gebhart/patrepeval huggingface dataset:
Further investigation on solant–rectenna‐based flexible Hilbert‐shaped metamaterials (2020)

This study discusses the design of a low‐profile metamaterial‐based antenna consisting of a 3 × 5 array of Hilbert shaped unit cells organised as a rectangular patch. The antenna is backed by with a partial ground plane loaded with square electromagnetic band gap defects for energy harvesting applications in the context of ultra‐wideband self‐powered wearable wireless devices. The antenna is mounted on a 28 × 32 mm FR4 substrate, with a thickness of 0.394 mm, a relative permittivity of 4.2 and a loss tangent of 0.02. The antenna is also printed on a flexible solar panel for self‐powered devices through solant–rectenna output terminals. The proposed solant–rectenna is found to cover the frequency range from 0.8 up to 10 GHz. The I – V characteristics of the solar panel are measured with and without the antenna structure to realize low shadowing effects. After that, the solant radiofrequency (RF) port is connected to a rectifier circuit to create a rectenna port that collects the RF energy and converts it to an output DC voltage at 0.915 GHz. It is found that the proposed rectenna provides an output DC voltage of 1.42 V with a conversion efficiency of 90%.
Distribution Agnostic Structured Sparsity Recovery: Algorithms and Applications (2015)

Compressed sensing has been a very active area of research and several elegant algorithms have been developed for the recovery of sparse signals in the past few years. However, most of these algorithms are either computationally expensive or make some assumptions that are not suitable for all real world problems. Recently, focus has shifted to Bayesian-based approaches that are able to perform sparse signal recovery at much lower complexity while invoking constraint and/or a priori information about the data. While Bayesian approaches have their advantages, these methods must have access to a priori statistics. Usually, these statistics are unknown and are often difficult or even impossible to predict. An effective workaround is to assume a distribution which is typically considered to be Gaussian, as it makes many signal processing problems mathematically tractable. Seemingly attractive, this assumption necessitates the estimation of the associated parameters; which could be hard if not impossible. In the thesis, we focus on this aspect of Bayesian recovery and present a framework to address the challenges mentioned above. The proposed framework allows Bayesian recovery of sparse signals but at the same time is agnostic to the distribution of the unknown sparse signal components. The algorithms based on this framework are agnostic to signal statistics and utilize a priori statistics of additive noise and the sparsity rate of the signal, which are shown to be easily estimated from data if not available. In the thesis, we propose several algorithms based on this framework which utilize the structure present in signals for improved recovery. In addition to the algorithm that considers just the sparsity structure of sparse signals, tools that target additional structure of the sparsity recovery problem are proposed. These include several algorithms for a) block-sparse signal estimation, b) joint reconstruction of several common support sparse signals, and c) distributed estimation of sparse signals. Extensive experiments are conducted to demonstrate the power and robustness of our proposed sparse signal estimation algorithms. Specifically, we target the problems of a) channel estimation in massive-MIMO, and b) Narrowband interference mitigation in SC-FDMA. We model these problems as sparse recovery problems and demonstrate how these could be solved naturally using the proposed algorithms.
Characterization of twoDrosophila melanogastercylochrome c genes and their transcripts (1985)

Analysis of total Drosophila melanogaster DNA by genomic blot hybridization indicates that two cytochrome c-like sequences exist in the Drosophila genome. These two sequences, DC3 and DC4, have been isolated from a Charon 4A-D. melanogaster genomic library. DC3 and DC4 are located within a 4 kb region of DNA, at position 36A 10-11, on the left arm of chromosome 2. The nucleotide sequence of these two clones has been determined. Both DC3 and DC4 can encode functional cytochrome c proteins. The polypeptide sequences predicted by these two genes, however, differ at 32 amino acid residues. DC4 is expressed at varying, but relatively high levels throughout Drosophila development. In contrast, DC3 is expressed at constant, but relatively low levels throughout development.
Sound event detection in urban soundscape using two-level classification (2016)

A huge increase in automobile field h as lead t o the creation of different sounds in large volume, especially in urban cities. An analysis of the increased quantity of automobiles will give information related to traffic and vehicles. It also provides a scope to understand the scenario of particular location using sound scape information. In this paper, a two level classification is proposed to classify urban sound events such as bus engine (BE), bus horn (BH), car horn (CH) and whistle (W) sounds. The above sounds are taken as they place a major role in traffic scenario. A real-time data is collected from the live recordings at major locations of the urban city. Prior to the detection of events, the class of events is identified u sing signal processing techniques. Further, features such as Mel-frequency cepstral coefficients (MFCCs) a re extracted based on the analysis of a spectrum of the above-mentioned events and they are prominent to classify even in the complex scenario. Classifiers such as artificial neural networks (ANN), naive-Bayesian (NB), decision tree (J48), random forest (RF) are used at two levels. The proposed approach outperforms the existing approaches that usually does direct feature extraction without signal level analysis.
Contamination of Health Care Personnel During Removal of Personal Protective Equipment (2015)

Contamination of the skin and clothing of health care personnel occurs frequently during removal of contaminated gloves or gowns. Educational interventions that include practice with immediate visual feedback on skin and clothing contamination can significantly reduce the risk of contamination during removal of PPE.
Real-time 3D Traffic Cone Detection for Autonomous Driving (2019)

Considerable progress has been made in semantic scene understanding of road scenes with monocular cameras. It is, however, mainly focused on certain specific classes such as cars, bicyclists and pedestrians. This work investigates traffic cones, an object category crucial for traffic control in the context of autonomous vehicles. 3D object detection using images from a monocular camera is intrinsically an ill-posed problem. In this work, we exploit the unique structure of traffic cones and propose a pipelined approach to solve this problem. Specifically, we first detect cones in images by a modified 2D object detector. Following which the keypoints on a traffic cone are recognized with the help of our deep structural regression network, here, the fact that the cross-ratio is projection invariant is leveraged for network regularization. Finally, the 3D position of cones is recovered via the classical Perspective n-Point algorithm using correspondences obtained from the keypoint regression. Extensive experiments show that our approach can accurately detect traffic cones and estimate their position in the 3D world in real time. The proposed method is also deployed on a real-time, autonomous system. It runs efficiently on the low-power Jetson TX2, providing accurate 3D position estimates, allowing a race-car to map and drive autonomously on an unseen track indicated by traffic cones. With the help of robust and accurate perception, our race-car won both Formula Student Competitions held in Italy and Germany in 2018, cruising at a top speed of 54 km/h on our driverless platform “gotthard driverless” https://youtu. be/HegmIXASKow?t==11694. Visualization of the complete pipeline, mapping and navigation can be found on our project page http://people.ee.ethz.ch/=tracczucrich/Trnfflcf.lonc/.
Tag and contour detection in tagged MR images of the left ventricle (1994)

Tracking magnetic resonance tags in myocardial tissue promises to be an effective tool for the assessment of myocardial motion. The authors describe a hierarchy of image processing steps which rapidly detects both the contours of the myocardial boundaries of the left ventricle and the tags within the myocardium. The method works on both short axis and long axis images containing radial and parallel tag patterns, respectively. Left ventricular boundaries are detected by first removing the tags using morphological closing and then selecting candidate edge points. The best inner and outer boundaries are found using a dynamic program that minimizes a nonlinear combination of several local cost functions. Tags are tracked by matching a template of their expected profile using a least squares estimate. Since blood pooling, contiguous and adjacent tissue, and motion artifacts sometimes cause detection errors, a graphical user interface was developed to allow user correction of anomalous points. The authors present results on several tagged images of a human. A fully automated run generally finds the endocardial boundary and the tag lines extremely well, requiring very little manual correction. The epicardial boundary sometimes requires more intervention to obtain an acceptable result. These methods are currently being used in the analysis of cardiac strain and as a basis for the analysis of alternate tag geometries.
Infusion of Cognitive Engineering into Systems Engineering Processes and Practices (2006)

The infusion of cognitive engineering (CogE) methods and tools into traditional systems engineering processes and practices is becoming an important priority as the systems engineering community begins to tackle system of systems (SoS) problems. As one illustration, the military is interested in creating cognitively-inspired systems (as small as a PDA and as large as a weapon platform) that maximally exploit human potential while also accelerating both human supported and automated decision making. To date, cognitive engineering has been successfully applied to the planning and requirements definition phases of systems engineering (also known as front-end analysis) but has yet to be infused into the remaining phases of systems engineering. To span the full systems engineering lifecycle, it is important, first and foremost, to communicate the return-on-investment to the various stakeholders to get their buy in. The second question that needs to be answered is whether or not "cognitive engineering is ready for primetime". This paper presents promising technical and management strategies to overcome the challenges in introducing cognitive engineering into system-of-systems engineering (SOSE). Specifically, it presents a representative set of cognitive engineering methods and tools to span the full SoS life-cycle as well as cognitive engineering awareness initiatives to penetrate both the DoD acquisition community and commercial industry.
T-Linkage: A Continuous Relaxation of J-Linkage for Multi-model Fitting (2014)

This paper presents an improvement of the J-linkage algorithm for fitting multiple instances of a model to noisy data corrupted by outliers. The binary preference analysis implemented by J-linkage is replaced by a continuous (soft, or fuzzy) generalization that proves to perform better than J-linkage on simulated data, and compares favorably with state of the art methods on public domain real datasets.
Practical applications of therapy with a glucagon-like peptide-1 receptor agonist. (2009)

Patients such as ML represent a common challenge in the primary care management of patients with T2DM. After some response to initial therapy with lifestyle management and metformin, the A1C goal of <7.0% after 2 to 3 months was not achieved, necessitating the initiation of combination therapy. The 4 groups of medications recommended by the ADA/EASD panel as the preferred therapies are basal insulin, the sulfonylureas, the TZD pioglitazone, and GLP-1 receptor agonists. In addition to considering efficacy, safety, cost, and other medication-related factors, the treatment plan must take into account the patient's individual needs, concerns, and capabilities. These additional considerations help to foster increased patient self-management and greater treatment adherence. To achieve these objectives, comprehensive patient education is essential. The unique mechanism of action of the GLP-1 receptor agonist class of medications makes these agents a desirable choice as add-on therapy to metformin.
Shock resistant PVDF hydrophones (1983)

Previous research successfully demonstrated the use of tubular PVDF in a shock resistant hydrophone [T. A. Henriquez, “Application of Tubular PVDF to Shock Resistant Hydrophones,” in Proceedings of the International Symposium of Applied Ferroelectrics (1983)]. The present work continued the development and refinement of a shock hardened underwater transducer. Nonvoided as well as voided tubular material with an outer diameter of 14 or 12 in. was used as the active element in each design. To evaluate the effects of stress rod material and circumferential prestress, the free-field voltage sensitivity (FFVS) was recorded for each transducer. The response of the element was dependent upon the acoustic coupling between the compression bolt and rubber mandril within the tube and between the rubber mandril and the tube itself. The hydrophones were also exposed to scaled down explosive tests to determine their ruggedness. The results support previous findings that tubular PVDF can be utilized as a broadband standard hydrophone. [Work supported by NAVSEA.]
Solid modeling (1994)

Solid modeling deals with the representation, design, visualization. and analysis of models of 3D parts. While the embodiment of solid modeling technology in contemporary commercial CAD systems is finally beginning to fulfil the old promise of providing major improvements in the productivity of the manufacturing industry, solid modeling research remains in its infancy. Recent developments focus on advanced design paradigms, topological and geometric extensions of the domain and the performance and reliability of the fundamental algorithms. The current trend follows two paths: capitalizing on the concepts of features, constraints, and model parameterization, which provide a more intuitive and suitable design vocabulary than the traditional edges, faces, or Boolean operations; and incorporating information about the tolerances, assembly relations, and mechanical properties of parts and assemblies, which provides a suitable product database for the development of analysis and planning applications. We selected the articles in the special issue carefully, choosing from among the papers presented at the 1993 ACM/IEEE Second Symposium on Solid Modeling and Applications.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>
Modelling stomatal conductanceof field‐grown sunflower under varying soil water content and leafenvironment: comparison of three models of stomatal response toleaf environment and coupling with an abscisic acid‐based modelof stomatal response to soil drying (2002)

Abstract Stomatal conductance, g s , responds both tothe immediate or local environment of the leaf, such as CO 2 partialpressure and irradiance, and to root‐sourced signals of water stress,particularly abscisic acid (ABA). Two models for the combined controlof g s were formulated and tested in sunflower( Helianthus annuus ). First, several empirical models weretested for the local control, demonstrating that the Ball–Berrymodel [Ball, Woodrow &amp; Berry (in Progress in PhotosynthesisResearch Vol. 4 , pp. 5.221–5.224: M. Nijhoff,Dordrecht, The Netherlands) 1987] is consistently amongthe most accurate. A problem of statistical non‐independence inthis model is shown to be minor. The model offers regularity ofparameter values among most species and, despite an oversimplicationin representing known humidity‐response mechanisms, it incorporates othersignalling loops from CO 2 and assimilation. In the firstcombined model, ABA as its concentration in xylem sap, [ABA] xy ,down‐regulates the slope, m , in the Ball–Berry modelby the factor g fac = exp(– β [ABA] xy ).The ABA‐induced reduction in g s decreases CO 2 assimilation andsurface humidity, thus appearing to induce the local‐control mechanismto amplify the ABA‐induced stomatal closure. In the second combinedmodel, g s is estimated as the minimum of the local(Ball–Berry) response and the product g fac g s,max ,with g s,max as a maximal unstressed conductance.Both models can predict g s from the external environmentalvariables with good accuracy ( r 2 near 0·8 over20‐fold variations in g s ). Further analyses showthat g s responds to humidity almost quadraticallyrather than linearly. It also responds to assimilation as a powerlaw with an exponent that is significantly less than 1. These limitations,shared by other models, suggest more research into biochemical signalling.
Materials Design of Organic Lasers Aimed at Low Lasing Threshold (2022)

As the next generation optoelectronic devices, i.e., post- organic light emitting diodes (OLEDs), organic semiconductor laser diodes (OSLDs) are supposed to be fascinating devices due to their unique properties such as a wide range of emission wavelength tunability, low-temperature fabrication allowing flexible devices, and the compatibility with present OLED technologies. In this report, by focusing on the most promising laser material of 4,4’-bis[(N-carbazole)styryl]biphenyl (BSBCz), the materials design of organic lasing molecules with their photophysical and current injection device properties are summarized.
The NLM Gateway: a metasearch engine for disparate resources. (2004)

The U.S. National Library of Medicine (NLM) has created a metasearch engine called the NLM Gateway at the URL "gateway.nlm.nih.gov". The Gateway allows the user to issue one search that takes place on multiple NLM retrieval engines. A composite result set is presented in several categories of information: journal citations; books, serials and audiovisuals; consumer health; meeting abstracts; and other collections.
A low power Class D audio amplifier with discrete time loop filter compensation (2009)

This brief describes a new Class D amplifier topology with digital input and a digital compensation loop filter to improve linearity. The core of the system is a high resolution hybrid multi-bit SigmaDelta-Pulse Width Modulation (PWM) modulator. The modulator does not require dynamic element matching nor signal processing to correct for distortion arising from the discrete PWM process. A system prototype based on a FPGA and commercial 16b analog to digital converter (ADC) validate the system design before implementation in 0.13 mum CMOS. Measurement results at 1 kHz yield a Total Harmonic Distortion (THD) better than 0.03% and greater than 30 dB of noise rejection and linearity enhancement. The system is inherently scalable to deep submicron processes due to its predominately digital architecture.
Identification of a new subset of lymph node stromal cells involved in regulating plasma cell homeostasis (2018)

Antibody-secreting plasma cells (PCs) arise rapidly during adaptive immunity to control infections. The early PCs are retained within the reactive lymphoid organ where their localization and homeostasis rely on extrinsic factors, presumably produced by local niche cells. While myeloid cells have been proposed to form those niches, the contribution by colocalizing stromal cells has remained unclear. Here, we characterized a subset of fibroblastic reticular cells (FRCs) that forms a dense meshwork throughout medullary cords of lymph nodes (LNs) where PCs reside. This medullary FRC type is shown to be anatomically, phenotypically, and functionally distinct from T zone FRCs, both in mice and humans. By using static and dynamic imaging approaches, we provide evidence that medullary FRCs are the main cell type in contact with PCs guiding them in their migration. Medullary FRCs also represent a major local source of the PC survival factors IL-6, BAFF, and CXCL12, besides also producing APRIL. In vitro, medullary FRCs alone or in combination with macrophages promote PC survival while other LN cell types do not have this property. Thus, we propose that this FRC subset, together with medullary macrophages, forms PC survival niches within the LN medulla, and thereby helps in promoting the rapid development of humoral immunity, which is critical in limiting early pathogen spread.
High-Sensitivity, High-Resolution Magnetic Force Microscopy System. (2003)

Magnetic force microscopy (MFM) is a useful tool for investigating magnetic recording media, ferromagnetic patterns and magnetic devices. Ultra-thin magnetic coating probes were developed with the aim of providing high-resolution MFM. High-sensitivity MFM system with quality factor auto control (QFAC) was developed for use with such thin magnetic coating probes. We studied performance of the QFAC system in air and in vacuum. As a result, we found this is a powerful technique for imaging a magnetic domain. The QFAC in vacuum was superior to that in air. We observed finer magnetic domains than those observable with a conventional MFM system. This paper, we reports experimental results for ultra-high-density recording media; we estimate the lateral resolution is less than 20 nm.
Generational accounting in Norway: Is Norway overconsuming its petroleum wealth (1993)

oil industry ; accounting ; resource allocation
A cloud platform for atomic pair distribution function analysis: PDFitc (2020)

A cloud web platform for analysis and interpretation of atomic pair distribution function (PDF) data (PDFitc) is described. The platform is able to host applications for PDF analysis to help researchers study the local and nanoscale structure of nanostructured materials. The applications are designed to be powerful and easy to use and can, and will, be extended over time through community adoption and development. The currently available PDF analysis applications, structureMining, spacegroupMining and similarityMapping, are described. In the first and second the user uploads a single PDF and the application returns a list of best-fit candidate structures, and the most likely space group of the underlying structure, respectively. In the third, the user can upload a set of measured or calculated PDFs and the application returns a matrix of Pearson correlations, allowing assessment of the similarity between different data sets. structureMining is presented here as an example to show the easy-to-use workflow on PDFitc. In the future, as well as using the PDFitc applications for data analysis, it is hoped that the community will contribute their own codes and software to the platform.