gebhart/patrepeval huggingface dataset:
Color-Correction Techniques — Analog and Digital (1986)

Color-correction systems allow the operator to change the hue quality of the picture to compensate for several conditions that may have existed when a program originated. These include rebalancing of black and white levels, changing the gamma characteristic, compensating for lighting conditions, and modifying the overall scene colorimetry to create a particular mood. This article presents the theory of operation for a color-corrector system and compares analog and digital implementations.
A feasibility study on bedside upper airway ultrasonography compared to waveform capnography for verifying endotracheal tube location after intubation (2013)

National Medical Research Register NMRR11100810230.
A Comprehensive Survey of Video Encryption Algorithms (2012)

Encryption is the widely used technique to offer security for video communication and considerable numbers of video encryption algorithms have been proposed. The paper explores the literature for already proposed video encryption algorithms with the focus on the working principle of already proposed video encryption schemes. This study is aimed to give readers a quick overview about various video encryption algorithms proposed so far.
Hierarchical fusion of features and classifier decisions for Alzheimer's disease diagnosis (2013)

Pattern classification methods have been widely investigated for analysis of brain images to assist the diagnosis of Alzheimer's disease (AD) and its early stage such as mild cognitive impairment (MCI). By considering the nature of pathological changes, a large number of features related to both local brain regions and interbrain regions can be extracted for classification. However, it is challenging to design a single global classifier to integrate all these features for effective classification, due to the issue of small sample size. To this end, we propose a hierarchical ensemble classification method to combine multilevel classifiers by gradually integrating a large number of features from both local brain regions and interbrain regions. Thus, the large-scale classification problem can be divided into a set of small-scale and easier-to-solve problems in a bottom-up and local-to-global fashion, for more accurate classification. To demonstrate its performance, we use the spatially normalized grey matter (GM) of each MR brain image as imaging features. Specifically, we first partition the whole brain image into a number of local brain regions and, for each brain region, we build two low-level classifiers to transform local imaging features and the inter-region correlations into high-level features. Then, we generate multiple high-level classifiers, with each evaluating the high-level features from the respective brain regions. Finally, we combine the outputs of all high-level classifiers for making a final classification. Our method has been evaluated using the baseline MR images of 652 subjects (including 198 AD patients, 225 MCI patients, and 229 normal controls (NC)) from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database. The experimental results show that our classification method can achieve the accuracies of 92.0% and 85.3% for classifications of AD versus NC and MCI versus NC, respectively, demonstrating very promising classification performance compared to the state-of-the-art classification methods.
River Water Quality Modelling Using Artificial Neural Network Technique (2015)

Dissolved oxygen (DO) concentrations have been used as primary indicator of stream water quality. A problem of great social importance is determining how to best retain the quality of stream water and maintain DO concentrations using various pollution control activities. This paper presents the use of artificial neural network (ANN) technique to estimate the DO concentrations at the downstream of Mathura city, India, located at the bank of River Yamuna in the state of Uttar Pradesh, India. In the analysis, the most commonly used feed forward error back propagation neural network technique has been applied. Monthly data sets on flow discharge, temperature, pH, biochemical oxygen demand (BOD) and dissolved oxygen (DO) at three locations, namely, Mathura (upstream), Mathura (central) and Mathura (downstream) have been used for the analysis. Feed forward error back propagation algorithm, the most commonly used ANN technique, was used to develop three types of ANN models using different combinations of input variables and input stations, namely: (a) All the data sets for stations Mathura (upstream), Mathura (central) and Mathura (downstream) except DO values at Mathura (downstream) (b) All data sets for the stations Mathura (upstream), and Mathura (central), and (c) All the data sets for the stations Mathura (upstream). The performance of the ANN technique has been evaluated using statistical tools (in terms of root mean square error and coefficient of correlation). The predicted values of DO showed prominent accuracy by producing high correlations (upto 0.9) between measured and predicted values.
Scaling up Microbial Fuel Cells (2008)

The goal of this study was to quantify the relation between the surface area of the current-limiting electrode of a microbial fuel cell (MFC) and the power density generated by the MFC. Shewanella oneidensis (MR-1) was grown anaerobically in the anodic compartment of an MFC utilizing lactate as the electron donor. Graphite plate electrodes of various sizes were used as anodes. Commercially available air electrodes, composed of manganese-based catalyzed carbon bonded to a current-collecting screen made of platinum mesh, were used as cathodes, and dissolved oxygen was used as the cathodic reactant. The surface area of the cathode was always significantly larger than that of the anode, to ensure that the anode was the current-limiting electrode. The power density generated by the MFC decreased as the surface area of the anode increased, which fits well with the trend we detected comparing various published results. Thus, our findings bring into question the assertion that the overall power density generated by an MFC with large electrodes can be estimated by extrapolating from an electrode with a small surface area. Our results indicate that the maximum power density generated by an MFC is not directly proportional to the surface area of the anode, but is instead proportional to the logarithm of the surface area of the anode.
Control of Coccidiosis in Chickens: Immunization with Live Vaccines (2019)

E. M. Dickinson et al. were the first to vaccinate chickens deliberately against coccidiosis. In-feed vaccination through the use of live encapsulated oocysts is an attractive proposition for the control of coccidiosis. The procedure ensures that numbers of oocysts consumed are directly linked with food intake and that the small but increasing numbers of parasites enhance immunity without causing clinical disease. Control of disease was excellent, particularly in replacement flocks where coccidiosis was frequently diagnosed in contemporaneous flocks of the same age on the same site that were given a diet containing anticoccidial drugs. It is likely that any effective vaccine for coccidiosis used commercially will protect chickens against the pathogenic effects of a coccidial infection but will not necessarily induce an absolute immunity. While vaccines against coccidiosis are likely to become available, it must be realized that none will stimulate the wider effects that are associated with some anticoccidial drugs.
Understanding and improving the diagnostic workflow of MapReduce users (2011)

New abstractions are simplifying the programming of large clusters, but diagnosis nontheless gets more and more challenging as cluster sizes grow: Debugging information increases linearly with cluster size, and the count of intercomponent relationships grows quadratically. Worse, the new abstractions which simplified programming can also obscure the relationships between high-level (application) and low-level (task/process/disk/CPU) information flows. In this paper we analyze the workflow of several users and systems administrators connected with a large academic cluster (based the popular Hadoop implementation of the MapReduce abstraction) and propose improvements to the diagnosis-relevant information displays. We also offer a preliminary analysis of the efficacy of the changes we propose that demonstrates a 40% reduction in the time taken to accomplish 5 representative diagnostic tasks as compared to the current system.
Novel Percutaneous Epicardial Autonomic Modulation in the Canine for Atrial Fibrillation: Results of an Efficacy and Safety Study (2016)

Percutaneous epicardial ablation of GP using DC and novel catheters is safe and feasible and may be used as an adjunct to pulmonary vein isolation in the treatment of AF in order to minimize additional atrial myocardial ablation.
Fast scanning photoretinoscope for measuring peripheral refraction as a function of accommodation (2009)

A new device was designed to provide fast measurements (4 s) of the peripheral refraction (90 degrees central horizontal field). Almost-continuous traces are obtained with high angular resolution (0.4 degrees) while the subject is fixating a central stimulus. Three-dimensional profiles can also be measured. The peripheral refractions in 10 emmetropic subjects were studied as a function of accommodation (200 cm, 50 cm, and 25 cm viewing distances). Peripheral refraction profiles were largely preserved during accommodation but were different in each individual. Apparently, the accommodating lens changes its focal length evenly over the central 90 degrees of the visual field.
An efficient planning method for mobile robot based 3D digitization (2010)

Three dimensional digitization of an object is very important to many robotic applications. This paper introduces an efficient planning method for robotic 3D digitization. First, the scanning image in one viewpoint is separated into small cubes using the Octree method. Second, a least-square method is applied for normal vector calculation in each cube. Third, the distribution of surface normal vectors is analyzed to evaluate whether the surface contains sufficient constraints for the ICP-based scanning image registration. Based on this efficient surface constraint analysis, our method tries to find out the minimum overlapping area between two consecutive scanning images, which guarantees that the next scanning image can be merged to the previous one properly. This method is implemented on a low-cost mobile robot—iRobot.
Relating Input Concepts to Convolutional Neural Network Decisions (2017)

Many current methods to interpret convolutional neural networks (CNNs) use visualization techniques and words to highlight concepts of the input seemingly relevant to a CNN's decision. The methods hypothesize that the recognition of these concepts are instrumental in the decision a CNN reaches, but the nature of this relationship has not been well explored. To address this gap, this paper examines the quality of a concept's recognition by a CNN and the degree to which the recognitions are associated with CNN decisions. The study considers a CNN trained for scene recognition over the ADE20k dataset. It uses a novel approach to find and score the strength of minimally distributed representations of input concepts (defined by objects in scene images) across late stage feature maps. Subsequent analysis finds evidence that concept recognition impacts decision making. Strong recognition of concepts frequently-occurring in few scenes are indicative of correct decisions, but recognizing concepts common to many scenes may mislead the network.
Active integrated antennas using planar quasi-Yagi radiators (2002)

This paper reviews the development of several types of active integrated antennas at the authors group based on a novel planar quasi-Yagi structure which has broad bandwidth (>50%), high efficiency (>93%), low cross-polarization (<-13 dB), good front-to-back ration (>13 dB) and extremely compact size. The basic performances of the elementary quasi-Yagi antenna is first described, followed by several application examples including a high-efficiency push-pull power amplifier, a 5.8 GHz quadrature direct conversion receiver, as well as a 60 GHz self-oscillating mixer front-end.
Very low intensity alternating current decreases cell proliferation (2005)

Electric fields impact cellular functions by activation of ion channels or by interfering with cell membrane integrity. Ion channels can regulate cell cycle and play a role in tumorigenesis. While the cell cycle may be directly altered by ion fluxes, exposure to direct electric current of sufficient intensity may decrease tumor burden by generating chemical products, including cytotoxic molecules or heat. We report that in the absence of thermal influences, low-frequency, low-intensity, alternating current (AC) directly affects cell proliferation without a significant deleterious contribution to cell survival. These effects were observed in normal human cells and in brain and prostate neoplasms, but not in lung cancer. The effects of AC stimulation required a permissive role for GIRK2 (or K(IR)3.2) potassium channels and were mimicked by raising extracellular potassium concentrations. Cell death could be achieved at higher AC frequencies (>75 Hz) or intensities (>8.5 microA); at lower frequencies/intensities, AC stimulation did not cause apoptotic cellular changes. Our findings implicate a role for transmembrane potassium fluxes via inward rectifier channels in the regulation of cell cycle. Brain stimulators currently used for the treatment of neurological disorders may thus also be used for the treatment of brain (or other) tumors.
<i>Lachesis muta</i> (Viperidae) cDNAs Reveal Diverging Pit Viper Molecules and Scaffolds Typical of Cobra (Elapidae) Venoms: Implications for Snake Toxin Repertoire Evolution (2006)

Abstract Efforts to describe toxins from the two major families of venomous snakes (Viperidae and Elapidae) usually reveal proteins belonging to few structural types, particular of each family. Here we carried on an effort to determine uncommon cDNAs that represent possible new toxins from Lachesis muta (Viperidae). In addition to nine classes of typical toxins, atypical molecules never observed in the hundreds of Viperidae snakes studied so far are highly expressed: a diverging C-type lectin that is related to Viperidae toxins but appears to be independently originated; an ohanin-like toxin, which would be the third member of the most recently described class of Elapidae toxins, related to human butyrophilin and B30.2 proteins; and a 3FTx-like toxin, a new member of the widely studied three-finger family of proteins, which includes major Elapidae neurotoxins and CD59 antigen. The presence of these common and uncommon molecules suggests that the repertoire of toxins could be more conserved between families than has been considered, and their features indicate a dynamic process of venom evolution through molecular mechanisms, such as multiple recruitments of important scaffolds and domain exchange between paralogs, always keeping a minimalist nature in most toxin structures in opposition to their nontoxin counterparts.
Strategies for Soil Quality Assessment Using Visible and Near‐Infrared Reflectance Spectroscopy in a Western Kenya Chronosequence (2012)

Visible and near-infrared reflectance spectroscopy (VNIRS) is a rapid and nondestructive method that can predict multiple soil properties simultaneously, but its application in multidimensional soil quality (SQ) assessment in the tropics still needs to be further assessed. In this study, VNIRS (350–2500 nm) was employed to analyze 227 air-dried soil samples of Ultisols from a soil chronosequence in western Kenya and assess 16 SQ indicators. Partial least squares regression (PLSR) was validated using the full-site cross-validation method by grouping samples from each farm or forest site. Most suitable models successfully predicted SQ indicators (R2 ≥ 0.80; ratio of performance to deviation [RPD] ≥ 2.00) including soil organic matter (OMLOI), active C, Ca, cation exchange capacity (CEC), and clay. Moderately-well predicted indicators (0.50 ≤ R2 < 0.80; 1.40 ≤ RPD < 2.00) were water stable aggregation (WSA), Cu, silt, Mg, pH, sand, water content at permanent wilting point (Θpwp), and field capacity (Θfc). Poorly predicted indicators (R2 < 0.50; RPD < 1.40) were EC, S, P, available water capacity (AWC), K, Zn, and penetration resistance. Combining VNIRS with selected field- and laboratory-measured SQ indicator values increased predictability. Furthermore, VNIRS showed moderate to substantial agreement in predicting interpretive SQ scores and a composite soil quality index (CSQI) especially when combined with directly measured SQ indicator values. In conclusion, VNIRS has good potential for low cost, rapid assessment of physical and biological SQ indicators but conventional soil chemical tests may need to be retained to provide comprehensive SQ assessments.
Employment and regional tourism in Europe, 1990-2000 (2002)

espanolEste articulo analiza varios indicadores de actividad turistica en 100 regiones de 12 paises de la Union Europea durante el periodo 1990-2000. Analizamos las posiciones que las distintas regiones ocupan en el ranking de indicadores de turismo hotelero y extra-hotelero. Consideramos que ambos tipos de turismo son importantes pues tienen una influencia positiva sobre el desarrollo del Valor Anadido y el Empleo en varios sectores, especialmente en los servicios comerciales y en la construccion. Presentamos un modelo econometrico que tiene en cuenta el impacto positivo de ambos tipos de turismo sobre el empleo no agrario de las regiones europeas. EnglishThis article analyses some indicators of tourist activity on a regional level in 100 European Union regions belonging to 12 countries during the period 1990-2000. We analyse ranking positions in hotel tourism indicators and extra-hotel tourism indicators. Both types of tourism have a positive influence in the development of Value-Added and Employment in several sectors, particularly in commercial services and building activities. We present an econometric model that has into account the positive impact of both types of tourism in non-agrarian employment of European regions.
A PAC-Bayesian approach to adaptive classification (2004)

Abstract. This is meant to be a self-contained presentation of adaptive classification seen from the PAC-Bayesian point of view. Although most of the results are original, some review materials about the VC dimension and support vector machines are also included. This study falls in the field of statistical learning theory, where complex data have to be analyzed from a limited amount of informations, drawn from a finite sample. It relies on non asymptotic deviation inequalities, where the complexity of models is captured through the use of prior measures. The main improvements brought here are more localized bounds and the use of exchangeable prior distributions. Interesting consequences are drawn for the generalization properties of support vector machines and the design of new classification algorithms.
(–)-Epicatechin is associated with increased angiogenic and mitochondrial signalling in the hindlimb of rats selectively bred for innate low running capacity (2013)

Alternative approaches to reduce congenital muscle dysfunction are needed in cases where the ability to exercise is limited. (-)-Epicatechin is found in cocoa and may stimulate capillarity and mitochondrial proliferation in skeletal muscle. A total of 21 male rats bred for LCR (low running capacity) from generation 28 were randomized into three groups: vehicle for 30 days (control); (-)-epicatechin for 30 days; and (-)-epicatechin for 30 days followed by 15 days without (-)-epicatechin. Groups 2 and 3 received 1.0 mg of (-)-epicatechin/kg of body mass twice daily, whereas water was given to the control group. The plantaris muscle was harvested for protein and morphometric analyses. In addition, in vitro experiments were conducted to examine the role of (-)-epicatechin on mitochondrial respiratory kinetics at different incubation periods. Treatment for 30 days with (-)-epicatechin increased capillarity (P<0.001) and was associated with increases in protein expression of VEGF (vascular endothelial growth factor)-A with a concomitant decrease in TSP-1 (thrombospondin-1) and its receptor, which remained after 15 days of (-)-epicatechin cessation. Analyses of the p38 MAPK (mitogen-activated protein kinase) signalling pathway indicated an associated increase in phosphorylation of MKK3/6 (MAPK kinase 3/6) and p38 and increased protein expression of MEF2A (myocyte enhancer factor 2A). In addition, we observed significant increases in protein expression of PGC-1α (peroxisome-proliferator-activated receptor γ co-activator 1α), PGC-1β, Tfam and cristae abundance. Interestingly, these increases associated with (-)-epicatechin treatment remained after 15 days of cessation. Lastly, in vitro experiments indicated that acute exposure of LCR muscle to (-)-epicatechin incubation was not sufficient to increase mitochondrial respiration. The results suggest that increases in skeletal muscle capillarity and mitochondrial biogenesis are associated with 30 days of (-)-epicatechin treatment and sustained for 15 days following cessation of treatment. Clinically, the use of this natural compound may have potential application in populations that experience muscle fatigue and are unable to perform endurance exercise.
Chaos-Based Physical Unclonable Functions (2019)

The concept presented in this paper fits into the current trend of highly secured hardware authentication designs utilizing Physically Unclonable Functions (PUFs) or Physical Obfuscated Keys (POKs). We propose an idea that the PUF cryptographic keys can be derived from a chaotic circuit. We point out that the chaos theory should be explored for the sake of PUFs as a natural mechanism of amplifying random process variations of digital circuits. We prove the idea based on a novel design of a chaotic circuit, which utilizes time in a feedback loop as an analog continuous variable in a purely digital system. Our design is small and simple, and therefore feasible to implement in inexpensive reprogrammable devices (not equipped with digital clock manager, programmable delay line, phase locked loop, RAM/ROM memory, etc.). Preliminary tests proved that the chaotic circuit PUFs work in both advanced Field-Programmable Gate Arrays (FPGAs) as well as simple Complex Programmable Logic Devices (CPLDs). We showed that different PUF challenges (slightly different implementations based on variations in elements placement and/or routing) have provided significantly different keys generated within one CPLD/FPGA device. On the other hand, the same PUF challenges used in a different CPLD/FPGA instance (programmed with precisely the same bit-stream resulting in exactly the same placement and routing) have enhanced differences between devices resulting in different cryptographic keys.
Thermal stabilization of shape memory alloy wires (2003)

We show that fast, localized heating and cooling of a Shape Memory material can provide a very effective means of damping vibrational energy. We model the thermally induced pseudo-elastic behavior of a NiTi Shape Memory wire using the variant of Landau-Devonshire potential. We assume that the wire consists of martensitic NiTi single crystal. Dynamically, we model the material response using conservation of momentum and a nonlinear heat equation. We use a frame invariant version of the Fourier heat flux which incorporates dependence on the atomic lattice through the stretch. In the settings used in this paper, the computational experiments confirm that circa 80% of the vibrational energy can be eliminated at the moment of the onset of the thermally induced phase transition.