Nonorthogonal Tight-Binding Molecular Dynamics for Si(1-x)Ge(x) Alloys

We present a theoretical study of Si(1-x)Ge(x) alloys based on tight-binding molecular dynamics (TBMD) calculations. First, we introduce a new set of nonorthogonal tight-binding parameters for silicon and germanium based on the previous work by Menon and Subbaswamy [Phys. Rev. B 55, 9231 (1997); J. Phys: Condens. Matter 10, 10991 (1998)]. We then apply the method to structural analyses of Si(1-x)Ge(x) alloys. The equilibrium volume and atomic structure for a given x are obtained by the TBMD method. We also calculate the bulk modulus B, elastic constants C(11), C(12) and C(44) as a function of x. The results show that the moduli vary monotonically, but nonlinearly, between the values of Si crystal and Ge crystal. The validity of the results is also discussed

Development of a multipurpose hand controller for JEMRMS

A prototype multipurpose hand controller for the JEMRMS (Japanese Experiment Module Remote Manipulator System) was developed. The hand controller (H/C) is an orthogonal type, with 6 degrees of freedom (DOF) and small size. The orthogonal type H/C is very simple for coordinate transformations and can easily control any type of manipulators. In fact, the JEMRMS is planned to have two manipulators controlled by a common H/C at this stage. The H/C was able to be used as a rate control joystick and a force reflection master arm, using an experimental 6 DOF manipulator. Good maneuverability was confirmed in the verification test. The orthogonal type H/C is suitable for use as a common H/C for the two manipulators of the JEMRMS

Scale-up protein separation on stainless steel wide bore toroidal columns in the type-J counter-current chromatography

Manufacturing high-value added biotech biopharmaceutical products (e.g. therapeutic proteins) requires quick-to-develop, GMP-compliant, easy-to-scale and cost effective preparatory chromatography technologies. In this work, we describe the construction and testing of a set of 5-mm inner diameter stainless steel toroidal columns for use on commercially available preparatory scale synchronous J-type counter-current chromatography (CCC) machinery. We used a 20.2 m long column with an aqueous two-phase system containing 14% (w/w) PEG1000 and 14% (w/w) potassium phosphate at pH 7, and tested a sample loading of 5% column volume and a mobile phase flow rate of 20 ml/min. We then satisfactorily demonstrated the potential for a weekly protein separation and preparation throughput of ca. 11 g based on a normal weekly routine for separating a pair of model proteins by making five stacked injections on a single portion of stationary phase with no stripping. Compared to our previous 1.6 mm bore PTFE toroidal column, the present columns enlarged the nominal column processing throughput by nearly 10. For an ideal model protein injection modality, we observed a scaling up factor of at least 21. The 2 scales of protein separation and purification steps were realized on the same commercial CCC device.The BBSRC Grant number BB/FOF/206. YHG and YZ also acknowledge financial support by National Basic Research Program (973 Program 2013CB733600).Ms Yan Zhao (School of Mechanical and Power Engineering) has been grateful to a Training Program of Innovation and Entrepreneurship for Undergraduates Grant number X13219 by East China University of Science and Technology. Contribution and/or encouragement to this work from D. Fisher, T. Bunce, Ying-Dong Liu, Zheng-Tao Zhang, Li-Li Ba

Effects of valerian extract on the sleep-wake cycle in sleep-disturbed rats.

The present study was performed to investigate the effects of valerian extract on the sleep-wake cycle using sleep-disturbed model rats. A significant shortening in sleep latency was observed with valerian extract at doses of 1000 and 3000 mg/kg. On the other hand, valerian extract had no significant effects on total times of wakefulness, non-rapid eye movement (non-REM) sleep, or REM sleep, even at a dose of 3000 mg/kg. Valerian extract at doses of 1000 and 3000 mg/kg showed a significant increase in the delta activity during non-REM sleep. In conclusion, valerian extract may be useful as an herbal medicine having not only sleep-inducing effects but also sleep quality-enhancement effects.</p

Effects of Imipramine and Lithium on the Suppression of Cell Proliferation in the Dentate Gyrus of the Hippocampus in Adrenocorticotropic Hormone-treated Rats

We examined the influence of chronic adrenocorticotropic hormone (ACTH) treatment on the number of Ki-67-positive cells in the dentate gyrus of the hippocampus in rats. ACTH treatment for 14 days decreased the number of such cells. The administration of imipramine or lithium alone for 14 days had no effect in saline-treated rats. The effect of ACTH was blocked by the administration of imipramine. Furthermore, the coadministration of imipramine and lithium for 14 days significantly increased the number of Ki-67-positive cells in both the saline and ACTH-treated rats. The coadministration of imipramine and lithium normalized the cell proliferation in the dentate gyrus of the hippocampus in rats treated with ACTH

Deep Collaborative Filtering Approaches for Context-Aware Venue Recommendation

In recent years, vast amounts of user-generated data have being created on Location-Based Social Networks (LBSNs) such as Yelp and Foursquare. Making effective personalised venue suggestions to users based on their preferences and surrounding context is a challenging task. Context-Aware Venue Recommendation (CAVR) is an emerging topic that has gained a lot of attention from researchers, where context can be the user's current location for example. Matrix Factorisation (MF) is one of the most popular collaborative filtering-based techniques, which can be used to predict a user's rating on venues by exploiting explicit feedback (e.g. users' ratings on venues). However, such explicit feedback may not be available, particularly for inactive users, while implicit feedback is easier to obtain from LBSNs as it does not require the users to explicitly express their satisfaction with the venues. In addition, the MF-based approaches usually suffer from the sparsity problem where users/venues have very few rating, hindering the prediction accuracy. Although previous works on user-venue rating prediction have proposed to alleviate the sparsity problem by leveraging user-generated data such as social information from LBSNs, research that investigates the usefulness of Deep Neural Network algorithms (DNN) in alleviating the sparsity problem for CAVR remains untouched or partially studied