Air motion determination by tracking humidity patterns in isentropic layers

Determining air motions by tracking humidity patterns in isentropic layers was investigated. Upper-air rawinsonde data from the NSSL network and from the AVE-II pilot experiment were used to simulate temperature and humidity profile data that will eventually be available from geosynchronous satellites. Polynomial surfaces that move with time were fitted to the mixing-ratio values of the different isentropic layers. The velocity components of the polynomial surfaces are part of the coefficients that are determined in order to give an optimum fitting of the data. In the mid-troposphere, the derived humidity motions were in good agreement with the winds measured by rawinsondes so long as there were few or no clouds and the lapse rate was relatively stable. In the lower troposphere, the humidity motions were unreliable primarily because of nonadiabatic processes and unstable lapse rates. In the upper troposphere, the humidity amounts were too low to be measured with sufficient accuracy to give reliable results. However, it appears that humidity motions could be used to provide mid-tropospheric wind data over large regions of the globe

Studies of vertical wind profiles at Cape Kennedy, Florida Final report

Vertical wind profiles spectral analysis and numerical wind forecasts at Cape Kenned

Representing and analysing molecular and cellular function in the computer

Determining the biological function of a myriad of genes, and understanding how they interact to yield a living cell, is the major challenge of the post genome-sequencing era. The complexity of biological systems is such that this cannot be envisaged without the help of powerful computer systems capable of representing and analysing the intricate networks of physical and functional interactions between the different cellular components. In this review we try to provide the reader with an appreciation of where we stand in this regard. We discuss some of the inherent problems in describing the different facets of biological function, give an overview of how information on function is currently represented in the major biological databases, and describe different systems for organising and categorising the functions of gene products. In a second part, we present a new general data model, currently under development, which describes information on molecular function and cellular processes in a rigorous manner. The model is capable of representing a large variety of biochemical processes, including metabolic pathways, regulation of gene expression and signal transduction. It also incorporates taxonomies for categorising molecular entities, interactions and processes, and it offers means of viewing the information at different levels of resolution, and dealing with incomplete knowledge. The data model has been implemented in the database on protein function and cellular processes 'aMAZE' (http://www.ebi.ac.uk/research/pfbp/), which presently covers metabolic pathways and their regulation. Several tools for querying, displaying, and performing analyses on such pathways are briefly described in order to illustrate the practical applications enabled by the model

5-(carbamoylmethylene)-oxazolidin-2-ones as a promising class of heterocycles inducing apoptosis triggered by increased ROS levels and mitochondrial dysfunction in breast and cervical cancer

Oxazolidinones are antibiotics that inhibit protein synthesis by binding the 50S ribosomal subunit. Recently, numerous worldwide researches focused on their properties and possible involvement in cancer therapy have been conducted. Here, we evaluated in vitro the antiproliferative activity of some 5-(carbamoylmethylene)-oxazolidin-2-ones on MCF-7 and HeLa cells. The tested compounds displayed a wide range of cytotoxicity on these cancer cell lines, measured by MTT assay, exhibiting no cytotoxicity on non-tumorigenic MCF-10A cells. Among the nine tested derivatives, four displayed a good anticancer potential. Remarkably, OI compound showed IC50 values of 17.66 and 31.10 µM for MCF-7 and HeLa cancer cells, respectively. Furthermore, we assessed OI effect on the cell cycle by FACS analysis, highlighting a G1 phase arrest after 72 h, supported by a low expression level of Cyclin D1 protein. Moreover, mitochondrial membrane potential was reduced after OI treatment driven by high levels of ROS. These findings demonstrate that OI treatment can inhibit MCF-7 and HeLa cell proliferation and induce apoptosis by caspase-9 activation and cytochrome c release in the cytosol. Hence, 5-(carbamoylmethylene)-oxazolidin-2-ones have a promising anticancer activity, in particular, OI derivative could represent a good candidate for in vivo further studies and potential clinical use

Application of an artificial neural network (ANN) for the identification of grapevine genotypes

Neural networks were employed to distinguish between 15 accessions of "coloured" (fruit gives intense red colour to the wine) grapevines found in some viticultural zones of Tuscany. Our results enabled us to distinguish, with considerable certainty, between 9 accessions and to denote three pairs of synonyms. The use of neural networks opens interesting prospects for ampelography; its advantages over traditional ampelographic methods are demonstrated

Exploring the selective gray matter profile of autism spectrum disorder through Bayes Factor Modeling

INTRODUCTION: Despite decades of brain MRI research demonstrating atypical neuroanatomical substrate in patients with autism spectrum disorder (ASD), it remains unclear whether and to what extent disorder-selective neuroanatomical abnormalities occur in this spectrum. This, and the fact that multiple brain disorders report a common neuroanatomical substrate, makes transference and the application of neuroimaging findings into the clinical setting an open challenge. OBJECTIVES: To investigate the selective neuroanatomical alteration profile of the ASD brain, we employed a meta-analytic, data-driven, and reverse inference-based approach (i.e.; Bayes fACtor mOdeliNg). METHODS: Eligible voxel-based morphometry data were extracted by a standardized search on BrainMap and MEDLINE databases (849 published experiments, 131 brain disorders, 22747 clinical subjects, 16572 x-y-z coordinates). Two distinct datasets were generated: the ASD dataset, composed of ASD-related data; and the non-ASD dataset, composed of all other clinical conditions data. Starting from the two unthresholded activation likelihood estimation (ALE) maps, the calculus of the Bayes fACtor mOdeliNg was performed. This allowed us to obtain posterior probability distributions on the evidence of brain alteration specificity in ASD. RESULTS: We revealed both cortical and cerebellar areas of neuroanatomical alteration selectivity in ASD. Eight clusters showed a selectivity value ≥ 90%, namely the bilateral precuneus, the right inferior occipital gyrus, left lobule IX, left Crus II, right Crus I, and the right lobule VIIIA (Fig. 1). CONCLUSIONS: The identification of this neuroanatomical pattern provides new insights into the complex pathophysiology of ASD, opening attractive prospects for future neuroimaging-based interventions. DISCLOSURE: No significant relationships

The ν\nu-cleus experiment: A gram-scale fiducial-volume cryogenic detector for the first detection of coherent neutrino-nucleus scattering

We discuss a small-scale experiment, called $\nu$-cleus, for the first detection of coherent neutrino-nucleus scattering by probing nuclear-recoil energies down to the 10 eV-regime. The detector consists of low-threshold CaWO$_4$ and Al$_2$O$_3$ calorimeter arrays with a total mass of about 10 g and several cryogenic veto detectors operated at millikelvin temperatures. Realizing a fiducial volume and a multi-element target, the detector enables active discrimination of $\gamma$, neutron and surface backgrounds. A first prototype Al$_2$O$_3$ device, operated above ground in a setup without shielding, has achieved an energy threshold of ${\sim20}$ eV and further improvements are in reach. A sensitivity study for the detection of coherent neutrino scattering at nuclear power plants shows a unique discovery potential (5$\sigma$) within a measuring time of ${\lesssim2}$ weeks. Furthermore, a site at a thermal research reactor and the use of a radioactive neutrino source are investigated. With this technology, real-time monitoring of nuclear power plants is feasible.Comment: 14 pages, 19 figure