gebhart/patrepeval huggingface dataset:
Kinetic energy functional derivative for the Thomas–Fermi atom in D dimensions (1997)

The self-consistent Thomas–Fermi atom satisfying Poisson's equation in D dimensions has a functional derivative of the kinetic energy T with respect to the ground-state density n(r) proportional to n2/D. But the Poisson equation relates n1−2/D to “reduced” density derivatives n. Thus δT/δn can be written also, quite compactly, solely in terms of these derivatives. An analytic solution to the Thomas–Fermi equation in D dimensions can be presented as an expansion about the known analytic solution at D=2. © 1997 John Wiley & Sons, Inc. Int J Quant Chem 65: 411–413, 1997
Detection of residual traces of explosives by surface enhanced Raman scattering using gold coated substrates produced by nanospheres imprint technique (2008)

Explosives detection for national and aviation security has been an area of concern for many years. In order to improve the security in risk areas, much effort has been focused on direct detection of explosive materials in vapor and bulk form. New techniques and highly sensitive detectors have been extensively investigated and developed to detect and identify residual traces that may indicate an individual's recent contact with explosive materials. This paper reports on the use and results of Surface Enhanced Raman Scattering (SERS) technique, to analyze residual traces of explosives in highly diluted solutions by using low-resolution Raman spectroscopy (LRRS). An evaluation of the detection sensitivity of this technique has been accomplished using samples of explosives such as Trinitrotoluene(TNT), Cyclotrimethylenetrinitramine (RDX) and HMX evaluated at different concentrations. Additionally, different SERS substrates have been studied in order to achieve the best enhancement of the Raman spectrum for residual amounts of materials. New substrates produced by gold-coated polystyrene nanospheres have been investigated. Two different sizes of polystyrene nanospheres, 625nm and 992nm, have been used to produce nanopatterns and nanocavities on the surface of a glass slide which has been coated with sputtered gold. Results from homemade substrates have been compared to a commercial gold-coated substrate consisting of an array of resonant cavities that gives the SERS effect. Sample concentration, starting from 1000ppm was gradually diluted to the smallest detectable amount. Raman spectrum was obtained using a portable spectrometer operating at a wavelength of 780nm.
Slow-wave propagation in a rectangular waveguide (1975)

A theoretical and experimental investigation of the conditions required for the support of the dipole mode as a slow wave inside a rectangular channel is presented. From this a number of conclusions can be drawn. First, it can be concluded that the wall structure, both the bare-metal and grid surfaces, presents to the adjoining field anisotropic impedances significantly different from those which might have been expected from planewave considerations. Secondly, the attenuation and phase-change behaviour can vary, according to boundary conditions, over a wide range of slow waves, and possibly extending to fast waves in some cases, with losses in the 3 GHz region that are of the same order as those of an equivalent TEM line. Thirdly, that a sudden transition can be traced from a transverse evanescent E1n field in the waveguide, when it is open-sided, to a dipole configuration freely propagating when closed by a grid structure. And, fourthly, that the wave can be usefully applied not only to lines employed for ordinary transmission, but also, in cases where coupling is required en route, to an adjacent circuit. Alternatively, by suitable design, it can be used for delay lines.
GPCRDB: information system for G protein-coupled receptors (2010)

The GPCRDB is a Molecular Class-Specific Information System (MCSIS) that collects, combines, validates and disseminates large amounts of heterogeneous data on G protein-coupled receptors (GPCRs). The GPCRDB contains experimental data on sequences, ligand-binding constants, mutations and oligomers, as well as many different types of computationally derived data such as multiple sequence alignments and homology models. The GPCRDB provides access to the data via a number of different access methods. It offers visualization and analysis tools, and a number of query systems. The data is updated automatically on a monthly basis. The GPCRDB can be found online at http://www.gpcr.org/7tm/.
Duodenal and faecal microbiota of celiac children: molecular, phenotype and metabolome characterization (2011)

As shown by the parallel microbiology and metabolome approach, the gluten-free diet lasting at least two years did not completely restore the microbiota and, consequently, the metabolome of CD children. Some molecules (e.g., ethyl-acetate and octyl-acetate, some short chain fatty acids and free amino acids, and glutamine) seems to be metabolic signatures of CD.
Constant phase uniform current loop for detection of metallic objects using longitudinal magnetic field projection (2013)

Currents on remote metallic objects such as landmines can be induced by projecting strong magnetic fields. These currents result in electromagnetic fields that can be subsequently detected. The magnetic field varies slowly as it passes from air into the ground and is sufficient to excite currents in buried metallic objects. Traditionally strong magnetic fields are produced using short-range transformer like inductive coupling, or as a component of powerful propagating electromagnetic fields. The strength of the magnetic component of the propagating electromagnetic field is restricted by regulatory limits on the total radiated radio frequency power. There is a need for a means to produce forward projected strong magnetic field at medium ranges with low-level propagation. This paper reports on a non-radiating loop antenna which maintains a constant amplitude and phase current around the loop and projects a strong magnetic field. The radiated field is small and results from the relativistic time-of-flight effect from one side of the loop to the other. The result is that a very strong magnetic field is produced in the near- to mid-field region, up to one wavelength away from the loop. Experiments with a prototype antenna and modeling show that the H-field is very high, radiated electromagnetic fields are negligible, and the drop off in field strength is inversely proportional to the distance squared. This agreement between experiments and modeling allows for a design based on computer simulations.
Acetylcholinesterase‐rich pyramidal neurons in the human neocortex and hippocampus: Absence at birth, development during the life span, and dissolution in Alzheimer's disease (1988)

Acetylcholinesterase-rich pyramidal neurons in the human association neocortex and hippocampal formation are virtually absent early in life, become established by adolescence, and appear to increase in density during adulthood and perhaps even senescence. Analogous neurons are not detectable in the adult monkey brain. This novel class of neurons may represent a uniquely human adaptation in primate evolution and may provide a neuroanatomical substrate for the mental development that occurs during the adult stages of life. These phylogenetically and ontogenetically progressive neurons are also markedly vulnerable to degeneration in Alzheimer's disease.
A capacity maximization scheme for intersection management with automated vehicles (2017)

With the advent of connected and automated vehicle technology, in this paper, we propose an innovative intersection operation scheme named as MCross: Maximum Capacity inteRsection Operation Scheme with Signals. This new scheme maximizes intersection capacity by utilizing all lanes of a road simultaneously. Lane assignment and green durations are dynamically optimized by solving a multi-objective mixed-integer non-linear programming problem. The demand conditions under which full capacity can be achieved in MCross is derived analytically. Numerical examples show that MCross can almost double the intersection capacity (increase by as high as 99.51% in comparison to that in conventional signal operation scheme).
Airflow Based Model to Estimate Commercial Building HVAC Energy Use: Analysis to determine principal factors for different climate zones (2016)

The paper presents an airflow based modeling method to estimate HVAC energy consumption in large commercial office buildings. The model was developed by analyzing operational data from building automation system, relating load profiles and efficiency of key HVAC equipment, Â based on economizer control policies that determine outside and return airflow rates.Â The model predicts annual energy use for buildings HVAC loads based on Â hourly climate data (temperature and relative humidity), and building airflow requirements. Â The model determines HVAC energy use in terms of building airflow rates for systems utilizing central air handler units with economizers, and identifies the key consumption drivers. Â Some parts of the model (economizer performance and fan energy use) were based on data collected from the building automation system, relating major component energy use in terms of airflow rates and control laws.Â Data was obtained for three commercial scale office-lab buildings at Boston University. Â Results are given in terms of major contributors to HVAC energy use and cost in terms of heating, cooling, and fan motor power for 4 different US cities. Â A comparison to other building HVAC models used to disaggregate CBECs data is presented.
Genito-Sensory Analysis in Women with Arousal and Orgasmic Dysfunction (2009)

Most of the study women had at least one genitor-sensory pathology on GSA testing, indicating a possible organic component in their disorder. Our findings support the incorporation of the GSA as a quantitative tool in the assessment and diagnosis of patients with FSD.
Loss of Precursor B Cell Expansion but Not Allelic Exclusion in <i>VpreB1</i>/<i>VpreB2</i> Double-Deficient Mice (2001)

The pre-B cell receptor consists of immunoglobulin (Ig) mu heavy chains and surrogate light chain, i.e., the VpreB and lambda5 proteins. To analyze the role of the two VpreB proteins, mice lacking the VpreB1 and VpreB2 genes were generated. VpreB1(-/-) VpreB2(-/-) mice were impaired in their B cell development at the transition from pre-BI to large pre-BII cells. Pre-BII cells did not expand by proliferation, consequently 40-fold less small pre-BII and immature B cells were found in bone marrow, and the generation of immature and mature conventional B cells in spleen appeared reduced. In addition, only low numbers of B-1a cells were detected in the peritoneum. Surprisingly, Ig heavy chain allelic exclusion was still active, apparently ruling out a signaling role of a VpreB1/VpreB2-containing receptor in this process.
OLIVE: Speech-Based Video Retrieval (1999)

This paper describes the Olive project which aims to support automated indexing of video material by use of human language technologies. Olive is making use of speech recognition to automatically derive transcriptions of the sound tracks, generating time-coded linguistic elements which serve as the basis for text-based retrieval functionality. The retrieval demonstrator builds on and extends the architecture from the Pop-Eye project, a system applying human language technology on subtitles for the disclosure of video fragments.
Solar Irradiance Capturing in Cloudy Sky Days–A Convolutional Neural Network Based Image Regression Approach (2020)

Global horizontal irradiance (GHI) is a critical index to indicate the output power of the photovaltaic (PV). In traditional approaches, the local GHI can be measured with very expensive instruments, and the large-area GHI collection depends on complex satellite-based models, solargis algorithms, and the high-performance computers (HPC). In this paper, a novel approach is proposed to capture the GHI conveniently and accurately. Considering the nonstationary property of the GHI on cloudy days, the GHI capturing is cast as an image regression problem. In traditional approaches, the image regression problem is treated as two parts, feature extraction (for the images) and regression model (for the regression targets), which are optimized separately and blocked the interconnections. Considering the nonlinear regression capability, a convolutional neural network (CNN) based image regression approach is proposed to provide an End-to-End solution for the cloudy day GHI capturing problem in this paper. The multilayer CNN is based on the AlexNet and VGG. The L2 (least square errors) with regularization is used as the loss function in the regression layer. For data cleaning, the Gaussian mixture model with Bayesian inference is employed to detect and eliminate the anomaly data in a nonparametric manner. The purified data are used as input data for the proposed image regression approach. In the experiments, three-month sky images and GHI data (with 1-min resolution) are provided by the National Renewable Energy Laboratory (NREL) with the HPC system. The numerical results demonstrate the feasibility and effectiveness of the proposed approach.
Compact and low-loss manner of waveguide grating router passband flattening and demonstration in a 64-channel blocker/multiplexer (2002)

We present a compact design for flattening the passband of a waveguide grating router theoretically without excess loss or chromatic dispersion. We demonstrate its use in a 64-wavelength-channel blocker/multiplexer.
Identification and characterization of [6]‐shogaol from ginger as inhibitor of vascular smooth muscle cell proliferation (2015)

This study demonstrates for the first time inhibitory potential of ginger constituents on VSMC proliferation. The presented data suggest that [6]-shogaol exerts its antiproliferative effect through accumulation of cells in the G0 /G1 cell-cycle phase associated with activation of the Nrf2/HO-1 pathway.
Multi-digit Number Recognition from Street View Imagery using Deep Convolutional Neural Networks (2013)

Recognizing arbitrary multi-character text in unconstrained natural photographs is a hard problem. In this paper, we address an equally hard sub-problem in this domain viz. recognizing arbitrary multi-digit numbers from Street View imagery. Traditional approaches to solve this problem typically separate out the localization, segmentation, and recognition steps. In this paper we propose a unified approach that integrates these three steps via the use of a deep convolutional neural network that operates directly on the image pixels. We employ the DistBelief implementation of deep neural networks in order to train large, distributed neural networks on high quality images. We find that the performance of this approach increases with the depth of the convolutional network, with the best performance occurring in the deepest architecture we trained, with eleven hidden layers. We evaluate this approach on the publicly available SVHN dataset and achieve over $96\%$ accuracy in recognizing complete street numbers. We show that on a per-digit recognition task, we improve upon the state-of-the-art, achieving $97.84\%$ accuracy. We also evaluate this approach on an even more challenging dataset generated from Street View imagery containing several tens of millions of street number annotations and achieve over $90\%$ accuracy. To further explore the applicability of the proposed system to broader text recognition tasks, we apply it to synthetic distorted text from reCAPTCHA. reCAPTCHA is one of the most secure reverse turing tests that uses distorted text to distinguish humans from bots. We report a $99.8\%$ accuracy on the hardest category of reCAPTCHA. Our evaluations on both tasks indicate that at specific operating thresholds, the performance of the proposed system is comparable to, and in some cases exceeds, that of human operators.
Low Pressure Chemical Etching of Silicon by HCl /  H 2 Gas Mixtures (1987)

The mechanism and kinetics of silicon etching with mixtures in low pressure conditions in a hot wall reactor have been analyzed. Experiments were conducted according to the variables of the system (temperature, total pressure, concentration, and total flow rate). It was observed that there are two zones of reaction according to the temperature, one controlled by gaseous diffusion and the other controlled by the reaction on the surface. The etch mechanism varies with the process conditions so that different thermodynamically stable species may be generated, depending on the adsorption of or . Both mechanisms compete, and a general kinetic equation has not yet been established.
Science Data Management For The E-Elt: Usecase Micado (2015)

The E-ELT First-light instrument MICADO will explore new parameter space in terms of precision astrometry, photometry and spectroscopy. This provides challenges for the data handling and reduction to ensure MICADO takes the observational capabilities of the AO-assisted E-ELT towards its limits. Our plan is to achieve this via iterative improvement of data quality. We present implications for the science data management system and pipelines. The iterative feedback loop between improving science data quality and improving the instrument, telescope and atmospheric calibration leads to an ever better observational model. For this reason the MICADO instrument data simulator plays a vital role in the design of pipelines and science data management system. It should provide realistic data for all science cases to guide the trade-off between calibration via hardware and software. It can then also guide how to embed the observational model in the data management system. We discuss our current models of instrument, E-ELT and sky background and the type of science data management system that supports their continuous monitoring and iterative improvement.
Toward Highly Stable Electrocatalysts via Nanoparticle Pore Confinement (2012)

The durability of electrode materials is a limiting parameter for many electrochemical energy conversion systems. In particular, electrocatalysts for the essential oxygen reduction reaction (ORR) present some of the most challenging instability issues shortening their practical lifetime. Here, we report a mesostructured graphitic carbon support, Hollow Graphitic Spheres (HGS) with a specific surface area exceeding 1000 m(2) g(-1) and precisely controlled pore structure, that was specifically developed to overcome the long-term catalyst degradation, while still sustaining high activity. The synthetic pathway leads to platinum nanoparticles of approximately 3 to 4 nm size encapsulated in the HGS pore structure that are stable at 850 °C and, more importantly, during simulated accelerated electrochemical aging. Moreover, the high stability of the cathode electrocatalyst is also retained in a fully assembled polymer electrolyte membrane fuel cell (PEMFC). Identical location scanning and scanning transmission electron microscopy (IL-SEM and IL-STEM) conclusively proved that during electrochemical cycling the encapsulation significantly suppresses detachment and agglomeration of Pt nanoparticles, two of the major degradation mechanisms in fuel cell catalysts of this particle size. Thus, beyond providing an improved electrocatalyst, this study describes the blueprint for targeted improvement of fuel cell catalysts by design of the carbon support.
Multi-agent architecture for generating and monitoring adaptive virtual environments (2005)

Virtual environments able to track users actions and adapt to the user's profile are closer to their needs. This article presents a multi-agent architecture for managing virtual reality components, allowing the generation of adaptive virtual environments in real time adapted to the user's cognitive evolution. The agents which act in such architecture, employ a domain ontology to generate 3D virtual world objects and perform queries to a DBMS in order to obtain new objects. Agents need updated information from the user model for the decision process, so user-modelling techniques are also considered in this proposal.
Plant secondary siRNA production determined by microRNA-duplex structure (2012)

Processing of microRNA (miRNA) precursors results in the release of a double-stranded miRNA/miRNA* duplex. The miRNA or guide strand, is loaded onto the Argonaute (AGO) effector, and the miRNA* or passenger strand is typically degraded. The loaded AGO-containing RNA-induced silencing complex specifically recognizes a target mRNA, leading to its degradation or translational inhibition. In plants, miRNA-mediated cleavage of a target triggers in some cases the production of secondary small interfering RNAs (siRNAs), which in turn can silence other genes in trans. This alternative pathway depends on the length of the miRNA and the specific AGO in the effector complex. However, 22-nt miRNAs are sufficient, but not essential for this pathway. Using a combination of computational and experimental approaches, we show that transitivity can be triggered when the small RNA that is not retained in AGO is 22-nt long. Moreover, we demonstrate that asymmetrically positioned bulged bases in the miRNA:miRNA* duplex, regardless of miRNA or miRNA* length, are sufficient for the initiation of transitivity. We propose that the RNA-induced silencing complex reprogramming occurs during the early steps of miRNA loading, before the miRNA duplex is disassembled and the guide strand is selected.
A reference model for crowdsourcing as a service (2015)

Online and mobile crowdsourcing services call for thorough definition of components and attributes. As cloud-based services have become widely adopted, a cloudified reference model has been emergent for crowdsourcing platforms and applications. This paper, introduces for the first time a cloudified four-phase reference model for crowdsourcing along with a generic workflow for crowdsourcing development utilizing the facilities offered by cloud service providers. Moreover, useful insights are presented for the evolution of today's online crowdsourcing applications and platforms towards the concept of crowdsourcing as a service.
Radar and RGB-Depth Sensors for Fall Detection: A Review (2017)

This paper reviews recent works in the literature on the use of systems based on radar and RGB-Depth (RGB-D) sensors for fall detection, and discusses outstanding research challenges and trends related to this research field. Systems to detect reliably fall events and promptly alert carers and first responders have gained significant interest in the past few years in order to address the societal issue of an increasing number of elderly people living alone, with the associated risk of them falling and the consequences in terms of health treatments, reduced well-being, and costs. The interest in radar and RGB-D sensors is related to their capability to enable contactless and non-intrusive monitoring, which is an advantage for practical deployment and users' acceptance and compliance, compared with other sensor technologies, such as video-cameras, or wearables. Furthermore, the possibility of combining and fusing information from The heterogeneous types of sensors is expected to improve the overall performance of practical fall detection systems. Researchers from different fields can benefit from multidisciplinary knowledge and awareness of the latest developments in radar and RGB-D sensors that this paper is discussing.