Pathway to health: Cluster-randomized trail to increase fruit and vegetable consumption among smokers in public housing.

Objectives: Examine the effectiveness of an intervention to increase fruits and vegetables (FV) consumption among smokers. Design: Cluster-randomized trial of 20 public housing developments; 10 randomly assigned to an FV intervention and 10 to a smoking cessation intervention. Main outcome measures: Usual (past 7 days) and past 30 days change in daily FV intake at 8 weeks and 6 months postbaseline. Results: Greater increases were seen in the FV group. At Week 8 and Month 6, the FV group had consumed 1.58 (p = .001) and 0.78 (p = .04), respectively, more daily FV servings in the past 7 days than the cessation group. At the same time points, the FV group had consumed 3.61 (p = .01) and 3.93 (p = .01), respectively, more FV servings in the past 30 days than the cessation group. Completing more motivational interviewing sessions (p = .02) and trying more recipes (p = .02) led to significantly greater increases at Month 6 among FV participants. Conclusions: Motivational interviewing counseling and lifestyle modification through trying out healthy recipes may be effective in helping a high-risk population increase their FV intake. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Loose-part signal properties

Lamb's solution for two-dimensional wave propagation was used to identify plate bending wave characteristics observed in loose part impact signals. The surface displacement wave is shown to have large second derivatives at points that can be used to measure the impact contact time. General features of the initial impact wave shape provide guidance for the use of spectral analysis techniques to identify the contact time and wave arrival time when there is a low signal-to-noise ratio. Improvements in the determination of contact time improve the estimation of loose part mass and energy through the Hertz impact parameters. The shape of the initial impact wave shape can also be used to identify on which side of the plate the impact took place. This information has applications for Loose Part Monitoring System metal impact signal validation and for improved estimation of loose part parameters.     

Electrospun fibers based on porcine plasma: a rheological and morphological study

Iranian Polymer Journal - The present work focuses on the assessment of the ability of porcine plasma protein (PPP) to be electrospun satisfactorily to form fibre mats, and their rheological and...     

A complete and efficient CUDA-sharing solution for HPC clusters

In this paper we detail the key features, architectural design, and implementation of rCUDA, an advanced framework to enable remote and transparent GPGPU acceleration in HPC clusters. rCUDA allows decoupling GPUs from nodes, forming pools of shared accelerators, which brings enhanced flexibility to cluster configurations. This opens the door to configurations with fewer accelerators than nodes, as well as permits a single node to exploit the whole set of GPUs installed in the cluster. In our proposal, CUDA applications can seamlessly interact with any GPU in the cluster, independently of its physical location. Thus, GPUs can be either distributed among compute nodes or concentrated in dedicated GPGPU servers, depending on the cluster administrator’s policy. This proposal leads to savings not only in space but also in energy, acquisition, and maintenance costs. The performance evaluation in this paper with a series of benchmarks and a production application clearly demonstrates the viability of this proposal. Concretely, experiments with the matrix–matrix product reveal excellent performance compared with regular executions on the local GPU; on a much more complex application, the GPU-accelerated LAMMPS, we attain up to 11x speedup employing 8 remote accelerators from a single node with respect to a 12-core CPU-only execution. GPGPU service interaction in compute nodes, remote acceleration in dedicated GPGPU servers, and data transfer performance of similar GPU virtualization frameworks are also evaluated.     

Conditional-sampling spectrograph detection system for fluorescence measurements of individual airborne biological particles

We report the design and operation of a prototype conditional-sampling spectrograph detection system that can record the fluorescence spectra of individual, micrometer-sized aerosols as they traverse an intense 488-nm intracavity laser beam. The instrument's image-intensified CCD detector is gated by elastic scattering or by undispersed fluorescence from particles that enter the spectrograph's field of view. It records spectra only from particles with preselected scattering-fluorescence levels (a fiber-optic-photomultiplier subsystem provides the gating signal). This conditional-sampling procedure reduces data-handling rates and increases the signal-to-noise ratio by restricting the system's exposures to brief periods when aerosols traverse the beam. We demonstrate these advantages by reliably capturing spectra from individual fluorescent microspheres dispersed in an airstream. The conditional-sampling procedure also permits some discrimination among different types of particles, so that spectra may be recorded from the few interesting particles present in a cloud of background aerosol. We demonstrate such discrimination by measuring spectra from selected fluorescent microspheres in a mixture of two types of microspheres, and from bacterial spores in a mixture of spores and nonfluorescent kaolin particles.     

Learning teamwork skills in university programming courses

University courses about computer programming usually seek to provide students not only with technical knowledge, but also with the skills required to work in real-life software projects. Nowadays, the development of software applications requires the coordinated efforts of the members of one or more teams. Therefore, it is important for software professionals to master the sort of skills that assure the success of teamwork, such as communication, leadership, negotiation, or team management. However, these abilities are difficult to teach, one of the reasons being that they require true commitment from the students. However, today students are taking a more and more passive role in their own education, two of the more evident consequences being the increase in dropout rates and the decrease in marks obtained in exams. The NUCLEO e-learning framework has been designed to promote the effective acquisition of teamwork skills and, at the same time, to promote the more active participation of the students in their own learning process. NUCLEO adopts a socio-constructivist pedagogical approach that pursues the development of communities of practice for Problem Based Learning. Our research has rooted the design decisions of NUCLEO in the analysis of its socio-cultural environment with Activity Theory, which considers conflicts within groups as the impetus of their evolution and the forges of their environments. This paper presents the analysis of the main features of NUCLEO according to Activity Theory, as well as the experimental results obtained with the framework in three different case studies in university courses.     

Large-scale linear system solver using secondary storage: Self-energy in hybrid nanostructures

We present a Fortran library which can be used to solve large-scale dense linear systems, Ax=b. The library is based on the LU decomposition included in the parallel linear algebra library PLAPACK and on its out-of-core extension POOCLAPACK. The library is complemented with a code which calculates the self-polarization charges and self-energy potential of axially symmetric nanostructures, following an induced charge computation method. Illustrative calculations are provided for hybrid semiconductor–quasi-metal zero-dimensional nanostructures. In these systems, the numerical integration of the self-polarization equations requires using a very fine mesh. This translates into very large and dense linear systems, which we solve for ranks up to 3×¹⁰⁵. It is shown that the self-energy potential on the semiconductor–metal interface has important effects on the electronic wavefunction.

Program summary

Program title: HDSS (Huge Dense System Solver)Catalogue identifier: AEHU_v1_0Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AEHU_v1_0.htmlProgram obtainable from: CPC Program Library, Queen's University, Belfast, N. IrelandLicensing provisions: Standard CPC licence, http://cpc.cs.qub.ac.uk/licence/licence.htmlNo. of lines in distributed program, including test data, etc.: 98 889No. of bytes in distributed program, including test data, etc.: 1 009 622Distribution format: tar.gzProgramming language: Fortran 90, CComputer: Parallel architectures: multiprocessors, computer clustersOperating system: Linux/UnixHas the code been vectorized or parallelized?: Yes. 4 processors used in the sample tests; tested from 1 to 288 processorsRAM: 2 GB for the sample tests; tested for up to 80 GBClassification: 7.3External routines: MPI, BLAS, PLAPACK, POOCLAPACK. PLAPACK and POOCLAPACK are included in the distribution file.Nature of problem: Huge scale dense systems of linear equations, Ax=B, beyond standard LAPACK capabilities. Application to calculations of self-energy potential in dielectrically mismatched semiconductor quantum dots.Solution method: The linear systems are solved by means of parallelized routines based on the LU factorization, using efficient secondary storage algorithms when the available main memory is insufficient. The self-energy solver relies on an induced charge computation method. The differential equation is discretized to yield linear systems of equations, which we then solve by calling the HDSS library.Restrictions: Simple precision. For the self-energy solver, axially symmetric systems must be considered.Running time: About 32 minutes to solve a system with approximately 100 000 equations and more than 6000 right-hand side vectors using a four-node commodity cluster with a total of 32 Intel cores.     

Differential susceptibility of primary and established human glioma cells to adenovirus infection: targeting via the epidermal growth factor receptor achieves fiber receptor-independent gene transfer

Adenovirus (Ad) vectors are promising for gene therapy of glioma due to their ability to achieve efficient gene transfer upon intratumoral administration. Yet in this context, Ad mediates widespread gene transfer to both tumor and surrounding parenchyma. Ad entry is dependent upon the expression of fiber receptors, such as coxsackie/adenovirus receptor, and alpha(v) integrins on the target cells for binding and internalization, respectively. We hypothesized that the susceptibility of human gliomas to Ad would likely be heterogeneous due to variable expression of these receptors. It was found that established human glioma cell lines exhibited differential susceptibility to Ad-mediated gene transfer, which correlated directly with the level of radiolabeled Ad binding and with the expression of coxsackie/adenovirus receptor but not with the expression of alpha(v) integrins. To circumvent the lack of fiber receptors and to target Ad gene transfer specifically to tumor cells, we used a bispecific antibody conjugate to ablate Ad binding to fiber receptors and retarget binding to the epidermal growth factor receptor (EGFR), a tumor-associated marker negligibly expressed in normal, mitotically quiescent neural tissues. The results demonstrate that EGFR-targeted Ad gene transfer was EGFR specific and independent of fiber-fiber receptor interactions. Furthermore, EGFR targeting significantly enhanced Ad gene delivery to 7 of 12 established glioma cell lines and to 6 of 8 cultured primary gliomas. Interestingly, EGFR-targeted Ad gene transfer did not correlate with EGFR expression across cell lines, suggesting the importance of other factors. This study establishes that fiber receptor expression limits the utility of Ad vectors for gene transfer to glioma cells and suggests that targeting Ad via EGFR may prove valuable for tumor-specific gene transfer to high-grade gliomas. These findings have key relevance in the context of Ad vector-based approaches for glioma gene therapy.     

Plant oil bioconversion into increase biological activity through lipases derived from wastes

The aim of this study was to show that abundant and inexpensive plant oils can be biotransformed to increase biological activity (antioxidant, antimicrobial and cytotoxicity) through hydrolysis reaction catalysed by lipases. We tested homemade and commercial lipases through the biotransformation of nine different plant oils in forty different combinations. First, the chemical composition of the samples was investigated. Thereafter, biological tests were conducted to assess the antioxidant and antimicrobial activity of the sampled biotransformation products, as well as analyzed their influence on the viability of healthy and cancer cells. Summarising, sunflower, corn and olive oils modified by orange waste-obtained lipases presented the most promising results, reaching up to 90% of antioxidant activity increase and significant growth inhibition of bacteria colonies belonging to genera Escherichia, Listeria, Staphylococcus, Pseudomonas and Salmonella. In addition, those compounds affected human oral squamous carcinoma cells. The bioconversion of plant oils through lipases improves their biological properties and might be an option for biotechnological application.