gebhart/patrepeval huggingface dataset:
Neural Spatio-Temporal Beamformer for Target Speech Separation (2020)

Purely neural network (NN) based speech separation and enhancement methods, although can achieve good objective scores, inevitably cause nonlinear speech distortions that are harmful for the automatic speech recognition (ASR). On the other hand, the minimum variance distortionless response (MVDR) beamformer with NN-predicted masks, although can significantly reduce speech distortions, has limited noise reduction capability. In this paper, we propose a multi-tap MVDR beamformer with complex-valued masks for speech separation and enhancement. Compared to the state-of-the-art NN-mask based MVDR beamformer, the multi-tap MVDR beamformer exploits the inter-frame correlation in addition to the inter-microphone correlation that is already utilized in prior arts. Further improvements include the replacement of the real-valued masks with the complex-valued masks and the joint training of the complex-mask NN. The evaluation on our multi-modal multi-channel target speech separation and enhancement platform demonstrates that our proposed multi-tap MVDR beamformer improves both the ASR accuracy and the perceptual speech quality against prior arts.
Hydrogenation of dicarboxylic acids to diols over Re–Pd catalysts (2016)

<italic>Ex situ</italic> liquid-phase reduced Re–Pd/SiO<sub>2</sub> (Re/Pd = 8) showed good performance in the hydrogenation of dicarboxylic acids to diols.
A performance analysis of the partial randomization dynamic element matching DAC architecture (2002)

This paper presents the results of a performance analysis of a novel dynamic element matching technique for low harmonic distortion digital-to-analog converters. The technique promises to be suitable for applications such as direct digital synthesis systems, wherein low hardware complexity is essential in addition to low harmonic distortion. As the main result of the analysis, the DAC can be designed such that the hardware complexity is reduced to a minimum while still providing a given least required spurious-free dynamic range.
<title>Real-time passive millimeter-wave imaging from a helicopter platform</title> (2000)

Real time passive millimeter-wave imaging systems have a wide variety of uses from aircraft navigation and landing in fog to detection of concealed weapons. A useful imaging system for flight platforms requires a large number of pixels and a high frame rate combined with a small antenna volume and a lost cost. We present a millimeter-wave imaging system which uses 32 MMIC low noise amplifiers to display a 60 X 75 pixel image at a 30 Hz frame rate. The system's pupil-plane phased array architecture allows for a relatively thin large aperture antenna. A remotely located processor utilizes microwave guiding circuit boards to perform phase and frequency discrimination on the radiation received by the antenna array.
Combinatorial discovery of polymers resistant to bacterial attachment (2012)

Bacterial attachment and subsequent biofilm formation pose key challenges to the optimal performance of medical devices. In this study, we determined the attachment of selected bacterial species to hundreds of polymeric materials in a high-throughput microarray format. Using this method, we identified a group of structurally related materials comprising ester and cyclic hydrocarbon moieties that substantially reduced the attachment of pathogenic bacteria (Pseudomonas aeruginosa, Staphylococcus aureus and Escherichia coli). Coating silicone with these 'hit' materials achieved up to a 30-fold (96.7%) reduction in the surface area covered by bacteria compared with a commercial silver hydrogel coating in vitro, and the same material coatings were effective at reducing bacterial attachment in vivo in a mouse implant infection model. These polymers represent a class of materials that reduce the attachment of bacteria that could not have been predicted to have this property from the current understanding of bacteria-surface interactions.
3D Printing of Regenerated Silk Fibroin and Antibody-Containing Microstructures via Multiphoton Lithography (2017)

Regenerated silk fibroin, a biopolymer derived from silkworm cocoons, is a versatile material that has been widely explored for a number of applications (e.g., drug delivery, tissue repair, biocompatible electronics substrates, and optics) due to its attractive biochemical properties and processability. Here, we report on the free-form printing of silk-based, 3D microstructures through multiphoton lithography. Utilizing multiphoton lithography in conjunction with specific photoinitiator chemistry and postprint cross-linking, a number of microarchitectures were achieved including self-supporting fibroin arches. Further, the straightforward production of high fidelity and biofunctional protein architectures was enabled through the printing of aqueous fibroin/immunoglobulin solutions.
676. An Engineered CAR T Cell Platform for Allogeneic Combination Immunotherapy (2016)

The adoptive transfer of CAR T cell represents a highly promising strategy to fight against multiple cancers. The clinical outcome of such therapies is intimately linked to the ability of effector cells to engraft, proliferate and specifically kill tumor cells within patients. When allogeneic CAR T cell infusion is considered, host versus graft and graft versus host reactions must be avoided to prevent rejection of adoptively transferred cells, host tissue damages and to elicit significant antitumoral outcome. This work proposes to address these three requirements through the development of multidrug resistant TCR-deficient CAR T cells. We demonstrate in vitro and in an in vivo xenograft mice model, that these engineered T cells displayed efficient antitumor activity and proliferated in the presence of single or muliple nucleotide analogues, currently used in clinic as preconditioning lymphodepleting regimens and antineoplastic agents. The absence of TCR at their cell surface along with their nucleotide analogues-resistance properties could prevent their alloreactivity and enable them to resist to lymphodepleting regimens that may be required to avoid their ablation via HvG reaction. By providing a basic frame work to develop a universal T cell compatible with allogeneic adoptive transfer, this work is laying the foundation stone of the large scale utilization of CAR T cell immunotherapies.
High-molecular-size mite allergens with high carbohydrate content in mite extract containing mite feces of Dermatophagoides farinae. (1995)

A series of mite allergens with high carbohydrate content was fractionated from mite extract containing mite feces by ultrafiltration, and successive chromatography on Ultrogel AcA 54, Sepharose CL-6B, and DEAE Toyopearl 650S. The final fractions isolated were termed HM1-2-Eff, -0.1A, -0.1B, -0.3A, -0.3B, and -1M according to the eluted salt concentration. These six fractions were stained weakly with Coomassie Brilliant Blue but strongly with periodate-Schiff's reagent on SDS-PAGE. Their molecular weight were estimated to be 150-155 KD on Sepharose CL-6B. All of these six fractions provoked strong erythema in skin of mite-sensitive and asthmatic patients. HM1-2-Eff, -0.1A, -0.1B and -0.3B reacted with 73% of mite-sensitive patients' IgE by the nitrocellulose dot blotting. One ng/ml of 4 fractions (HM1-2-0.1A, 0.3A, 0.3B and -1M) released histamine from mite allergic patient's blood cells. HM1-2-0.3A induced proliferation of T cell from immunized mouse by mite extract containing mite feces (Dff).
Bayesian Sequential Indicator Simulation of Channel Sands From 3-D Seismic Data in The Oseberg Field, Norwegian North Sea (1994)

Abstract Subsurface models of lithology are often poorly constrained due to the lack of dense well control. Although limited in vertical resolution, high quality 3-D seismic data usually provide valuable information regarding the lateral variations of lithology. The Bayesian Sequential Indicator SIMulation (BSISIM) technique is a new stochastic method to generate seismically constrained models of lithology. Unlike cokriging-based simulation methods, BSISIM does not rely on a generalized linear regression model, which is inadequate when combining lithology indicator variables and continuous seismic attributes. Instead, BSISIM uses a Bayesian updating rule to construct a posterior probability distribution of lithoclasses at each location. The posterior distribution combines a local prior distribution obtained by indicator kriging with a function representing the seismic likelihood of the different lithofacies. The local posterior distributions are sampled sequentially at all points in space to generate realizations from the joint posterior distribution. The realizations define alternative, equiprobable lithologic models, representing a compromise between fidelity to the seismic data, as measured by the likelihood functions, and consistency with spatial continuity information, as expressed by the lithology indicator correlation functions. The simulation technique is applied to predict the lateral distribution of channel sands in the Ness Formation of the Oseberg Field. Channel sand maps are simulated using lithologic observations in fourteen wells, and seismic amplitude and channel orientation data extracted from a 3-D survey. Sand probability maps, generated by summarizing a large number of simulations, allow delineation of the probable lateral extent of the channel deposits. Comparison of seismically derived lithologic models to well-derived models demonstrates the improved definition of channel geometry achieved by integrating the geophysical information.
Training Deep Networks with Synthetic Data: Bridging the Reality Gap by Domain Randomization (2018)

We present a system for training deep neural networks for object detection using synthetic images. To handle the variability in real-world data, the system relies upon the technique of domain randomization, in which the parameters of the simulator-such as lighting, pose, object textures, etc.-are randomized in non-realistic ways to force the neural network to learn the essential features of the object of interest. We explore the importance of these parameters, showing that it is possible to produce a network with compelling performance using only non-artistically-generated synthetic data. With additional fine-tuning on real data, the network yields better performance than using real data alone. This result opens up the possibility of using inexpensive synthetic data for training neural networks while avoiding the need to collect large amounts of hand-annotated real-world data or to generate high-fidelity synthetic worlds-both of which remain bottlenecks for many applications. The approach is evaluated on bounding box detection of cars on the KITTI dataset.
Development of an Automatic Photometric Analyzer (1974)

A new automatic photometric analyzer has been developed as a series of studies on automation of wet chemical analysis of iron and steel samples. The developed analyzer (Photo. 1, Fig. 1) performs automatically and continuously all the photometric procedures after preparation of sample sulution usually by acid dissolution method. The above procedures were previously carried out by complicated and time-comsuming manual operation.The analyzer is mainly composed of the injecting davice for sample solution, the adding device for reagent solutions and water, the device for developing color and measuring the absorbancy, the controlling device and the recording device. The third device is most characteristic and is composed of the reaction vessel and the solution circulating pipe with a gas blowing tube, a bubble eliminator, an absorbancy measuring cell and a drain cock.The analyzer was applied to determination of phosphorus, silicon, manganese and acid soluble aluminum in steel samples. From 0.0005% to 0.1% of phosphorus was determined in 6 min for one determination on principle of molybdenum blue spectrophotometry. From 0.002% to 1% of silicon was determined in 6 min on principle of molybdenum blue spectrophotometry. From 0.001% to 1% of manganese was determined in 5 min on priciple of sodium periodate oxidization spectrophotometry. From 0.0005% to 0.01% of acid soluble aluminum was determined in 6 min on principle of eriochrome cyanine R spectrophotometry.
Inheritance of Sulfonylurea Herbicide Resistance in<i>Lactuca</i>spp. (1990)

Sulfonylurea herbicide resistance was crossed into a susceptible (S) prickly lettuce biotype and into ‘Bibb’ (B), a domestic lettuce cultivar, and inheritance of the resistance trait was determined. The best fit for Chi Square analysis of the metsulfuron treated F 2 generations was a 1:2:1 ratio indicating the trait was controlled by a single nuclear gene with incomplete dominance. F 3 generations also were treated with metsulfuron. The F 3 seedlings from resistant F 2 plants were resistant while the F 3 seedlings from intermediate F 2 plants segregated.
Investigation into Low-Temperature Urea-Water Solution Decomposition by Addition of Titanium-Based Isocyanic Acid Hydrolysis Catalyst and Surfactant (2020)

<div class="section abstract"><div class="htmlview paragraph">Mitigation of urea deposit formation and improved ammonia production at low exhaust temperatures continues to be one of the most significant challenges for current generation selective catalytic reduction (SCR) aftertreatment systems. Various technologies have been devised to alleviate these issues including: use of alternative reductant sources, and thermal treatment of the urea-water solution (UWS) pre-injection. The objective of this work was to expand the knowledge base of a potential third option, which entails chemical modification of UWS by addition of a titanium-based urea/isocyanic acid (HNCO) decomposition catalysts and/or surfactant to the fluid. Physical solid mixtures of urea with varying concentrations of ammonium titanyl oxalate (ATO), oxalic acid, and titanium dioxide (TiO<sub>2</sub>) were generated, and the differences in NH<sub>3</sub> and CO<sub>2</sub> produced upon thermal decomposition were quantified. It was found that addition of 2.0 mol % ATO to urea increased CO<sub>2</sub> production by 821 % and NH<sub>3</sub> production by 96 % at temperatures ≤ 215 °C, indicating significantly enhanced hydrolysis of HNCO. Conversely, it was demonstrated that addition of oxalic acid or TiO<sub>2</sub> to urea exhibited little effect on NH<sub>3</sub> and CO<sub>2</sub> production, indicating both the importance of titanium in the mixture and adequate catalyst-substrate contact. Previous work by the authors demonstrated that addition of ATO to UWS did indeed result in decreased deposit formation in the exhaust system when compared to conventional UWS, and the extent of deposit reduction could be further enhanced by addition of surfactant to the solution. In this work, six distinct surfactants were added to UWS both with and without ATO, and the effect on deposit formation was quantified. In all cases, addition of both surfactant and ATO resulted in superior deposit mitigation when compared to UWS treated with ATO or surfactant individually. Finally, various ammonium peroxo-hydroxo titanium coordination complexes were synthesized and evaluated for catalytic urea decomposition using TGA-FTIR and compared against the observed activity of ATO.</div></div>
High relaxivity MRI imaging reagents from bimodal star polymers (2011)

Star polymer architectures were developed as multimodal imaging systems as fluorescence and magnetic resonance imaging (MRI) agents. Acrylate star polymers in hydrodynamic diameters of 10 ± 2 nm comprising fluorene derivatives as core units were modified with dopamine derivatives in adjustable quantities to chelate lanthanides such as Gd3+ and Eu3+. Ionic relaxivity values of 84 mM−1s−1 in an applied magnetic field of 0.5T at 37 °C confirmed the rapid water exchange of the highly hydrated star polymer. The utility is extended by the consecutive modification with allyl groups to perform thiol-ene reactions to conjugate thiol modified targeting units such as (cRGD) and dendritic molecular transporter as cell penetrating units. Cell uptake experiments in NIH 3T3 cells showed a rapid uptake of the star polymer independently of the presence of molecular transporter unit as it was detected through both the blue fluorescence of the fluorine core and the red fluorescence of the complexed Eu3+ to the linear polymer arms. In vivo mouse models confirmed the star polymer imaging reagent altered the image contrast significantly. In this work, we have adapted macromolecules as imaging agents for fluorescence microscopy and magnetic resonance imaging in conjunction with intracellular delivery and targeting.
New streptozotocin analogs with improved antileukemic activity (1974)

ADVERTISEMENT RETURN TO ISSUEPREVArticleNEXTNew streptozotocin analogs with improved antileukemic activityAllan N. Fujiwara, Edward M. Acton, and David W. HenryCite this: J. Med. Chem. 1974, 17, 4, 392–396Publication Date (Print):April 1, 1974Publication History Published online1 May 2002Published inissue 1 April 1974https://pubs.acs.org/doi/10.1021/jm00250a004https://doi.org/10.1021/jm00250a004research-articleACS PublicationsRequest reuse permissionsArticle Views64Altmetric-Citations11LEARN ABOUT THESE METRICSArticle Views are the COUNTER-compliant sum of full text article downloads since November 2008 (both PDF and HTML) across all institutions and individuals. These metrics are regularly updated to reflect usage leading up to the last few days.Citations are the number of other articles citing this article, calculated by Crossref and updated daily. Find more information about Crossref citation counts.The Altmetric Attention Score is a quantitative measure of the attention that a research article has received online. Clicking on the donut icon will load a page at altmetric.com with additional details about the score and the social media presence for the given article. Find more information on the Altmetric Attention Score and how the score is calculated. Share Add toView InAdd Full Text with ReferenceAdd Description ExportRISCitationCitation and abstractCitation and referencesMore Options Share onFacebookTwitterWechatLinked InRedditEmail Other access optionsGet e-Alertsclose Get e-Alerts
Oscillatory Neurocomputers with Dynamic Connectivity (1999)

Our study of thalamo-cortical systems suggests a new architecture for a neurocomputer that consists of oscillators having different frequencies and that are connected weakly via a common medium forced by an external input. Even though such oscillators are all interconnected homogeneously, the external input imposes a dynamic connectivity. We use Kuramoto's model to illustrate the idea and to prove that such a neurocomputer has oscillatory associative properties. Then we discuss a general case. The advantage of such a neurocomputer is that it can be built using voltage controlled oscillators, optical oscillators, lasers, microelectromechanical systems, Josephson junctions, macromolecules, or oscillators of other kinds. (Provisional patent 60/108,353)
Approximation of functions over redundant dictionaries using coherence (2003)

One of the central problems of modern mathematical approximation theory is to approximate functions, or signals, concisely, with elements from a large candidate set called a dictionary. Formally, we are given a signal A ∈ RN and a dictionary D = {φi}i∈I of unit vectors that span RN. A representation R of B terms for input A ∈ RN is a linear combination of dictionary elements, R = σi∈A αiφi, for φi ∈ D and some A, vAv ≥ B. Typically, B ⪡ N, so that R is a concise approximation to signal A. The error of the representation indicates by how well it approximates A, and is given by ∥A - R∥2 = √Σt|A[t - R[t]|2. The problem is to find the best B-term representation, i.e., find a R that minimizes ∥A - R∥2. A dictionary may be redundant in the sense that there is more than one possible exact representation for A, i.e., vDv > N = dim(RN). Redundant dictionaries are used because, both theoretically and in practice, for important classes of signals, as the size of a dictionary increases, the error and the conciseness of the approximations improve.We present the first known efficient algorithm for finding a provably approximate representation for an input signal over redundant dictionaries. We identify and focus on redundant dictionaries with small coherence (ie., vectors are nearly orthogonal). We present an algorithm that preprocesses any such dictionary in time and space polynomial in vDv, and obtains an 1 + e approximate representation of the given signal in time nearly linear in signal size N and polylogarithmic in vDv; by contrast, most algorithms in the literature require Ω(vDv)time, and, yet, provide no provable bounds. The technical crux of our result is our proof that two commonly used local search techniques, when combined appropriately, gives a provably near-optimal signal representation over redundant dictionaries with small coherence. Our result immediately applies to several specific redundant dictionaries considered by the domain experts thus far. In addition, we present new redundant dictionaries which have small coherence (and therefore are amenable to our algorithms) and yet have significantly large sizes, thereby adding to the redundant dictionary construction literature.Work with redundant dictionaries forms the emerging field of highly nonlinear approximation theory. We have presented algorithmic results for some of the most basic problems in this area, but other mathematical and algorithmic questions remain to be explored.
A General Method for Estimating Correlated Aggregates over a Data Stream (2012)

On a stream of two dimensional data items (x,y) where x is an item identifier, and y is a numerical attribute, a correlated aggregate query requires us to first apply a selection predicate along the second (y) dimension, followed by an aggregation along the first (x) dimension. For selection predicates of the form (y <; c) or (y >;, c), where parameter c is provided at query time, we present new streaming algorithms and lower bounds for estimating statistics of the resulting sub stream of elements that satisfy the predicate. We provide the first sub linear space algorithms for a large family of statistics in this model, including frequency moments. We experimentally validate our algorithms, showing that their memory requirements are significantly smaller than existing linear storage schemes for large datasets, while simultaneously achieving fast per-record processing time. We also study the problem when the items have weights. Allowing negative weights allows for analyzing values which occur in the symmetric difference of two datasets. We give a strong space lower bound which holds even if the algorithm is allowed up to a logarithmic number of passes over the data(before the query is presented). We complement this with a small space algorithm which uses a logarithmic number of passes.