A derivation of high-frequency asymptotic values of 3D added mass and damping based on properties of the Cummins' equation

This brief paper provides a novel derivation of the known asymptotic values of three-dimensional (3D) added mass and damping of marine structures in waves. The derivation is based on the properties of the convolution terms in the Cummins's Equation as derived by Ogilvie. The new derivation is simple and no approximations or series expansions are made. The results follow directly from the relative degree and low-frequency asymptotic properties of the rational representation of the convolution terms in the frequency domain. As an application, the extrapolation of damping values at high frequencies for the computation of retardation functions is also discussed.

Key derivation function based on stream ciphers

A key derivation function (KDF) is a function that transforms secret non-uniformly random source material together with some public strings into one or more cryptographic keys. These cryptographic keys are used with a cryptographic algorithm for protecting electronic data during both transmission over insecure channels and storage. In this thesis, we propose a new method for constructing a generic stream cipher based key derivation function. We show that our proposed key derivation function based on stream ciphers is secure if the under-lying stream cipher is secure. We simulate instances of this stream cipher based key derivation function using three eStream nalist: Trivium, Sosemanuk and Rabbit. The simulation results show these stream cipher based key derivation functions offer efficiency advantages over the more commonly used key derivation functions based on block ciphers and hash functions.

Fluid-structure interaction analysis by coupled FE-SPH model based on a novel searching algorithm

Fluid–Structure Interaction (FSI) problem is significant in science and engineering, which leads to challenges for computational mechanics. The coupled model of Finite Element and Smoothed Particle Hydrodynamics (FE-SPH) is a robust technique for simulation of FSI problems. However, two important steps of neighbor searching and contact searching in the coupled FE-SPH model are extremely time-consuming. Point-In-Box (PIB) searching algorithm has been developed by Swegle to improve the efficiency of searching. However, it has a shortcoming that efficiency of searching can be significantly affected by the distribution of points (nodes in FEM and particles in SPH). In this paper, in order to improve the efficiency of searching, a novel Striped-PIB (S-PIB) searching algorithm is proposed to overcome the shortcoming of PIB algorithm that caused by points distribution, and the two time-consuming steps of neighbor searching and contact searching are integrated into one searching step. The accuracy and efficiency of the newly developed searching algorithm is studied on by efficiency test and FSI problems. It has been found that the newly developed model can significantly improve the computational efficiency and it is believed to be a powerful tool for the FSI analysis.

Tailored interventions based on sputum eosinophils versus clinical symptoms for asthma in children and adults

BACKGROUND Asthma severity and control can be measured both subjectively and objectively. Sputum analysis for evaluation of percentage of sputum eosinophilia directly measures airway inflammation, and is one method of objectively monitoring asthma. Interventions for asthma therapies have been traditionally based on symptoms and spirometry. OBJECTIVES To evaluate the efficacy of tailoring asthma interventions based on sputum analysis in comparison to clinical symptoms (with or without spirometry/peak flow) for asthma related outcomes in children and adults. SEARCH STRATEGY We searched the Cochrane Airways Group Specialised Register of Trials, the Cochrane Central Register of Controlled Trials (CENTRAL), MEDLINE, EMBASE and reference lists of articles. The last search was on 31 October 2006. SELECTION CRITERIA All randomised controlled comparisons of adjustment of asthma therapy based on sputum eosinophils compared to traditional methods (primarily clinical symptoms and spirometry/peak flow). DATA COLLECTION AND ANALYSIS Results of searches were reviewed against pre-determined criteria for inclusion. Three sets of reviewers selected relevant studies.Two review authors independently assessed trial quality extracted data. Authors were contacted for further information but none were received. Data was analysed as "treatment received" and sensitivity analyses performed. MAIN RESULTS Three adult studies were included; these studies were clinically and methodologically heterogenous (use of medications, cut off for percentage of sputum eosinophils and definition of asthma exacerbation). There were no eligible paediatric studies. Of 246 participants randomised, 221 completed the trials. In the meta-analysis, a significant reduction in number of participants who had one or more asthma exacerbations occurred when treatment was based on sputum eosinophils in comparison to clinical symptoms; pooled odds ratio (OR) was 0.49 (95% CI 0.28 to 0.87); number needed to treat to benefit (NNTB) was 6 (95% CI 4 to 32).There were also differences between groups in the rate of exacerbation (any exacerbation per year) and severity of exacerbations defined by requirement for use of oral corticosteroids but the reduction in hospitalisations was not statistically significant. Data for clinical symptoms, quality of life and spirometry were not significantly different between groups. The mean dose of inhaled corticosteroids per day was similar in both groups and no adverse events were reported. However sputum induction was not always possible. AUTHORS' CONCLUSIONS Tailored asthma interventions based on sputum eosinophils is beneficial in reducing the frequency of asthma exacerbations in adults with asthma. This review supports the use of sputum eosinophils to tailor asthma therapy for adults with frequent exacerbations and severe asthma. Further studies need to be undertaken to strengthen these results and no conclusion can be drawn for children with asthma.

Tailored interventions based on exhaled nitric oxide versus clinical symptoms for asthma in children and adults

Background The measurement of severity and control of asthma in both children and adults can be based on subjective or objective measures. It has been advocated that fractional exhaled nitric oxide (FeNO) can be used to monitor airway inflammation as it correlates with some markers of asthma. Interventions for asthma therapies have been traditionally based on symptoms and/or spirometry. Objectives To evaluate the efficacy of tailoring asthma interventions based on exhaled nitric oxide in comparison to clinical symptoms (with or without spirometry/peak flow) for asthma related outcomes in children and adults. Search methods We searched the Cochrane Airways Group Specialised Register of Trials, the Cochrane Central Register of Controlled Trials (CENTRAL), MEDLINE, EMBASE and reference lists of articles. The last search was completed in February 2009. Selection criteria All randomised controlled comparisons of adjustment of asthma therapy based on exhaled nitric oxide compared to traditional methods (primarily clinical symptoms and spirometry/peak flow). Data collection and analysis Results of searches were reviewed against pre-determined criteria for inclusion. Relevant studies were independently selected in duplicate. Two authors independently assessed trial quality and extracted data. Authors were contacted for further information with response from one. Main results Two studies have been added for this update, which now includes six (2 adults and 4 children/adolescent) studies; these studies differed in a variety of ways including definition of asthma exacerbations, FeNO cut off levels, the way in which FeNO was used to adjust therapy and duration of study. Of 1053 participants randomised, 1010 completed the trials. In the meta-analysis, there was no significant difference between groups for the primary outcome of asthma exacerbations or for other outcomes (clinical symptoms, FeNO level and spirometry). In post-hoc analysis, a significant reduction in mean final daily dose inhaled corticosteroid per adult was found in the group where treatment was based on FeNO in comparison to clinical symptoms, (mean difference -450 mcg; 95% CI -677 to -223 mcg budesonide equivalent/day). However, the total amount of inhaled corticosteroid used in one of the adult studies was 11% greater in the FeNO arm. In contrast, in the paediatric studies, there was a significant increase in inhaled corticosteroid dose in the FeNO strategy arm (mean difference of 140 mcg; 95% CI 29 to 251, mcg budesonide equivalent/day). Authors' conclusions Tailoring the dose of inhaled corticosteroids based on exhaled nitric oxide in comparison to clinical symptoms was carried out in different ways in the six studies and found only modest benefit at best and potentially higher doses of inhaled corticosteroids in children. The role of utilising exhaled nitric oxide to tailor the dose of inhaled corticosteroids cannot be routinely recommended for clinical practice at this stage and remains uncertain.

Management based on exhaled nitric oxidelevels adjusted for atopy reduces asthma exacerbations in children : A dual centre randomised controlled trial

While several randomised control trials (RCTs) have evaluated the use of fractional exhaled nitric oxide (FeNO) to improve asthma outcomes, none used FeNO cut-offs adjusted for atopy, a determinant of FeNO levels. In a dual centre RCT, we assessed whether a treatment strategy based on FeNO levels, adjusted for atopy, reduces asthma exacerbations compared with the symptoms-based management (controls). Children with asthma from hospital clinics of two hospitals were randomly allocated to receive an a-priori determined treatment hierarchy based on symptoms or FeNO levels. There was a 2-week run-in period and they were then reviewed ten times over 12-months. The primary outcome was the number of children with exacerbations over 12-months. Sixty-three children were randomised (FeNO=31, controls=32); 55 (86%) completed the study. Although we did achieve our planned sample size, significantly fewer children in the FeNO group (6 of 27) had an asthma exacerbation compared to controls (15 of 28), p=0.021; number to treat for benefit=4 (95%CI 3-24). There was no difference between groups for any secondary outcomes (quality of life, symptoms, FEV1). The final daily inhaled corticosteroids (ICS) dose was significantly (p=0.037) higher in the FeNO group (median 400µg, IQR 250-600) compared to the controls (200, IQR100-400). Taking atopy into account when using FeNO to tailor asthma medications is likely beneficial in reducing the number of children with severe exacerbations at the expense of increased ICS use. However, the strategy is unlikely beneficial for improving asthma control. A larger study is required to confirm or refute our findings.

Conductometric gas sensors based on nanostrutured WO3 thin films

Nanostructured WO3 thin films have been prepared bythermal evaporation to detect hydrogen at low t emperatures. The influence of heat treatment on the physical, chemical and electronic properties of these films has been investigated. The films were annealed at 400oC for 2 hours in air. AFM and TEM analysis revealed that the as-deposited WO3 film is high amorphous and made up of cluster of particles. Annealing at 400oC for 2 hours in air resulted in very fine grain size of the order of 5 nm and porous structure. GIXRD and Raman analysis revealed that annealing improved the crystallinity of WO3 film. Gas sensors based on annealed WO3 films have shown a high response towards various concentrations (10-10000 ppm) H2 at an operating temperature of 150oC. The improved sensing performance at low operating temperature is due to the optimum physical, chemical and electronic properties achieved in the WO3 film through annealing. - See more at: http://dl4.globalstf.org/?wpsc-product=conductometric-gas-sensors-based-on-nanostructured-wo3-thin-films-2#sthash.IrfhlZ6H.dpuf

Molecular sliding filament model for muscular contraction based on multiscale investigation

A multiscale approach that bridges the biophysics of the actin molecules at nanoscale and the biomechanics of actin filament at microscale level is developed and used to evaluate the mechanical performances of actin filament bundles. In order to investigate the contractile properties of skeletal muscle which is induced by the protein motor of myosin, a molecular model is proposed in the prediction of the dynamic behaviors of skeletal muscle based on classic sliding filament model. Randomly distributed myosin motors are applied on a 2.2 μm long sarcomere, whose principal components include actin and myosin filaments. It can be found that, the more myosin motors on the sarcomere, the faster the sarcomere contracts. The result demonstrates that the sarcomere shortening speed cannot increase infinitely by the modulation of myosin, thus providing insight into the self-protective properties of skeletal muscles. This molecular filament sliding model provides a theoretical way to evaluate the properties of skeletal muscles, and contributes to the understandings of the molecular mechanisms in the physiological phenomenon of muscular contraction.

Traffic incident clearance time and arrival time prediction based on hazard models

Accurate prediction of incident duration is not only important information of Traffic Incident Management System, but also an ffective input for travel time prediction. In this paper, the hazard based prediction odels are developed for both incident clearance time and arrival time. The data are obtained from the Queensland Department of Transport and Main Roads’ STREAMS Incident Management System (SIMS) for one year ending in November 2010. The best fitting distributions are drawn for both clearance and arrival time for 3 types of incident: crash, stationary vehicle, and hazard. The results show that Gamma, Log-logistic, and Weibull are the best fit for crash, stationary vehicle, and hazard incident, respectively. The obvious impact factors are given for crash clearance time and arrival time. The quantitative influences for crash and hazard incident are presented for both clearance and arrival. The model accuracy is analyzed at the end.

Developing agency in the creative career : a design-based framework for work integrated learning

Research shows that approximately half of creative practitioners operate as embedded creatives by securing gainful employment within organisations located in the field beyond their core discipline. This foregrounds the significance of having the skills necessary to successfully cross the disciplinary boundaries in order to negotiate a professional role. The multiple implications of such reframing for emerging creative practitioners who navigate uncertain professional boundaries include developing a skill of identifying and successfully targeting the shifting professional and industry coordinates while remaining responsive to changes. A further implication involves creative practitioners engaging in a continuous cycle of re-negotiation of their professional identity making the management of multiple professional selves - along with creating and recreating a meaningful frame of references such as the language around their emerging practice - a necessary skill. This chapter presents a case study of a set of Work Integrated Learning subjects designed to develop in creative industries practitioners the skills to manage their emerging professional identities in response to the shifts in the professional world.

A sensor fault detection and isolation method in interior permanent-magnet synchronous motor drives based on an extended Kalman filter

Interior permanent-magnet synchronous motors (IPMSMs) become attractive candidates in modern hybrid electric vehicles and industrial applications. Usually, to obtain good control performance, the electric drives of this kind of motor require one position, one dc link, and at least two current sensors. Failure of any of these sensors might lead to degraded system performance or even instability. As such, sensor fault resilient control becomes a very important issue in modern drive systems. This paper proposes a novel sensor fault detection and isolation algorithm based on an extended Kalman filter. It is robust to system random noise and efficient in real-time implementation. Moreover, the proposed algorithm is compact and can detect and isolate all the sensor faults for IPMSM drives. Thorough theoretical analysis is provided, and the effectiveness of the proposed approach is proven by extensive experimental results.

Adipose tissue engineering based on the controlled release of fibroblast growth factor-2 in a collagen matrix

Adipose tissue forms when basement membrane extract (Matrigel™) and fibroblast growth factor-2 (FGF-2) are added to our mouse tissue engineering chamber model. A mouse tumor extract, Matrigel is unsuitable for human clinical application, and finding an alternative to Matrigel is essential. In this study we generated adipose tissue in the chamber model without using Matrigel by controlled release of FGF-2 in a type I collagen matrix. FGF-2 was impregnated into biodegradable gelatin microspheres for its slow release. The chambers were filled with these microspheres suspended in 60 μL collagen gel. Injection of collagen containing free FGF-2 or collagen containing gelatin microspheres with buffer alone served as controls. When chambers were harvested 6 weeks after implantation, the volume and weight of the tissue obtained were higher in the group that received collagen and FGF-2 impregnated microspheres than in controls. Histologic analysis of tissue constructs showed the formation of de novo adipose tissue accompanied by angiogenesis. In contrast, control groups did not show extensive adipose tissue formation. In conclusion, this study has shown that de novo formation of adipose tissue can be achieved through controlled release of FGF-2 in collagen type I in the absence of Matrigel.

Enhanced coloration efficiency for electrochromic devices based on anodized N2O5 / Electrodeposited MoO3 Binary Systems

There is a continuous quest for developing electrochromic (EC)transition metal oxides (TMOs) with increased coloration efficiency. As emerging TMOs, Nb2O5 films, even those of ordered anodized nanochannels, have failed to produce the required EC performance for practical applications. This is attributed to limitations presented by its relatively wide bandgap and low capacity for accommodating ions. To overcome such issues, MoO3 was electrodeposited onto Nb2O5 nanochannelled films as homogeneously conformal and stratified α-MoO3 coatings of different thickness. The EC performance of the resultant MoO3 coated Nb2O5 binary system was evaluated. The system exhibited a coloration efficiency of 149.0 cm2 C−1, exceeding that of any previous reports on MoO3 and Nb2O5 individually or their compounds. The enhancement was ascribed to a combination of the reduced effective bandgap of the binary system, the increased intercalation probability from the layered α-MoO3 coating, and a high surface-tovolume ratio, while the Nb2O5 nanochannelled templates provided stability and low impurity pathways for charge transfer to occur.

A model of a large-area planar plasma producer based on surface wave propagation in a plasma-metal structure with a dielectric sheath

A theoretical model of a large-area planar plasma producer based on surface wave (SW) propagation in a plasma-metal structure with a dielectric sheath is presented. The SW which produces and sustains the microwave gas discharge in the planar structure propagates along an external magnetic field and possesses an eigenfrequency within the range between electron cyclotron and electron plasma frequencies. The spatial distributions of the produced plasma density, electromagnetic fields, energy flow density, phase velocity and reverse skin depth of the SW are obtained analytically and numerically.

Brain decoding based on functional magnetic resonance imaging using machine learning : a comparative study

Brain decoding of functional Magnetic Resonance Imaging data is a pattern analysis task that links brain activity patterns to the experimental conditions. Classifiers predict the neural states from the spatial and temporal pattern of brain activity extracted from multiple voxels in the functional images in a certain period of time. The prediction results offer insight into the nature of neural representations and cognitive mechanisms and the classification accuracy determines our confidence in understanding the relationship between brain activity and stimuli. In this paper, we compared the efficacy of three machine learning algorithms: neural network, support vector machines, and conditional random field to decode the visual stimuli or neural cognitive states from functional Magnetic Resonance data. Leave-one-out cross validation was performed to quantify the generalization accuracy of each algorithm on unseen data. The results indicated support vector machine and conditional random field have comparable performance and the potential of the latter is worthy of further investigation.