HPLC flavonoid profiles as markers for the botanical origin of European unifloral honeys

The HPLC phenolic profiles of 52 selected unifloral honey samples produced in Europe were analysed to detect possible markers for the floral origin of the different honeys. Lime‐tree (five markers), chestnut (five markers), rapeseed (one marker), eucalyptus (six markers) and heather (three markers) honeys had specific markers with characteristic UV spectra. In addition, the flavanone hesperetin was confirmed as a marker for citrus honey, as well as kaempferol for rosemary honey and quercetin for sunflower honey. Abscisic acid, which had been reported to be a possible marker for heather honey, was also detected in rapeseed, lime‐tree and acacia honeys. Ellagic acid in heather honey and the hydroxycinnamates caffeic, p‐coumaric and ferulic acids in chestnut, sunflower, lavender and acacia honeys were also detected. The characteristic propolis‐derived flavonoids pinocembrin, pinobanksin and chrysin were present in most samples in variable amounts. © 2001 Society of Chemical Industry     

Genomic Analysis Made It Possible to Identify Gene-Driver Alterations Covering the Time Window between Diagnosis of Neuroblastoma 4S and the Progression to Stage 4

Neuroblastoma (NB) is a tumor of the developing sympathetic nervous system. Despite recent advances in understanding the complexity of NB, the mechanisms that determine its regression or progression are still largely unknown. Stage 4S NB is characterized by a favorable course of disease and often by spontaneous regression, while progression to true stage 4 is a very rare event. Here, we focused on genomic analysis of an NB case that progressed from stage 4S to stage 4 with a very poor outcome. Array-comparative genomic hybridization (a-CGH) on tumor-tissue DNA, and whole-exome sequencing (WES) on exosomes DNA derived from plasma collected at the onset and at the tumor progression, pointed out relevant genetic changes that can explain this clinical worsening. The combination of a-CGH and WES data allowed for the identification iof somatic copy number aberrations and single-nucleotide variants in genes known to be responsible for aggressive NB. KLRB1, MAPK3 and FANCA genes, which were lost at the time of progression, were studied for their possible role in this event by analyzing in silico the impact of their expression on the outcome of 786 NB patients.     

Occurrence of non-lactic acid bacteria populations involved in protein hydrolysis of cold-stored high moisture Mozzarella cheese

The aim of this study was to analyse non-lactic acid bacteria populations (NLABPs) and evaluate their role in proteolysis of cold-stored high moisture (HM) Mozzarella cheese. NLABPs reached values close to 8 log cfu mL⁻¹ after seven days of cold storage. Sequencing of 16 rDNA and rpoB genes and molecular biotyping allowed to identify 66 bacterial strains belonging to 25 species from 15 genera, mainly represented by Pseudomonas, Acinetobacter, and Rahnella. Fifteen strains showed proteolytic activity values higher than 1000.00 μg Gly mL⁻¹ after 24 h of growth in skimmed milk. Moreover, as shown by Urea-PAGE, 11 proteolytic strains caused partial or total disappearance of at least one of the caseins. Their proteolytic behaviour was assessed even when they grew inside the governing liquid together with HM Mozzarella cheese at 4 °C for 12 days. This is the first report that throws light on the complexity of NLABPs in HM Mozzarella cheese, demonstrating that some strains caused the partial hydrolysis of α, β, and γ caseins on its outer surface where a concomitant wrinkling and successive exfoliation became visible without significant changes in texture characteristics.     

A Matrix-Based Approach to the Image Moment Problem

An image can be seen as an element of a vector space and hence it can be expressed in as a linear combination of the elements of any non necessarily orthogonal basis of this space. After giving a matrix formulation of this well-known fact, this paper presents a reconstruction method of an image from its moments that sheds new light on this inverse problem. Two main contributions are presented: (a) the results using the standard approach based on the least squares approximation of the result using orthogonal polynomials can also be obtained using matrix pseudoinverses, which implies higher control on the numerical stability of the problem; and (b) it is possible to use basis functions in the reconstruction different from orthogonal polynomials, such as Fourier or Haar basis, allowing to introduce constraints relative to the bandwidth or the spatial resolution on the image to be reconstructed. Judit Martònez received the B.Sc. degree in 1993 and the PhD degree (with honors) in 1998, both in telecommunications engineering from the Technical University of Catalonia. She developed her research at the Institut de Robútica i Informütica Industrial of the Spanish High Council for Scientific Research. In 1999 she joined the Computer Vision Center, a R&D center founded by the Autonomous University of Barcelona and the Autonomous Government of Catalonia. She has been principal researcher of several industrial and research projects related to computer vision technologies. Her research interests include industrial applications of machine vision, efficient algorithms for low-level image processing, multiresolution mathematical models, statistical clustering, pattern classification and inverse problems. Josep M. Porta received the Engineer Degree in Computer Science in 1994 and the Ph.D. in Artificial Intelligence in 2001, both from the Technical University of Catalonia (UPC). After that, he joined the IAS group of the University of Amsterdam and currently, he holds a post-doc position at the Institut de Robútica i Informütica Industrial (CSIC-UPC) in Barcelona. He carried research in legged robots, machine learning, vision-based methods for autonomous robot localization, and computational kinematics. Federico Thomas is Research Professor at the Spanish Scientific Research Council (CSIC) and director of the Institut de Robútica i Informütica Industrial (CSIC-UPC), Barcelona, Spain. He received the telecommunications engineering degree in 1984, and the Ph.D. degree (with honors) in computer science in 1988, both from the Technical University of Catalonia (UPC). In 1991, he won a NATO postdoctoral scholarship at the University of Massachusetts with the late Prof. Robin Popplestone. In 1999, he was visiting professor, sponsored by the Autonomous Government of Catalonia, at the Oxford University Computing Laboratory with Prof. Stephen Cameron. He has been project leader of several national projects financed by the Spanish Committee for Science and Technology (CICYT), and by local companies such as ENHER, a power generation company now part of ENDESA. His current research interests are in Geometry and Kinematics with applications to Robotics, Computer Graphics and Computer Vision. Prof. Thomas is an Associate Editor of the IEEE Transactions on Robotics.     

Probabilistic methods for eigenvalue estimates

Some probabilistic techniques are discussed regarding their use in estimating the principal eigenvalue of an elliptic operator. Such estimates are useful when studying models for biochemical reactions governed by lateral diffusion.In this paper we summarize recent results on some mathematical techniques that were developed to study certain biological models.     

Phase retrieval in digital speckle pattern interferometry by use of a smoothed space-frequency distribution

We evaluate the use of a smoothed space-frequency distribution (SSFD) to retrieve optical phase maps in digital speckle pattern interferometry (DSPI). The performance of this method is tested by use of computer-simulated DSPI fringes. Phase gradients are found along a pixel path from a single DSPI image, and the phase map is finally determined by integration. This technique does not need the application of a phase unwrapping algorithm or the introduction of carrier fringes in the interferometer. It is shown that a Wigner-Ville distribution with a smoothing Gaussian kernel gives more-accurate results than methods based on the continuous wavelet transform. We also discuss the influence of filtering on smoothing of the DSPI fringes and some additional limitations that emerge when this technique is applied. The performance of the SSFD method for processing experimental data is then illustrated.     

Control of fuel cell power output

A simplified dynamic model for fuel cells is developed, based on the concept of instantaneous characteristic, which is the set of values of current and voltage that a fuel cell can reach instantaneously. This is used to derive a theorem that indicates the conditions under which the power output of fuel cells can, in theory, be perfectly controlled. A fuel cell connected to a DC/DC converter is simulated numerically, with a control system based on switching rules in order to control the converter’s output voltage. The resulting transients settle in about 5–10 ms. The converter is then used as an actuator in a cascade control loop to control the torque output of a DC electric motor with a PI controller in the external loop. In this loop, the resulting in transients settle in less than 0.2 s.     

COMPLIANCE VERIFICATION OF AGENT INTERACTION: A LOGIC-BASED SOFTWARE TOOL

In open societies of agents, where agents are autonomous and heterogeneous, it is not realistic to assume that agents will always act so as to comply with interaction protocols. Thus, the need arises for a formalism to specify constraints on agent interaction, and for a tool able to observe and check for agent compliance with interaction protocols. In this paper we present a JAVA-PROLOG software component built on logic programming technology, which can be used to verify compliance of agent interaction to protocols, and that has been integrated with the PROSOCS platform.