gebhart/patrepeval huggingface dataset:
A Stereoscopic Video Generation Method Using Stereoscopic Display Characterization and Motion Analysis (2008)

Stereoscopic video generation methods can produce stereoscopic content from conventional video filmed with monoscopic cameras. In this paper, we propose a stereoscopic video generation method using motion analysis which converts motion into disparity values and considers multi-user conditions and the characteristics of the display device. The field of view and the maximum and minimum disparity values were calculated in the stereoscopic display characterization stage and were then applied to various types of 3D displays. After motion estimation, we used three cues to decide the scale factor of motion-to-disparity conversion. These cues were the magnitude of motion, camera movements and scene complexity. A subjective evaluation showed that the proposed method generated more satisfactory video sequence.
Large-Scale Synthesis of Functional Spiking Neural Circuits (2014)

In this paper, we review the theoretical and software tools used to construct Spaun, the first (and so far only) brain model capable of performing cognitive tasks. This tool set allowed us to configure 2.5 million simple nonlinear components (neurons) with 60 billion connections between them (synapses) such that the resulting model can perform eight different perceptual, motor, and cognitive tasks. To reverse-engineer the brain in this way, a method is needed that shows how large numbers of simple components, each of which receives thousands of inputs from other components, can be organized to perform the desired computations. We achieve this through the neural engineering framework (NEF), a mathematical theory that provides methods for systematically generating biologically plausible spiking networks to implement nonlinear and linear dynamical systems. On top of this, we propose the semantic pointer architecture (SPA), a hypothesis regarding some aspects of the organization, function, and representational resources used in the mammalian brain. We conclude by discussing Spaun, which is an example model that uses the SPA and is implemented using the NEF. Throughout, we discuss the software tool Neural ENGineering Objects (Nengo), which allows for the synthesis and simulation of neural models efficiently on the scale of Spaun, and provides support for constructing models using the NEF and the SPA. The resulting NEF/SPA/Nengo combination is a general tool set for both evaluating hypotheses about how the brain works, and for building systems that compute particular functions using neuron-like components.
A Single-Phase Current-Source PV Inverter With Power Decoupling Capability Using an Active Buffer (2014)

This paper proposes a new circuit configuration and a control scheme for a single-phase current-source inverter with a power decoupling circuit which is called as the active buffer. The proposed inverter achieves a low-dc-input voltage ripple and also provides a sinusoidal current that can achieve unity power factor, without large passive components in the dc bus such as smoothing inductors and electrolytic capacitors. These components are conventionally required in order to decouple the power pulsation caused by the single-phase power source. In this paper, the fundamental operations of the proposed inverter are demonstrated experimentally. From the experimental results, the input voltage ripple is 8.87%, and the output current total harmonic distortion is 4.24%. In addition, an output power factor of 99% and a maximum efficiency of 94.9% are obtained. Finally, it is confirmed that the maximum power densities of the conventional circuit and the proposed circuit are 2.75 kW/L at the switching frequency of 70 kHz and 4.86 kW/L at the switching frequency of 80 kHz, respectively.
Processing, mechanical properties, and interfacial bonding of a thermoplastic core‐foam/composite‐skin sandwich panel (2010)

Abstract In this work, a thermoplastic sandwich panel was designed, produced, and tested for use in insulating walls of containers for food transportation. A sandwich construction comprising a poly(ethylene terephthalate) core and polypropylene/glass fiber skins was evaluated as possible replacement of systems consisting of polyurethane foam in combination with unsaturated polyester glass‐reinforced skins that are currently used for the manufacture of these structures. Factors were taken into account to satisfy the simultaneous need of thermal insulation and adequate mechanical properties that are required for the production of large flat panels 100‐mm thick. The influences of different manufacturing processes and skin‐core adhesion on the mechanical properties of this thermoplastic sandwich were investigated and are discussed in the text. © 2010 Wiley Periodicals, Inc. Adv Polym Techn 29:137–145, 2010; View this article online at wileyonlinelibrary . DOI 10.1002/adv.20186
An efficient cascaded system for latent fingerprint recognition (2013)

This paper proposes a cascaded scheme to improve the efficiency of latent fingerprint identification system. In this scheme, the feature set of latent fingerprint such as finger codes, basic patterns, ridge counts and minutia with their local structures are sequentially exploited in four cascaded layers. In the first layer, possible finger codes of latent fingerprint are recognized based on basic pattern features and then reordered to determine their database access priority. In the second layer, its minutiae are extracted and assessed to affine matching in the third layer. In the fourth layer, any case having too many candidates in the previous layer is further matched based on exploiting local structure in order to downsizing the result list. On the verification layer, the minutiae information and local structure of corresponding pairs are presented to human experts for further verification. Experimental results on C@FRIS database show that our proposed method obtains high matching accuracy and considerably low identification time.
LA FORMACION DE DOCENTES PARA LA EDUCACION BASICA EN COLOMBIA (1994)

This article describes the training process of Colombian primary and secondary school teachers. We begin with the summarization of the political and legal context under which some changes of the educational system are taking place, then its current structure and organization, its philosophy and objectives, its strategies of continuing education, and finally its short tenn development perspectives are described.
Silencing of hepcidin enforces the apoptosis in iron-induced human cardiomyocytes (2014)

Our findings suggest that hepcidin can rescue human cardiomyocytes from iron-induced apoptosis through the regulation of GATA-4/Bcl-2 and the extrinsic apoptotic pathway.
Electromigration in Cu(Al) and Cu(Mn) damascene lines (2012)

The effects of impurities, Mn or Al, on interface and grain boundary electromigration (EM) in Cu damascene lines were investigated. The addition of Mn or Al solute caused a reduction in diffusivity at the Cu/dielectric cap interface and the EM activation energies for both Cu-alloys were found to increase by about 0.2 eV as compared to pure Cu. Mn mitigated and Al enhanced Cu grain boundary diffusion; however, no significant mitigation in Cu grain boundary diffusion was observed in low Mn concentration samples. The activation energies for Cu grain boundary diffusion were found to be 0.74 ± 0.05 eV and 0.77 ± 0.05 eV for 1.5 μm wide polycrystalline lines with pure Cu and Cu (0.5 at. % Mn) seeds, respectively. The effective charge number in Cu grain boundaries Z*GB was estimated from drift velocity and was found to be about −0.4. A significant enhancement in EM lifetimes for Cu(Al) or low Mn concentration bamboo-polycrystalline and near-bamboo grain structures was observed but not for polycrystalline-only alloy lines. These results indicated that the existence of bamboo grains in bamboo-polycrystalline lines played a critical role in slowing down the EM-induced void growth rate. The bamboo grains act as Cu diffusion blocking boundaries for grain boundary mass flow, thus generating a mechanical stress-induced back flow counterbalancing the EM force, which is the equality known as the “Blech short length effect.”
Fusion of multi-classifiers for online signature verification using fuzzy logic inference (2011)

Compared to physiologically based biometric systems such as fingerprint, face, palm-vein and retina, behavioral based biometric systems such as signature, voice, gait, etc. are less popular and many of the research in these areas are still in their infancy. One of the reasons is due to the inconsistencies in human behavior which requires more robust algorithms in their developments. In this paper, an online signature verifi- cation system is proposed based on fuzzy logic inference. To ensure higher accuracy, the signature verification system is designed to include the fusion of multi classifiers, namely, the back propagation neural network algorithm and the Pearson correlation technique. A fuzzy logic inference engine is also designed to fuse two global features which are the time taken to sign and the length of the signature. The use of the fuzzy logic inference engine is to overcome the boundary limitations of fixed thresholds and overcome the uncertainties of thresholds for various users and to have a more human-like output. The system has been developed with a robust validation module based on Pearson’s correlation algorithm in which more consistent sets of signatures are enrolled. In this way, more consistent sets of training patterns are used for training. The results show that the incorporation of multi classifier fusion technique has improved the false rejection rate and false acceptance rate of the system as compared to the individual classifiers and the use of fuzzy logic inference module for the final decision helps to further improved the system performance.
Choline acetyltransferase mutations cause myasthenic syndrome associated with episodic apnea in humans (2001)

Choline acetyltransferase (ChAT; EC ) catalyzes the reversible synthesis of acetylcholine (ACh) from acetyl CoA and choline at cholinergic synapses. Mutations in genes encoding ChAT affecting motility exist in Caenorhabditis elegans and Drosophila, but no CHAT mutations have been observed in humans to date. Here we report that mutations in CHAT cause a congenital myasthenic syndrome associated with frequently fatal episodes of apnea (CMS-EA). Studies of the neuromuscular junction in this disease show a stimulation-dependent decrease of the amplitude of the miniature endplate potential and no deficiency of the ACh receptor. These findings point to a defect in ACh resynthesis or vesicular filling and to CHAT as one of the candidate genes. Direct sequencing of CHAT reveals 10 recessive mutations in five patients with CMS-EA. One mutation (523insCC) is a frameshifting null mutation. Three mutations (I305T, R420C, and E441K) markedly reduce ChAT expression in COS cells. Kinetic studies of nine bacterially expressed ChAT mutants demonstrate that one mutant (E441K) lacks catalytic activity, and eight mutants (L210P, P211A, I305T, R420C, R482G, S498L, V506L, and R560H) have significantly impaired catalytic efficiencies.
Using Machine Learning to Optimize the Quality of Survey Data: Protocol for a Use Case in India (Preprint) (2019)

<sec> <title>BACKGROUND</title> Data quality is vital for ensuring the accuracy, reliability, and validity of survey findings. Strategies for ensuring survey data quality have traditionally used quality assurance procedures. Data analytics is an increasingly vital part of survey quality assurance, particularly in light of the increasing use of tablets and other electronic tools, which enable rapid, if not real-time, data access. Routine data analytics are most often concerned with outlier analyses that monitor a series of data quality indicators, including response rates, missing data, and reliability of coefficients for test-retest interviews. Machine learning is emerging as a possible tool for enhancing real-time data monitoring by identifying trends in the data collection, which could compromise quality. </sec> <sec> <title>OBJECTIVE</title> This study aimed to describe methods for the quality assessment of a household survey using both traditional methods as well as machine learning analytics. </sec> <sec> <title>METHODS</title> In the Kilkari impact evaluation’s end-line survey amongst postpartum women (n=5095) in Madhya Pradesh, India, we plan to use both traditional and machine learning–based quality assurance procedures to improve the quality of survey data captured on maternal and child health knowledge, care-seeking, and practices. The quality assurance strategy aims to identify biases and other impediments to data quality and includes seven main components: (1) tool development, (2) enumerator recruitment and training, (3) field coordination, (4) field monitoring, (5) data analytics, (6) feedback loops for decision making, and (7) outcomes assessment. Analyses will include basic descriptive and outlier analyses using machine learning algorithms, which will involve creating features from time-stamps, “don’t know” rates, and skip rates. We will also obtain labeled data from self-filled surveys, and build models using k-folds cross-validation on a training data set using both supervised and unsupervised learning algorithms. Based on these models, results will be fed back to the field through various feedback loops. </sec> <sec> <title>RESULTS</title> Data collection began in late October 2019 and will span through March 2020. We expect to submit quality assurance results by August 2020. </sec> <sec> <title>CONCLUSIONS</title> Machine learning is underutilized as a tool to improve survey data quality in low resource settings. Study findings are anticipated to improve the overall quality of Kilkari survey data and, in turn, enhance the robustness of the impact evaluation. More broadly, the proposed quality assurance approach has implications for data capture applications used for special surveys as well as in the routine collection of health information by health workers. </sec> <sec> <title>CLINICALTRIAL</title> <p/> </sec> <sec> <title>INTERNATIONAL REGISTERED REPORT</title> DERR1-10.2196/17619 </sec>
Levorphanol: a simplified radioimmunoassay for clinical use. (1981)

A recently reported radioimmunoassay (RIA) procedure (Res. Comm. Chem. Pathol. Pharmacol 29, 535, 1980) developed for the quantitation of the narcotic analgesic, levorphanol, in dog plasma has been simplified for clinical use using the original antiserum to an albumin conjugate of (-)-3-hydroxy-N-carboxymethylmorphinan. Due to the absence of and/or insignificant concentrations of the cross-reactive metabolite, nor-levorphanol, in human plasma, the new simplified procedure allows for the specific quantitation of levorphanol directly in clinical plasma samples, thereby circumventing the extraction and chromatographic steps of the original procedure. The direct procedure has a limit of sensitivity of 1 ng/ml of levorphanol using a 20 microliter sample of plasma and is ideally suited for the routine determination of steady state plasma concentrations of levorphanol in patients receiving various therapeutic doses of the drug. In two subjects studied the apparent half-lives of elimination of levorphanol from plasma were 10 and 16 hr. The characteristics and use of another antiserum to levorphanol, obtained by immunization of rabbits with an albumin conjugate of (-)-3-O-carboxymethyl-N-methylmorphinan, is discussed.
Analysis and Implementation of Speech/Music Classification for 3GPP2 SMV Based on GMM (2007)

In this letter, we propose a novel approach to improve the performance of speech/music classification for the selectable mode vocoder(SMV) of 3GPP2 using the Gaussian mixture model(GMM) which is based on the expectation-maximization(EM) algorithm. We first present an effective analysis of the features and the classification method adopted in the conventional SMV. And then feature vectors which are applied to the GMM are selected from relevant Parameters of the SMV for the efficient speech/music classification. The performance of the proposed algorithm is evaluated under various conditions and yields better results compared with the conventional scheme of the SMV.
Yeast <i>KEX2</i> Endopeptidase Correctly Cleaves a Neuroendocrine Prohormone in Mammalian Cells (1988)

Mammalian cell lines (BSC-40, NG108-15, and GH4C1) that cannot process the murine neuroendocrine peptide precursor prepro-opiomelanocortin (mPOMC) when its synthesis is directed by a vaccinia virus vector were coinfected with a second recombinant vaccinia virus carrying the yeast KEX2 gene, which encodes an endopeptidase that cleaves at pairs of basic amino acid residues. mPOMC was cleaved intracellularly to a set of product peptides normally found in vivo, including mature gamma-lipotropin and beta-endorphin1-31. In GH4C1 cells (a rat pituitary line), product peptides were incorporated into stored secretory granules. These results suggest that the inability of any particular cell line to process a prohormone precursor is due to the absence of a suitable endogenous processing enzyme.
On Mobile Edge Caching (2019)

With the widespread adoption of various mobile applications, the amount of traffic in wireless networks is growing at an exponential rate, which exerts a great burden on mobile core networks and backhaul links. Mobile edge caching, which enables mobile edges with cache storages, is a promising solution to alleviate this problem. In this paper, we aim to review the state-of-the-art of mobile edge caching. We first present an overview of mobile edge caching and its advantages. We then discuss the locations where mobile edge caching can be realized in the network. We also analyze different caching criteria and their respective effects on the caching performances. Moreover, we compare several caching schemes and discuss their pros and cons. We further present a detailed and in-depth discussion on the caching process, which can be delineated into four phases including content request, exploration, delivery, and update. For each phase, we identify different issues and review related works in addressing these issues. Finally, we present a number of challenges faced by current mobile edge caching architectures and techniques for further studies.
Effect of Co doping on the structural, optical and magnetic properties of ZnO nanoparticles (2007)

We report the results of a detailed investigation of sol-gel-synthesized nanoscale Zn(1-x)Co(x)O powders processed at 350 °C with 0≤x≤0.12 to understand how the structural, morphological, optical and magnetic properties of ZnO are modified by Co doping, in addition to searching for the theoretically predicted ferromagnetism. With x increasing to 0.03, both lattice parameters a and c of the hexagonal ZnO decreased, suggesting substitutional doping of Co at the tetrahedral Zn(2+) sites. For x>0.03, these trends reversed and the lattice showed a gradual expansion as x approached 0.12, probably due to additional interstitial incorporation of Co. Raman spectroscopy measurements showed a rapid change in the ZnO peak positions for x>0.03, suggesting significant disorder and changes in the ZnO structure, in support of additional interstitial Co doping possibility. Combined x-ray photoelectron spectroscopy (XPS), electron paramagnetic resonance spectroscopy, photoluminescence spectroscopy and diffuse reflectance spectroscopy showed clear evidence for tetrahedrally coordinated high-spin Co(2+) ions occupying the lattice sites of ZnO host system, which became saturated for x>0.03. Magnetic measurements showed a paramagnetic behaviour in Zn(1-x)Co(x)O with increasing antiferromagnetic interactions as x increased to 0.10. Surprisingly, a weak ferromagnetic behaviour was observed for the sample with x = 0.12 with a characteristic hysteresis loop showing a coercivity H(c)∼350 Oe, 25% remanence M(r), a low saturation magnetization M(s)∼0.04 emu g(-1) and with a Curie temperature T(c)∼540 K. The XPS data collected from Zn(1-x)Co(x)O samples showed a gradual increase in the oxygen concentration, changing the oxygen-deficient undoped ZnO to an excess oxygen state for x = 0.12. This indicates that such high Co concentrations and appropriate oxygen stoichiometry may be needed to achieve adequate ferromagnetic exchange coupling between the incorporated Co(2+) ions.
Activity of temozolomide in the treatment of central nervous system tumor xenografts. (1995)

The activity of 8-carbamoyl-3-methylimidazo[5,1-d]-1,2,3,5-tetrazin- 4(3H)-one (temozolomide) in the treatment of a panel of xenografts derived from ependymoma, medulloblastoma, and childhood and adult high-grade glioma was evaluated in athymic nude mice bearing s.c. and intracranial tumors. Temozolomide administered daily for a total of five doses demonstrated marked activity against a panel of Mer+ xenografts despite marginal to moderate activity of 1,3-bis(2-chloroethyl)-1-nitrosourea. The growth delays produced by temozolomide in these xenografts were 1.8-7.5-fold greater than those produced by procarbazine. Although temozolomide demonstrated marginal activity against the Mer+ cell line D341 Med when a 5-day schedule was used, a high-dose 1-day schedule resulted in moderate activity. Temozolomide produced increases in median survival of 1285% (adult glioma D-54 MG), 323% (childhood glioma D-456 MG), and 68% (ependymoma D612 EP). Pretreatment of mice with O6-benzylguanine increased temozolomide-induced mortality, requiring reduction of the dosage from 1200 to 750 mg/m2 on the single-day regimen. O6-Benzylguanine pretreatment of mice bearing Mer+ D341 Med increased the growth delay of temozolomide, in duplicate experiments, from -3.1 to 4.8 and 1.1 to 4.9 days. These studies suggest that temozolomide may be active in the treatment of a broad spectrum of central nervous system cancers, including Mer+ tumors resistant to 1,3-bis(2-chloroethyl)-1-nitrosourea.
Effectiveness of Covid-19 Vaccines in Ambulatory and Inpatient Care Settings (2021)

Covid-19 vaccines in the United States were highly effective against SARS-CoV-2 infection requiring hospitalization, ICU admission, or an emergency department or urgent care clinic visit. This vaccine effectiveness extended to populations that are disproportionately affected by SARS-CoV-2 infection. (Funded by the Centers for Disease Control and Prevention.).
Structural investigation of bacterial lipopolysaccharides by mass spectrometry and tandem mass spectrometry (2010)

Mass spectrometric studies are now playing a leading role in the elucidation of lipopolysaccharide (LPS) structures through the characterization of antigenic polysaccharides, core oligosaccharides and lipid A components including LPS genetic modifications. The conventional MS and MS/MS analyses together with CID fragmentation provide additional structural information complementary to the previous analytical experiments, and thus contribute to an integrated strategy for the simultaneous characterization and correct sequencing of the carbohydrate moiety.
FE Analysis of Cornering Fatigue Test for Wheel Rim of Light Commercial Vehicle (2023)

Automobile wheels are an essential and important part of any automobile from their invention to today they have taken on various designs changes, structures, and styles. Main function of automobile wheels is to carry the overall weight of vehicle, resist the forces & stresses created during driving and transmit the driving torque to achieve the required speed & torque while driving. Wheels must have well strength stiffness and having durable design to withstand running at high speeds. Also they are capable to absorb various shocks and vibration on various road load condition like braking, bump, cornering. Automobile wheel assembly consist of various parts like tire, wheel rim, disc, and bearing. Wheel is mounted on axle hub to provide vehicle motion through bearing. Tires reduce shock and provide traction & cushioning. They can be considered part of the suspension system. They transmit engine power, as well as braking and cornering efforts, to the road. Tires prevent wheel rim from various force which are directly comes from roads while driving.