A model for generating synthetic dendrites of cortical neurons

One of the main challenges in neuroscience is to define the detailed structural design of the nervous system. This challenge is one of the first steps towards understanding how neural circuits contribute to the functional organization of the nervous system. In the cerebral cortex pyramidal neurons are key elements in brain function as they represent the most abundant cortical neuronal type and the main source of cortical excitatory synapses. Therefore, many researchers are interested in the analysis of the microanatomy of pyramidal cells since it constitutes an excellent tool for better understanding cortical processing of information. Computational models of neuronal networks based on real cortical circuits have become useful tools for studying certain aspects of the functional organization of the neocortex. Neuronal morphologies (morphological models) represent key features in these functional models. For these purposes, synthetic or virtual dendritic trees can be generated through a morphological model of a given neuronal type based on real morphometric parameters obtained from intracellularly-filled single neurons. This paper presents a new method to construct virtual dendrites by means of sampling a branching model that represents the dendritic morphology. This method has been contrasted using complete basal dendrites from 374 layer II/III pyramidal neurons of the mouse neocortex

Conversion of natural forest results in a significant degradation of soil hydraulic properties in the highlands of Kenya

Land use change, especially conversion of native forests can have large impacts on water resources. Large scale conversion of native forests to agricultural land has occurred in the last few decades in the Mau Forest region. To quantify and understand landscape hydrologic responses, this study aimed at evaluating the effects of land use on soil infiltration, saturated hydraulic conductivity, bulk density, sorptivity, and soil moisture retention. A total of 136 plots representing five different land uses (native forest: n = 39, forest plantations: n = 14, tea plantations: n = 24, croplands: n = 23 and pasture: n = 36) were sampled in three catchments with similar parental material in the Mau Forest region, Western Kenya. Native forest topsoils (0–5 cm) had a bulk density of 1.0 ± 0.2 g cm−3 which was similar to values found for topsoils of forest plantations (1.1 ± 0.2 g cm−3), but significantly lower than topsoils from croplands (1.4 ± 0.2 g cm−3), tea plantation (1.3 ± 0.3 g cm−3) and pastures (1.4 ± 0.2 g cm−3). Similarly, soil infiltration rates were higher in native forest (76.1 ± 50 cm h−1) and in forest plantation (60.2 ± 47.9 cm h−1) than in croplands (40.5 ± 21.5 cm h‐1), tea plantations (43.3 ± 29.2 cm h−1) and pastures (13.8 ± 14.6 cm h−1). Native forest had the highest topsoil organic carbon contents (8.11 ± 2.42%) and field capacity (0.62 ±0.12 cm3 cm−3), while the highest permanent wilting point was recorded for pasture soils (mean of 0.41 ± 0.06 cm cm−3). The highest plant available water capacity was recorded for soils in native forest (mean of 0.27 ± 0.14 cm cm−3). Our study indicates that land use changes result in a significant degradation of soil hydraulic properties, which has likely resulted in changes of the regional water balance. Given the magnitude in which managed land use types have changed infiltration rates in our study area, we conclude that changes in land use types occurring in our study region in the last decades have already affected the hydrological regime of the landscapes and the compositions of flow components. The reduction in infiltration and hydraulic conductivity could result in increased surface run-off, erosion and frequency of flooding events

On the role of the upper part of words in lexical access : evidence with masked priming

More than 100 years ago, Huey (1908) indicated that the upper part of words was more relevant for perception than the lower part. Here we examined whether mutilated words, in their upper/lower portions (e.g., , , , ), can automatically access their word units in the mental lexicon. To that end, we conducted four masked repetition priming experiments with the lexical decision task. Results showed that mutilated primes produced a sizeable masked repetition priming effect. Furthermore, the magnitude of the masked repetition priming effect was greater when the upper part of the primes was preserved than when the lower portion was preserved –this was the case not only when the mutilated words were presented in lowercase but also when the mutilated words were presented in uppercase. Taken together, these findings suggest that the front-end of computational models of visual-word recognition should be modified to provide a more realistic account at the level of letter features.The research reported in this article has been partially supported by Grant PSI2008-04069/PSIC and CONSOLIDER-INGENIO2010 CSD2008-00048 from the Spanish Ministry of Science and Innovation and by Grant PTDC/PSI-PCO/104671/2008 from the Portuguese Foundation for Science and Technology

Neural networks in petroleum geology as interpretation tools

Abstract Three examples of the use of neural networks in analyses of geologic data from hydrocarbon reservoirs are presented. All networks are trained with data originating from clastic reservoirs of Neogene age located in the Croatian part of the Pannonian Basin. Training always included similar reservoir variables, i.e. electric logs (resistivity, spontaneous potential) and lithology determined from cores or logs and described as sandstone or marl, with categorical values in intervals. Selected variables also include hydrocarbon saturation, also represented by a categorical variable, average reservoir porosity calculated from interpreted well logs, and seismic attributes. In all three neural models some of the mentioned inputs were used for analyzing data collected from three different oil fields in the Croatian part of the Pannonian Basin. It is shown that selection of geologically and physically linked variables play a key role in the process of network training, validating and processing. The aim of this study was to establish relationships between log-derived data, core data, and seismic attributes. Three case studies are described in this paper to illustrate the use of neural network prediction of sandstone-marl facies (Case Study # 1, Okoli Field), prediction of carbonate breccia porosity (Case Study # 2, Beničanci Field), and prediction of lithology and saturation (Case Study # 3, Kloštar Field). The results of these studies indicate that this method is capable of providing better understanding of some clastic Neogene reservoirs in the Croatian part of the Pannonian Basin

ARGONAUT-I: Activity of cefiderocol (s-649266), a siderophore cephalosporin, against gram-negative bacteria, including carbapenem-resistant nonfermenters and enterobacteriaceae with defined extended-spectrum β-lactamases and carbapenemases

The activity of the siderophore cephalosporin cefiderocol is targeted against carbapenem-resistant Gram-negative bacteria. In this study, the activity of cefiderocol against characterized carbapenem-resistant Acinetobacter baumannii complex, Stenotrophomonas maltophilia, Pseudomonas aeruginosa, and Enterobacteriaceae strains was determined by microdilution in iron-depleted Mueller-Hinton broth. The MIC90s against A. baumannii, S. maltophilia, and P. aeruginosa were 1, 0.25, and 0.5 mg/ liter, respectively. Against Enterobacteriaceae, the MIC90 was 1 mg/liter for the group harboring OXA-48-like, 2 mg/liter for the group harboring KPC-3, and 8 mg/liter for the group harboring TEM/SHV ESBL, NDM, and KPC-2

The PHENIX Experiment at RHIC

The physics emphases of the PHENIX collaboration and the design and current status of the PHENIX detector are discussed. The plan of the collaboration for making the most effective use of the available luminosity in the first years of RHIC operation is also presented.Comment: 5 pages, 1 figure. Further details of the PHENIX physics program available at http://www.rhic.bnl.gov/phenix

Azimuthal anisotropy of K0s and Lambda prduction at mid-rapidity from Au+Au collisions at root s = 130 GeV

We report STAR results on the azimuthal anisotropy parameter v2 for strange particles K0S, L and Lbar at midrapidity in Au+Au collisions at sNN = 130 GeV at RHIC. The value of v2 as a function of transverse momentum of the produced particles pt and collision centrality is presented for both particles up to pt 3.0 GeV/c. A strong pt dependence in v2 is observed up to 2.0 GeV/c. The v2 measurement is compared with hydrodynamic model calculations. The physics implications of the pt integrated v2 magnitude as a function of particle mass are also discussed.Comment: 6 pages, 4 figures, by the STAR collaboratio