gebhart/patrepeval huggingface dataset:
Automatic Configuration and Wavelength Locking of Coupled Silicon Ring Resonators (2017)

Coupled silicon ring resonator filters offer high-order spectral features such as steep roll-offs, high extinction ratios, and wide pass-bands, which are attractive to many applications in telecommunications and quantum computing systems. However, so far, their sensitivity to fabrication and temperature variations have limited the usability of such filters in practical applications. Here, by using in-resonator photoconductive heaters (IRPHs) to both sense and tune the resonance conditions of ring resonators, we demonstrate automatic configuration and wavelength locking of multiring resonator filters to an input laser's wavelength. We demonstrate the automatic configuration of a four-ring Vernier filter across a 36.7-nm wavelength range spanning the entire C-band and the wavelength locking of the same filter to counteract a practical chip temperature variation of 65 ${^\circ }$C. As IRPHs do not require additional material depositions, photodetectors, or power taps and use the same contact pads for both the sense and the tune operations, these results are achieved without compromising the cost or area of the devices. Furthermore, by localizing the feedback loops to only rely on the resonance conditions of adjacent rings, we present a tuning algorithm in which the number of iterations scales linearly with the number of coupled rings in the system. As this method does not rely on the output spectral shape of the system, it is, in general, applicable to a wide range of coupled resonator systems. Our results pave a path toward practical deployment of high-order and large-scale silicon ring resonator systems.
Characterization of MicroRNA Expression Profiles and the Discovery of Novel MicroRNAs Involved in Cancer during Human Embryonic Development (2013)

MicroRNAs (miRNAs), approximately 22-nucleotide non-coding RNA molecules, regulate a variety of pivotal physiological or pathological processes, including embryonic development and tumorigenesis. To obtain comprehensive expression profiles of miRNAs in human embryos, we characterized miRNA expression in weeks 4-6 of human embryonic development using miRNA microarrays and identified 50 human-embryo-specific miRNAs (HES-miRNAs). Furthermore, we selected three non-conserved or primate-specific miRNAs, hsa-miR-638, -720, and -1280, and examined their expression levels in various normal and tumor tissues. The results show that expression of most miRNAs is extremely low during early human embryonic development. In addition, the expression of some non-conserved or primate-specific miRNAs is significantly different between tumor and the corresponding normal tissue samples, suggesting that the miRNAs are closely related to the pathological processes of various tumors. This study presents the first comprehensive overview of miRNA expression during human embryonic development and offers immediate evidence of the relationship between human early embryonic development and tumorigenesis.
Unbound molecular complexes in M33 (1990)

The HI content of the nearby spiral galaxy M33 (d approx. 0.8 Mpc) has been the subject of many detailed studies (most recently Deul and van der Hulst 1987), but similar data on the molecular gas component has been lacking. This galaxy is currently undergoing vigorous high-mass star formation, as evidenced by the many OB associations and HII regions, and so is expected to possess at least some molecular gas. Interferometric studies have detected molecular clouds similar to Galactic Giant Molecular Clouds (GMCs) (Boulanger et al. 1988; Wilson et al. 1988). Researchers have recently mapped the nuclear region of M33 in the CO J=1-0 line with a 12 m telescope (half power beam width 55 inches approx. 210 pc) out to a radius of 3.5 minutes in order to trace the detailed distribution of the molecular gas. The resulting map reveals six large complexes with diameters of 200 to 400 pc. Interferometer observations of these regions have resolved them into individual molecular clouds similar to Galactic GMCs (Wilson et al. 1988). The complexes shown are much larger than individual Galactic GMCs (Sanders, Scoville, and Solomon 1985), but are somewhat smaller on average than the large associations seen in the grand-design spiral galaxy M51 (Rand and Kulkarni 1989). If we extend the velocity-diameter relation observed for Galactic GMCs to these larger structures, the predicted velocity widths are a factor of 1.5 to 3 times greater than the observed full-width half-maximum velocities (13 to 29 km (s-1). The peak brightness temperatures are approx. 0.2 K, at least a factor of 10 lower than what is observed for Galactic GMCs. If these large structures are made up of objects similar to Galactic GMCs, the area filling factor of the small clouds is roughly 10 percent. These results suggest that these complexes are not very large GMCs, but rather are associations of many individual GMCs or GMCs embedded in a diffuse gas component.
Disentangled Variational Auto-Encoder for Semi-supervised Learning (2017)

Semi-supervised learning is attracting increasing attention due to the fact that datasets of many domains lack enough labeled data. Variational Auto-Encoder (VAE), in particular, has demonstrated the benefits of semi-supervised learning. The majority of existing semi-supervised VAEs utilize a classifier to exploit label information, where the parameters of the classifier are introduced to the VAE. Given the limited labeled data, learning the parameters for the classifiers may not be an optimal solution for exploiting label information. Therefore, in this paper, we develop a novel approach for semi-supervised VAE without classifier. Specifically, we propose a new model called Semi-supervised Disentangled VAE (SDVAE), which encodes the input data into disentangled representation and non-interpretable representation, then the category information is directly utilized to regularize the disentangled representation via the equality constraint. To further enhance the feature learning ability of the proposed VAE, we incorporate reinforcement learning to relieve the lack of data. The dynamic framework is capable of dealing with both image and text data with its corresponding encoder and decoder networks. Extensive experiments on image and text datasets demonstrate the effectiveness of the proposed framework.
Image processing algorithms for improved character recognition and components inspection (2009)

The importance of inspection process has been magnified by the requirements of the modern manufacturing environment. A variety of approaches for automatic inspection of machine parts have been reported over last two decades. In this work it is targeted to develop an automated machine vision software system, which is used to inspect automotive parts like PE pumps after assembly of different components. Inspection is carried out to detect missing components, misalignment of components and out of tolerance of components. This work proposes some methodologies for Optical Character Recognition (OCR) and feature extraction. An improved Local Mean-Gradient thresholding algorithm is proposed and implanted to recognize the characters like type number and serial number printed on the automotive parts like PE-PUMP, irrespective of the variation in background colors, industrial noises like dust particles, oily surfaces etc. The proposed methodologies have been implemented and explained here with some generic examples which overcome various industrial constraints. In this work, it is proved that automatic selection of threshold based on the background colors has improved the OCR performance to 100% recognition. The second part focuses on the extraction of suitable features in order to obtain a good pattern matching result even under various industrial constraints. Laplacian method of edge which is based on difference in gray level is more sensitive to noise. The second part gives an improved edge detection method using Laplacian operator.
Palliative Care in Obstetrics and Gynecology (2016)

Palliative care is specialized care for people with life-limiting illness; it focuses on symptom management and quality of life and ensures that a patient's care is concordant with her goals and values. Unlike end-of-life care, palliative care can be offered concurrently with disease-directed therapies, including when the goal is cure. Obstetrics and gynecology patients for whom palliative care is most appropriate include women with gynecologic cancer and women with a fetus or neonate with a potentially life-limiting illness. Integration of palliative care for these patients offers both clinical and health care utilization benefits, including improved symptom management, improved quality of life, and high-value care. Palliative care can be provided by palliative care specialists (specialty palliative care) or by the team treating the life-limiting illness (primary palliative care), depending on the complexity of the need. Health care providers caring for patients with life-limiting illness, including obstetrician-gynecologists, must possess a basic primary palliative care skill set, including symptom management for common symptoms such as pain and nausea and communication skills such as breaking bad news. This skill set must be taught and evaluated during training and used consistently in practice to ensure that our patients receive truly comprehensive care.
Sensing Picornaviruses Using Molecular Imprinting Techniques on a Quartz Crystal Microbalance (2009)

Molecular imprinting techniques were adapted to design a sensor for the human rhinovirus (HRV) and the foot-and-mouth disease virus (FMDV), which are two representatives of picornaviruses. Stamp imprinting procedures lead to patterned polyurethane layers that depict the geometrical features of the template virus, as confirmed by AFM for HRV. Quartz crystal microbalance (QCM) measurements show that the resulting layers incorporate the template viruses reversibly and lead to mass effects that are almost an order of magnitude higher than those of nonspecific adsorption. Thus, for example, the sensor yields a net frequency effect of -300 Hz when applying a virus suspension with a concentration of approximately 100 microg/mL with an excellent signal-to-noise ratio. The cavities are not only selective to shape but also to surface chemistry: different HRV serotypes (HRV1A, HRV2, HRV14, and HRV16, respectively) can be distinguished with the sensor materials by a selectivity factor of 3, regardless of the group (major/minor) to which they belong. The same selectivity factor can be observed between HRV and FMDV. Hence, imprinting leads to an "artificial antibody" toward viruses, which does not only recognize their receptor binding sites, but rather detects the whole virus as an entity. Brunauer-Emmett-Teller (BET) studies allow simulation of the sensor characteristics and reveal the number of favorable binding sites in the coatings.
Bidirectional Long Short-Term Memory Networks for Relation Classification (2015)

Relation classification is an important se-mantic processing, which has achieved great attention in recent years. The main challenge is the fact that important infor-mation can appear at any position in the sentence. Therefore, we propose bidirec-tional long short-term memory networks (BLSTM) to model the sentence with complete, sequential information about all words. At the same time, we also use fea-tures derived from the lexical resources such as WordNet or NLP systems such as dependency parser and named entity rec-ognizers (NER). The experimental results on SemEval-2010 show that BLSTM-based method only with word embeddings as input features is sufficient to achieve state-of-the-art performance, and import-ing more features could further improve the performance. 1
Physicochemical characteristics of soluble oligomeric A<i>β</i>and their pathologic role in Alzheimer's disease (2005)

Extracellular fibrillar amyloid deposits are prominent and universal Alzheimer's disease (AD) features, but senile plaque abundance does not always correlate directly with the degree of dementia exhibited by AD patients. The mechanism(s) and dynamics of Abeta fibril genesis and deposition remain obscure. Enhanced Abeta synthesis rates coupled with decreased degradative enzyme production and accumulating physical modifications that dampen proteolysis may all enhance amyloid deposit formation. Amyloid accumulation may indirectly exert the greatest pathologic effect on the brain vasculature by destroying smooth muscle cells and creating a cascade of negative impacts on cerebral blood flow. The most visible manifestation of amyloid dis-equilibrium could actually be a defense mechanism employed to avoid serious vascular wall degradation while the major toxic effects to the gray and white matter neurons are mediated by soluble oligomeric Abeta peptides with high beta-sheet content. The recognition that dynamic soluble oligomeric Abeta pools exist in AD and are correlated to disease severity led to neurotoxicity and physical conformation studies. It is now recognized that the most basic soluble Abeta peptides are stable dimers with hydrophobic regions sequestered from the aqueous environment and are capable of higher order aggregations. Time course experiments employing a modified ELISA method able to detect Abeta oligomers revealed dynamic intermolecular interactions and additional experiments physically confirmed the presence of stable amyloid multimers. Amyloid peptides that are rich in beta-sheet structure are capable of creating toxic membrane ion channels and a capacity to self-assemble as annular structures was confirmed in vitro using atomic force microscopy. Biochemical studies have established that soluble Abeta peptides perturb metabolic processes, provoke release of deleterious reactive compounds, reduce blood flow, induce mitochondrial apoptotic toxicity and inhibit angiogenesis. While there is no question that gross amyloid deposition does contribute to AD pathology, the destructive potential now associated with soluble Abeta suggests that treatment strategies that target these molecules may be efficacious in preventing some of the devastating effects of AD.
Aptamers: prospects in therapeutics and biomedicine (2005)

Most biopolymer drugs to date have been proteins. However, the ability to select nucleic acid binding species (aptamers) has led to the development of protein inhibitors and modulators that are small, readily synthesized nucleic acids. The techniques for optimizing, stabilizing, and delivering nucleic acid therapies are just beginning to be developed, but the same engineering flexibility that has so far allowed the generation of multiple, high affinity and specificity binding species appears to also apply to the methods for adapting nucleic acids to clinical applications. We review the selection and characterization of various aptamers and their applications to a variety of disease states, and then focus on the hurdles that must be overcome for the use of aptamers as both exogenously delivered drugs and as gene therapies.
Low-bandwidth dynamic aspect ratio region-based motion estimation (2006)

In the domain of motion estimation based applications, in order to keep the bandwidth requirements low, the usage of multiple levels of memory hierarchy is a necessity. We analyze and optimize the two-level memory hierarchy system for motion estimation where the first level (L0 scratchpad) holds the search area of the estimator and the second level (L1 scratchpad) holds the region wherein the estimation is performed. In our system, the L1 scratchpad is reconfigurable and the aspect ratio of the region dynamically changes per video field. The aspect ratio is changed such that physically available region (L1) memory is maximally utilized. We extend this idea to the extreme case where the aspect ratio of the region changes from horizontal stripe to vertical column. This idea keeps the bandwidth requirements towards the off-chip image memory minimal, one access per pixel, regardless of the number of motion estimation scans. Further, switching the aspect ratio of the region to extreme values enables fast convergence of the motion estimator. To demonstrate our idea, experiments were performed on the test set of video sequences using the state-of-the-art de-interlacing as the application. The results are encouraging regarding both, objective quality metric as well as visual perception.
Screening Mammography with Computer-aided Detection: Prospective Study of 12,860 Patients in a Community Breast Center (2001)

The use of CAD in the interpretation of screening mammograms can increase the detection of early-stage malignancies without undue effect on the recall rate or positive predictive value for biopsy.
<i>Glucocerebrosidase</i> mutations in a <scp>S</scp>erbian <scp>P</scp>arkinson's disease population (2012)

Glucocerebrosidase mutations represent a PD risk factor in the Serbian population.
An Evaluation of the Stochastic Resonance Phenomenon as a Potential Tool for Signal Processing (1994)

Stochastic resonance is a nonlinear stochastic phenomenon which can cause a transfer of energy from a random process (noise) to a periodic signal over a certain range of signal and system parameters. It has been observed in many diverse natural and physical systems, and may be one means by which biological sensor systems amplify weak sensory signals for detection. This paper is an evaluation of the use of the stochastic resonance phenomenon as a tool for signal processing in terms of its processing gain. >
A Systematic Comparison and Evaluation of k-Anonymization Algorithms for Practitioners (2014)

The vast amount of data being collected about individuals has brought new challenges in protecting their privacy when this data is disseminated. As a result, Privacy-Preserving Data Publishing has become an active research area, in which multiple anonymization algorithms have been proposed. However, given the large number of algorithms available and limited information regarding their performance, it is difficult to identify and select the most appropriate algorithm given a particular publishing scenario, especially for practitioners. In this paper, we perform a systematic comparison of three well-known k-anonymization algorithms to measure their efficiency (in terms of resources usage) and their effectiveness (in terms of data utility). We extend the scope of their original evaluation by employing a more comprehensive set of scenarios: different parameters, metrics and datasets. Using publicly available implementations of those algorithms, we conduct a series of experiments and a comprehensive analysis to identify the factors that influence their performance, in order to guide practitioners in the selection of an algorithm. We demonstrate through experimental evaluation, the conditions in which one algorithm outperforms the others for a particular metric, depending on the input dataset and privacy requirements. Our findings motivate the necessity of creating methodologies that provide recommendations about the best algorithm given a particular publishing scenario.
Secure Determinant Codes: A Class of Secure Exact-Repair Regenerating Codes (2019)

<sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">1</sup> We present a construction for exact-repair regenerating codes with an information-theoretic secrecy guarantee against an eavesdropper with access to the content of (up to) ℓ nodes. The proposed construction works for the entire range of per-node storage and repair bandwidth for any distributed storage system with parameters (n, k = d, d, ℓ), aiming to maximize the size of the file that can be securely stored in the system. We provide an upper bound for the optimum trade-off for secure exact-repair regenerating codes.
Light Scattering from Long Submicron Glass Cylinders at Normal Incidence* (1966)

Fused silica and Pyrex fibers having radii less than one micron have been prepared and mounted in a light-scattering photometer. Each of the polarized components of the scattered light has been observed over the angular range from 15° to 130° for perpendicular incidence. Experiments were carried out for λ=436 mμ and 546 mμ. By comparison of these data with computations corresponding to the model of an infinitely long circular cylinder, it has been possible to determine the radius to within less than 1%. These results have been compared with direct electron microscope observations which are considerably less precise and less accurate.Other fibers consisting of tungsten, platinum, gold-coated Pyrex and paraffin-coated tungsten were also studied, but these have not yet been successfully analyzed.
A latent semantic classification model (2005)

Latent Semantic Indexing (LSI) has been successfully applied to information retrieval and text classification. However, when LSI is used in classification, some important features for small classes may be ignored because of their small feature values. To solve this problem, we propose the latent semantic classification (LSC) model which extends the LSI model in the following way: the classification information of the training documents is introduced into the latent semantic structure via a second set of latent variables, so that both indexing and classification information can be taken into account during the classification process. Our experiments on Reuters show that our new model performs better than the existing classification methods such as kNN and SVM.
Estimating the Capital Service of Beijing: 1978-2012 (2014)

In macroeconomics, the measure of capital input and its contribution to production has been a spot in research. This paper takes Beijing city as the research object, referring to the 2008 SNA concepts and categories on capital service, making the full use of existing data, applying the PIM method to estimate the capital service and its index of 1978-2012. Because the capital service estimate is a new research field in China, the conclusions of this research can provide data support for the accurate accounting of total factor productivity and the decision support for the economic growth policies making in Beijing. Key words: Capital service; Beijing; Productive capital stock; Age-efficiency profile
Bis(acetonitrile)(η<sup>4</sup>-1,5-cyclooctadiene) Rhodium(I) Tetrafluoroborate (2017)

[32679-02-0] C12H18BF4N2Rh (MW 379.99) InChI = 1S/C8H12.2C2H3N.BF4.Rh/c1-2-4-6-8-7-5-3-1;2*1-2-3;2-1(3,4)5;/h1-2,7-8H,3-6H2;2*1H3;;/q;;;-1;+1/b2-1-,8-7-;;;; InChIKey = KSMAFOANQHYEJG-SUESZSCISA-N (catalyst for the formation of C–C bonds between various organic electrophiles and organometallic reagents. Also used as a catalyst for hydroformylation and hydrogenation reactions) Physical Data: mp 188–190 °C (dec).2 Solubility: soluble in most organic solvents; insoluble in H2O. Form Supplied in: yellow crystals, commercially available from Aldrich (cat. #640360). Analysis of Reagent Purity: melting point, IR.2 Preparative Methods: can be prepared by reaction of [RhCl(cod)]2 and AgBF4 in CH2Cl2 and CH3CN, followed by filtration, concentration of the reaction solution, and precipitation of the product using Et2O.3 A similar synthesis has also been performed using Ph3CBF4 instead of AgBF4.2 Purification: recrystallization can be done from acetonitrile with slow addition of diethyl ether. Handling, Storage, and Precautions: store in a cool, dry place in a tightly sealed container. Handle and store under an inert atmosphere of nitrogen or argon. May cause mild to severe irritation of the eyes, skin, nose, mucous membrane, or respiratory tract. Avoid ingestion, inhalation, or direct contact with skin or clothing. The toxicological effects of this reagent have not been thoroughly tested; unknown hazards may be present. Chemical-safety goggles and appropriate gloves are highly recommended. Use only in a chemical fume hood and near safety shower and eye bath. Do not breathe dust. Compound is incompatible with oxidizing agents and active metals and decomposes to carbon dioxide, carbon monoxide, boron oxides, hydrogen fluoride, and rhodium salts.