Vaccination of pregnant macaques protects newborns against mucosal simian immunodeficiency virus infection

Simian immunodeficiency virus (SIV) infection of newborn rhesus macaques is a rapid, sensitive animal model of human pediatric AIDS. Newborn macaques were readily infected by uncloned SIVmac following oral-conjunctival exposure and had persistently high viremia and rapid development of AIDS. In contrast, when 3 pregnant macaques were vaccinated against SIV, 2 of the newborns that had transplacentally acquired antiviral antibodies were protected against mucosal SIV infection at birth. These results suggest that intervention strategies such as active immunization of human immunodeficiency virus (HIV)-infected pregnant women and anti-HIV immunoglobulin administration may decrease the rate of perinatal HIV infection.     

An effective extension of the applicability of alignment-free biological sequence comparison algorithms with Hadoop

Alignment-free methods are one of the mainstays of biological sequence comparison, i.e., the assessment of how similar two biological sequences are to each other, a fundamental and routine task in computational biology and bioinformatics. They have gained popularity since, even on standard desktop machines, they are faster than methods based on alignments. However, with the advent of Next-Generation Sequencing Technologies, datasets whose size, i.e., number of sequences and their total length, is a challenge to the execution of alignment-free methods on those standard machines are quite common. Here, we propose the first paradigm for the computation of k-mer-based alignment-free methods for Apache Hadoop that extends the problem sizes that can be processed with respect to a standard sequential machine while also granting a good time performance. Technically, as opposed to a standard Hadoop implementation, its effectiveness is achieved thanks to the incremental management of a persistent hash table during the map phase, a task not contemplated by the basic Hadoop functions and that can be useful also in other contexts.     

A New Indicator for Unsteady Flow Analysis in Pressurized Irrigation Systems

Pressurized irrigation systems operating on-demand offer large flexibility to farmers for managing their irrigation practices. Within these systems, the fast moving water and the sudden closing of hydrants generates unsteady flow and may create a significant pressure variation in the pipes causing noise, vibration and, sometimes, also pipes’ collapse. The present study describes a simulation tool that was developed for the analysis of unsteady flow effects. A large number of configurations of hydrants simultaneously open has been used to reflect farmers’ behaviour. A new indicator, called Relative Pressure Variation (RPV), was proposed to evaluate the pressure variation occurring into the system in respect to the steady-state pressure. This is very relevant and can be used to identify pipes with potential risk of failure. In addition, an analysis with different gate-valves’ closing time was carried out. It demonstrated that closing time shorter than Tc?=?3 s may create dangerous pressures for the pipes.     

A Borda count for collective sentiment analysis

A method for detecting potential violations of integrity constraints of concurrent transactions running under snapshot isolation (SI) is presented. Although SI provides a high level of isolation, it does not, by itself, ensure that all integrity constraints are satisfied. In particular, while current implementations of SI enforce all internal integrity constraints, in particular key constraints, they fail to enforce constraints implemented via triggers. One remedy is to turn to serializable SI (SSI), in which full serializability is guaranteed. However, SSI comes at the price of either a substantial number of false positives, or else a high cost of constructing the full direct serialization graph. In this work, a compromise approach, called constraint-preserving snapshot isolation (CPSI), is developed, which while not guaranteeing full serializability, does guarantee that all constraints, including those enforced via triggers, are satisfied. In contrast to full SSI, CPSI requires testing concurrent transactions for conflict only pairwise, and thus involves substantially less overhead while providing a foundation for resolving conflicts via negotiation rather than via abort and restart. As is the case with SSI, CPSI can result in false positives. To address this, a hybrid approach is also developed which combines CPSI with a special version of SSI called CSSI, resulting in substantially fewer false positives than would occur using either approach alone.     

A variable-accuracy metamodel-based architecture for global MDO under uncertainty

A method for simulation-based multidisciplinary robust design optimization (MRDO) of problems affected by uncertainty is presented. The challenging aspects of simulation-based MRDO are both algorithmic and computational, since the solution of a MRDO problem typically requires simulation-based multidisciplinary analyses (MDA), uncertainty quantification (UQ) and optimization. Herein, the identification of the optimal design is achieved by a variable-accuracy, metamodel-based optimization, following a multidisciplinary feasible (MDF) architecture. The approach encompasses a variable (i) density of the design of experiments for the metamodel training, (ii) sample size for the UQ analysis by quasi Monte Carlo simulation and (iii) tolerance for the multidisciplinary consistency in MDA. The focus is on two-way steady fluid-structure interaction problem, assessed by partitioned solvers for the hydrodynamic and the structural analysis. Two analytical test problems are shown, along with the design of a racing-sailboat keel fin subject to the stochastic variation of the yaw angle. The method is validated versus a standard MDF approach to MRDO, taken as a benchmark and solved by fully coupled MDA, fully converged UQ, without metamodels. The method is evaluated in terms of optimal design performances and number of simulations required to achieve the optimal solution. For the current application, the optimal configuration shows performances very close to the benchmark solution. The convergence analysis to the optimum shows a promising reduction of the computational cost.     

On the asymptotic accuracy of reduced-order models

International Journal of Control, Automation and Systems - Popular model reduction methods can easily be adapted to retain the asymptotic response to inputs with rational transform. To this...     

Note on gossypol and its relation to color fixation in cottonseed oil

1. The crude oils studied contained from 0.00 to 0.04% gossypol.
2. Much of the gossypol added to crude cottonseed oils disappeared in one hour.
3. The disappearance of gossypol from refined, bleached, and deodorized cottonseed oil, from highly purified tripelargonin, and from ethyl acetate is demonstrable after the lapse of one hour.
4. It is suggested that the initial reaction of gossypol in the oils is an ester exchange reaction.
5. It is further suggested that secondary reactions result in the production of a red coloration product that is not removable from the oil by the standard refining and bleaching methods.

     

Model reference adaptive control of discrete‐time piecewise linear systems

This article presents a switched model reference adaptive controller for discrete‐time piecewise linear systems. In the spirit of the work by Landau in the late seventies, proof of asymptotic stability of the closed‐loop error system is obtained, recasting its dynamics as a feedback system and showing the feedforward and the feedback paths are both passive. The challenge is that both paths can be piecewise linear. Numerical results show excellent performance of the proposed controller even in the face of sudden variations of the plant parameters. Copyright © 2012 John Wiley & Sons, Ltd.