gebhart/patrepeval huggingface dataset:
Investigation of Membrane Pinhole Effects in Polymer Electrolyte Fuel Cells by Locally Resolved Current Density (2010)

In order to increase the reliability of fuel cells, an online diagnostic method for detection of operation malfunctions, as well as the early detection of failures in the fuel cells, is necessary. For this purpose, locally resolved current density measurements are an important tool, but the interpretation of the data related to the detection of malfunctions or failures is not straightforward. Here, segmented cell technology is applied to investigate the current density distributions in the anode and cathode electrodes to ascertain their equivalence due to the strong perpendicular coupling of currents. Current density distributions are further used to determine the signature of pinhole formation in the membrane. Different behavior is observed for membrane leakage under open circuit and under applied load conditions. Whereas the cell at open circuit is characterized by a positive current in the vicinity of the pinhole and small negative currents in the remaining area, an applied load leads to large negative currents at the pinhole. The characteristic behavior can be explained by high crossover rates of hydrogen from the anode to the cathode. The nongeneric signature is used to detect the deterioration of a membrane electrode assembly after a test stand malfunction. A sudden pressure drop associated with vaporation of water and the fast cooling of the cell is assumed to trigger the failure of the membrane. After 48 h, fissures in several positions of the membrane near the edges of the cell holder are observed. Through the evolution of leakages in the fuel cell, a malfunction can be detected at an early stage and thereby catastrophic failure of the whole stack may be avoided or anticipated.
Study of ethnobotanical implications of the places of religious activities in Kolkata: 1. Jain temples (2016)

In conformity with the cultural heritage of India, religious organizations and institutions have always been concerned with protection of nature and her creations for conveying the benevolence to mankind. Considering revelation of the direct man-plant relationship sustained traditionally by the devotees of different religions as one the important objective of ethnobotany in optimization of environment and invigoration of environmental ethics, the present study was strategically undertaken in Kolkata. In Kolkata, one of the busiest metropolises in India, the motto has not been eroded as is reflected in the green diversity in the premises of Jain temples. The study revealed the concern of five Jain temples in Kolkata in sustaining appreciable plant diversity and conserving useful and rare species which can be used as a model of purity, aesthetic pleasure, sense of peace and tranquility to the perceivable senses, maintaining a harmony with the life style of the people of Kolkata.
A New Nucleoporin-like Protein Interacts with Both HIV-1 Rev Nuclear Export Signal and CRM-1 (1999)

The HIV-1 Rev is a shuttling protein required for the nuclear export of unspliced and partially spliced viral mRNA. In this study, we have identified a new Rev-interacting protein, that specifically interacts with the Rev nuclear export signal both in yeast and mammalian cells. This protein has features found in nucleoporins including many phenylalanine-glycine repeats, a very high serine content, a putative zinc finger, and a coiled-coil domain; we thus called it NLP-1 (nucleoporin-like protein 1). In addition, gene expression analysis and wheat germ agglutinin chromatography experiments suggested that NLP-1 is an ubiquitous O-glycosylated nuclear protein. Recently, a cellular factor called CRM-1 has been shown to be an essential nuclear export factor interacting directly with nuclear export signals including the Rev nuclear export signal in a RanGTP-dependent manner. We show here that NLP-1, like the previously described Rev-interacting protein hRIP/Rab and several nucleoporins, also interacts with CRM-1 both in yeast and mammalian cells.
Real-time robust estimation of vanishing points through nonlinear optimization (2010)

Vanishing points are elements of great interest in the computer vision field, since they are the main source of information about the geometry of the scene and the projection process associated to the camera. They have been studied and applied during decades for plane rectification, 3D reconstruction, and mainly auto-calibration tasks. Nevertheless, the literature lacks accurate online solutions for multiple vanishing point estimation. Most strategies focalize on the accuracy, using highly computational demanding iterative procedures. We propose a novel strategy for multiple vanishing point estimation that finds a trade-off between accuracy and efficiency, being able to operate in real time for video sequences. This strategy takes advantage of the temporal coherence of the images of the sequences to reduce the computational load of the processing algorithms while keeping a high level of accuracy due to an optimization process. The key element of the approach is a robust scheme based on the MLESAC algorithm, which is used in a similar way to the EM algorithm. This approach ensures robust and accurate estimations, since we use the MLESAC in combination with a novel error function, based on the angular error between the vanishing point and the image features. To increase the speed of the MLESAC algorithm, the selection of the minimal sample sets is substituted by a random sampling step that takes into account temporal information to provide better initializations. Besides, for the sake of flexibility, the proposed error function has been designed to work using as image features indiscriminately gradient-pixels or line segments. Hence, we increase the range of applications in which our approach can be used, according to the type of information that is available. The results show a real-time system that delivers real-time accurate estimations of multiple vanishing points for online processing, tested in moving camera video sequences of structured scenarios, both indoors and outdoors, such as rooms, corridors, facades, roads, etc.
Nonlinear time-series analysis of current signal in cathodic contact glow discharge electrolysis (2016)

In the standard two-electrode configuration employed in electrolytic process, when the control dc voltage is brought to a critical value, the system undergoes a transition from conventional electrolysis to contact glow discharge electrolysis (CGDE), which has also been referred to as liquid-submerged micro-plasma, glow discharge plasma electrolysis, electrode effect, electrolytic plasma, etc. The light-emitting process is associated with the development of an irregular and erratic current time-series which has been arbitrarily labelled as “random,” and thus dissuaded further research in this direction. Here, we examine the current time-series signals measured in cathodic CGDE configuration in a concentrated KOH solution at different dc bias voltages greater than the critical voltage. We show that the signals are, in fact, not random according to the NIST SP. 800-22 test suite definition. We also demonstrate that post-processing low-pass filtered sequences requires less time than the native as-measured sequences, suggesting a superposition of low frequency chaotic fluctuations and high frequency behaviors (which may be produced by more than one possible source of entropy). Using an array of nonlinear time-series analyses for dynamical systems, i.e., the computation of largest Lyapunov exponents and correlation dimensions, and re-construction of phase portraits, we found that low-pass filtered datasets undergo a transition from quasi-periodic to chaotic to quasi-hyper-chaotic behavior, and back again to chaos when the voltage controlling-parameter is increased. The high frequency part of the signals is discussed in terms of highly nonlinear turbulent motion developed around the working electrode.
Challenges in generating bookmarks from TOC entries in e-books (2012)

ABSTRACT The task of extracting document structures from a digital e-book is difficult and is an active area of research. On the other hand, many e-books already have a table of contents (TOC) at the beginning of the document. This may lead us to believe that adding bookmarks into digital document (e-book) based on the existing TOC would be trivial. In this paper, we highlight the challenges involved in this task of automatically adding bookmarks to an existing e-book based on the TOC that exists within the document. If we are able to reliably identify the specific locations of each TOC entry within the document, the algorithms can be easily extended to identify document structures within e-books that have TOC. We describe a tool we have built called Booky that tries to add automatic PDF bookmarks to existing PDF based e-books as they have TOC as part of the document content. The tool addresses most of the challenges that have been identified while still leaving a few tricky scenarios still open.
Development and Validation of a Finite Element Model of the Lower Limb (2004)

Pedestrians struck by a vehicle frequently sustain lower limb injuries. Moreover, the biomechanics of the lower limb under lateral impact influences the trajectory of the pedestrian and subsequent injuries to the pelvis, thorax, and head. In order to increase the understanding of injury mechanisms in the lower limb, a finite element (FE) model of the lower limb was developed. The geometry of the bones and flesh was originally obtained from the Visible Human Project Database and was scaled to a 50th percentile male. The geometry of the knee ligaments was originally obtained from the 3D-CAD-Browser Database and was scaled according to the published anatomical data to align with the bones and the corresponding insertion sites. The FE mesh consists mostly of hexahedral elements which was developed using a structural mesh generator. The material and failure properties were initially selected from the literature and were later tuned based on the validation tests. The FE model was validated using the literature data and several cadaveric component tests performed specifically for model development and evaluation. The validation tests included quasi-static and dynamic lateral three-point-bend tests of the femur and the leg with flesh, and lateral four-point-bend tests of the knee joint.
Collagen-binding proteins: insights from the Collagen Toolkits (2019)

The Collagen Toolkits are libraries of 56 and 57 triple-helical synthetic peptides spanning the length of the collagen II and collagen III helices. These have been used in solid-phase binding assays to locate sites where collagen receptors and extracellular matrix components bind to collagens. Truncation and substitution allowed exact binding sites to be identified, and corresponding minimal peptides to be synthesised for use in structural and functional studies. 170 sites where over 30 proteins bind to collagen II have been mapped, providing firm conclusions about the amino acid distribution within such binding sites. Protein binding to collagen II is not random, but displays a periodicity of approximately 28 nm, with several prominent nodes where multiple proteins bind. Notably, the vicinity of the collagenase-cleavage site in Toolkit peptide II-44 is highly promiscuous, binding over 20 different proteins. This may reflect either the diverse chemistry of that locus or its diverse function, together with the interplay between regulatory binding partners. Peptides derived from Toolkit studies have been used to determine atomic level resolution of interactions between collagen and several of its binding partners and are finding practical application in tissue engineering.
Cell surface‐associated aggregation‐promoting factor from <scp><i>L</i></scp><i>actobacillus gasseri</i> <scp>SBT</scp>2055 facilitates host colonization and competitive exclusion of <scp><i>C</i></scp><i>ampylobacter jejuni</i> (2015)

Campylobacter jejuni, one of the most common causes of gastroenteritis worldwide, is transmitted to humans through poultry. We previously reported that Lactobacillus gasseri SBT2055 (LG2055) reduced C. jejuni infection in human epithelial cells in vitro and inhibited pathogen colonization of chickens in vivo. This suggested that the LG2055 adhesion and/or co-aggregation phenotype mediated by cell-surface aggregation-promoting factors (APFs) may be important for the competitive exclusion of C. jejuni. Here, we show that cell surface-associated APF1 promoted LG2055 self-aggregation and adhesion to human epithelial cells and exhibited high affinity for the extracellular matrix component fibronectin. These effects were absent in the apf1 knockout mutant, indicating the role of APF1 in LG2055-mediated inhibition of C. jejuni in epithelial cells and chicken colonization. Similar to APF1, APF2 promoted the co-aggregation of LG2055 and C. jejuni but did not inhibit C. jejuni infection. Our data suggest a pivotal role for APF1 in mediating the interaction of LG2055 with human intestinal cells and in inhibiting C. jejuni colonization of the gastrointestinal tract. We thus provide new insight into the health-promoting effects of probiotics and mechanisms of competitive exclusion in poultry. Further research is needed to determine whether the probiotic strains reach the epithelial surface.
Transdermal electroosmotic flow generated by a porous microneedle array patch (2021)

A microneedle array is an attractive option for a minimally invasive means to break through the skin barrier for efficient transdermal drug delivery. Here, we report the applications of solid polymer-based ion-conductive porous microneedles (PMN) containing interconnected micropores for improving iontophoresis, which is a technique of enhancing transdermal molecular transport by a direct current through the skin. The PMN modified with a charged hydrogel brings three innovative advantages in iontophoresis at once: (1) lowering the transdermal resistance by low-invasive puncture of the highly resistive stratum corneum, (2) transporting of larger molecules through the interconnected micropores, and (3) generating electroosmotic flow (EOF). In particular, the PMN-generated EOF greatly enhances the transdermal molecular penetration or extraction, similarly to the flow induced by external pressure. The enhanced efficiencies of the EOF-assisted delivery of a model drug (dextran) and of the extraction of glucose are demonstrated using a pig skin sample. Furthermore, the powering of the PMN-based transdermal EOF system by a built-in enzymatic biobattery (fructose / O<sub>2</sub> battery) is also demonstrated as a possible totally organic iontophoresis patch.
Bounds on end-to-end performance via greedy, multi-path routing in integrated services networks (2002)

We focus on the design and performance of resource management controls, specifically state dependent routing, with which to compute the bounds on the end-to-end performance in integrated services networks. The routing control problem at each hop is transformed into an optimization problem, the solution of which suggests a path selection algorithm that relies on the available capacity process at adjacent nodes. We focus on computing a bound on the average end to end packet loss, although our results can easily be adapted to minimize the mean transfer delay. The routing scheme based on the solution to the optimization problem is as follows: each node computes multiple alternate paths to a given destination. The available capacity process, e.g., available bandwidth, available buffer, etc., is derived from the link state updates received at each node and the forwarding rule is based on some function of the maximum available capacity process applied to the set of possible nodes corresponding to the next hop on an alternate path for a particular source destination pair. A consequence of this path selection rule is the pooling of network resources when the load is increased. This allows us to prove the bound (at each hop) on the packet loss in terms of the network parameters. We show how the node reduction technique (and its associated bound) can be used as a building block to compute end to-end performance bounds in a network setting.
Complete Center Pivot Automation Using the Temperature-Time Threshold Method of Irrigation Scheduling. (2004)

It has been shown that the temperature-time threshold (TTT) method of automaticirrigation scheduling is a viable alternative to traditional soil water based irrigation scheduling in theSouthern High Plains. The TTT method involves using infrared thermocouples (IRTCs) to remotelyexamine crop canopy temperatures over the course of a day. If a threshold canopy temperature isexceeded for a predetermined threshold time an irrigation event is scheduled. Applying this methodusing IRTCs mounted on self propelled irrigation systems such as center pivots or linear movespresents special challenges. First, it necessitates a method of estimating the diurnal canopytemperature dynamics using only a one-time-of-day canopy temperature measurement. Secondly, itrequires a method of automatically collecting and analyzing the canopy temperature data andcontrolling the moving irrigation system based on the data analysis. A method of determining thediurnal canopy temperature curve using a one-time-of-day temperature measurement and areference temperature curve was developed. The mean absolute error from calculated to observedwas approximately 0.5 C from 0800 h to 2200 h. An array of 16 IRTCs were connected to adatalogger and mounted on a three tower center pivot. A separate array of IRTCs was located instationary positions in the field and also connected to a datalogger. Two different spread spectrum (900 MHz) radios were connected to a desktop computer located nearby that queried bothdataloggers, and got pivot status information and send commands to the center pivot control panel.Using scheduled data collection intervals, this computer was able to collect the data, analyze it,determine need for an irrigation event, and issue control commands thus completely automating thecenter pivot.
Theory of two-dimensional ‘fingerprint’ resonators (1989)

A series of concentric circular curves etched on the surface of optical chips forms a resonator. A high quality value can be achieved in a small size.
Direct synthesis of W<sub>18</sub>O<sub>49</sub>nanorods from W<sub>2</sub>N film by thermal annealing (2007)

Tungsten oxide nanorods were prepared from W2N film by a simple annealing method. W2N film was deposited on a Si( 100) substrate by chemical vapour deposition (CVD) at 450 degrees C, and then heating of the film at 600 - 700 degrees C produces a high density of tungsten oxide nanorods. The morphology, structure, composition and chemical binding states of the prepared nanorods were characterized by scanning electron microscopy (SEM), x-ray diffraction (XRD), x-ray photoelectron spectroscopy (XPS), energy dispersive x-ray analysis (EDX) and transmission electron microscopy (TEM) measurements. XRD and TEM analysis showed that the grown nanorods were single-crystalline W18O49. According to XPS analysis, the W18O49 nanorods contained similar to 62% of W6+, similar to 28% of W5+, and similar to 10% of W4+. Field-emission measurements showed a low turn-on field of 9.5 V mu m(-1) for the W18O49 nanorods, indicating that they can be used as potential field emitters. Also, a synthesis reaction mechanism based on thermodynamics is proposed for the growth of tungsten oxide nanorods from W2N.
Purification of haemopoietic progenitor cells from patients with chronic granulocytic leukaemia using Percoll density gradients and elutriation (1986)

S ummary Purification of haemopoietic progenitor cells from chronic granulocytic leukaemia buffy coat preparations requires a multistep approach using complementary cell separation techniques. In this study Percoll density gradient centrifugation and centrifugal elutriation were used to isolate large numbers of immature progenitor cells. Percoll density gradients were valuable as a first separation step: CFU‐GM and CFU‐GEMM could be enriched 75‐fold in a light density fraction of d< 1mD056 g/ml and the technique could be adapted to cope with more than 10 10 buffy coat leucocytes. Progenitors cells were concentrated 3‐fold by elutriation used as single method to separate buffy coat cells or when used to purify further light density Percoll fractions. When Percoll gradients and elutriation were used sequentially, undifferentiated mononuclear cells were enriched to more than 90% purity arid between 5% and 40% of these cells formed CFU‐GM or BFU‐E colonies consisting of more than 40 cells. The enriched fractions were further characterized with monoclonal antibodies. The density and elutriation profiles of these colony forming cells resembled corresponding profiles of cells that reacted with the monoclonal antibody BI‐3C5, which recognizes an antigen on primitive haemopoietic progenitor cells. Physical separation methods are a valuable first stage in the attempt to procure relatively pure myeloid progenitor cell populations, whose characteristics can then be further studied at a cellular or molecular level.
Light scattering properties of surface‐textured substrates (2010)

Abstract Light trapping in state‐of‐the‐art thin‐film silicon solar cells is accomplished by scattering of light at rough interfaces. Further enhancement of light absorption in the absorber layers can be achieved by optimizing the scattering via designing the morphology of these interfaces. The haze parameter and the angular intensity distribution of the scattered light were measured. The angular intensity measurements were carried out with variable angle spectrometry, allowing wavelengths in the visible and near infrared range. The measurements revealed new insights regarding the strong effects of the substrate surface roughness and morphology on the wavelength dependent variations of the angular intensity distribution. (© 2010 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)
Physics-based scene-level reasoning for object pose estimation in clutter (2019)

This paper focuses on vision-based pose estimation for multiple rigid objects placed in clutter, especially in cases involving occlusions and objects resting on each other. Progress has been achieved recently in object recognition given advancements in deep learning. Nevertheless, such tools typically require a large amount of training data and significant manual effort to label objects. This limits their applicability in robotics, where solutions must scale to a large number of objects and variety of conditions. Moreover, the combinatorial nature of the scenes that could arise from the placement of multiple objects is difficult to capture in the training dataset. Thus, the learned models might not produce the desired level of precision required for tasks, such as robotic manipulation. This work proposes an autonomous process for pose estimation that spans from data generation to scene-level reasoning and self-learning. In particular, the proposed framework first generates a labeled dataset for training a convolutional neural network (CNN) for object detection in clutter. These detections are used to guide a scene-level optimization process, which considers the interactions between the different objects present in the clutter to output pose estimates of high precision. Furthermore, confident estimates are used to label online real images from multiple views and re-train the process in a self-learning pipeline. Experimental results indicate that this process is quickly able to identify in cluttered scenes physically consistent object poses that are more precise than those found by reasoning over individual instances of objects. Furthermore, the quality of pose estimates increases over time given the self-learning process.