extension, contraction, twisting, and others). Paper, when used to introduce anisotropy into elastomers, can be readily folded into three-dimensional structures following the principles of origami; these folded structures increase the stiffness and anisotropy of the elastomeric actuators, while keeping them light in weight.
Importance of Ligand Bioactive Conformation in the Discovery of Potent Indole-Diamide Inhibitors of the Hepatitis C Virus NS5B (2010)

Significant advances have led to receptor induced-fit and conformational selection models for describing bimolecular recognition, but a more comprehensive view must evolve to also include ligand shape and conformational changes. Here, we describe an example where a ligand's "structural hinge" influences potency by inducing an "L-shape" bioactive conformation, and due to its solvent exposure in the complex, reasonable conformation-activity-relationships can be qualitatively attributed. From a ligand design perspective, this feature was exploited by successful linker hopping to an alternate "structural hinge" that led to a new and promising chemical series which matched the ligand bioactive conformation and the pocket bioactive space. Using a combination of X-ray crystallography, NMR and modeling with support from binding-site resistance mutant studies and photoaffinity labeling experiments, we were able to derive inhibitor-polymerase complexes for various chemical series.
Reservoir Fluid Geodynamics: The Chemistry and Physics of Oilfield Reservoir Fluids after Trap Filling (2017)

Oilfield reservoirs exhibit a wide array of complexities that have great impact on the efficiency of oil production. Major challenges include delineating overall reservoir architecture and the distributions of the contained fluids. Reservoir crude oils consist of dissolved gases, liquids, and dissolved solids (the asphaltenes); the corresponding compositional variations and phase transitions within reservoirs greatly impact production strategies and economic value. Standard workflows for understanding reservoir (rock) architecture are subsumed in the discipline “geodynamics”, which incorporates the initial rock depositional setting and subsequent alterations through geologic time to yield the present-day reservoir. However, reservoir fluids are not generally treated in such a systematic manner. Petroleum system modeling provides the timing, type, and volume of hydrocarbon fluids that charge into reservoirs. However, there is little treatment regarding how these fluids change after filling the reservoir. A significant limitation had been the lack of thermodynamic treatment of asphaltenes in reservoir crude oils. Consequently, projecting reservoir fluid properties away from the wellbore has been problematic. “Reservoir fluid geodynamics” (RFG) is the newly formalized discipline that incorporates changes in the distributions of reservoir fluids and phase transitions over geologic time. A key enabling advance is the recently developed ability to treat asphaltene gradients in oilfield reservoirs using the Flory–Huggins–Zuo equation of state (FHZ EoS) with its reliance on the Yen–Mullins model of asphaltenes. In addition, in situ downhole fluid analysis in oil wells provides accurate vertical and lateral fluid gradients in reservoirs in a cost-effective manner. Thermodynamic equilibrium can now be recognized; equilibrated fluids imply connected reservoirs, meaning a single flow unit. Disequilibrium fluid gradients imply ongoing or recent fluid processes in geologic time. The analysis of 35 oilfields (with more than 100 oil reservoirs) has allowed the identification of various reservoir fluid geodynamic processes. Some processes, such as biodegradation, have long been studied; nevertheless, even in these cases, inclusion of the thermodynamic modeling yields accurate predictions of distributions of key fluid attributes. Many other RFG processes are elucidated herein and are shown to impact major reservoir concerns for production. The resulting fundamental understanding of the physics and chemistry of these RFG processes enables measurements made at the wellbore to be used as a basis for accurate prediction of fluid properties throughout the reservoir.
UnbiasedDTI: Mitigating Real-World Bias of Drug-Target Interaction Prediction by Using Deep Ensemble-Balanced Learning (2022)

Drug-target interaction (DTI) prediction through in vitro methods is expensive and time-consuming. On the other hand, computational methods can save time and money while enhancing drug discovery efficiency. Most of the computational methods frame DTI prediction as a binary classification task. One important challenge is that the number of negative interactions in all DTI-related datasets is far greater than the number of positive interactions, leading to the class imbalance problem. As a result, a classifier is trained biased towards the majority class (negative class), whereas the minority class (interacting pairs) is of interest. This class imbalance problem is not widely taken into account in DTI prediction studies, and the few previous studies considering balancing in DTI do not focus on the imbalance issue itself. Additionally, they do not benefit from deep learning models and experimental validation. In this study, we propose a computational framework along with experimental validations to predict drug-target interaction using an ensemble of deep learning models to address the class imbalance problem in the DTI domain. The objective of this paper is to mitigate the bias in the prediction of DTI by focusing on the impact of balancing and maintaining other involved parameters at a constant value. Our analysis shows that the proposed model outperforms unbalanced models with the same architecture trained on the BindingDB both computationally and experimentally. These findings demonstrate the significance of balancing, which reduces the bias towards the negative class and leads to better performance. It is important to note that leaning on computational results without experimentally validating them and by relying solely on AUROC and AUPRC metrics is not credible, particularly when the testing set remains unbalanced.
Signal waveforms and range/angle coupling in coherent colocated MIMO radar (2013)

In this paper, we consider the coherent colocated MIMO radar framework. We show in this paper that the MIMO ambiguity function presents a range/angle coupling for any waveform family except for perfectly orthogonal families that are unrealistic in practice. We then propose a general model for intrapulse coded MIMO waveforms, and we exhibit different waveform families within this model. For each coding scheme, the MIMO ambiguity function is studied and the range/angle coupling characterized. We also compute the corresponding Cramer-Rao Lower-Bounds. Finally real measurements obtained from a MIMO radar permit to confirm the shape of the ambiguity functions for the studied waveforms.
Calibration of projector-camera systems from virtual mutual projection (2008)

In this paper, we propose a new calibration method for projector-camera systems. The projector-camera systems have been studied extensively as one of new information presenting systems. For calibrating the systems, we in this paper use virtual mutual projections between a camera and a projector. We first show that by using a shadow of the camera, we can generate mutual projection between a camera and a projector virtually. By using the mutual projection, the projector camera system can be calibrated more stably than the existing calibration methods. Some experimental results show that the mutual projections work quite well for calibrating projector-camera systems.
Bending-induced birefringence of optical fiber cladding modes (2006)

The bend-induced lateral stresses that generate birefringence in an optical fiber are analytically determined throughout the fiber cross section. This stress profile is used to determine the birefringence of a cladding mode in a single-mode fiber. The result demonstrates that the birefringence of cladding modes may be much smaller than that of the core mode and knowledge of the mode profile and stress distribution is necessary for an accurate prediction.
A basic introduction to adaptive optics for microscopy (2019)

This document provides an introduction to adaptive optics for microscopy from a practical perspective. It is aimed at those who already have some experience in optics and preferably have experience in designing microscopes. It should prove useful to anyone who has an interest in using adaptive optics for their applications, but does not yet have experience with this technology.
Flow Control Applied to the Front Rounded Edge of a Bluff Body (2014)

An experimental study was performed on a 2D square prism with one rounded front edge with the purpose of reducing the aerodynamic drag by means of active flow control of boundary layer separation. Highly efficient suction and oscillatory blowing (SaOB) actuators were installed at the front curved edge, aimed to inhibit the separation phenomenon. The experimental results show significant decrease in the form-drag, narrowing of the wake and correspondingly an increase in the base pressure in the presence of the SaOB actuation. The mechanism of drag reduction is elimination of the separation from the front-cured edge of the model.
A Call to Craft (2014)

Educational institutions must begin training tissue engineers to think as both biomedical investigators and fabricators.
Minimizing Temperature Gradient in Photonic Sintering for Defect‐Free High‐Conductivity Cu‐Based Printed Patterns by Bidirectional Irradiation (2021)

Abstract Intense pulsed light (IPL)‐induced photothermal heating is relatively effective at reducing the annealing or sintering time of metal particle‐based conductive patterns in the manufacturing of printed electronics. However, defects such as cavities, delamination, and inhomogeneous shrinkage within the sintered patterns are a well‐known problem in IPL sintering. These defects are considerably influenced by undesired temperature gradients induced inside samples during IPL sintering. To solve this undesired temperature gradient problem, we propose a bidirectional IPL (B‐IPL) sintering approach using front‐ and back‐elliptical reflectors on both sides of the printed pattern. The effects of the B‐IPL energy density and number of shots on the electrical and mechanical properties of the printed patterns were systematically investigated using noncontact spectroscopic temperature sensing techniques with a µs‐timescale infrared temperature sensor system. Cross‐sectional field emission scanning electron microscopy images indicate that B‐IPL sintering significantly enhances the densification level and sintering uniformity of printed patterns compared to conventional IPL.
Synthesis of (4′R)-Azido-(2′R)-2′-Deoxy-2′-C-Methyluridine and Its Esters by Direct Iodide Displacement (2013)

The synthesis of an anti-infective nucleoside intermediate was accomplished through direct iodine displacement at C-5′ by a tetrabutylammonium carboxylate. This approach constitutes a more efficient alternative to the traditional oxidative displacement.
<title>Hybrid genetic approach for the dynamic weapon-target allocation problem</title> (2001)

This paper addresses the problem of threat engagement and dynamic weapon-target allocation (WTA) across the force or network-centric force optimization. The objective is to allocate and schedule defensive weapon resources over a given period of time so as to minimize surviving target value subject to resource availability and temporal constraints. The dynamic WTA problem is a NP-complete problem and belongs to a class of multiple-resource-constrained optimal scheduling problems. Inherent complexities in the problem of determining the optimal solution include limited weapon resources, time windows under which threats must be engaged, load-balancing across weapon systems, and complex interdependencies of various assignments and resources. We present a new hybrid genetic algorithm (GA) which is a combination of a traditional genetic algorithm and a simulated annealing-type algorithm for solving the dynamic WTA problem. The hybrid GA approach proposed here uses a simulated annealing-type heuristics to compute the fitness of a GA-selected population. This step also optimizes the temporal dimension (scheduling) under resource and temporal constraints. The proposed method provides schedules that are near-optimal in short cycle times and have minimal perturbation from one cycle to the next. We compare the performance of the proposed approach with a baseline WTA algorithm.