gebhart/patrepeval huggingface dataset:
Unexpected Hole Transfer Leads to High Efficiency Single-Walled Carbon Nanotube Hybrid Photovoltaic (2010)

We report surprisingly efficient photocurrent generation at individual single-walled carbon nanotube (SWNT) /poly(3-hexylthiophene-2,5-diyl) (P3HT) junctions. Contrary to previous prediction, both semiconducting SWNTs (s-SWNTs) and metallic SWNTs (m-SWNTs) function as efficient hole acceptors. By active tuning of SWNTs' Fermi level, we confirm that P3HT p-dopes both s-SWNT and m-SWNT, and the work function difference between the nanotube and P3HT leads to a built-in voltage driving the efficient exciton dissociation and hole transfer. We further demonstrate square millimeter scale SWNT/P3HT bilayer photovoltaics using horizontally aligned SWNT arrays. Importantly, the devices exhibit greater than 90% effective external quantum efficiency. These key findings will not only enhance our knowledge of photocurrent generation at nanoscale interfaces, but also make selective omission of m-SWNT redundant, promising carbon nanomaterial-based, low-cost, high-efficiency hybrid photovoltaics.
High Accuracy Ion Mobility Spectrometry for Instrument Calibration (2018)

Ion mobility spectrometry (IMS) is widely used to characterize compounds of interest (COIs) based on their reduced mobility ( K<sub>0</sub>) values. In an attempt to increase the accuracy and agreement of studies, the most recommended method has been to use a reference compound with a known K<sub>0</sub> value to calibrate the instrument and calculate COI K<sub>0</sub> values from normalized spectra. Researchers are limited by the accuracy of previous K<sub>0</sub> value reference measurements on which to base their calibrations. Any inaccuracy in these reference K<sub>0</sub> values, typically ±2%, will propagate through to the calculated K<sub>0</sub> value of the COI. For this reason, there is a need to standardize reference K<sub>0</sub> values with improved accuracy. Through improvement of the accuracy of reference measurements, a lower degree of error will propagate through new K<sub>0</sub> value calculations. The K<sub>0</sub> values of the ammonium reactant ion, the potential reference standard dimethyl methylphosphonate (DMMP), and three explosive COIs were characterized at multiple drift gas temperatures, drift gas water contents, and electric field strengths on an accurate ion mobility spectrometry instrument. K<sub>0</sub> values reported here are known to ±0.1% as a result of reducing the error of all instrumental parameters.
A corona discharge initiated electrochemical electrospray ionization technique (2009)

We report here the development of a corona discharge (CD) initiated electrochemical (EC) electrospray ionization (ESI) technique using a standard electrospray ion source. This is a new ionization technique distinct from ESI, electrochemistry inherent to ESI, APCI, and techniques using hydroxyl radicals produced under atmospheric pressure conditions. By maximizing the observable CD at the tip of a stainless steel ESI capillary, efficient electrochemical oxidation of electrochemically active compounds is observed. For electrochemical oxidation to be observed, the ionization potential of the analyte must be lower than Fe. Ferrocene labeled compounds were chosen as the electrochemically active moiety. The electrochemical cell in the ESI source was robust, and generated ions with selectivity according to the ionization potential of the analytes and up to zeptomolar sensitivity. Our results indicate that CD initiated electrochemical ionization has the potential to become a powerful technique to increase the dynamic range, sensitivity, and selectivity of ESI experiments.
Iterative decoding beyond belief propagation (2010)

At the heart of modern coding theory lies the fact that low-density parity-check (LDPC) codes can be efficiently decoded by belief propagation (BP). The BP is an inference algorithm which operates on a graphical model of a code, and lends itself to low-complexity and high-speed implementations, making it the algorithm of choice in many applications. It has unprecedentedly good error rate performance, so good that when decoded by the BP, LDPC codes approach theoretical limits of channel capacity. However, this capacity approaching property holds only in the asymptotic limit of code length, while codes of practical lengths suffer abrupt performance degradation in the low noise regime known as the error floor phenomenon. Our study of error floor has led to an interesting and surprising finding that it is possible to design iterative decoders which are much simpler yet better than belief propagation! These decoders do not propagate beliefs but a rather different kind of messages that reflect the local structure of the code graph. This has opened a plethora of exciting theoretical problems and applications. This paper introduces this new paradigm.
AnchorViz (2018)

When building a classifier in interactive machine learning, human knowledge about the target class can be a powerful reference to make the classifier robust to unseen items. The main challenge lies in finding unlabeled items that can either help discover or refine concepts for which the current classifier has no corresponding features (i.e., it has feature blindness). Yet it is unrealistic to ask humans to come up with an exhaustive list of items, especially for rare concepts that are hard to recall. This paper presents AnchorViz, an interactive visualization that facilitates error discovery through semantic data exploration. By creating example-based anchors, users create a topology to spread data based on their similarity to the anchors and examine the inconsistencies between data points that are semantically related. The results from our user study show that AnchorViz helps users discover more prediction errors than stratified random and uncertainty sampling methods.
Photoacoustic method and apparatus for measuring intensity of electromagnetic radiation (1980)

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Blinded Fault Resistant Exponentiation Revisited (2009)

Cryptographic algorithm implementations are subject to specific attacks, called side channel attacks, focusing on the analysis of their power consumption or execution time or on the analysis of faulty computations. At FDTC06, Fumaroli and Vigilant presented a generic method to compute an exponentiation resistant against different side channel attacks. However, even if this algorithm does not reveal information on the secrets in case of a fault attack, it can not be used to safely implement a crypto-system involving an exponentiation. In this paper, we propose a new exponentiation method without this drawback and give a security proof of resistance to fault attacks. As an application, we propose an RSA algorithm implemented using the Chinese Remainder Theorem protected against side channel attacks. The exponentiation algorithm is also 33% faster than the previous method.
Probing the impact of axial diffusion on nitric oxide exchange dynamics with heliox (2004)

Exhaled nitric oxide (NO) is a potential noninvasive index of lung inflammation and is thought to arise from the alveolar and airway regions of the lungs. A two-compartment model has been used to describe NO exchange; however, the model neglects axial diffusion of NO in the gas phase, and recent theoretical studies suggest that this may introduce significant error. We used heliox (80% helium, 20% oxygen) as the insufflating gas to probe the impact of axial diffusion (molecular diffusivity of NO is increased 2.3-fold relative to air) in healthy adults (21–38 yr old, n = 9). Heliox decreased the plateau concentration of exhaled NO by 45% (exhalation flow rate of 50 ml/s). In addition, the total mass of NO exhaled in phase I and II after a 20-s breath hold was reduced by 36%. A single-path trumpet model that considers axial diffusion predicts a 50% increase in the maximum airway flux of NO and a near-zero alveolar concentration (Ca NO ) and source. Furthermore, when NO elimination is plotted vs. constant exhalation flow rate (range 50–500 ml/s), the slope has been previously interpreted as a nonzero Ca NO (range 1–5 ppb); however, the trumpet model predicts a positive slope of 0.4–2.1 ppb despite a zero Ca NO because of a diminishing impact of axial diffusion as flow rate increases. We conclude that axial diffusion leads to a significant backdiffusion of NO from the airways to the alveolar region that significantly impacts the partitioning of airway and alveolar contributions to exhaled NO.
A new segmentation framework for infrared spectroscopic imaging using frequent pattern mining (2011)

Histologic analysis of a stained tissue sample by a trained pathologist forms the definitive diagnosis of prostate cancer. Rapid and objective second opinions are highly desirable to make more accurate diagnostic decisions. One alternate method is to use Fourier transform infrared (FT-IR) spectroscopic imaging, which is an emerging technique that combines the molecular selectivity of spectroscopy with the spatial specificity of optical microscopy. While instrumentation is well-developed for FT-IR imaging, information extraction from the data could benefit greatly from improved approaches. Here we propose a new approach to segment histologic classes in a tissue for FT-IR imaging using frequent pattern mining. Prior to applying frequent pattern mining, FT-IR images are discretized, and subsequent pruning method and feature selection method result in a classifier for the segmentation. The method is evaluated using two different datasets. Results indicate that accurate histologic segmentation is achievable by this approach.
Color Hologram Generation Using a Pancharatnam-Berry Phase Manipulating Metasurface (2015)

We propose a new scheme to generate polychromatic holograms by manipulating the Pancharatnam-Berry phase. Using anisotropic transmission characteristics and tuning the resonant wavelengths of nanoslits, multicolor holograms can be produced for arbitrary RGB images.
A Multi-Sensor Fusion MAV State Estimation from Long-Range Stereo, IMU, GPS and Barometric Sensors (2016)

State estimation is the most critical capability for MAV (Micro-Aerial Vehicle) localization, autonomous obstacle avoidance, robust flight control and 3D environmental mapping. There are three main challenges for MAV state estimation: (1) it can deal with aggressive 6 DOF (Degree Of Freedom) motion; (2) it should be robust to intermittent GPS (Global Positioning System) (even GPS-denied) situations; (3) it should work well both for low- and high-altitude flight. In this paper, we present a state estimation technique by fusing long-range stereo visual odometry, GPS, barometric and IMU (Inertial Measurement Unit) measurements. The new estimation system has two main parts, a stochastic cloning EKF (Extended Kalman Filter) estimator that loosely fuses both absolute state measurements (GPS, barometer) and the relative state measurements (IMU, visual odometry), and is derived and discussed in detail. A long-range stereo visual odometry is proposed for high-altitude MAV odometry calculation by using both multi-view stereo triangulation and a multi-view stereo inverse depth filter. The odometry takes the EKF information (IMU integral) for robust camera pose tracking and image feature matching, and the stereo odometry output serves as the relative measurements for the update of the state estimation. Experimental results on a benchmark dataset and our real flight dataset show the effectiveness of the proposed state estimation system, especially for the aggressive, intermittent GPS and high-altitude MAV flight.
Harnessing antiviral memory T cells for tumor immunotherapy (2020)

Abstract Overcoming the immunosuppressive tumor microenvironment remains a major impediment to successful cancer immunotherapy. Virus-specific memory T cells are positioned throughout the entire body to sense reinfection or recrudescence. Mouse models have demonstrated upon reencountering cognate antigen, these tissue resident memory T cells (TRM) induce a local immunostimulatory environment that activates and recruits innate and adaptive arms of the immune system, and we extend these functions to include recruitment of circulating antibody. Like healthy tissue, we observe that mouse and human tumors are commonly surveyed by virus-specific memory CD8+ T cells. This was seen in a range of tumor types including traditionally ‘immune-privilege’ tissues such as glioblastoma. Given the described immunostimualtory functions of antiviral TRM in healthy tissue, we tested if we could leverage antiviral CD8+ T cells in tumors as an immunotherapy. Local delivery of adjuvant-free peptide derived from previously encountered viruses successfully reactivated antiviral T cells within melanoma and glioblastoma tumors. This arrested growth of checkpoint blockade-resistant and poorly immunogenic tumors in mice. Antiviral T cell reactivation triggered antigen presentation and cytotoxic pathways within the tumor, activating T cells, dendritic cells and natural killer cells. Viral peptide treatment of ex vivo human tumors demonstrated upregulation of immune activation gene expression profiles similar to those observed in mice. Lastly, viral peptide therapy renders resistant mouse tumors susceptible to PD-L1 blockade. Thus, re-stimulating known antiviral immunity may provide a novel therapeutic approach for a broad range of tumors.
Do Not Capture: Automated Obscurity for Pervasive Imaging (2017)

The pervasive use of smartphones and wearables can compromise individuals' privacy, as they become unaware subjects of pictures and videos. Do Not Capture is a novel technology that removes unwilling subjects from media at capture time.
Compressive sensing of images with a priori known spatial support (2010)

In medical imaging, image background is often defined by zero signal. Moreover, in medical images the background area - or conversely, the spatial support (the extent of the non-zero part of the image) - is often known a priori or can be easily estimated. For example, support information can be estimated from the low-resolution "scout" images typically acquired during pre-scan localization in both MRI and CT. In dynamic scans, object support in a single time-frame is often obtainable from a prior time frame, or from a composite image formed from data from multiple time frames. In this work, incorporation of either complete or partial a priori knowledge of object spatial support into the compressive sensing (CS) framework is investigated. Following development of the augmented reconstruction model, examples of support-constrained CS reconstruction of phantom and MR images under both exact and inexact support definitions are given. For each experiment, the straightforward incorporation of the proposed spatial support constraint into the standard CS model was shown to both significantly accelerate reconstruction convergence and yield a lower terminal RMSE compared to a conventional CS reconstruction. The proposed augmented reconstruction model was also shown to be robust to inaccuracies in the estimated object support.
Entanglement-enabled interferometry using telescopic arrays (2018)

A protocol of measuring interferometric visibility function using imperfectly entangled states shared between remote telescopes is proposed. We demonstrate how quantum entanglement can be utilized to increase the baseline size of telescopic arrays thereby providing substantial enhancement to the resolution of direct-detection interferometric measurements. We demonstrate, through a comprehensive analysis, how errors in visibility measurements and in the intensity distribution of a distant object show dependence on the entanglement degree of the shared quantum resource. We analyse the feasibility of the protocol using currently available technology and identify the nature of sources that can benefit most from it.
A New Concept for Reconfigurable Planar Motion Generators (2013)

This paper presents a novel concept for Reconfigurable Motion Generators (RMGs) for multi-phase planar motion generation. Reconfigurable Motion Generators are a new class of mechanical devices that are designed for a specific part family and their associated motion generation tasks. Reconfigurable Motion Generators are capable of configuration changes according to variations in the motion generation requirements. Thus, Reconfigurable Motion Generators bridge the gap between the relatively high flexibility and high cost of totally flexible machines (e.g. industrial robots) and the low flexibility and low cost of fully dedicated mechanisms (e.g. cams & linkages). Here, we propose the concept of planar Reconfigurable Motion Generators for multi-phase motion generation tasks. This paper introduces design concepts and principles for the efficient and effective synthesis of Reconfigurable Motion Generators that may be deployed in various automated manufacturing environments.
T-cell responses to outer membrane proteins of Neisseria meningitidis: comparative study of the Opa, Opc, and PorA proteins (1996)

Former studies have shown that the class 5 outer membranes proteins (Opa and Opc proteins) of Neisseria meningitidis are at least as immunogenic as meningococcal porin proteins. High antibody titers to class 5 proteins have been observed in sera obtained during convalescence after meningococcal infection. A strong increase in anti-class 5 antibodies has also been observed in vaccinees who received a meningococcal outer membrane vesicle preparation. The enhanced B-cell response to class 5 proteins may be due to the presence of immunodominant helper T-cell epitopes in these proteins. In order to investigate this hypothesis, we tested purified Opa, Opc, and class 1 proteins for recognition by human T cells. a hierarchy of T-cell immunogenicity was observed among the outer membrane proteins, the Opa protein being more immunogenic than the other proteins. In most cases, the proliferative responses elicited by Opc were higher than the responses observed for the class 1 protein. The epitopes recognized by the immune T cells were identified by using overlapping synthetic peptides spanning the protein sequences of OpaB, Opa5d, and Opc.
Customized selection of frequency maps in an acoustic simulation of a cochlear implant (2006)

Cochlear implants can restore hearing to deaf individuals by electrically stimulating the auditory nerve. They do so by assigning different frequencies to different stimulating electrodes via a frequency map. We have developed a device that enables us to change the frequency map in real time. Here, in normal-hearing adults listening to an acoustic simulation of a cochlear implant, we investigate what frequency maps are initially preferred, and how the ability to understand speech with that preferred map compares with two other maps. We show that naive listeners prefer a map that balances the need for low-frequency information with the desire for a naturally-sounding stimulus, and that initial performance with this listener-selected map is better than that with a map that distorts the signal to provide low-frequency information.
The therapeutic phase I trial of the recombinant native HIV-1 Tat protein (2008)

The native HIV-1 Tat protein was chosen as a vaccine candidate based on its key role in the virus life cycle and on the correlation of Tat-specific immune responses with the asymptomatic stage and lower disease progression rates, but also due to its sequence conservation amongst the various HIV clades as well as the adjuvant effects on dendritic cells. Safety, immunogenicity and efficacy data in monkeys support the development of this vaccine concept.
Antitussive Activity of<i>Stemona</i>Alkaloids from<i>Stemona tuberosa</i> (2003)

Bioactivity-directed fractionation of the crude extract of Stemona tuberosa led to the isolation and characterization of four new stenine-type Stemona alkaloids, namely tuberostemonine J ( 2), tuberostemonine H ( 3), epi-bisdehydrotuberostemonine J ( 4) and neostenine ( 5), together with the known neotuberostemonine ( 1). These five isolated alkaloids were examined for antitussive activity in guinea pig after cough induction by citric acid aerosol stimulation. In this report, we demonstrated, for the first time, that compounds 1 and 5 showed significant antitussive activities. Further study of the structure-activity relationship on these isolated alkaloids and two synthetic analogues revealed that the saturated tricyclic pyrrolo[3,2,1- jk] benzazepine nucleus is the primary key structure contributing to the antitussive activity and all cis configurations at the three ring junctions are the optimal structure for the antitussive activity of stenine-type Stemona alkaloids.
Wide-field in vivo background free imaging by selective magnetic modulation of nanodiamond fluorescence (2014)

The sensitivity and resolution of fluorescence-based imaging in vivo is often limited by autofluorescence and other background noise. To overcome these limitations, we have developed a wide-field background-free imaging technique based on magnetic modulation of fluorescent nanodiamond emission. Fluorescent nanodiamonds are bright, photo-stable, biocompatible nanoparticles that are promising probes for a wide range of in vitro and in vivo imaging applications. Our readily applied background-free imaging technique improves the signal-to-background ratio for in vivo imaging up to 100-fold. This technique has the potential to significantly improve and extend fluorescent nanodiamond imaging capabilities on diverse fluorescence imaging platforms.
Quantum Algorithm for Simulating Real Time Evolution of Lattice Hamiltonians (2018)

We study the problem of simulating the time evolution of a lattice Hamiltonian, where the qubits are laid out on a lattice and the Hamiltonian only includes geometrically local interactions (i.e., a qubit may only interact with qubits in its vicinity). This class of Hamiltonians is very general and encompasses all physically reasonable Hamiltonians. Our algorithm simulates the time evolution of such a Hamiltonian on n qubits for time T up to error ε using O(T polylog(nT/ε)) gates with depth O(T polylog(nT/ε)). Our algorithm is the first simulation algorithm that achieves gate cost quasilinear in nT and polylogarithmic in 1/ε. Our algorithm also readily generalizes to time-dependent Hamiltonians and yields an algorithm with similar gate count for any piecewise slowly varying time-dependent bounded local Hamiltonian. We also prove a matching lower bound on the gate count of such a simulation, showing that any quantum algorithm that can simulate a piecewise constant bounded local Hamiltonian in one dimension to constant error requires (nT) gates in the worst case. The lower bound holds even if we only require the output state to be correct on local measurements. To our best knowledge, this is the first nontrivial lower bound on the gate complexity of the simulation problem. Our algorithm is based on a decomposition of the time-evolution unitary into a product of small unitaries using Lieb-Robinson bounds. In the appendix, we prove a Lieb-Robinson bound tailored to Hamiltonians with small commutators between local terms, giving zero Lieb-Robinson velocity in the limit of commuting Hamiltonians. This improves the performance of our algorithm when the Hamiltonian is close to commuting.