Sublimation-Driven Activity in Main-Belt Comet 313p/Gibbs

We present an observational and dynamical study of newly discovered main-belt comet 313P/Gibbs. We find that the object is clearly active both in observations obtained in 2014 and in precovery observations obtained in 2003 by the Sloan Digital Sky Survey, strongly suggestingthat its activity is sublimation-driven. This conclusion is supported by a photometric analysis showing an increase in the total brightness of the comet over the 2014 observing period, and dust modeling resultsshowing that the dust emission persists over at least three months during both active periods, where we find start dates for emission nolater than 2003 July 24 ± 10 for the 2003 active period and 2014 July 28 ± 10 for the 2014 active period. From serendipitous observations by the Subaru Telescope in 2004 when the object was apparently inactive, we estimate that the nucleus has an absolute R-band magnitude of HR = 17.1 ± 0.3, corresponding to aneffective nucleus radius of re ∼ 1.00 ± 0.15 km.The object’s faintness at that time means we cannot rule out the presence of activity, and so this computed radius should be consideredan upper limit. We find that 313P’s orbit is intrinsically chaotic, having a Lyapunov time of Tl = 12,000 yr and beinglocated near two three-body mean-motion resonances with Jupiter andSaturn, 11J-1S-5A and 10J+12S-7A, yet appears stable over >50 Myr in an apparent example of stable chaos. We furthermore find that 313P is the second main-belt comet, after P/2012 T1 (PANSTARRS), to belong tothe ∼155 Myr old Lixiaohua asteroid family.

Submicron ionography of nanostructures using a femtosecond-laser-driven-cluster-based source

An intense isotropic source of multicharged carbon and oxygen ions with energy above 300 keV and particle number >108 per shot was obtained by femtosecond Ti:Sa laser irradiation of submicron clusters. The source was employed for high-contrast contact ionography images with 600 nm spatial resolution. A variation in object thickness of 100 nm was well resolved for both Zr and polymer foils.

Nonlinear time series prediction based on a power-law noise model

In this paper we investigate the influence of a power-law noise model, also called noise, on the performance of a feed-forward neural network used to predict time series. We introduce an optimization procedure that optimizes the parameters the neural networks by maximizing the likelihood function based on the power-law model. We show that our optimization procedure minimizes the mean squared leading to an optimal prediction. Further, we present numerical results applying method to time series from the logistic map and the annual number of sunspots demonstrate that a power-law noise model gives better results than a Gaussian model.

Job strain and leisure-time physical activity in female and male public sector employees

Background. High work stress could decrease physical activity but the evidence of the relationship has remained equivocal, The present study examined the association between job strain and leisure-time physical activity in a large sample of employees.

P2Y(1) antagonists: Combining receptor-based modeling and QSAR for a quantitative prediction of the biological activity based on consensus scoring

P2Y(1) is an ADP-activated G protein-coupled receptor (GPCR). Its antagonists impede platelet aggregation in vivo and are potential antithrombotic agents. Combining ligand and structure-based modeling we generated a consensus model (LIST-CM) correlating antagonist structures with their potencies. We docked 45 antagonists into our rhodopsin-based human P2Y(1) homology model and calculated docking scores and free binding energies with the Linear Interaction Energy (LIE) method in continuum-solvent. The resulting alignment was also used to build QSAR based on CoMFA, CoMSIA, and molecular descriptors. To benefit from the strength of each technique and compensate for their limitations, we generated our LIST-CM with a PLS regression based on the predictions of each methodology. A test set featuring untested substituents was synthesized and assayed in inhibition of 2-MeSADP-stimulated PLC activity and in radioligand binding. LIST-CM outperformed internal and external predictivity of any individual model to predict accurately the potency of 75% of the test set.

Real-time GPU color-based segmentation of football players

In this paper, we propose a multi-camera application capable of processing high resolution images and extracting features based on colors patterns over graphic processing units (GPU). The goal is to work in real time under the uncontrolled environment of a sport event like a football match. Since football players are composed for diverse and complex color patterns, a Gaussian Mixture Models (GMM) is applied as segmentation paradigm, in order to analyze sport live images and video. Optimization techniques have also been applied over the C++ implementation using profiling tools focused on high performance. Time consuming tasks were implemented over NVIDIA's CUDA platform, and later restructured and enhanced, speeding up the whole process significantly. Our resulting code is around 4-11 times faster on a low cost GPU than a highly optimized C++ version on a central processing unit (CPU) over the same data. Real time has been obtained processing until 64 frames per second. An important conclusion derived from our study is the scalability of the application to the number of cores on the GPU. © 2011 Springer-Verlag.

Development of Novel Activity-Based Probes for the Detection of Serine Proteases

Cystic Fibrosis (CF) is a genetic disease featuring a chronic cycle of inflammation and infection in the airways of sufferers. Mutations lead to altered ion transport, which in turn causes dehydrated airways and reduced mucociliary clearance which predisposes the patient to infection, resulting in a severe immune response and tissue destruction (1). Airway dehydration is primarily caused by the hyperabsorption of sodium by the epithelial sodium channel (ENaC) (2). ENaC is activated by the action of a number of predominantly trypsin-like Channel Activating Proteases (CAPs) including prostasin, matriptase and furin (3). Additional proteases known to activate ENaC include human airway trypsin (3), plasmin, neutrophil elastase and chymotrypsin (4).

Activity profiling is a valuable technique which involves the use of small inhibitory molecules called Activity-Based Probes (ABPs) which can be used to covalently label the active site of proteases and provide a range of information regarding its structure, catalytic mechanism, location and function within biological systems. The development of novel ABPs for CAPs, would enhance understanding of the role of these proteases in CF airways disease and in particular their role in ENaC activation and airway dehydration. This project investigates the application of a range of novel broad-spectrum ABPs targeting the various subclasses of serine proteases, to include those proteases involved in ENaC activation. Additionally, the application of more selective ABPs in detecting specific serine proteases is investigated.

Compounds were synthesised by Solid-Phase Peptide Synthesis (SPPS) using a standard Fmoc/tBu strategy. Kinetic evaluation of synthesised ABPs against various serine proteases was determined by fluorogenic steady-state enzyme assays. Furthermore, application of ABPs and confirmation of irreversible nature of the compounds was carried out through SDS-PAGE and electroblotting techniques.

Synthesised compounds showed potent irreversible inhibition of serine proteases within their respective targeting class (NAP855 vs Trypsin k3/Ki = 2.60 x 106 M-1 min-1, NFP849 vs Chymotrypsin k3/Ki = 1.28 x 106 M-1 min-1 and NVP800 vs Neutrophil Elastase k3/Ki = 6.41 x 104 M-1 min-1). Furthermore ABPs showed little to no cross-reactivity between classes and so display selectivity between classes. The irreversible nature of compounds was further demonstrated through labelling of proteases, followed by separation and detection via SDS-PAGE and electroblotting techniques. Targeted labelling of active proteases only, was demonstrated by failure of ABPs to detect previously inactivated proteases. Extension of the substrate recognition site within probes resulted in an increased potency and selectivity in the detection of the target proteases. Successful detection of neutrophil elastase from CF sputum samples by NVP800, demonstrated the application of compounds within biological samples and their potential use in identifying further proteases involved in ENaC activation and airway dehydration in CF patients.

A Continuous Time Markov Chain Based Sequential Analytical Approach for Composite Power System Reliability Assessment

This paper proposes a continuous time Markov chain (CTMC) based sequential analytical approach for composite generation and transmission systems reliability assessment. The basic idea is to construct a CTMC model for the composite system. Based on this model, sequential analyses are performed. Various kinds of reliability indices can be obtained, including expectation, variance, frequency, duration and probability distribution. In order to reduce the dimension of the state space, traditional CTMC modeling approach is modified by merging all high order contingencies into a single state, which can be calculated by Monte Carlo simulation (MCS). Then a state mergence technique is developed to integrate all normal states to further reduce the dimension of the CTMC model. Moreover, a time discretization method is presented for the CTMC model calculation. Case studies are performed on the RBTS and a modified IEEE 300-bus test system. The results indicate that sequential reliability assessment can be performed by the proposed approach. Comparing with the traditional sequential Monte Carlo simulation method, the proposed method is more efficient, especially in small scale or very reliable power systems.

The application of a novel, cell permeable activity-based probe for the detection of cysteine cathepsins.

Cysteine cathepsins, such as cathepsin S (CTSS), are implicated in the pathology of a wide range of diseases and are of potential utility as diagnostic and prognostic biomarkers. In previous work, we demonstrated the potency and efficiency of a biotinylated diazomethylketone (DMK)-based activity-based probe (ABP), biotin-PEG-LVG-DMK, for disclosure of recombinant CTSS and CTSS in cell lysates. However, the limited cell permeability of both the biotin and spacer groups restricted detection of CTSS to cell lysates. The synthesis and characterisation of a cell permeable ABP to report on intracellular CTSS activity is reported. The ABP, Z-PraVG-DMK, a modified peptidyl diazomethylketone, was based on the N-terminus of human cystatin motif (Leu-Val-Gly). The leucine residue was substituted for the alkyne-bearing proparcylglycine to facilitate conjugation of an azide-tagged reporter group using click chemistry, following irreversible inhibition of CTSS. When incubated with viable Human Embryonic Kidney 293 cells, Z-PraVG-DMK permitted disclosure of CTSS activity following cell lysis and rhodamine azide conjugation, by employing standard click chemistry protocols. Furthermore, the fluorescent tag facilitated direct detection of CTSS using in-gel fluorescent scanning, obviating the necessity for downstream biotin-streptavidin conjugation and detection procedures.

Development of a rapid colorimetric time-kill assay for determining the in vitro activity of ceftazidime and tobramycin in combination against Pseudomonas aeruginosa

It is standard clinical practice to use a combination of two or more antimicrobial agents to treat an infection caused by Pseudonionas aeruginosa. The antibiotic combinations are usually selected empirically with methods to determine the antimicrobial effect of the combination such as the time-kill assay rarely used as they are time-consuming and labour intensive to perforin. Here, we report a modified time-kill assay, based on the reduction of the tetrazolium salt, 2,3-bis[2-methyloxy-4-nitro-5-sulfopheny1]-2H-tetrazolium-5-carboxanilide (XTT), that allows simple, inexpensive and more rapid determination of the in vitro activity of antibiotic combinations against P aeruginosa. The assay was used to determine the in vitro activity of ceftazidime and tobramycin in combination against P. aertiginosa isolates from cystic fibrosis patients and the results obtained compared with those from conventional viable count time-kill assays. There was good agreement in interpretation of results obtained by the XTT and conventional viable count assays, with similar growth curves apparent and the most effective concentration combinations determined by both methods identical for all isolates tested. The XTT assay clearly indicated whether an antibiotic combination had a synergistic, indifferent or antagonistic effect and could, therefore, provide a useful method for rapidly determining the activity of a large number of antibiotic combinations against clinical isolates. (C) 2004 Elsevier B.V. All rights reserved.

Intelligent Assembly Time Analysis Using a Digital Knowledge-Based Approach

The implementation of effective time analysis methods fast and accurately in the era of digital manufacturing has become a significant challenge for aerospace manufacturers hoping to build and maintain a competitive advantage. This paper proposes a structure oriented, knowledge-based approach for intelligent time analysis of aircraft assembly processes within a digital manufacturing framework. A knowledge system is developed so that the design knowledge can be intelligently retrieved for implementing assembly time analysis automatically. A time estimation method based on MOST, is reviewed and employed. Knowledge capture, transfer and storage within the digital manufacturing environment are extensively discussed. Configured plantypes, GUIs and functional modules are designed and developed for the automated time analysis. An exemplar study using an aircraft panel assembly from a regional jet is also presented. Although the method currently focuses on aircraft assembly, it can also be well utilized in other industry sectors, such as transportation, automobile and shipbuilding. The main contribution of the work is to present a methodology that facilitates the integration of time analysis with design and manufacturing using a digital manufacturing platform solution.