Creating heralded hyper-entangled photons using Rydberg atoms

Entangled photon pairs are a fundamental component for testing the foundations of quantum mechanics, and for modern quantum technologies such as teleportation a...     

Primers‐4‐Yeast: a comprehensive web tool for planning primers for Saccharomyces cerevisiae

The budding yeast Saccharomyces cerevisiae is a key model organism of functional genomics, due to its ease and speed of genetic manipulations. In fact, in this yeast, the requirement for homologous sequences for recombination purposes is so small that 40 base pairs (bp) are sufficient. Hence, an enormous variety of genetic manipulations can be performed by simply planning primers with the correct homology, using a defined set of transformation plasmids. Although designing primers for yeast transformations and for the verification of their correct insertion is a common task in all yeast laboratories, primer planning is usually done manually and a tool that would enable easy, automated primer planning for the yeast research community is still lacking. Here we introduce Primers‐4‐Yeast, a web tool that allows primers to be designed in batches for S. cerevisiae gene‐targeting transformations, and for the validation of correct insertions. This novel tool enables fast, automated, accurate primer planning for large sets of genes, introduces consistency in primer planning and is therefore suggested to serve as a standard in yeast research. Primers‐4‐Yeast is available at: http://www.weizmann.ac.il/Primers‐4‐Yeast Copyright © 2013 John Wiley & Sons, Ltd.     

Similarity-Based Models of Word Cooccurrence Probabilities

In many applications of natural language processing (NLP) it is necessary to determine the likelihood of a given word combination. For example, a speech recognizer may need to determine which of the two word combinations eat a peach and eat a beach is more likely. Statistical NLP methods determine the likelihood of a word combination from its frequency in a training corpus. However, the nature of language is such that many word combinations are infrequent and do not occur in any given corpus. In this work we propose a method for estimating the probability of such previously unseen word combinations using available information on most similar words.We describe probabilistic word association models based on distributional word similarity, and apply them to two tasks, language modeling and pseudo-word disambiguation. In the language modeling task, a similarity-based model is used to improve probability estimates for unseen bigrams in a back-off language model. The similarity-based method yields a 20% perplexity improvement in the prediction of unseen bigrams and statistically significant reductions in speech-recognition error.We also compare four similarity-based estimation methods against back-off and maximum-likelihood estimation methods on a pseudo-word sense disambiguation task in which we controlled for both unigram and bigram frequency to avoid giving too much weight to easy-to-disambiguate high-frequency configurations. The similarity-based methods perform up to 40% better on this particular task.     

Preparation of monodispersed polymeric microspheres for toner particles by the shirasu porous glass membrane emulsification technique

This investigation describes the experiment directed toward the production of monodispersed toner particles by suspension polymerization. That is, relatively monodispersed poly(styrene-co-divinylbenzene) microspheres containing electrifying additives were successfully prepared by suspension polymerization employing the Shirasu Porous Glass (SPG) membrane emulsification technique. The diameter distribution of the dispersed droplets prepared with an SPG membrane module was fairly narrow, compared with that prepared with a conventional mechanical homogenizer. The effect of Sumiplast Blue S as coloring matter and E-81 as charge control agent on the triboelectric discharging properties of prepared polymeric microspheres was studied. The addition of electrifying additives strongly affected the triboelectric discharging property. It was consequently clarified that a small amount of electrifying additives added raised the electrostatic capacity of polymeric microspheres. However, a further addition reduced the triboelectric discharge of polymeric microspheres. © 1997 John Wiley & Sons, Inc. J Appl Polym Sci 64: 1107–1113, 1997     

Biochemical,Sensory, and Molecular Evaluation of Flavour and Consumer Acceptability in Australian Papaya (Carica papaya L.) Varieties

Inconsistency in flavour is one of the major challenges to the Australian papaya industry. However, objectively measurable standards of the compound profiles that provide preferable taste and aroma, together with consumer acceptability, have not been set. In this study, three red-flesh papayas (i.e., ‘RB1’, ‘RB4’, and ‘Skybury’) and two yellow-flesh papayas (i.e., ‘1B’ and ‘H13’) were presented to a trained sensory panel and a consumer panel to assess sensory profiles and liking. The papaya samples were also examined for sugar components, total soluble solids, and 14 selected volatile compounds. Additionally, the expression patterns of 10 genes related to sweetness and volatile metabolism were assessed. In general, red papaya varieties had higher sugar content and tasted sweeter than yellow varieties, while yellow varieties had higher concentrations of citrus floral aroma volatiles and higher aroma intensity. Higher concentrations of glucose, linalool oxide, and terpinolene were significantly associated with decreased consumer liking. Significant differences were observed in the expression profiles of all the genes assessed among the selected papaya varieties. Of these, cpGPT2 and cpBGLU31 were positively correlated to glucose production and were expressed significantly higher in ‘1B’ than in ‘RB1’ or ‘Skybury’. These findings will assist in the strategic selective breeding for papaya to better match consumer and, hence, market demand.     

Nanoporous Membranes Prepared from Homogeneous Lamellar Structure Developed via Biaxial Melt-Drawing of Ultra-High Molecular Weight Polyethylene/Normal Molecular Weight Polyethylene Blend Films

Biaxial melt-drawing of blend films composed of ultra-high molecular weight polyethylene and normal molecular weight polyethylene produced a unique network structure consisting of 30-nm thick homogeneous folded chain crystals. Subsequent biaxial solid-drawing produced a nanoporous structure covering a large area of the membrane surface (120 mm × 120 mm). Effects of preparation parameters, including annealing and subsequent solid-drawing, on resultant nanoporous morphology are also testified to achieve the desirable membrane. The higher gas permeability coefficients of the nanoporous membranes indicate that these nanopores are interconnected along the thickness direction. Despite such excellent porosity, the tensile strength reached 30 MPa, which is similar to that for the initial non-porous film. Consistence of membrane porousness and robustness is highly desirable for various separation applications, including filtration, water purification, dialysis, and lithium-ion batteries.