Biogenic amines in Spanish beers: differences among breweries

Ten biogenic amines in Spanish beers were studied using HPLC. Agmatine, tyramine and putrescine were the prevailing amines, while histamine,-phenylethylamine, tryptamine, cadaverine, spermine and spermidine were detected at relatively low levels (in general <2 mg/l). On the basis of the wide range of levels observed for tyramine (from 1.90 to 31.55 mg/l), the consumption of beer requires restriction in patients receiving monoamine oxidase inhibitor drugs. Biogenic amine levels in beers of the same type from the same company and from different companies were monitored every month over 1 year. Agmatine and putrescine levels showed minimal fluctuations in beers from the same company as well as from different breweries. Raw materials and brewing conditions would not affect the levels of those amines. However, tyramine levels were subject to wide fluctuations in beers produced by particular breweries irrespective of whether they were produced by the same company. Relatively high levels of tyramine were specific to some breweries.     

Surface plasmon resonance imaging (SPRi) as an alternative technique for rapid and quantitative screening of small molecules, useful in drug discovery

Surface plasmon resonance imaging (SPRi) is a label free technology for biomolecular interaction, which gives access to binding kinetic parameters from real time acquisition. It offers the possibility to test in a single run a large number of interactions, allowing rapid identification of the most suitable compounds toward a given biological entity. Until now, this technique has proven to be relevant for interaction between relatively large molecules (protein, antibodies, DNA) but has not been challenged yet for the screening of small molecules that can be of interested in the field of drug discovery. As a proof a principle, we have used SPRi to screen for interaction of several small molecules, referred to as G4-ligands on G-quadruplex DNA. This technology allowed to easy discrimination of the binding properties of four G4-ligands on quadruplex DNA models.     

Autonomous motion planning of a hand-arm robotic system based on captured human-like hand postures

The paper deals with the problem of motion planning of anthropomorphic mechanical hands avoiding collisions and trying to mimic real human hand postures. The approach uses the concept of “principal motion directions” to reduce the dimension of the search space in order to obtain results with a compromise between motion optimality and planning complexity (time). Basically, the work includes the following phases: capturing the human hand workspace using a sensorized glove and mapping it to the mechanical hand workspace, reducing the space dimension by looking for the most relevant principal motion directions, and planning the hand movements using a probabilistic roadmap planner. The approach has been implemented for a four finger anthropomorphic mechanical hand (17 joints with 13 independent degrees of freedom) assembled on an industrial robot (6 independent degrees of freedom), and experimental examples are included to illustrate its validity.     

The effects of the number of links and navigation support on cognitive load and learning with hypertext: The mediating role of reading order

Problems in learning with hypertext systems have been claimed to be caused by high levels of disorientation and cognitive load. This was recognized by DeStefano and LeFevre [DeStefano, D., & LeFevre, J. -A., (2007). Cognitive load in hypertext reading: A review. Computers in Human Behavior, 23(3), 1616–1641.] who predicted an increase of cognitive load and impairment of learning for hypertexts with a higher number of links per page. From a practical perspective, several navigation support techniques, such as providing link suggestions, have been proposed for guiding learners and reducing cognitive overload. In an experiment, we tested DeStefano and LeFevre’s predictions as well as the usefulness of link suggestions. Participants used different versions of a hypertext, either with 3-links or 8-links per page, presenting link suggestions or not. We tested their cognitive load and learning outcomes. Results showed that there was a benefit of using link suggestions for learning, but no effect of number of links on learning was found. Moreover, the effects of our manipulations on cognitive load were mediated by the reading order that participants selected. Implications for research and the design of navigation support systems are discussed.     

Pattern analysis of dermoscopic images based on Markov random fields

In this paper a method for detecting different patterns in dermoscopic images is presented. In order to diagnose a possible skin cancer, physicians assess the lesion based on different rules. While the most famous one is the ABCD rule (asymmetry, border, colour, diameter), the new tendency in dermatology is to classify the lesion performing a pattern analysis. Due to the colour textured appearance of these patterns, this paper presents a novel method based on Markov random field (MRF) extended for colour images that classifies images representing different dermatologic patterns. First, each image plane in L^*a^*b^* colour space is modelled as a MRF following a finite symmetric conditional model (FSCM). Coupling of colour components is taken into account by supposing that features of the MRF in the three colour planes follow a multivariate Normal distribution. Performance is analysed in different colour spaces. The best classification rate is 86% on average.     

A framework for heading-guided recognition of human activity

A combined 2D, 3D approach is presented that allows for robust tracking of moving people and recognition of actions. It is assumed that the system observes multiple moving objects via a single, uncalibrated video camera. Low-level features are often insufficient for detection, segmentation, and tracking of non-rigid moving objects. Therefore, an improved mechanism is proposed that integrates low-level (image processing), mid-level (recursive 3D trajectory estimation), and high-level (action recognition) processes. A novel extended Kalman filter formulation is used in estimating the relative 3D motion trajectories up to a scale factor. The recursive estimation process provides a prediction and error measure that is exploited in higher-level stages of action recognition. Conversely, higher-level mechanisms provide feedback that allows the system to reliably segment and maintain the tracking of moving objects before, during, and after occlusion. Heading-guided recognition (HGR) is proposed as an efficient method for adaptive classification of activity. The HGR approach is demonstrated using “motion history images” that are then recognized via a mixture-of-Gaussians classifier. The system is tested in recognizing various dynamic human outdoor activities: running, walking, roller blading, and cycling. In addition, experiments with real and synthetic data sets are used to evaluate stability of the trajectory estimator with respect to noise.     

Positive N-periodic descriptor control systems

A small-gain theorem is presented for almost global stability of monotone control systems which are open-loop almost globally stable, when constant inputs are applied. The theorem assumes “negative feedback” interconnections. This typically destroys the monotonicity of the original flow and potentially destabilizes the resulting closed-loop system.     

Super‐resolution of the undersampled and subpixel shifted image sequence by a neural network

Numerous approaches to super‐resolution (SR) of sequentially observed images (image sequence) of low resolution (LR) have been presented in the past two decades. However, neural network methods are almost ignored for solving SR problems. This is because the SR problem traditionally has been regarded as the optimization of an ill‐posed large set of linear equations. A designed neural network based on this has a large number of neurons, thereby requiring a long learning time. Also, the deduced cost function is overly complex. These defects limit applications of a neural network to an SR problem. We think that the underlying meaning of the SR problem should refer to super‐resolving an imaging system by image sequence observation, instead of merely improving the image sequence itself. SR can be regarded as a pattern mapping from LR to SR images. The parameters of the pattern mapping can be learned from the imaging process of the image sequence. This article presents a neural network for SR based on learning from the imaging process of the image sequence. In order to speed up the convergence, we employ vector mapping to train the neural network. A mapping vector is composed of some neighbor subpixels. Such a well‐trained neural network has powerful generalization ability so that it can be used directly to estimate the SR image of the other image sequences without learning again. Our simulations show the effectiveness of the proposed neural network. © 2004 Wiley Periodicals, Inc. Int J Imaging Syst Technol 14, 8–15, 2004; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/ima.20001     

Neurotrophic control of ovarian development

Substantial evidence now exists indicating that the neurotrophins, a family of growth factors required for the survival, development, and differentiation of various neuronal populations of the nervous system, are also important for the development of nonneuronal tissues. Such a function was first suggested by studies showing the presence of high-affinity neurotrophin receptors in a variety of nonneuronal tissues including those of the cardiovascular, endocrine, immune, and reproductive systems. Within the latter, the gonads appear to be a preferential site of neurotrophin action as suggested by the presence in the mammalian ovary of at least four of the five known neurotrophins and all of the neurotrophin receptors thus far identified. While the various functions that the neurotrophins may have in the ovary are still being elucidated, it is now clear that in addition to recruiting the ovarian innervation, they play a direct role in the regulation of two different maturational periods that are critical for the acquisition of female reproductive function: early follicular development and ovulation. Neurotrophins facilitate the development of newly formed follicles by promoting the initial differentiation and the subsequent growth of primordial follicles. These actions appear to be related to the ability of neurotrophins to sustain the proliferation of both mesenchymal and granulosa cells, and to induce the synthesis of follicle stimulating hormone (FSH) receptors. At the time of the first ovulation, neurotrophins contribute to the ovulatory cascade by increasing prostaglandin E(2) release, reducing gap junction communication, and inducing cell proliferation within the thecal compartment of preovulatory follicles.     

Nanotribological characterization of human hair and skin using atomic force microscopy

Healthy hair and skin is highly desired. Characterization of their morphological, frictional, and adhesive properties (tribological properties) is essential to enhance understanding of hair and skin and to advance the science. Literature on the tribological characterization of hair and skin is scarce to date. The paper presents nanotribological data and analysis on hair (Caucasian, Asian, and African hair at virgin, chemo-mechanically damaged, and treated conditions) and synthetic hair and skin, as well as roughness data of human skin replica. Roughness statistics are presented to characterize the vertical and spatial surface parameters. Average coefficient of friction values were determined for each ethnicity and hair type, and are discussed. The directionality dependence of friction is also discussed. Magnitude and spatial distribution of adhesive force are used to estimate thickness and distribution of the conditioner film.