A scheme for efficient quantum computation wtih linear optics

Quantum computers promise to increase greatly the efficiency of solving problems such as factoring large integers, combinatorial optimization and quantum physics simulation. One of the greatest challenges now is to implement the basic quantum-computational elements in a physical system and to demonstrate that they can be reliably and scalably controlled. One of the earliest proposals for quantum computation is based on implementing a quantum bit with two optical modes containing one photon. The proposal is appealing because of the ease with which photon interference can be observed. Until now, it suffered from the requirement for non-linear couplings between optical modes containing few photons. Here we show that efficient quantum computation is possible using only beam splitters, phase shifters, single photon sources and photo-detectors. Our methods exploit feedback from photo-detectors and are robust against errors from photon loss and detector inefficiency. The basic elements are accessible to experimental investigation with current technology.

Task Complexity and Variation in L2 Learner’s Oral Discourse

There are many factors which affect the L2 learner’s performance at the levels of phonology, morphology and syntax. Consequently when L2 learners attempt to communicate in the target language, their language production will show systematic variability across the above mentioned linguistic domains. This variation can be attributed to some factors such as interlocutors, topic familiarity, prior knowledge, task condition, planning time and tasks types. This paper reports the results of an on going research investigating the issue of variability attributed to the task type. It is hypothesized that the particular type of task learners are required to perform will result in variation in their performance. Results of the statistical analyses of this study investigating the issue of variation in the performance of twenty L2 learners at the English department of Tabriz University provided evidence in support of the hypothesis that performance of L2 learners show systematic variability attributed to task.

Special issue on advances in data mining and its applications

Data mining is the process to identify valid, implicit, previously unknown, potentially useful and understandable information from large databases. It is an important step in the process of knowledge discovery in databases, (Olaru & Wehenkel, 1999). In a data mining process, input data can be structured, seme-structured, or unstructured. Data can be in text, categorical or numerical values. One of the important characteristics of data mining is its ability to deal data with large volume, distributed, time variant, noisy, and high dimensionality. A large number of data mining algorithms have been developed for different applications. For example, association rules mining can be useful for market basket problems, clustering algorithms can be used to discover trends in unsupervised learning problems, classification algorithms can be applied in decision-making problems, and sequential and time series mining algorithms can be used in predicting events, fault detection, and other supervised learning problems (Vapnik, 1999). Classification is among the most important tasks in the data mining, particularly for data mining applications into engineering fields. Together with regression, classification is mainly for predictive modelling. So far, there have been a number of classification algorithms in practice. According to (Sebastiani, 2002), the main classification algorithms can be categorized as: decision tree and rule based approach such as C4.5 (Quinlan, 1996); probability methods such as Bayesian classifier (Lewis, 1998); on-line methods such as Winnow (Littlestone, 1988) and CVFDT (Hulten 2001), neural networks methods (Rumelhart, Hinton & Wiliams, 1986); example-based methods such as k-nearest neighbors (Duda & Hart, 1973), and SVM (Cortes & Vapnik, 1995). Other important techniques for classification tasks include Associative Classification (Liu et al, 1998) and Ensemble Classification (Tumer, 1996).

The Learning Tourism Destination: The potential of a learning organisation approach for improving the sustainability of tourism destinations

Globalisation, increasing complexity, and the need to address triple-bottom line sustainability has seen the proliferation of Learning Organisations (LO) who, by definition, have the capacity to anticipate environmental changes and economic opportunities and adapt accordingly. Such organisations use system dynamics modelling (SDM) for both strategic planning and the promotion of organisational learning. Although SDM has been applied in the context of tourism destination management for predictive reasons, the current literature does not analyse or recognise how this could be used as a foundation for an LO. This study introduces the concept of the Learning Tourism Destinations (LTD) and discusses, on the basis of a review of 6 case studies, the potential of SDM as a tool for the implementation and enhancement of collective learning processes. The results reveal that SDM is capable of promoting communication between stakeholders and stimulating organisational learning. It is suggested that the LTD approach be further utilised and explored.

Review of Interpersonal adaptation: Dyadic interaction patterns By Judee K. Burgoon, Lesa

In this ambitious book, Burgoon, Stern, and Dillman present the most comprehensive coverage of the literature on interpersonal adaptation that I have seen in recent years. Their mission is to make a critical examination of this whole area from both theoretical and methodological perspectives, and then to present their own synthetic theory (interpersonal adaptation theory, IAT) and research agenda. Such a mission produces very high expectations in readers, and inevitably some readers will feel that the authors do not achieve all of it. Personally, I was impressed by how much they do achieve, and I was intrigued by the questions they did not answer. One can ask no more than this of any single book.

Molecular cocrystals of carboxylic acids. XXVII - An investigation into the use of triphenylphosphine oxide cocrystals for non-linear optics: the crystal structure of the adduct of triphenylphosphine oxide with N-methylpyrrole-2-carboxylic acid

Four adducts of triphenylphosphine oxide with aromatic carboxylic acids have been synthesized and tested for second-order non-linear optical properties. These were with N-methylpyrrole-2-carboxylic acid (I), indole-2-carboxylic acid (2), 3-dimethylaminobenzoic acid (3), and thiophen-2-carboxylic acid (4). Compound (1) produced clear, colourless crystals (space group P2(1)2(1)2(1) With a 9.892(1), b 14.033(1), c 15.305(1) Angstrom, Z 4) which allowed the structure to be determined by X-ray diffraction.

Disordered eating, weight dissatisfaction and dieting in relation to unwanted childhood sexual experiences in a community sample

A study was conducted to examine the relationships among eating pathology, weight dissatisfaction and dieting, and unwanted sexual experiences in childhood. An unselected community sample of 201 young and 268 middle-aged women were administered questionnaires assessing eating behaviors and attitudes, and past and current sexual abuse. Results showed differential relationships among these factors for the two age cohorts: for young women, past sexual abuse predicted weight dissatisfaction, but not dieting or disordered eating behaviors, whereas for middle-aged women, past abuse was predictive of disordered eating, but not dieting or weight dissatisfaction. Current physical or sexual abuse was also found to be predictive of disordered eating for the young women. These findings underscore the complexity of the relationships among unwanted sexual experiences and eating and weight pathology, and suggest that the timing of sexual abuse, and the age of the woman, are important mediating factors. (C) 1998 Elsevier Science Inc.

Type specific and genotype cross reactive B epitopes of the L1 protein of HPV16 defined by a panel of monoclonal antibodies

Mouse monoclonal antibodies (mAbs) were raised against the major capsid protein, L1, of human papillomavirus type 16 (HPV16), produced in Escherichia coil with the expression plasmid pTrcL1. Epitope specificity could be assigned to 11 of these 12 antibodies using a series of linear peptides and fusion proteins from HPV16. One mAb (MC53) recognized a novel linear epitope that appears to be unique to the HPV16 genotype. A further 11 mAbs were characterized as recognizing novel and previously defined linear and conformational epitopes shared among more than one HPV genotype. The apparently genotype specific mAb could be useful for the development of diagnostic tests for vegetative virus infection in clinical specimens. (C) 1998 Academic Press.

Temperature and sowing date affect the linear increase of sunflower harvest index

The linearity of daily linear harvest index (HI) increase can provide a simple means to predict grain growth and yield in field crops. However, the stability of the rate of increase across genotypes and environments is uncertain. Data from three field experiments were collated to investigate the phase of linear HI increase of sunflower (Helianthus annuus L,) across environments by changing genotypes, sowing time, N level, and solar irradiation level. Linear increase in HI was similar among different genotypes, N levels, and radiation treatments (mean 0.0125 d(-1)). but significant differences occurred between sowings, The linear increase in HI was not stable at very low temperatures (down to 9 degrees C) during grain filling, due to possible limitations to biomass accumulation and translocation (mean 0.0091 d(-1)). Using the linear increase in HI to predict grain yield requires predictions of the duration from anthesis to the onset of linear HI increase (lag phase) and the cessation of linear RT increase. These studies showed that the lag phase differed, and the linear HI increase ceased when 91% of the anthesis to physiological maturity period had been completed.

Morphine has a dual concentration-dependent effect on K+-evoked substance P release from rat peripheral airways

Our previous investigations of possible lung mechanisms underlying the effectiveness of nebulized morphine for the relief of dyspnoea, have shown a high density of non-conventional opioid binding sites in rat airways with similar binding characteristics (opioid alkaloid-sensitive, opioid peptide-insensitive) to that of putative mu(3)-opioid receptors on immune cells. To investigate whether these lung opioid binding sites are functional receptors, this study was designed to determine (using superfusion) whether morphine modulates the K+-evoked release of the pro-inflammatory neuropeptide, substance P (SP), from rat peripheral airways. Importantly, K+-evoked SP release was Ca2+-dependent, consistent with vesicular release. Submicromolar concentrations of morphine (1 and 200 nM) inhibited K+-evoked SP release from rat peripheral airways in a naloxone (1 mu M) reversible manner. By contrast, 1 mu M morphine enhanced K+-evoked SP release and this effect was not reversed by 1 mu M naloxone. However, 100 mu M naloxone not only antagonized the facilitatory effect of 1 mu M morphine on K+-evoked SP release from rat peripheral airways but it inhibited release to a similar extent as 200 nM morphine. It is possible that these latter effects are mediated by non-conventional opioid receptors located on mast cells, activation of which causes naloxone-reversible histamine release that in turn augments the release of SP from sensory nerve terminals in the peripheral airways. Clearly, further studies are required to investigate this possibility. (C) 1997 Academic Press Limited.