Numerical study of LSF floors made of hollow flange channels in fire

Light gauge steel frame (LSF) floor systems are generally made of lipped channel section joists and lined with gypsum plasterboards to provide adequate fire resistance rating under fire conditions. Recently a new LSF floor system made of welded hollow flange channel (HFC) section was developed and its fire performance was investigated using full scale fire tests. The new floor systems gave higher fire resistance ratings in comparison to conventional LSF floor systems. To avoid expensive and time consuming full scale fire tests, finite element analyses were also performed to simulate the fire performance of LSF floors made of HFC joists using both steady and transient state methods. This paper presents the details of the developed finite element models of HFC joists to simulate the structural fire performance of the LSF floor systems under standard fire conditions. Finite element analyses were performed using the measured time–temperature profiles of the failed joists from the fire tests, and their failure times, temperatures and modes, and deflection versus time curves were obtained. The developed finite element models successfully predicted the structural performance of LSF floors made of HFC joists under fire conditions. They were able to simulate the complex behaviour of thin cold-formed steel joists subjected to non-uniform temperature distributions, and local buckling and yielding effects. This study also confirmed the superior fire performance of the newly developed LSF floors made of HFC joists.

Performance of soft-hard-soft (SHS) cement based composite subjected to blast loading with consideration of interface properties

This paper presents a combined experimental and numerical study on the damage and performance of a soft-hard-soft (SHS) multi-layer cement based composite subjected to blast loading which can be used for protective structures and infrastructures to resist extreme loadings, and the composite consists of three layers of construction materials including asphalt concrete (AC) on the top, high strength concrete (HSC) in the middle, and engineered cementitious composites (ECC) at the bottom. To better characterize the material properties under dynamic loading, interface properties of the composite were investigated through direct shear test and also used to validate the interface model. Strain rate effects of the asphalt concrete were also studied and both compressive and tensile dynamic increase factor (DIF) curves were improved based on split Hopkinson pressure bar (SHPB) test. A full-scale field blast test investigated the blast behavior of the composite materials. The numerical model was established by taking into account the strain rate effect of all concrete materials. Furthermore, the interface properties were also considered into the model. The numerical simulation using nonlinear finite element software LS-DYNA agrees closely with the experimental data. Both the numerical and field blast test indicated that the SHS composite exhibited high resistance against blast loading.

Fractal and multifractal properties of a family of fractal networks

In this work, we study the fractal and multifractal properties of a family of fractal networks introduced by Gallos et al (2007 Proc. Nat. Acad. Sci. USA 104 7746). In this fractal network model, there is a parameter e which is between 0 and 1, and allows for tuning the level of fractality in the network. Here we examine the multifractal behavior of these networks, the dependence relationship of the fractal dimension and the multifractal parameters on parameter e. First, we find that the empirical fractal dimensions of these networks obtained by our program coincide with the theoretical formula given by Song et al (2006 Nature Phys. 2 275). Then from the shape of the τ(q) and D(q) curves, we find the existence of multifractality in these networks. Last, we find that there exists a linear relationship between the average information dimension 〈D(1)〉 and the parameter e.

Combining transcriptome assemblies from multiple de novo assemblers in the allo-tetraploid plant Nicotiana benthamiana

Background Nicotiana benthamiana is an allo-tetraploid plant, which can be challenging for de novo transcriptome assemblies due to homeologous and duplicated gene copies. Transcripts generated from such genes can be distinct yet highly similar in sequence, with markedly differing expression levels. This can lead to unassembled, partially assembled or mis-assembled contigs. Due to the different properties of de novo assemblers, no one assembler with any one given parameter space can re-assemble all possible transcripts from a transcriptome. Results In an effort to maximise the diversity and completeness of de novo assembled transcripts, we utilised four de novo transcriptome assemblers, TransAbyss, Trinity, SOAPdenovo-Trans, and Oases, using a range of k-mer sizes and different input RNA-seq read counts. We complemented the parameter space biologically by using RNA from 10 plant tissues. We then combined the output of all assemblies into a large super-set of sequences. Using a method from the EvidentialGene pipeline, the combined assembly was reduced from 9.9 million de novo assembled transcripts to about 235,000 of which about 50,000 were classified as primary. Metrics such as average bit-scores, feature response curves and the ability to distinguish paralogous or homeologous transcripts, indicated that the EvidentialGene processed assembly was of high quality. Of 35 RNA silencing gene transcripts, 34 were identified as assembled to full length, whereas in a previous assembly using only one assembler, 9 of these were partially assembled. Conclusions To achieve a high quality transcriptome, it is advantageous to implement and combine the output from as many different de novo assemblers as possible. We have in essence taking the ‘best’ output from each assembler while minimising sequence redundancy. We have also shown that simultaneous assessment of a variety of metrics, not just focused on contig length, is necessary to gauge the quality of assemblies.

Fractal and complex network analyses of protein molecular dynamics

Based on protein molecular dynamics, we investigate the fractal properties of energy, pressure and volume time series using the multifractal detrended fluctuation analysis (MF-DFA) and the topological and fractal properties of their converted horizontal visibility graphs (HVGs). The energy parameters of protein dynamics we considered are bonded potential, angle potential, dihedral potential, improper potential, kinetic energy, Van der Waals potential, electrostatic potential, total energy and potential energy. The shape of the h(q)h(q) curves from MF-DFA indicates that these time series are multifractal. The numerical values of the exponent h(2)h(2) of MF-DFA show that the series of total energy and potential energy are non-stationary and anti-persistent; the other time series are stationary and persistent apart from series of pressure (with H≈0.5H≈0.5 indicating the absence of long-range correlation). The degree distributions of their converted HVGs show that these networks are exponential. The results of fractal analysis show that fractality exists in these converted HVGs. For each energy, pressure or volume parameter, it is found that the values of h(2)h(2) of MF-DFA on the time series, exponent λλ of the exponential degree distribution and fractal dimension dBdB of their converted HVGs do not change much for different proteins (indicating some universality). We also found that after taking average over all proteins, there is a linear relationship between 〈h(2)〉〈h(2)〉 (from MF-DFA on time series) and 〈dB〉〈dB〉 of the converted HVGs for different energy, pressure and volume.

Underlying scaling relationships between solar activity and geomagnetic activity revealed by multifractal analyses

his paper identifies some scaling relationships between solar activity and geomagnetic activity. We examine the scaling properties of hourly data for two geomagnetic indices (ap and AE), two solar indices (solar X-rays Xl and solar flux F10.7), and two inner heliospheric indices (ion density Ni and flow speed Vs) over the period 1995–2001 by the universal multifractal approach and the traditional multifractal analysis. We found that the universal multifractal model (UMM) provides a good fit to the empirical K(q) and τ(q) curves of these time series. The estimated values of the Lévy index α in the UMM indicate that multifractality exists in the time series for ap, AE, Xl, and Ni, while those for F10.7 and Vs are monofractal. The estimated values of the nonconservation parameter H of this model confirm that these time series are conservative which indicate that the mean value of the process is constant for varying resolution. Additionally, the multifractal K(q) and τ(q) curves, and the estimated values of the sparseness parameter C1 of the UMM indicate that there are three pairs of indices displaying similar scaling properties, namely ap and Xl, AE and Ni, and F10.7 and Vs. The similarity in the scaling properties of pairs (ap,Xl) and (AE,Ni) suggests that ap and Xl, AE and Ni are better correlated—in terms of scaling—than previous thought, respectively. But our results still cannot be used to advance forecasting of ap and AE by Xl and Ni, respectively, due to some reasons

Simulating the dissipation of two herbicides using micro paddy lysimeters

A set of packed micro paddy lysimeters, placed in a greenhouse, was used to simulate the dissipation of two herbicides, simetryn and thiobencarb, in a controlled environment. Data from a field monitoring study in 2003, including the soil condition and water balances, were used in the simulation. The herbicides were applied and monitored over a period of 21 d. The water balances under two water management scenarios, intermittent irrigation management (AI) and continuous irrigation management (CI), were simulated. In the AI scenario, the pattern of herbicide dissipation in the surface water of the field were simulated, following the first-order kinetics. In the CI scenario, similarity was observed in most lysimeter and field concentrations, but there were differences in some data points. Dissipation curves of both herbicides in the surface water of the two simulated scenarios were not significantly different (P > 0.05) from the field data except for intercept of the thiobencarb curve in the CI scenario. The distribution of simetryn and thiobencarb in the soil profile after simulation were also similar to the field data. The highest concentrations of both herbicides were found on the topsoil layer at 0-2.5 cm depth. Only a small amount of herbicides moved down to the deeper soil layers. Micro paddy lysimeters are thus a good alternative for the dissipation study of pesticides in the paddy environment.

Finite element analysis investigation of response of pumpkin tissue under uniaxial loading

Finite element analysis (FEA) models of uniaxial loading of pumpkin peel and flesh tissues were developed and validated using experimental results. The tensile model was developed for both linear elastic and plastic material models, the compression model was develop d only with the plastic material model. The outcomes of force versus time curves obtained from FEA models followed similar pattern to the experimental curves however the curve resulted with linear elastic material properties had a higher difference with the experimental curves. The values of predicted forces were determined and compared with the experimental curve. An error indicator was introduced and computed for each case and compared. Additionally Root Mean Square Error (RMSE) values were also calculated for each model and compared. The results of modelling were used to develop material model for peel and flesh tissues in FEA modelling of mechanical peeling of tough skinned vegetables.

Melanopsin mediated post-illumination pupil response in early age-related macular degeneration

Purpose To determine whether melanopsin expressing intrinsically photosensitive Retinal Ganglion Cell (ipRGC) inputs to the pupil light reflex (PLR) are affected in early age-related macular degeneration (AMD). Methods The PLR was measured in 40 participants (20 early AMD and 20 age-matched controls) using a custom-built Maxwellian-view pupillometer. Sinusoidal stimuli (0.5 Hz, 11.9 s duration, 35.6° diameter) were presented to the study eye and the consensual pupil response was measured for stimuli with high melanopsin excitation (464nm; blue) and with low melanopsin excitation (638 nm; red) that biased activation to the outer retina. Two melanopsin PLR metrics were quantified: the Phase Amplitude Percentage (PAP) during the sinusoidal stimulus presentation and the Post-Illumination Pupil Response (PIPR). The PLR during stimulus presentation was analyzed using latency to constriction, transient pupil response and maximum pupil constriction metrics. Diagnostic accuracy was evaluated using receiver operating characteristic (ROC) curves. Results The blue PIPR was significantly less sustained in the early AMD group (p<0.001). The red PIPR was not significantly different between groups (p>0.05). The PAP and blue stimulus constriction amplitude were significantly lower in the early AMD group (p < 0.05). There was no significant difference between groups in the latency or transient amplitude for both stimuli (p>0.05). ROC analysis showed excellent diagnostic accuracy for the blue PIPR metrics (AUC>0.9). Conclusions This is the initial report that the melanopsin controlled PIPR is dysfunctional in early AMD. The non-invasive, objective measurement of the ipRGC controlled PIPR has excellent diagnostic accuracy for early AMD.

An experimental study on anisotropic mechanical properties of porcine thoracic aorta

Objective: To study the anisotropic mechanical properties of the thoracic aorta in porcine. Methods: Twenty-one porcine thoracic aortas were collected and categorized into three groups. The aortas were then cut through in their axial directions and expanded into two-dimensional planes. Then, by setting the length direction of the planar aortas (i.e., axial directions of the aortas) as 0°, each planar aorta was counterclockwisely cut into 8 samples with orientation of 30°, 45°, 60°, 90°, 120°, 135°, 150° and 180°, respectively. Finally, the uniaxial tensile tests were applied on three groups of samples at the loading rates of 1, 5 and 10 mm/min, respectively, to obtain the elastic modulus and ultimate stress of the aorta in different directions and at different loading rates. Results: The stress-strain curves exhibited different viscoelastic behaviors. With the increase of sample orientations, the elastic modulus gradually increased from 30°, reached the maximum value at 90°, and then gradually decreased till 180°. The variation trend of ultimate stress was similar to that of elastic modulus. Moreover, different loading rates showed a significant influence on the results of elastic modulus and ultimate stress, but a weak influence on the anisotropic degree. Conclusions: The porcine thoracic aorta is highly anisotropic. This research finding provides parameter references for assignment of material properties in finite element modeling, and is significant for understanding biomechanical properties of the arteries.

A pilot study in different unstable designs on the biomechanical effect of gait characteristics

The purpose of this study was to compare kinematics and kinetics during walking for healthy subjects using unstable shoes with different designs. Ten subjects participated in this study, and foot biomechanical data during walking were quantified using motion analysis system and a force plate. Data were collected for unstable shoes condition after accommodation period of one week. With soft material added in the heel region, the peak impact force was effectively reduced when compared among similar shapes. In addition, the soft material added in the rocker bottom showed more to be in dorsiflexed position during the initial stance. The shoe with three rocker curves design reduced the contact area in the heel strike, which may result in increasing human body forward speed. Further studies shall be carried out after adapting to long periods of wearing unstable shoes.

On Visual Detection of Highly-occluded Objects for Harvesting Automation in Horticulture

Developing accurate and reliable crop detection algorithms is an important step for harvesting automation in horticulture. This paper presents a novel approach to visual detection of highly-occluded fruits. We use a conditional random field (CRF) on multi-spectral image data (colour and Near-Infrared Reflectance, NIR) to model two classes: crop and background. To describe these two classes, we explore a range of visual-texture features including local binary pattern, histogram of oriented gradients, and learn auto-encoder features. The pro-posed methods are evaluated using hand-labelled images from a dataset captured on a commercial capsicum farm. Experimental results are presented, and performance is evaluated in terms of the Area Under the Curve (AUC) of the precision-recall curves.Our current results achieve a maximum performance of 0.81AUC when combining all of the texture features in conjunction with colour information.

Statistical modelling and power analysis for detecting trends in total suspended sediment loads

The export of sediments from coastal catchments can have detrimental impacts on estuaries and near shore reef ecosystems such as the Great Barrier Reef. Catchment management approaches aimed at reducing sediment loads require monitoring to evaluate their effectiveness in reducing loads over time. However, load estimation is not a trivial task due to the complex behaviour of constituents in natural streams, the variability of water flows and often a limited amount of data. Regression is commonly used for load estimation and provides a fundamental tool for trend estimation by standardising the other time specific covariates such as flow. This study investigates whether load estimates and resultant power to detect trends can be enhanced by (i) modelling the error structure so that temporal correlation can be better quantified, (ii) making use of predictive variables, and (iii) by identifying an efficient and feasible sampling strategy that may be used to reduce sampling error. To achieve this, we propose a new regression model that includes an innovative compounding errors model structure and uses two additional predictive variables (average discounted flow and turbidity). By combining this modelling approach with a new, regularly optimised, sampling strategy, which adds uniformity to the event sampling strategy, the predictive power was increased to 90%. Using the enhanced regression model proposed here, it was possible to detect a trend of 20% over 20 years. This result is in stark contrast to previous conclusions presented in the literature. (C) 2014 Elsevier B.V. All rights reserved.

Generalised growth models for aquatic species with an application to blacklip abalone (Haliotis rubra)

This paper presents a maximum likelihood method for estimating growth parameters for an aquatic species that incorporates growth covariates, and takes into consideration multiple tag-recapture data. Individual variability in asymptotic length, age-at-tagging, and measurement error are also considered in the model structure. Using distribution theory, the log-likelihood function is derived under a generalised framework for the von Bertalanffy and Gompertz growth models. Due to the generality of the derivation, covariate effects can be included for both models with seasonality and tagging effects investigated. Method robustness is established via comparison with the Fabens, improved Fabens, James and a non-linear mixed-effects growth models, with the maximum likelihood method performing the best. The method is illustrated further with an application to blacklip abalone (Haliotis rubra) for which a strong growth-retarding tagging effect that persisted for several months was detected

Sediment concentration prediction and statistical evaluation for annual load estimation

We consider the development of statistical models for prediction of constituent concentration of riverine pollutants, which is a key step in load estimation from frequent flow rate data and less frequently collected concentration data. We consider how to capture the impacts of past flow patterns via the average discounted flow (ADF) which discounts the past flux based on the time lapsed - more recent fluxes are given more weight. However, the effectiveness of ADF depends critically on the choice of the discount factor which reflects the unknown environmental cumulating process of the concentration compounds. We propose to choose the discount factor by maximizing the adjusted R-2 values or the Nash-Sutcliffe model efficiency coefficient. The R2 values are also adjusted to take account of the number of parameters in the model fit. The resulting optimal discount factor can be interpreted as a measure of constituent exhaustion rate during flood events. To evaluate the performance of the proposed regression estimators, we examine two different sampling scenarios by resampling fortnightly and opportunistically from two real daily datasets, which come from two United States Geological Survey (USGS) gaging stations located in Des Plaines River and Illinois River basin. The generalized rating-curve approach produces biased estimates of the total sediment loads by -30% to 83%, whereas the new approaches produce relatively much lower biases, ranging from -24% to 35%. This substantial improvement in the estimates of the total load is due to the fact that predictability of concentration is greatly improved by the additional predictors.