Impairment of synaptic vesicle clustering and of synaptic transmission, and increased seizure propensity, in synapsin I-deficient mice.

Synapsin I has been proposed to be involved in the modulation of neurotransmitter release by controlling the availability of synaptic vesicles for exocytosis. To further understand the role of synapsin I in the function of adult nerve terminals, we studied synapsin I-deficient mice generated by homologous recombination. The organization of synaptic vesicles at presynaptic terminals of synapsin I-deficient mice was markedly altered: densely packed vesicles were only present in a narrow rim at active zones, whereas the majority of vesicles were dispersed throughout the terminal area. This was in contrast to the organized vesicle clusters present in terminals of wild-type animals. Release of glutamate from nerve endings, induced by K+,4-aminopyridine, or a Ca2+ ionophore, was markedly decreased in synapsin I mutant mice. The recovery of synaptic transmission after depletion of neurotransmitter by high-frequency stimulation was greatly delayed. Finally, synapsin I-deficient mice exhibited a strikingly increased response to electrical stimulation, as measured by electrographic and behavioral seizures. These results provide strong support for the hypothesis that synapsin I plays a key role in the regulation of nerve terminal function in mature synapses.

Auxins induce clustering of the auxin-binding protein at the surface of maize coleoptile protoplasts.

The predominant localization of the major auxin-binding protein (ABP1) of maize is within the lumen of the endoplasmic reticulum. Nevertheless, all the electrophysiological evidence supporting a receptor role for ABP1 implies that a functionally important fraction of the protein must reside at the outer face of the plasma membrane. Using methods of protoplast preparation designed to minimize proteolysis, we report the detection of ABP at the surface of maize coleoptile protoplasts by the technique of silver-enhanced immunogold viewed by epipolarization microscopy. We also show that ABP clusters following auxin treatment and that this response is temperature-dependent and auxin-specific.

Large-scale clustering measurements with photometric redshifts: comparing the dark matter haloes of X-ray AGN, star-forming and passive galaxies at z ≈ 1

We combine multi-wavelength data in the AEGIS-XD and C-COSMOS surveys to measure the typical dark matter halo mass of X-ray selected active galactic nuclei (AGN) [L_X(2–10 keV) > 10^42 erg s^− 1] in comparison with far-infrared selected star-forming galaxies detected in the Herschel/PEP survey (PACS Evolutionary Probe; L_IR > 10^11 L_⊙) and quiescent systems at z ≈ 1. We develop a novel method to measure the clustering of extragalactic populations that uses photometric redshift probability distribution functions in addition to any spectroscopy. This is advantageous in that all sources in the sample are used in the clustering analysis, not just the subset with secure spectroscopy. The method works best for large samples. The loss of accuracy because of the lack of spectroscopy is balanced by increasing the number of sources used to measure the clustering. We find that X-ray AGN, far-infrared selected star-forming galaxies and passive systems in the redshift interval 0.6 < z < 1.4 are found in haloes of similar mass, log M_DMH/(M_⊙ h^−1) ≈ 13.0. We argue that this is because the galaxies in all three samples (AGN, star-forming, passive) have similar stellar mass distributions, approximated by the J-band luminosity. Therefore, all galaxies that can potentially host X-ray AGN, because they have stellar masses in the appropriate range, live in dark matter haloes of log M_DMH/(M_⊙ h^−1) ≈ 13.0 independent of their star formation rates. This suggests that the stellar mass of X-ray AGN hosts is driving the observed clustering properties of this population. We also speculate that trends between AGN properties (e.g. luminosity, level of obscuration) and large-scale environment may be related to differences in the stellar mass of the host galaxies.

Central compact objects and the hidden magnetic field scenario

Central compact objects (CCOs) are X-ray sources lying close to the centre of supernova remnants, with inferred values of the surface magnetic fields significantly lower (≲1011 G) than those of standard pulsars. In this paper, we revise the hidden magnetic field scenario, presenting the first 2D simulations of the submergence and re-emergence of the magnetic field in the crust of a neutron star. A post-supernova accretion stage of about 10−4–10−3 M⊙ over a vast region of the surface is required to bury the magnetic field into the inner crust. When accretion stops, the field re-emerges on a typical time-scale of 1–100 kyr, depending on the submergence conditions. After this stage, the surface magnetic field is restored close to its birth values. A possible observable consequence of the hidden magnetic field is the anisotropy of the surface temperature distribution, in agreement with observations of several of these sources. We conclude that the hidden magnetic field model is viable as an alternative to the antimagnetar scenario, and it could provide the missing link between CCOs and the other classes of isolated neutron stars.

A study of a soft computing based method for 3D scenario reconstruction

Several recent works deal with 3D data in mobile robotic problems, e.g., mapping. Data comes from any kind of sensor (time of flight, Kinect or 3D lasers) that provide a huge amount of unorganized 3D data. In this paper we detail an efficient approach to build complete 3D models using a soft computing method, the Growing Neural Gas (GNG). As neural models deal easily with noise, imprecision, uncertainty or partial data, GNG provides better results than other approaches. The GNG obtained is then applied to a sequence. We present a comprehensive study on GNG parameters to ensure the best result at the lowest time cost. From this GNG structure, we propose to calculate planar patches and thus obtaining a fast method to compute the movement performed by a mobile robot by means of a 3D models registration algorithm. Final results of 3D mapping are also shown.

Estadística Aplicada a los Recursos Marinos. Clustering. Análisis de segmentación

Introducción al análisis con Clustering

An adaptive algorithm for clustering cumulative probability distribution functions using the Kolmogorov–Smirnov two-sample test

This paper proposes an adaptive algorithm for clustering cumulative probability distribution functions (c.p.d.f.) of a continuous random variable, observed in different populations, into the minimum homogeneous clusters, making no parametric assumptions about the c.p.d.f.’s. The distance function for clustering c.p.d.f.’s that is proposed is based on the Kolmogorov–Smirnov two sample statistic. This test is able to detect differences in position, dispersion or shape of the c.p.d.f.’s. In our context, this statistic allows us to cluster the recorded data with a homogeneity criterion based on the whole distribution of each data set, and to decide whether it is necessary to add more clusters or not. In this sense, the proposed algorithm is adaptive as it automatically increases the number of clusters only as necessary; therefore, there is no need to fix in advance the number of clusters. The output of the algorithm are the common c.p.d.f. of all observed data in the cluster (the centroid) and, for each cluster, the Kolmogorov–Smirnov statistic between the centroid and the most distant c.p.d.f. The proposed algorithm has been used for a large data set of solar global irradiation spectra distributions. The results obtained enable to reduce all the information of more than 270,000 c.p.d.f.’s in only 6 different clusters that correspond to 6 different c.p.d.f.’s.

Competing Lipid-Protein and Protein-Protein Interactions Determine Clustering and Gating Patterns in the Potassium Channel from Streptomyces lividans (KcsA)

There is increasing evidence to support the notion that membrane proteins, instead of being isolated components floating in a fluid lipid environment, can be assembled into supramolecular complexes that take part in a variety of cooperative cellular functions. The interplay between lipid-protein and protein-protein interactions is expected to be a determinant factor in the assembly and dynamics of such membrane complexes. Here we report on a role of anionic phospholipids in determining the extent of clustering of KcsA, a model potassium channel. Assembly/disassembly of channel clusters occurs, at least partly, as a consequence of competing lipid-protein and protein-protein interactions at nonannular lipid binding sites on the channel surface and brings about profound changes in the gating properties of the channel. Our results suggest that these latter effects of anionic lipids are mediated via the Trp67–Glu71–Asp80 inactivation triad within the channel structure and its bearing on the selectivity filter.

Human Behaviour Recognition based on Trajectory Analysis using Neural Networks

Automated human behaviour analysis has been, and still remains, a challenging problem. It has been dealt from different points of views: from primitive actions to human interaction recognition. This paper is focused on trajectory analysis which allows a simple high level understanding of complex human behaviour. It is proposed a novel representation method of trajectory data, called Activity Description Vector (ADV) based on the number of occurrences of a person is in a specific point of the scenario and the local movements that perform in it. The ADV is calculated for each cell of the scenario in which it is spatially sampled obtaining a cue for different clustering methods. The ADV representation has been tested as the input of several classic classifiers and compared to other approaches using CAVIAR dataset sequences obtaining great accuracy in the recognition of the behaviour of people in a Shopping Centre.

Quantitative Reference Scenario for the MEDPRO Project. MEDPRO Report No. 6, May 2013

In general equilibrium models the reference scenario is important, as the evaluation of the alternative policies modelled is based on their deviation from the reference scenario. The reference scenario relates to the development of an economic outlook for each region and sector of the model. This means that assumptions are made about the main drivers of growth, e.g. population growth and technical progress. This report provides the main assumptions used for the development of the reference scenario in the MEDPRO project. The report also provides a brief country and sectoral overview for each of the southern and eastern Mediterranean countries covered by the MEDPRO project.

Effects of ocean acidification on growth and physiology of Ulva lactuca (Chlorophyta) in a rockpool-scenario, link to supplementary data

Rising atmospheric CO2-concentrations will have severe consequences for a variety of biological processes. We investigated the responses of the green alga Ulva lactuca (Linnaeus) to rising CO2-concentrations in a rockpool scenario. U. lactuca was cultured under aeraton with air containing either preindustrial pCO2 (280µatm) or for the end of the 21st century predicted (700µatm) pCO2 for 31 days. We addressed the following question: Will elevated CO2-concentrations affect photosynthesis (net photosynthesis, rETR(max), Fv/Fm, pigment composition) and growth of U. lactuca in rockpools with limited water exchange? Two phases of the experiment were distinguished: In the initial phase (day 1-4) the Seawater Carbonate System (SWCS) of the culture medium could be adjusted to the selected atmospheric pCO2 condition by continuous aeration with target pCO2 values. In the second phase (day 4-31) the SWCS was largely determined by the metabolism of the growing U. lactuca biomass. In the initial phase, Fv/Fm and rETR(max) were only slightly elevated at high CO2-concentrations whereas growth was significantly enhanced. After 31 days the Chl a content of the thalli was significantly lower under future conditions and the photosynthesis of thalli grown under preindustrial conditions was not dependent on external carbonic anhydrase. Biomass increased significantly at high CO2-concentrations. At low CO2-concentrations most adult thalli disintegrated between day 14 and 21, whereas at high CO2-concentrations most thalli remained integer until day 31. Thallus disintegration at low CO2-concentrations was mirrored in a drastic decline in seawater DIC and HCO3-. Accordingly, the SWCS differed significantly between the treatments. Our results indicated a slight enhancement of photosynthetic performance and significantly elevated growth of U. lactuca at future CO2-concentrations. The accelerated thallus disintegration at high CO2-concentrations under conditions of limited water exchange indicates additional CO2 effects on the life cycle of U. lactuca when living in rockpools.

Knowledge acquisition through conceptual clustering : a theoretical framework and an algorithm for partitioning data into conjunctive concepts /

"May 1980."