gebhart/patrepeval huggingface dataset:
Single and multiscale detection of masses in digital mammograms (1999)

Scale is an important issue in the automated detection of masses in mammograms, due to the range of possible sizes masses can have. In this work, it was examined if detection of masses can be done at a single scale, or whether it is more appropriate to use the output of the detection method at different scales in a multiscale scheme. Three different pixel-based mass-detection methods were used for this purpose. The first method is based on convolution of a mammogram with the Laplacian of a Gaussian, the second method is based on correlation with a model of a mass, and the third is a new approach, based on statistical analysis of gradient-orientation maps. Experiments with simulated masses indicated that little can be gained by applying the methods at a number of scales. These results were confirmed by experiments on a set of 71 cases (132 mammograms) containing a malignant tumor. The performance of each method in a multiscale scheme was similar to the performance at the optimal single scale. A slight improvement was found for the correlation method when the output of different scales was combined. This was especially evident at low specificity levels. The correlation method and the gradient-orientation-analysis method have similar performances. A sensitivity of approximately 75% is reached at a level of one false positive per image. The method based on convolution with the Laplacian of the Gaussian performed considerably worse, in both a single and multiscale scheme.
Imaging across multiple spatial scales with the multi-camera array microscope (2023)

This paper experimentally examines different configurations of a multi-camera array microscope (MCAM) imaging technology. The MCAM is based upon a densely packed array of “micro-cameras” to jointly image across a large field-of-view (FOV) at high resolution. Each micro-camera within the array images a unique area of a sample of interest, and then all acquired data with 54 micro-cameras are digitally combined into composite frames, whose total pixel counts significantly exceed the pixel counts of standard microscope systems. We present results from three unique MCAM configurations for different use cases. First, we demonstrate a configuration that simultaneously images and estimates the 3D object depth across a 100×135mm 2 FOV at approximately 20 µm resolution, which results in 0.15 gigapixels (GP) per snapshot. Second, we demonstrate an MCAM configuration that records video across a continuous 83×123mm 2 FOV with twofold increased resolution (0.48 GP per frame). Finally, we report a third high-resolution configuration (2 µm resolution) that can rapidly produce 9.8 GP composites of large histopathology specimens.
Empirical Tuning of an On-Board Gas Turbine Engine Model for Real-Time Module Performance Estimation (2008)

A practical consideration for implementing a real-time on-board engine component performance tracking system is the development of high fidelity engine models capable of providing a reference level from which performance changes can be trended. Real-time engine models made their advent as state variable models in the mid-1980s, which utilized a piecewise linear model that granted a reasonable representation of the engine during steady state operation and mild transients. Increased processor speeds over the next decade allowed more complex models to be considered, that were a combination of linear and nonlinear physics-based elements. While the latter provided greater fidelity over both transient operation and the engine operational flight envelope, these models could be further improved to provide the high level of accuracy required for long-term performance tracking, as well as address the issue of engine-to-engine variation. Over time, these models may deviate enough from the actual engine being monitored, as a result of improvements made during an engine’s life cycle such as hardware modifications, bleed and stator vane schedule alterations, cooling flow adjustments, and the like, that the module performance estimations are inaccurate and often misleading. The process described in this paper will address these shortcomings while maintaining the execution speed required for real-time implementation.
Biocompatibility of pristine graphene for neuronal interface (2013)

Object Graphene possesses unique electrical, physical, and chemical properties that may offer significant potential as a bioscaffold for neuronal regeneration after spinal cord injury. The purpose of this investigation was to establish the in vitro biocompatibility of pristine graphene for interface with primary rat cortical neurons. Methods Graphene films were prepared by chemical vapor deposition on a copper foil catalytic substrate and subsequent apposition on bare Permanox plastic polymer dishes. Rat neuronal cell culture was grown on graphene-coated surfaces, and cell growth and attachment were compared with those on uncoated and poly- d -lysine (PDL)-coated controls; the latter surface is highly favorable for neuronal attachment and growth. Live/dead cell analysis was conducted with flow cytometry using ethidium homodimer-1 and calcein AM dyes. Lactate dehydrogenase (LDH) levels—indicative of cytotoxicity—were measured as markers of cell death. Phase contrast microscopy of active cell culture was conducted to assess neuronal attachment and morphology. Results Statistically significant differences in the percentage of live or dead neurons were noted between graphene and PDL surfaces, as well as between the PDL-coated and bare surfaces, but there was little difference in cell viability between graphene-coated and bare surfaces. There were significantly lower LDH levels in the graphene-coated samples compared with the uncoated ones, indicating that graphene was not more cytotoxic than the bare control surface. According to phase contrast microscopy, neurons attached to the graphene-coated surface and were able to elaborate long, neuritic processes suggestive of normal neuronal metabolism and morphology. Conclusions Further use of graphene as a bioscaffold will require surface modification that enhances hydrophilicity to increase cellular attachment and growth. Graphene is a nanomaterial that is biocompatible with neurons and may have significant biomedical applications.
Metabolite biomarkers of prostate cancer (2008)

A27 Background: There are 35 million men ages 50-74 in the United States. The American Cancer Society recommends that men ages 50 and over be screened for prostate cancer. Each year over 20 million Prostate Specific Antigen (PSA) tests are performed, and over one million of these tests are returned positive indicating a risk of prostate cancer. Eight hundred thousand men who have a positive PSA screening test undergo a biopsy where multiple prostate tissue samples are taken and examined by a pathologist. Only 30% of biopsies are confirmed positive for prostate cancer, indicating that a majority represented unnecessary procedures and costs.  Aim: Identify, using metabolomics, biomarkers to be used as a diagnostic for determining which men with elevated PSA levels have prostate cancer, and which do not.  Methods: Metabolomics was performed on post-DRE (digital rectal exam), pre-biopsy urine specimens obtained from men at-risk for prostate cancer on the basis of a positive PSA test or DRE. All of the men subsequently underwent a prostate biopsy and the tissue was scored for presence [biopsy+] or absence [biopsy-] of prostate cancer. Metabolomics was performed on a mass spectrometry-based platform including LC-MS-MS and GC-MS instrumentation and automated peak resolution and compound identification software. Small molecular weight metabolites in the mass range of 80-1000 daltons were identified in a non-targeted fashion. Multiple statistical analyses were performed identifying biomarkers correlated with the clinical diagnoses.  Results: The results showed that the levels of specific metabolites in the urine samples could be used to discriminate men that had prostate cancer from those that did not (determined by later needle biopsy). Seventy metabolites were identified as significantly changed (Wilcoxon rank sum test, p In vitro experiments confirmed the role for sarcosine in tumor progression. Addition of MG to benign prostate epithelial cells rendered them invasive as measured by Boyden chamber matrigel invasion assays. In addition, RNAi mediated knock-down of glycine-N-methyltransferase (an enzyme that catalyzes MG production) reduced both MG levels and cell invasive properties. Another metabolite biomarker of prostate cancer was N-acetylasparate (NAA). This biomarker correlates mechanistically with the known behavior of Prostate Specific Membrane Antigen (PSMA). PSMA is a carboxypeptidase overexpressed in prostate cancer whose product is NAA.  Conclusion: Metabolomics has been employed to identify new biomarkers for diagnosis of prostate cancer in a clinically challenging cohort comprised of high PSA individuals. These biomarkers are being employed to develop a panel of metabolites with diagnostic potential for this deadly disease.  Supported in part by the Early Detection Research Network (UO1 CA111275-01 to AMC.), National Institutes of Health (RO1CA133458 to AS., TMR and AMC).
Implementation Complexity for Achieving Bit Permutations in One or Two Cycles in Superscalar Processors (2004)

Abstract — The increasing importance of secure information processing in publicly accessible Internet and wireless networks poses new challenges in the architecture of future general-purpose processors. Symmetric-key cryptography algorithms are an important class of algorithms used to achieve confidentiality. Many of them use a category of operations that are not well supported by today’s word-oriented microprocessors: bit-oriented permutations. In this paper, we show how arbitrary bit permutations within a word can be achieved in just one or two cycles. This improves upon the O(n) instructions needed to achieve any one of n! permutations of n bits in existing RISC processors; it also improves upon recent work that achieves this in O(log(n)) instructions and cycles. This paper contributes two new architectural solutions, one with only microarchitecture changes, and another with ISA support as well. Slightly enhanced 4-way and 2-way superscalar microprocessors can achieve arbitrary 64-bit permutations in one or two cycles. We also define new architectural concepts for (s,t) datapaths and functional units, and grouped instructions. Keywords—cryptography; bit permutation; superscalar; processor architecture; instruction set architecture (ISA); microarchitecture; I.
NewsQA: A Machine Comprehension Dataset (2016)

We present NewsQA, a challenging machine comprehension dataset of over 100,000 human-generated question-answer pairs. Crowdworkers supply questions and answers based on a set of over 10,000 news articles from CNN, with answers consisting of spans of text from the corresponding articles. We collect this dataset through a four-stage process designed to solicit exploratory questions that require reasoning. A thorough analysis confirms that NewsQA demands abilities beyond simple word matching and recognizing textual entailment. We measure human performance on the dataset and compare it to several strong neural models. The performance gap between humans and machines (0.198 in F1) indicates that significant progress can be made on NewsQA through future research. The dataset is freely available at https://datasets.maluuba.com/NewsQA.
Planarized process for resonant leaky-wave coupled phase-locked arrays of mid-IR quantum cascade lasers (2015)

On-chip resonant leaky-wave coupling of quantum cascade lasers (QCLs) emitting at 8.36 μm has been realized by selective regrowth of interelement layers in curved trenches, defined by dry and wet etching. The fabricated structure provides large index steps (Δn = 0.10) between antiguided-array element and interelement regions. In-phase-mode operation to 5.5 W front-facet emitted power in a near-diffraction-limited far-field beam pattern, with 4.5 W in the main lobe, is demonstrated. A refined fabrication process has been developed to produce phased-locked antiguided arrays of QCLs with planar geometry. The main fabrication steps in this process include non-selective regrowth of Fe:InP in interelement trenches, defined by inductive-coupled plasma (ICP) etching, a chemical polishing (CP) step to planarize the surface, non-selective regrowth of interelement layers, ICP selective etching of interelement layers, and non-selective regrowth of InP cladding layer followed by another CP step to form the element regions. This new process results in planar InGaAs/InP interelement regions, which allows for significantly improved control over the array geometry and the dimensions of element and interelement regions. Such a planar process is highly desirable to realize shorter emitting wavelength (4.6 μm) arrays, where fabrication tolerance for single-mode operation are tighter compared to 8 μm-emitting devices.
A 3D Model of the Membrane Protein Complex Formed by the White Spot Syndrome Virus Structural Proteins (2010)

From our present results in conjunction with other previously established interactions we construct a 3D model in which VP24 acts as a core protein that directly associates with VP26, VP28, VP38A, VP51A and WSV010 to form a membrane-associated protein complex. VP19 and VP37 are attached to this complex via association with VP51A and VP28, respectively. Through the VP26-VP51C interaction this envelope complex is anchored to the nucleocapsid, which is made of layers of rings formed by VP664. A 3D model of the nucleocapsid and the surrounding outer membrane is presented.
Zero-Shot Sketch-Image Hashing (2018)

Recent studies show that large-scale sketch-based image retrieval (SBIR) can be efficiently tackled by cross-modal binary representation learning methods, where Hamming distance matching significantly speeds up the process of similarity search. Providing training and test data subjected to a fixed set of pre-defined categories, the cutting-edge SBIR and cross-modal hashing works obtain acceptable retrieval performance. However, most of the existing methods fail when the categories of query sketches have never been seen during training. In this paper, the above problem is briefed as a novel but realistic zero-shot SBIR hashing task. We elaborate the challenges of this special task and accordingly propose a zero-shot sketch-image hashing (ZSIH) model. An end-to-end three-network architecture is built, two of which are treated as the binary encoders. The third network mitigates the sketch-image heterogeneity and enhances the semantic relations among data by utilizing the Kronecker fusion layer and graph convolution, respectively. As an important part of ZSIH, we formulate a generative hashing scheme in reconstructing semantic knowledge representations for zero-shot retrieval. To the best of our knowledge, ZSIH is the first zero-shot hashing work suitable for SBIR and cross-modal search. Comprehensive experiments are conducted on two extended datasets, i.e., Sketchy and TU-Berlin with a novel zero-shot train-test split. The proposed model remarkably outperforms related works.
paGAN (2018)

With the rising interest in personalized VR and gaming experiences comes the need to create high quality 3D avatars that are both low-cost and variegated. Due to this, building dynamic avatars from a single unconstrained input image is becoming a popular application. While previous techniques that attempt this require multiple input images or rely on transferring dynamic facial appearance from a source actor, we are able to do so using only one 2D input image without any form of transfer from a source image. We achieve this using a new conditional Generative Adversarial Network design that allows fine-scale manipulation of any facial input image into a new expression while preserving its identity. Our photoreal avatar GAN (paGAN) can also synthesize the unseen mouth interior and control the eye-gaze direction of the output, as well as produce the final image from a novel viewpoint. The method is even capable of generating fully-controllable temporally stable video sequences, despite not using temporal information during training. After training, we can use our network to produce dynamic image-based avatars that are controllable on mobile devices in real time. To do this, we compute a fixed set of output images that correspond to key blendshapes, from which we extract textures in UV space. Using a subject's expression blendshapes at run-time, we can linearly blend these key textures together to achieve the desired appearance. Furthermore, we can use the mouth interior and eye textures produced by our network to synthesize on-the-fly avatar animations for those regions. Our work produces state-of-the-art quality image and video synthesis, and is the first to our knowledge that is able to generate a dynamically textured avatar with a mouth interior, all from a single image.
Computer Control of Drug Delivery by Continuous Intravenous Infusion (2014)

Compared with conventional methods, algorithm-based computer control of carrier and drug flows can improve drug delivery by pump-driven intravenous infusion to better match intent. For norepinephrine infusions, the amount of drug reaching the bloodstream per time appears to be a dominant factor in the hemodynamic response to infusion.
Crystallization method employgin microwave radiation (1988)

A crystallization method which comprises: (a) providing a crystallization medium comprising crystallizable zeolite precursor materials and a heat transfer agent sympathetic to microwave energy; and (b) subjecting the crystallization medium to microwave energy at a frequency range effective to crystallize the crystallizable zeolite precursor materials to produce zeolite.
Redesign of a cross-reactive antibody to dengue virus with broad-spectrum activity and increased in vivo potency (2013)

Affinity improvement of proteins, including antibodies, by computational chemistry broadly relies on physics-based energy functions coupled with refinement. However, achieving significant enhancement of binding affinity (>10-fold) remains a challenging exercise, particularly for cross-reactive antibodies. We describe here an empirical approach that captures key physicochemical features common to antigen-antibody interfaces to predict protein-protein interaction and mutations that confer increased affinity. We apply this approach to the design of affinity-enhancing mutations in 4E11, a potent cross-reactive neutralizing antibody to dengue virus (DV), without a crystal structure. Combination of predicted mutations led to a 450-fold improvement in affinity to serotype 4 of DV while preserving, or modestly increasing, affinity to serotypes 1-3 of DV. We show that increased affinity resulted in strong in vitro neutralizing activity to all four serotypes, and that the redesigned antibody has potent antiviral activity in a mouse model of DV challenge. Our findings demonstrate an empirical computational chemistry approach for improving protein-protein docking and engineering antibody affinity, which will help accelerate the development of clinically relevant antibodies.
Cyclopentane-Peptide Nucleic Acids for Qualitative, Quantitative, and Repetitive Detection of Nucleic Acids (2012)

We report the development of chemically modified peptide nucleic acids (PNAs) as probes for qualitative and quantitative detection of DNA. The remarkable stability of PNAs toward enzymatic degradation makes this class of molecules ideal to develop as part of a diagnostic device that can be used outside of a laboratory setting. Using an enzyme-linked reporter assay, we demonstrate that excellent levels of detection and accuracy for anthrax DNA can be achieved using PNA probes with suitable chemical components designed into the probe. In addition, we report on DNA-templated cross-linking of PNA probes as a way to preserve genetic information for repetitive and subsequent analysis. This report is the first detailed examination of the qualitative and quantitative properties of chemically modified PNA for nucleic acid detection and provides a platform for studying and optimizing PNA probes prior to incorporation into new technological platforms.
Attenuated Influenza Virus Construct with Enhanced Hemagglutinin Protein Expression (2012)

Influenza A viruses encoding an altered viral NS1 protein have emerged as promising live attenuated vaccine platforms. A carboxy-terminal truncation in the NS1 protein compromises its interferon antagonism activity, making these viruses attenuated in the host yet still able to induce protection from challenge with wild-type viruses. However, specific viral protein expression by NS1-truncated viruses is known to be decreased in infected cells. In this report, we show that recombinant H5N1 and H1N1 influenza viruses encoding a truncated NS1 protein expressed lower levels of hemagglutinin (HA) protein in infected cells than did wild-type viruses. This reduction in HA protein expression correlated with a reduction in HA mRNA levels in infected cells. NS1 truncation affected the expression of HA protein but not that of the nucleoprotein (NP). This segment specificity was mapped to the terminal sequences of their specific viral RNAs. Since the HA protein is the major immunogenic component in influenza virus vaccines, we sought to restore its expression levels in NS1-truncated viruses in order to improve their vaccine efficacy. For this purpose, we generated an NS1-truncated recombinant influenza A/Puerto Rico/8/34 (rPR8) virus carrying the G3A C8U "superpromoter" mutations in the HA genomic RNA segment. This strategy retained the attenuation properties of the recombinant virus but enhanced the expression level of HA protein in infected cells. Finally, mice immunized with rPR8 viruses encoding a truncated NS1 protein and carrying the G3A C8U mutations in the HA segment demonstrated enhanced protection from wild-type virus challenge over that for mice vaccinated with an rPR8 virus encoding the truncated NS1 protein alone.
Water-cooled internal combustion engine with a sound-absorbing cover (1985)

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A real-time distributed fiber strain sensor for long-distance perimeter intruder detection (2005)

A real-time distributed fiber sensor is described, which is based on Brillouin optical time-domain reflectometry using our propriety fiber laser technology. The sensor offers capabilities of protecting security sectors to larger perimeters using commercial fiber.
Rapid Identification of <i>Candida</i> Species with Species-Specific DNA Probes (1998)

Rapid identification of Candida species has become more important because of an increase in infections caused by species other than Candida albicans, including species innately resistant to azole antifungal drugs. We previously developed a PCR assay with an enzyme immunoassay (EIA) format to detect amplicons from the five most common Candida species by using universal fungal primers and species-specific probes directed to the ITS2 region of the gene for rRNA. We designed probes to detect seven additional Candida species (C. guilliermondii, C. kefyr, C. lambica, C. lusitaniae, C. pelliculosa, C. rugosa, and C. zeylanoides) included in the API 20C sugar assimilation panel, five probes for species not identified by API 20C (C. haemulonii, C. norvegica, C. norvegensis, C. utilis, and C. viswanathii), and a probe for the newly described species C. dubliniensis, creating a panel of 18 Candida species probes. The PCR-EIA correctly identified multiple strains of each species tested, including five identified as C. albicans by the currently available API 20C database but determined to be C. dubliniensis by genotypic and nonroutine phenotypic characteristics. Species identification time was reduced from a mean of 3.5 days by conventional identification methods to 7 h by the PCR-EIA. This method is simple, rapid, and feasible for identifying Candida species in clinical laboratories that utilize molecular identification techniques and provides a novel method to differentiate the new species, C. dubliniensis, from C. albicans.