On the Processing of might

This study examines the processing of the implicature of “might” (NOT must). The literature on implicatures contains both studies that suggest rapid computation of scalar implicatures, and studies that provide evidence for extra processing costs in generating them. The present study extends existing work by comparing “might” to “must”, and by adapting a paradigm that integrates experimental sentences into a natural discourse within a game. The experiment employed the visual world paradigm, using a guessing game with a confederate: in critical trials participants’ eye movements were recorded while they listened to utterances (guesses) made by a confederate. Our results show a delay in incorporating the ‘not must’ implicature of “might”, which is comparable in size to previous studies finding delays in implicature computation. Hence our results provide further support for the notion that implicatures incur processing cost, based on different implicature triggers and using an experimental paradigm based on natural dialogue

3D discomfort from vertical and torsional disparities in natural images

The two major aspects of camera misalignment that cause visual discomfort when viewing images on a 3D display are vertical and torsional disparities. While vertical disparities are uniform throughout the image, torsional rotations introduce a range of disparities that depend on the location in the image. The goal of this study was to determine the discomfort ranges for the kinds of natural image that people are likely to take with 3D cameras rather than the artificial line and dot stimuli typically used for laboratory studies. We therefore assessed visual discomfort on a five-point scale from ‘none’ to ‘severe’ for artificial misalignment disparities applied to a set of full-resolution images of indoor scenes. For viewing times of 2 s, discomfort ratings for vertical disparity in both 2D and 3D images rose rapidly toward the discomfort level of 4 (‘severe’) by about 60 arcmin of vertical disparity. Discomfort ratings for torsional disparity in the same image rose only gradually, reaching only the discomfort level of 3 (‘strong’) by about 50 deg of torsional disparity. These data were modeled with a second-order hyperbolic compression function incorporating a term for the basic discomfort of the 3D display in the absence of any misalignments through a Minkowski norm. These fits showed that, at a criterion discomfort level of 2 (‘moderate’), acceptable levels of vertical disparity were about 15 arcmin. The corresponding values for the torsional disparity were about 30 deg of relative orientation

Bipolar querying of valid-time intervals subject to uncertainty

Databases model parts of reality by containing data representing properties of real-world objects or concepts. Often, some of these properties are time-related. Thus, databases often contain data representing time-related information. However, as they may be produced by humans, such data or information may contain imperfections like uncertainties. An important purpose of databases is to allow their data to be queried, to allow access to the information these data represent. Users may do this using queries, in which they describe their preferences concerning the data they are (not) interested in. Because users may have both positive and negative such preferences, they may want to query databases in a bipolar way. Such preferences may also have a temporal nature, but, traditionally, temporal query conditions are handled specifically. In this paper, a novel technique is presented to query a valid-time relation containing uncertain valid-time data in a bipolar way, which allows the query to have a single bipolar temporal query condition

An intuitionistic approach to scoring DNA sequences against transcription factor binding site motifs

Background: Transcription factors (TFs) control transcription by binding to specific regions of DNA called transcription factor binding sites (TFBSs). The identification of TFBSs is a crucial problem in computational biology and includes the subtask of predicting the location of known TFBS motifs in a given DNA sequence. It has previously been shown that, when scoring matches to known TFBS motifs, interdependencies between positions within a motif should be taken into account. However, this remains a challenging task owing to the fact that sequences similar to those of known TFBSs can occur by chance with a relatively high frequency. Here we present a new method for matching sequences to TFBS motifs based on intuitionistic fuzzy sets (IFS) theory, an approach that has been shown to be particularly appropriate for tackling problems that embody a high degree of uncertainty. Results: We propose SCintuit, a new scoring method for measuring sequence-motif affinity based on IFS theory. Unlike existing methods that consider dependencies between positions, SCintuit is designed to prevent overestimation of less conserved positions of TFBSs. For a given pair of bases, SCintuit is computed not only as a function of their combined probability of occurrence, but also taking into account the individual importance of each single base at its corresponding position. We used SCintuit to identify known TFBSs in DNA sequences. Our method provides excellent results when dealing with both synthetic and real data, outperforming the sensitivity and the specificity of two existing methods in all the experiments we performed. Conclusions: The results show that SCintuit improves the prediction quality for TFs of the existing approaches without compromising sensitivity. In addition, we show how SCintuit can be successfully applied to real research problems. In this study the reliability of the IFS theory for motif discovery tasks is proven

A Microelectronic Sensor Device Powered by a Small Implantable Biofuel Cell

Biocatalytic buckypaper electrodes modified with pyrroloquinoline quinone (PQQ)‐dependent glucose dehydrogenase and bilirubin oxidase for glucose oxidation and oxygen reduction, respectively, were prepared for their use in a biofuel cell. A small (millimeter‐scale; 2×3×2 mm3) enzyme‐based biofuel cell was tested in a model glucose‐containing aqueous solution, in human serum, and as an implanted device in a living gray garden slug (Deroceras reticulatum), producing electrical power in the range of 2–10 μW (depending on the glucose source). A microelectronic temperature‐sensing device equipped with a rechargeable supercapacitor, internal data memory and wireless data downloading capability was specifically designed for activation by the biofuel cell. The power management circuit in the device allowed the optimized use of the power provided by the biofuel cell dependent on the sensor operation activity. The whole system (power‐producing biofuel cell and power‐consuming sensor) operated autonomously by extracting electrical energy from the available environmental source, as exemplified by extracting power from the glucose‐containing hemolymph (blood substituting biofluid) in the slug to power the complete temperature sensor system and read out data wirelessly. Other sensor systems operating autonomously in remote locations based on the concept illustrated here are envisaged for monitoring different environmental conditions or can be specially designed for homeland security applications, particularly in detecting bioterrorism threats.Sluggish sensor? A microelectronic sensor device was powered by an enzyme biofuel cell implanted in a slug to operate autonomously.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/152860/1/cphc201900700_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/152860/2/cphc201900700.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/152860/3/cphc201900700-sup-0001-misc_information.pd

Exchange current density as an effective descriptor of poisoning of active sites in platinum group metal-free electrocatalysts for oxygen reduction reaction

The oxygen reduction reaction (ORR) is of primary importance for the direct and clean conversion of energy in fuel cells, necessarily requiring an electrocatalyst to be exploited. At the state of the art, platinum group metal-free (PGM-free) electrocatalysts are the most promising alternative to carbon-supported Pt nanoparticles (Pt/C), which are more expensive and more performing but highly prone to deactivation in a contaminated working environment. The comparison of the two materials is at the level of fine-tuning, requiring specific activity descriptors, namely, turnover frequency (TOF) and site density (SD), to understand how to compare the performance of PGM-free electrocatalysts with Pt/C electrocatalysts. Specific probing molecules that bind with the active sites are required to evaluate the SD of PGM-free electrocatalysts. However, PGM-free electrocatalysts possess not a single active site like Pt/C, but a multitude of primary (metal-containing) and secondary (metal-free) sites arising from the pyrolysis synthesis process, eventually complicating SD evaluation. In this work, we propose a method for evaluating the direct interaction through the chemisorption of probing molecules over the PGM-free primary and secondary sites, the discrimination of which is of paramount importance in an effective SD evaluation. Based on the rotating disk electrode technique, the study investigates the electrochemistry of Fe-based PGM-free electrocatalysts poisoned with hydrogen sulfide at pH 1 in comparison with a Pt/C sample. In addition, X-ray photoelectron spectroscopy (XPS) is used to establish a relationship between the electrochemistry and surface chemistry of the poisoned material. The results identify the exchange current density as a meaningful tool that allows the discrimination of poisoning of specific active sites (metal-containing or metal-free). In addition, the understanding of the interaction phenomenon occurring between sites and probing molecules will be paramount for the selection of those contaminants capable of selectively interacting with the active sites of interest, paving the way to a more accurate SD evaluation

Development of Grid e-Infrastructure in South-Eastern Europe

Over the period of 6 years and three phases, the SEE-GRID programme has established a strong regional human network in the area of distributed scientific computing and has set up a powerful regional Grid infrastructure. It attracted a number of user communities and applications from diverse fields from countries throughout the South-Eastern Europe. From the infrastructure point view, the first project phase has established a pilot Grid infrastructure with more than 20 resource centers in 11 countries. During the subsequent two phases of the project, the infrastructure has grown to currently 55 resource centers with more than 6600 CPUs and 750 TBs of disk storage, distributed in 16 participating countries. Inclusion of new resource centers to the existing infrastructure, as well as a support to new user communities, has demanded setup of regionally distributed core services, development of new monitoring and operational tools, and close collaboration of all partner institution in managing such a complex infrastructure. In this paper we give an overview of the development and current status of SEE-GRID regional infrastructure and describe its transition to the NGI-based Grid model in EGI, with the strong SEE regional collaboration.Comment: 22 pages, 12 figures, 4 table

Increased power generation in supercapacitive microbial fuel cell stack using Fe-N-C cathode catalyst

The anode and cathode electrodes of a microbial fuel cell (MFC) stack, composed of 28 single MFCs, were used as the negative and positive electrodes, respectively of an internal self-charged supercapacitor. Particularly, carbon veil was used as the negative electrode and activated carbon with a Fe-based catalyst as the positive electrode. The red-ox reactions on the anode and cathode, self-charged these electrodes creating an internal electrochemical double layer capacitor. Galvanostatic discharges were performed at different current and time pulses. Supercapacitive-MFC (SC-MFC) was also tested at four different solution conductivities. SC-MFC had an equivalent series resistance (ESR) decreasing from 6.00 Ω to 3.42 Ω in four solutions with conductivity between 2.5 mScm−1 and 40 mScm−1. The ohmic resistance of the positive electrode corresponded to 75–80% of the overall ESR. The highest performance was achieved with a solution conductivity of 40 mS cm−1 and this was due to the positive electrode potential enhancement for the utilization of Fe-based catalysts. Maximum power was 36.9mW (36.9Wm−3) that decreased with increasing pulse time. SC-MFC was subjected to 4520 cycles (8 days) with a pulse time of 5 s (ipulse 55 mA) and a self-recharging time of 150 s showing robust reproducibility

Importance Sampling for Objetive Funtion Estimations in Neural Detector Traing Driven by Genetic Algorithms

To train Neural Networks (NNs) in a supervised way, estimations of an objective function must be carried out. The value of this function decreases as the training progresses and so, the number of test observations necessary for an accurate estimation has to be increased. Consequently, the training computational cost is unaffordable for very low objective function value estimations, and the use of Importance Sampling (IS) techniques becomes convenient. The study of three different objective functions is considered, which implies the proposal of estimators of the objective function using IS techniques: the Mean-Square error, the Cross Entropy error and the Misclassification error criteria. The values of these functions are estimated by IS techniques, and the results are used to train NNs by the application of Genetic Algorithms. Results for a binary detection in Gaussian noise are provided. These results show the evolution of the parameters during the training and the performances of the proposed detectors in terms of error probability and Receiver Operating Characteristics curves. At the end of the study, the obtained results justify the convenience of using IS in the training