1,384 research outputs found

    Macropolyhedral boron-containing cluster chemistry. Ligand-induced two-electron variations of intercluster bonding intimacy. Structures of nineteen-vertex[(eta(5)-C5Me5) HIrB18H19(PMe2Ph)] and the related carbene complex [(eta(5)-C5Me5)HIrB18H19{C(NHMe)(2)}]

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    Addition of PMe2Ph to fused-cluster syn-[(η5-C5Me5)IrB18H20] 1 to give [(η5-C5Me5)HIrB18H19(PMe2Ph)] 3 entails a diminution in the degree of intimacy of the intercluster fusion, rather than retention of inter-subcluster binding intimacy and a nido → arachno conversion of the character of either of the subclusters. Reaction with MeNC gives [(η5-C5Me5)HIrB18H19{C(NHMe)2}] 4 which has a similar structure, but with the ligand now being the carbene {:C(NHMe)2}, resulting from a reductive assembly reaction involving two MeNC residues and the loss of a carbon atom

    Optimal Planar Electric Dipole Antenna

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    Considerable time is often spent optimizing antennas to meet specific design metrics. Rarely, however, are the resulting antenna designs compared to rigorous physical bounds on those metrics. Here we study the performance of optimized planar meander line antennas with respect to such bounds. Results show that these simple structures meet the lower bound on radiation Q-factor (maximizing single resonance fractional bandwidth), but are far from reaching the associated physical bounds on efficiency. The relative performance of other canonical antenna designs is compared in similar ways, and the quantitative results are connected to intuitions from small antenna design, physical bounds, and matching network design.Comment: 10 pages, 15 figures, 2 tables, 4 boxe

    Retinal Vessel Segmentation Using the 2-D Morlet Wavelet and Supervised Classification

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    We present a method for automated segmentation of the vasculature in retinal images. The method produces segmentations by classifying each image pixel as vessel or non-vessel, based on the pixel's feature vector. Feature vectors are composed of the pixel's intensity and continuous two-dimensional Morlet wavelet transform responses taken at multiple scales. The Morlet wavelet is capable of tuning to specific frequencies, thus allowing noise filtering and vessel enhancement in a single step. We use a Bayesian classifier with class-conditional probability density functions (likelihoods) described as Gaussian mixtures, yielding a fast classification, while being able to model complex decision surfaces and compare its performance with the linear minimum squared error classifier. The probability distributions are estimated based on a training set of labeled pixels obtained from manual segmentations. The method's performance is evaluated on publicly available DRIVE and STARE databases of manually labeled non-mydriatic images. On the DRIVE database, it achieves an area under the receiver operating characteristic (ROC) curve of 0.9598, being slightly superior than that presented by the method of Staal et al.Comment: 9 pages, 7 figures and 1 table. Accepted for publication in IEEE Trans Med Imag; added copyright notic

    Epidemiological and clinical features of travel-associated cryptosporidiosis

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    ABSTRACTData concerning the clinical and epidemiological features of travel-associated cryptosporidiosis are lacking. In order to investigate the impact of this disease on travellers' health, a retrospective study was conducted at the Institute of Tropical Medicine, Berlin. In total, 57 cryptosporidial infections were identified between 2000 and 2004, resulting in a prevalence of 2.9% in patients with travel-associated diarrhoea. Travel to south-central Asia, especially India, was associated with a higher prevalence of infection than was travel to other destinations. Clinically, the disease resembled giardiasis, but fever and arthralgias seemed to occur more frequently

    Modified embedded-atom method interatomic potentials for the Mg-Al alloy system

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    We developed new modified embedded-atom method (MEAM) interatomic potentials for the Mg-Al alloy system using a first-principles method based on density functional theory (DFT). The materials parameters, such as the cohesive energy, equilibrium atomic volume, and bulk modulus, were used to determine the MEAM parameters. Face-centered cubic, hexagonal close packed, and cubic rock salt structures were used as the reference structures for Al, Mg, and MgAl, respectively. The applicability of the new MEAM potentials to atomistic simulations for investigating Mg-Al alloys was demonstrated by performing simulations on Mg and Al atoms in a variety of geometries. The new MEAM potentials were used to calculate the adsorption energies of Al and Mg atoms on Al (111) and Mg (0001) surfaces. The formation energies and geometries of various point defects, such as vacancies, interstitial defects and substitutional defects, were also calculated. We found that the new MEAM potentials give a better overall agreement with DFT calculations and experiments when compared against the previously published MEAM potentials.Comment: Fixed a referenc

    Virtual Affinity Fingerprints for Target Fishing: A New Application of Drug Profile Matching

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    We recently introduced Drug Profile Matching (DPM), a novel virtual affinity fingerprinting bioactivity prediction method. DPM is based on the docking profiles of ca. 1200 FDA-approved small-molecule drugs against a set of nontarget proteins and creates bioactivity predictions based on this pattern. The effectiveness of this approach was previously demonstrated for therapeutic effect prediction of drug molecules. In the current work, we investigated the applicability of DPM for target fishing, i.e. for the prediction of biological targets for compounds. Predictions were made for 77 targets, and their accuracy was measured by Receiver Operating Characteristic (ROC) analysis. Robustness was tested by a rigorous 10-fold cross-validation procedure. This procedure identified targets (N = 45) with high reliability based on DPM performance. These 45 categories were used in a subsequent study which aimed at predicting the off-target profiles of currently approved FDA drugs. In this data set, 79% of the known drug-target interactions were correctly predicted by DPM, and additionally 1074 new drug-target interactions were suggested. We focused our further investigation on the suggested interactions of antipsychotic molecules and confirmed several interactions by a review of the literature
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