gebhart/patrepeval huggingface dataset:
Automatic image annotation based on decision tree machine learning (2009)

With the rapid development of digital imaging technology, image annotation is an important and challenging task in image retrieval. At present, many machine learning methods have been applied to solve the problem of automatic image annotation (AIA). However, there exists enormous semantic expressive gap between the low-level image features and high-level semantic concepts. Due to the problem, the annotation performance of existing methods is not satisfactory, and needs to be further improved. This paper proposes an automatic annotation framework via a novel decision tree-based Bayesian (DTB) machine learning algorithm. It is a hybrid approach that attempts to utilize the advantages of both DT and Naive-Bayesian (NB). We firstly segment an image into different regions and extract low-level features of each region. From these features, high-level semantic concepts are obtained using a DTB learning algorithm. Finally, experiments conducted on the Corel dataset demonstrate the effectiveness of DTB machine learning. The DTB can not only enhance the classification accuracy, but also associate low-level region features with high-level image concepts. This method presents the advantages of the Bayesian method and the DT. Moreover, this semantic interpretation capability is a natural simulation of human learning.
CHAUFFEUR assistant a driver assistance system for commercial vehicles based on fusion of advanced ACC and lane keeping (2004)

This paper presents the integrated approach for environment perception and vehicle control developed for the CHAUFFEUR Assistant application. Using a combination of radar and video sensor, the sensor fusion approach provides the vehicle controllers with valuable data about preceding vehicles and about the lane. These controllers guide the truck to stay in the lane and keep a short but still safe distance to the preceding vehicle.
Synthesis, purification, and characterization of human ciliary neuronotrophic factor from E. coli (1991)

The cDNA for human ciliary neuronotrophic factor (CNTF) has been cloned into an expression vector under the control of the T7 promoter. The BL21 strain of E. coli was transformed with this vector. Human CNTF accounted for about 30% of the total bacterial protein after induction with isopropyl-B-D-thiogalactopyranoside. This human CNTF was purified to homogeneity from inclusion bodies by a combination of ion exchange chromatography and reverse-phase high performance liquid chromatography. The amino-terminal amino acid sequence of the purified protein was identical to the deduced amino acid sequence; however, the methionyl residue has been removed. On SDS-PAGE gels, human CNTF displayed a molecular weight of about 24 kDa, in accord with its deduced molecular mass; a pI of 5.8 indicates the acidic nature of the molecule. A proposed structure for human CNTF includes major alpha helical regions. The ED50 of purified human CNTF was approximately 30 pM, using cultured embryonic day 10 chicken dorsal root ganglion neurons; no activity was observed with neurons from embryonic day 8 ganglia. Polyclonal antibodies prepared against both a synthetic peptide of CNTF and the entire human CNTF protein recognized a single 24 kDa band on Western blots, corresponding to human CNTF. However, only the antibodies against intact CNTF blocked its biological activity. This represents the first molecular expression and purification of human CNTF.
MOCVD (BaxSr1−x)Ti1+yO3+z (BST) thin films for high frequency tunable devices (2001)

Abstract We have investigated the structural and electrical characteristics of (BaxSr1−x)Ti1+yO3+z (BST) thin films synthesized at 650°C on Pt/SiO2/Si substrates using a large area, vertical metalorganic chemical vapor deposition (MOCVD) reactor equipped with a liquid delivery system. Films with a Ba/Sr ratio of 70/30 were studied, as determined using X-ray fluorescence spectroscopy (XRF) and Rutherford backscattering spectrometry (RBS). A substantial reduction of the dielectric loss was achieved when annealing the entire capacitor structure in air at 700°C. Dielectric tunability as high as 2.3:1 was measured for BST capacitors with the currently optimized processing conditions. Key Words: BSTMOCVDdielectric tenabilitydielectric loss
Qualitative analysis of the odoriferous fraction of oakmoss (Evernia prunastri) (1975)

ADVERTISEMENT RETURN TO ISSUEPREVArticleNEXTQualitative analysis of the odoriferous fraction of oakmoss (Evernia prunastri)Roelo. Ter Heide, Nicolai. Provatoroff, Piet C. Traas, Pieter J. De Valois, Nico. Van der Plasse, Henk J. Wobben, and Rien. TimmerCite this: J. Agric. Food Chem. 1975, 23, 5, 950–957Publication Date (Print):May 1, 1975Publication History Published online1 May 2002Published inissue 1 May 1975https://pubs.acs.org/doi/10.1021/jf60201a022https://doi.org/10.1021/jf60201a022research-articleACS PublicationsRequest reuse permissionsArticle Views253Altmetric-Citations31LEARN 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-AlertscloseSupporting Info (1)»Supporting Information Supporting Information Get e-Alerts
One-liter Hg ion clock for space and ground applications (2004)

We describe the development of a small Hg/sup +/ ion clock suitable for space use. A small clock occupying 1-2 liters volume and producing stability of 10/sup -12///spl radic//spl tau/ would significantly advance the state of space-qualified atomic clocks. Based on recent measurements, this technology should produce long-term stability as good as 10/sup -15/.
Robust Design of Power Minimizing Symbol-Level Precoder under Channel Uncertainty (2018)

In this paper, we investigate the downlink transmission of a multiuser multiple-input single-output (MISO) channel under a symbol-level precoding (SLP) scheme, having imperfect channel knowledge at the transmitter. In defining the SLP problem, a general category of constructive interference regions (CIR) called distance preserving CIR (DPCIR) is adopted. In particular, we are interested in the robust SLP design minimizing the total transmit power while satisfying the users' quality-of-service (QoS) requirements. We consider two common models for the channel uncertainty region, namely, norm-bounded spherical and stochastic. For the spherical uncertainty model, a worst-case robust precoder is proposed, while for the stochastic uncertainties, we define a convex optimization problem with probabilistic constraints. We simulate the performance of the proposed robust approaches, and compare them with the existing methods. Through the simulation results, we also show that there is an essential trade-off between the two robust approaches.
Velocity Constancy in a Virtual Reality Environment (2000)

During everyday life the brain is continuously integrating multiple perceptual cues in order to allow us to make decisions and to guide our actions. In this study we have used a simulated (virtual reality--VR) visual environment to investigate how cues to speed judgments are integrated. There are two sources that could be used to provide signals for velocity constancy: temporal-frequency or distance cues. However, evidence from most psychophysical studies favours temporal-frequency cues. Here we report that two depth cues that provide a relative object--object distance--disparity and motion parallax--can provide a significant input to velocity-constancy judgments, particularly when combined. This result indicates that the second mechanism can also play a significant role in generating velocity constancy. Furthermore, we show that cognitive factors, such as familiar size, can influence the perception of object speed. The results suggest that both low-level cues to spatiotemporal structure and depth, and high-level cues, such as object familiarity, are integrated by the brain during velocity estimation in real-world viewing.
Fermi-Level Pinning at the Polysilicon/Metal Oxide Interface—Part I (2004)

We report here that Fermi pinning at the polysilicon/metal oxide interface causes high threshold voltages in MOSFET devices. Results indicate that pinning occurs due to the interfacial Si-Hf and Si-O-Al bonds for HfO/sub 2/ and Al/sub 2/O/sub 3/, respectively. Oxygen vacancies at polysilicon/HfO/sub 2/ interfaces also lead to Fermi pinning. We show that this fundamental characteristic affects the observed polysilicon depletion. In Part I, the theoretical background is reviewed and the impact of the different gate stack regions are separated out by investigating the relative threshold voltage shifts of devices with Hf-based dielectrics. The effects of the interfacial bonding are examined in Part II.
Coherent back scattering and Anderson localization of ultra-cold atoms in a laser speckle (2013)

Sémaire
A new adaptive subpixel-based downsampling scheme using edge detection (2009)

In this paper, a new adaptive subpixel-based downsampling scheme is proposed. Inside this scheme, we take full advantage of subpixels by adaptively choosing the sample directions based on edge information which has not been addressed before. Then, an adaptive filter is designed to suppress color fringing artifacts. Moreover, a good cut-off frequency is derived and deployed in our filter to obtain extra information. Simulation results illustrate that the proposed adaptive subpixel-based downsampling scheme successfully improves the resolution while efficiently removes visible color fringing artifacts.
LOW-LEAKAGE FLIP-FLOPS BASED ON DUAL-THRESHOLD AND MULTIPLE LEAKAGE REDUCTION TECHNIQUES (2011)

The scaling of transistor sizes has resulted in dramatic increase of leakage currents. The sub-threshold and gate leakages have now become a major contributor to total power dissipations. This paper presents two flip-flops based on dual-threshold CMOS and multiple leakage reduction techniques to reduce their leakage dissipations. In the DT-TG FF (Dual-Threshold Transmission Gate Flip-Flop), some transistors on non-critical paths use high-threshold devices to reduce their leakage currents, while the other transistors on critical paths use low-threshold devices to maintain performance. The MLRT FF (Multiple Leakage Reduction Technique Flip-Flop) uses P-type CMOS techniques, MTCMOS (Multi-Threshold CMOS) power-gating and dual-threshold technique to reduce both sub-threshold and gate leakage dissipations. Taken as an example, a practical sequential system realized with the two low-leakage flip-flops is demonstrated using a mode-5 × 5 × 5 counter. The simulation results show that the two flip-flops achieve considerable leakage reductions.
Redox-mediated conversion of atomically dispersed platinum to sub-nanometer particles (2017)

The concentration of Ce<sup>3+</sup> centers in Pt–CeO<sub>2</sub> films determines the onset of reduction of atomically dispersed platinum species.
Low-Threshold Dielectric-Cavity Microlasers (2014)

We present low-threshold dielectric-cavity surface-emitting microlasers working at room temperature under continuous-wave electrical injection with device diameter down to 2 μm. Size-dependent lasing properties are predicted theoretically and demonstrated experimentally.
Robotic Telesurgery Research (2010)

Abstract : This project aims to demonstrate the feasibility of miniature, inexpensive, in vivo robots to provide basic diagnosis and triage in military environments. This work comprises the first phase of a two phase project. The first phase focuses on the design and construction of an in vivo camera robot. The robot will be designed to be fully inserted into a patient and, in a future project, tested in patients. The robot will return live in vivo video images that allow the surgeon to explore, diagnose, and stabilize the patient while geographically separated. Several functional prototypes capable of tissue manipulation, abdominal exploration, and surgical utilization have been developed. This revolutionary, robotic technology has demonstrated its applicability in natural orifice and single incision minimally invasive surgical procedures. Such innovative procedures are virtually impossible to perform without the design and creation of new tools like our miniature robots. Successful completion of prototype development is a critical first step toward our ultimate objective, development of a group of in vivo robots that can provide diagnosis and therapeutics, as it builds on previous successes and focuses on developing an image-guided robot capable of provisions of basic triage in forward and traditional healthcare environments.
Mesoporous Zeolite for Biomass Conversion (2017)

This chapter discusses and evaluates mesoporous zeolite-based catalysts in the conversion of biomass molecules, mainly including the production of biofuels and transformation of glycerol to platform chemicals. The biomass conversion by a rapid pyrolysis of lignocelluloses, producing pyrolysis oil containing a variety of substituted phenolic molecules, acids, and sugars. In addition to pyrolysis oil from cellulose and lignin, lipids from animal oils are also important sources of renewable fuels, which have rich triglyceride and free fatty acid contents. A combination of the metal with zeolites is suitable for the direct hydrodeoxygenation to produce alkanes from lipids. The chapter explains the conversion of glycerol to valuable chemicals. The processes involved are hydrogenation, dehydration, dehydrogenation, oxidation, and esterification. The production of aromatic compounds like benzene, toluene and xylene are obtained by the process of aromatization of glycerol using zeolite catalysts. The mesopores in the zeolite catalysts are important for catalytic activity, product selectivity, and catalyst life-time.
Mapping and Visualizing Deep-Learning Urban Beautification (2018)

Information visualization has great potential to make sense of the increasing amount of data generated by complex machine-learning algorithms. We design a set of visualizations for a new deep-learning algorithm called FaceLift (goodcitylife.org/facelift). This algorithm is able to generate a beautified version of a given urban image (such as from Google Street View), and our visualizations compare pairs of original and beautified images. With those visualizations, we aim at helping practitioners understand what happened during the algorithmic beautification without requiring them to be machine-learning experts. We evaluate the effectiveness of our visualizations to do just that with a survey among practitioners. From the survey results, we derive general design guidelines on how information visualization makes complex machine-learning algorithms more understandable to a general audience.
St John's wort, a herbal antidepressant, activates the steroid X receptor (2000)

St John's wort (SJW), an extract of the medicinal plant Hypericum perforatum, is widely used as a herbal antidepressant. Recently, this agent has been found to adversely affect the metabolism of various coadministered drugs. Steroid X receptor (SXR), an orphan nuclear receptor, induces hepatic cytochrome P450 gene expression in response to diverse endogenous steroids, xenobiotics and drugs. Here, we report that, when coexpressed with SXR, a reporter construct derived from the cytochrome P450 3A promoter is activated by St John's wort. A GAL4-SXR ligand binding domain (LBD) fusion mediates concentration-dependent transactivation by SJW, whereas a mutant GAL4-SXR fusion, containing substitutions in key residues in a transactivation domain, is inactive. SJW recruits steroid receptor coactivator-1 to SXR in a two-hybrid assay and competes with radiolabelled ligand in binding studies, suggesting it interacts directly with the receptor LBD. Of two constituents of SJW, we find that hyperforin, but not hypericin, mediates both transactivation and coactivator recruitment by SXR. Our observations suggest that SXR activation by St John's wort mediates its adverse interaction with drugs metabolised via the CYP 3A pathway. Future development of SJW derivatives lacking SXR activation, may enable its antidepressant and drug-metabolising properties to be dissociated.
Survival of HeartMate II Patients Despite Cessation of Anticoagulation　― Outcomes and Hemostatic Analysis ― (2017)

We experienced good results with AT cessation in specific HMII patients. The simultaneous onset of AvWS and high TAT values could explain at least in part the low thromboembolic rate in HMII patients without VKA.
Hyperdimensional computing with 3D VRRAM in-memory kernels: Device-architecture co-design for energy-efficient, error-resilient language recognition (2016)

The ability to learn from few examples, known as one-shot learning, is a hallmark of human cognition. Hyperdimensional (HD) computing is a brain-inspired computational framework capable of one-shot learning, using random binary vectors with high dimensionality. Device-architecture co-design of HD cognitive computing systems using 3D VRRAM/CMOS is presented for language recognition. Multiplication-addition-permutation (MAP), the central operations of HD computing, are experimentally demonstrated on 4-layer 3D VRRAM/FinFET as non-volatile in-memory MAP kernels. Extensive cycle-to-cycle (up to 10 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">12</sup> cycles) and wafer-level device-to-device (256 RRAMs) experiments are performed to validate reproducibility and robustness. For 28-nm node, the 3D in-memory architecture reduces total energy consumption by 52.2% with 412 times less area compared with LP digital design (using registers as memory), owing to the energy-efficient VRRAM MAP kernels and dense connectivity. Meanwhile, the system trained with 21 samples texts achieves 90.4% accuracy recognizing 21 European languages on 21,000 test sentences. Hard-error analysis shows the HD architecture is amazingly resilient to RRAM endurance failures, making the use of various types of RRAMs/CBRAMs (1k ~ 10M endurance) feasible.
LDL particle core enrichment in cholesteryl oleate increases proteoglycan binding and promotes atherosclerosis (2013)

Several studies in humans and animals suggest that LDL particle core enrichment in cholesteryl oleate (CO) is associated with increased atherosclerosis. Diet enrichment with MUFAs enhances LDL CO content. Steroyl O-acyltransferase 2 (SOAT2) is the enzyme that catalyzes the synthesis of much of the CO found in LDL, and gene deletion of SOAT2 minimizes CO in LDL and protects against atherosclerosis. The purpose of this study was to test the hypothesis that the increased atherosclerosis associated with LDL core enrichment in CO results from an increased affinity of the LDL particle for arterial proteoglycans. ApoB-100-only Ldlr(-/-) mice with and without Soat2 gene deletions were fed diets enriched in either cis-MUFA or n-3 PUFA, and LDL particles were isolated. LDL:proteogylcan binding was measured using surface plasmon resonance. Particles with higher CO content consistently bound with higher affinity to human biglycan and the amount of binding was shown to be proportional to the extent of atherosclerosis of the LDL donor mice. The data strongly support the thesis that atherosclerosis was induced through enhanced proteoglycan binding of LDL resulting from LDL core CO enrichment.
Differences in high-definition transcranial direct current stimulation over the motor hotspot versus the premotor cortex on motor network excitability (2018)

Abstract The effectiveness of transcranial direct current stimulation (tDCS) placed over the motor hotspot (thought to represent the primary motor cortex (M1)) to modulate motor network excitability is highly variable. The premotor cortex—particularly the dorsal premotor cortex (PMd)—may be a promising alternative target to more effectively modulate motor excitability, as it influences motor control across multiple pathways, one independent of M1 and one with direct, modulating connections to M1. This double-blind, placebo-controlled study aimed to differentially excite motor and premotor regions using high-definition tDCS (HD-tDCS) with concurrent functional magnetic resonance imaging (fMRI). HD-tDCS applied over either the motor hotspot or the premotor cortex demonstrated high inter-individual variability in changes on cortical motor excitability. However, HD-tDCS over the premotor cortex led to a higher number of responders and greater changes in local fMRI-based complexity than HD-tDCS over the motor hotspot. Furthermore, an analysis of individual motor hotspot anatomical locations revealed that, in more than half of the participants, the motor hotspot is not located over anatomical M1 boundaries, despite using a canonical definition of the motor hotspot. This heterogeneity in stimulation site may contribute to the variability of tDCS results. Altogether, these findings provide new considerations to enhance tDCS reliability.
Localized Metabolomic Gradients in Patient-Derived Xenograft Models of Glioblastoma (2019)

Glioblastoma (GBM) is increasingly recognized as a disease involving dysfunctional cellular metabolism. GBMs are known to be complex heterogeneous systems containing multiple distinct cell populations and are supported by an aberrant network of blood vessels. A better understanding of GBM metabolism, its variation with respect to the tumor microenvironment, and resulting regional changes in chemical composition is required. This may shed light on the observed heterogeneous drug distribution, which cannot be fully described by limited or uneven disruption of the blood-brain barrier. In this work, we used mass spectrometry imaging (MSI) to map metabolites and lipids in patient-derived xenograft models of GBM. A data analysis workflow revealed that distinctive spectral signatures were detected from different regions of the intracranial tumor model. A series of long-chain acylcarnitines were identified and detected with increased intensity at the tumor edge. A 3D MSI dataset demonstrated that these molecules were observed throughout the entire tumor/normal interface and were not confined to a single plane. mRNA sequencing demonstrated that hallmark genes related to fatty acid metabolism were highly expressed in samples with higher acylcarnitine content. These data suggest that cells in the core and the edge of the tumor undergo different fatty acid metabolism, resulting in different chemical environments within the tumor. This may influence drug distribution through changes in tissue drug affinity or transport and constitute an important consideration for therapeutic strategies in the treatment of GBM. SIGNIFICANCE: GBM tumors exhibit a metabolic gradient that should be taken into consideration when designing therapeutic strategies for treatment.<i>See related commentary by Tan and Weljie, p. 1231</i>.