954 resultados para distributed combination of classifiers


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To find the range of pressure required for effective high-pressure inactivation of bacterial spores and to investigate the role of alpha/beta-type small, acid-soluble proteins (SASP) in spores under pressure treatment, mild heat was combined with pressure (room temperature to 65 degrees C and 100 to 500 MPa) and applied to wild-type and SASP-alpha(-/)beta(-) Bacillus subtilis spores. On the one hand, more than 4 log units of wild-type spores were reduced after pressurization at 100 to 500 MPa and 65 degrees C, On the other hand, the number of surviving mutant spores decreased by 2 log units at 100 MPa and by more than 5 log units at 500 MPa. At 500 MPa and 65 degrees C, both wild-type and mutant spore survivor counts were reduced by 5 log units. Interestingly, pressures of 100, 200, and 300 MPa at 65 degrees C inactivated wild-type SASP-alpha(+)/beta(+) spores more than mutant SASP-alpha(-)/beta(-) spores, and this was attributed to less pressure-induced germination in SASP-alpha(-)/beta(-) spores than in wild-type SASP-alpha(+)/beta(+) spores. However, there was no difference in the pressure resistance between SASP-alpha(+)/beta(+) and SASP-alpha(-)/beta(-) spores at 100 MPa and ambient temperature (approximately 22 degrees C) for 30 min. A combination of high pressure and high temperature is very effective for inducing spore germination, and then inactivation of the germinated spore occurs because of the heat treatment. This study showed that alpha/beta-type SASP play a role in spore inactivation by increasing spore germination under 100 to 300 MPa at high temperature.

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The discovery of polymers with stimuli responsive physical properties is a rapidly expanding area of research. At the forefront of the field are self-healing polymers, which, when fractured can regain the mechanical properties of the material either autonomically, or in response to a stimulus. It has long been known that it is possible to promote healing in conventional thermoplastics by heating the fracture zone above the Tg of the polymer under pressure. This process requires reptation and subsequent re-entanglement of macromolecules across the fracture void, which serves to bridge, and ‘heal’ the crack. The timescale for this mechanism is highly dependent on the molecular weight of the polymer being studied. This process is in contrast to that required to affect healing in supramolecular polymers such as the plasticised, hydrogen bonded elastomer reported by Leibler et al. The disparity in bond energies between the non-covalent and covalent bonds within supramolecular polymers results in fractures propagating through scission of the comparatively weak supramolecular interactions, rather than through breaking the stronger, covalent bonds. Thus, during the healing process the macromolecules surrounding the fracture site only need sufficient energy to re-engage their supramolecular interactions in order to regenerate the strength of the pristine material. Herein we describe the design, synthesis and optimization of a new class of supramolecular polymer blends that harness the reversible nature of pi-pi stacking and hydrogen bonding interactions to produce self-supporting films with facile healable characteristics.

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The past decade has witnessed explosive growth of mobile subscribers and services. With the purpose of providing better-swifter-cheaper services, radio network optimisation plays a crucial role but faces enormous challenges. The concept of Dynamic Network Optimisation (DNO), therefore, has been introduced to optimally and continuously adjust network configurations, in response to changes in network conditions and traffic. However, the realization of DNO has been seriously hindered by the bottleneck of optimisation speed performance. An advanced distributed parallel solution is presented in this paper, as to bridge the gap by accelerating the sophisticated proprietary network optimisation algorithm, while maintaining the optimisation quality and numerical consistency. The ariesoACP product from Arieso Ltd serves as the main platform for acceleration. This solution has been prototyped, implemented and tested. Real-project based results exhibit a high scalability and substantial acceleration at an average speed-up of 2.5, 4.9 and 6.1 on a distributed 5-core, 9-core and 16-core system, respectively. This significantly outperforms other parallel solutions such as multi-threading. Furthermore, augmented optimisation outcome, alongside high correctness and self-consistency, have also been fulfilled. Overall, this is a breakthrough towards the realization of DNO.

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The combination of the synthetic minority oversampling technique (SMOTE) and the radial basis function (RBF) classifier is proposed to deal with classification for imbalanced two-class data. In order to enhance the significance of the small and specific region belonging to the positive class in the decision region, the SMOTE is applied to generate synthetic instances for the positive class to balance the training data set. Based on the over-sampled training data, the RBF classifier is constructed by applying the orthogonal forward selection procedure, in which the classifier structure and the parameters of RBF kernels are determined using a particle swarm optimization algorithm based on the criterion of minimizing the leave-one-out misclassification rate. The experimental results on both simulated and real imbalanced data sets are presented to demonstrate the effectiveness of our proposed algorithm.

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Existing research on synchronous remote working in CSCW has highlighted the troubles that can arise because actions at one site are (partially) unavailable to remote colleagues. Such ‘local action’ is routinely characterised as a nuisance, a distraction, subordinate and the like. This paper explores interconnections between ‘local action’ and ‘distributed work’ in the case of a research team virtually collocated through ‘MiMeG’. MiMeG is an e-Social Science tool that facilitates ‘distributed data sessions’ in which social scientists are able to remotely collaborate on the real-time analysis of video data. The data are visible and controllable in a shared workspace and participants are additionally connected via audio conferencing. The findings reveal that whilst the (partial) unavailability of local action is at times problematic, it is also used as a resource for coordinating work. The paper considers how local action is interactionally managed in distributed data sessions and concludes by outlining implications of the analysis for the design and study of technologies to support group-to-group collaboration.

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An evaluation of the 'Barefoot in the Head' performance event, I co-curated with Alun Rowlands and Mark Beasley, at Bruce High Quality Foundation University, New York, as part of Performa 09 New York, 12 November 2009 - an examination of my own performance and the other performances occurring simultaneously at the event.

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This paper explores the possibility of combining moderate vacuum frying followed by post-frying high vacuum application during the oil drainage stage, with the aim to reduce oil content in potato chips. Potato slices were initially vacuum fried under two operating conditions (140 °C, 20 kPa and 162 °C, 50.67 kPa) until the moisture content reached 10 and 15 % (wet basis), prior to holding the samples in the head space under high vacuum level (1.33 kPa). This two-stage process was found to lower significantly the amount of oil taken up by potato chips by an amount as high as 48 %, compared to drainage at the same pressure as the frying pressure. Reducing the pressure value to 1.33 kPa reduced the water saturation temperature (11 °C), causing the product to continuously lose moisture during the course of drainage. Continuous release of water vapour prevented the occluded surface oil from penetrating into the product structure and released it from the surface of the product. When frying and drainage occurred at the same pressure, the temperature of the product fell below the water saturation temperature soon after it was lifted out of the oil, which resulted in the oil getting sucked into the product. Thus, lowering the pressure after frying to a value well below the frying pressure is a promising method to lower oil uptake by the product.

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Wernicke’s aphasia (WA) is the classical neurological model of comprehension impairment and, as a result, the posterior temporal lobe is assumed to be critical to semantic cognition. This conclusion is potentially confused by (a) the existence of patient groups with semantic impairment following damage to other brain regions (semantic dementia and semantic aphasia) and (b) an ongoing debate about the underlying causes of comprehension impairment in WA. By directly comparing these three patient groups for the first time, we demonstrate that the comprehension impairment in Wernicke’s aphasia is best accounted for by dual deficits in acoustic-phonological analysis (associated with pSTG) and semantic cognition (associated with pMTG and angular gyrus). The WA group were impaired on both nonverbal and verbal comprehension assessments consistent with a generalised semantic impairment. This semantic deficit was most similar in nature to that of the semantic aphasia group suggestive of a disruption to semantic control processes. In addition, only the WA group showed a strong effect of input modality on comprehension, with accuracy decreasing considerably as acoustic-phonological requirements increased. These results deviate from traditional accounts which emphasise a single impairment and, instead, implicate two deficits underlying the comprehension disorder in WA.

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Attaching and effacing (AE) lesions were observed in the caecum, proximal colon and rectum of one of four lambs experimentally inoculated at 6 weeks. of age with Escherichia coli O157:H7. However, the attached bacteria did not immunostain with O157-specific antiserum. Subsequent bacteriological analysis of samples from this animal yielded two E. coli O115:H- strains, one from the colon (CO) and one from the rectum (RC), and those bacteria forming the AE lesions were shown to be of the O115 serogroup by immunostaining. The O115:H(-)isolates formed microcolonies and attaching and effacing lesions, as demonstrated by the fluorescence actin staining test, on HEp-2 tissue culture cells. Both isolates were confirmed by PCR to encode the epsilon (epsilon) subtype of intimin. Supernates of both O115:H- isolates induced cytopathic effects on Vero cell monolayers, and PCR analysis verified that both isolates encoded EAST1, CNF1 and CNF2 toxins but not Shiga-like toxins. Both isolates harboured similar sized plasmids but-PCR analysis indicated that only one of the O115:H- isolates (CO) possessed the plasmid-associated virulence determinants ehxA and etpD. Neither strain possessed the espP, katP or bfpA plasmid-associated virulence determinants. These E. coli O115:H- strains exhibited a novel combination of virulence determinants and are the first isolates found to possess both CNF1 and CNF2.

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The P-found protein folding and unfolding simulation repository is designed to allow scientists to perform analyses across large, distributed simulation data sets. There are two storage components in P-found: a primary repository of simulation data and a data warehouse. Here we demonstrate how grid technologies can support multiple, distributed P-found installations. In particular we look at two aspects, first how grid data management technologies can be used to access the distributed data warehouses; and secondly, how the grid can be used to transfer analysis programs to the primary repositories --- this is an important and challenging aspect of P-found because the data volumes involved are too large to be centralised. The grid technologies we are developing with the P-found system will allow new large data sets of protein folding simulations to be accessed and analysed in novel ways, with significant potential for enabling new scientific discoveries.

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The P-found protein folding and unfolding simulation repository is designed to allow scientists to perform data mining and other analyses across large, distributed simulation data sets. There are two storage components in P-found: a primary repository of simulation data that is used to populate the second component, and a data warehouse that contains important molecular properties. These properties may be used for data mining studies. Here we demonstrate how grid technologies can support multiple, distributed P-found installations. In particular, we look at two aspects: firstly, how grid data management technologies can be used to access the distributed data warehouses; and secondly, how the grid can be used to transfer analysis programs to the primary repositories — this is an important and challenging aspect of P-found, due to the large data volumes involved and the desire of scientists to maintain control of their own data. The grid technologies we are developing with the P-found system will allow new large data sets of protein folding simulations to be accessed and analysed in novel ways, with significant potential for enabling scientific discovery.

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A novel combination of site-specific isotope labelling, polarised infrared spectroscopy and molecular combing reveal local orientational ordering in the fibril-forming peptide YTIAALLSPYSGGRADS. Use of 13C-18O labelled alanine residues demonstrates that the Nterminal end of the peptide is incorporated into the cross-beta structure, while the C-terminal end shows orientational disorder

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An alternating hexameric water (H2O)(6) cluster and a chlorine-water cluster [Cl-2(H2O)(4)](2-) in the chair forms combine axially to each other to form a 1D chain [{Cl-2(H2O)(6)}(2-)](n) in complex [FeL2]Cl center dot(H2O)(3) (L=2-[(2-methylaminoethylimino)-methyl]-phenol)]. The water molecules display extensive H-bonding interactions with monomeric iron-organic units to form a hydrogen-bonded 2D supramolecular assembly.

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The Mobile Network Optimization (MNO) technologies have advanced at a tremendous pace in recent years. And the Dynamic Network Optimization (DNO) concept emerged years ago, aimed to continuously optimize the network in response to variations in network traffic and conditions. Yet, DNO development is still at its infancy, mainly hindered by a significant bottleneck of the lengthy optimization runtime. This paper identifies parallelism in greedy MNO algorithms and presents an advanced distributed parallel solution. The solution is designed, implemented and applied to real-life projects whose results yield a significant, highly scalable and nearly linear speedup up to 6.9 and 14.5 on distributed 8-core and 16-core systems respectively. Meanwhile, optimization outputs exhibit self-consistency and high precision compared to their sequential counterpart. This is a milestone in realizing the DNO. Further, the techniques may be applied to similar greedy optimization algorithm based applications.

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It has been years since the introduction of the Dynamic Network Optimization (DNO) concept, yet the DNO development is still at its infant stage, largely due to a lack of breakthrough in minimizing the lengthy optimization runtime. Our previous work, a distributed parallel solution, has achieved a significant speed gain. To cater for the increased optimization complexity pressed by the uptake of smartphones and tablets, however, this paper examines the potential areas for further improvement and presents a novel asynchronous distributed parallel design that minimizes the inter-process communications. The new approach is implemented and applied to real-life projects whose results demonstrate an augmented acceleration of 7.5 times on a 16-core distributed system compared to 6.1 of our previous solution. Moreover, there is no degradation in the optimization outcome. This is a solid sprint towards the realization of DNO.