Blast response and failure analysis of pile foundations subjected to surface explosion

This paper presents the response of pile foundations to ground shocks induced by surface explosion using fully coupled and non-linear dynamic computer simulation techniques together with different material models for the explosive, air, soil and pile. It uses the Arbitrary Lagrange Euler coupling formulation with proper state material parameters and equations. Blast wave propagation in soil, horizontal pile deformation and pile damage are presented to facilitate failure evaluation of piles. Effects of end restraint of pile head and the number and spacing of piles within a group on their blast response and potential failure are investigated. The techniques developed and applied in this paper and its findings provide valuable information on the blast response and failure evaluation of piles and will provide guidance in their future analysis and design.

A transcriptomic analysis of striped catfish (Pangasianodon hypophthalmus) in response to salinity adaptation: De novo assembly, gene annotation and marker discovery

The striped catfish (Pangasianodon hypophthalmus) culture industry in the Mekong Delta in Vietnam has developed rapidly over the past decade. The culture industry now however, faces some significant challenges, especially related to climate change impacts notably from predicted extensive saltwater intrusion into many low topographical coastal provinces across the Mekong Delta. This problem highlights a need for development of culture stocks that can tolerate more saline culture environments as a response to expansion of saline water-intruded land. While a traditional artificial selection program can potentially address this need, understanding the genomic basis of salinity tolerance can assist development of more productive culture lines. The current study applied a transcriptomic approach using Ion PGM technology to generate expressed sequence tag (EST) resources from the intestine and swim bladder from striped catfish reared at a salinity level of 9 ppt which showed best growth performance. Total sequence data generated was 467.8 Mbp, consisting of 4,116,424 reads with an average length of 112 bp. De novo assembly was employed that generated 51,188 contigs, and allowed identification of 16,116 putative genes based on the GenBank non-redundant database. GO annotation, KEGG pathway mapping, and functional annotation of the EST sequences recovered with a wide diversity of biological functions and processes. In addition, more than 11,600 simple sequence repeats were also detected. This is the first comprehensive analysis of a striped catfish transcriptome, and provides a valuable genomic resource for future selective breeding programs and functional or evolutionary studies of genes that influence salinity tolerance in this important culture species.

Security analysis of the non-aggressive challenge response of the DNP3 Protocol using a CPN Model

Distributed Network Protocol Version 3 (DNP3) is the de-facto communication protocol for power grids. Standard-based interoperability among devices has made the protocol useful to other infrastructures such as water, sewage, oil and gas. DNP3 is designed to facilitate interaction between master stations and outstations. In this paper, we apply a formal modelling methodology called Coloured Petri Nets (CPN) to create an executable model representation of DNP3 protocol. The model facilitates the analysis of the protocol to ensure that the protocol will behave as expected. Also, we illustrate how to verify and validate the behaviour of the protocol, using the CPN model and the corresponding state space tool to determine if there are insecure states. With this approach, we were able to identify a Denial of Service (DoS) attack against the DNP3 protocol.

Comparative analysis of the Metarhizium anisopliae secretome in response to exposure to the greyback cane grub and grub cuticles

Metarhizium anisopliae is a well-characterized biocontrol agent of a wide range of insects including cane grubs. In this study, a two-dimensional (2D) electrophoresis was used to display secreted proteins of M. anisopliae strain FI-1045 growing on the whole greyback cane grubs and their isolated cuticles. Hydrolytic enzymes secreted by M. anisopliae play a key role in insect cuticle-degradation and initiation of the infection process. We have identified all the 101 protein spots displayed by cross-species identification (CSI) from the fungal kingdom. Among the identified proteins were 64-kDa serine carboxypeptidase, 1,3 beta-exoglucanase, Dynamin GTPase, THZ kinase, calcineurin like phosphoesterase, and phosphatidylinositol kinase secreted by M. ansiopliae (FI-1045) in response to exposure to the greyback cane grubs and their isolated cuticles. These proteins have not been previously identified from the culture supernatant of M. anisopliae during infection. To our knowledge, this the first proteomic map established to study the extracellular proteins secreted by M. ansiopliae (FI-1045) during infection of greyback cane grubs and its cuticles.

Blast response and sensitivity analysis of segmental tunnel

This research treated the response of underground transportation tunnels to surface blast loads using advanced computer simulation techniques. The influences of important parameters, such as tunnel material, geometrical configuration of segments and surrounding soil were investigated. The findings of this research offer significant new information on the blast performance of underground tunnels and will contribute towards future civil engineering applications.

Side Channel Analysis of Some Hash Based MACs: A Response to SHA-3 Requirements

The forthcoming NIST’s Advanced Hash Standard (AHS) competition to select SHA-3 hash function requires that each candidate hash function submission must have at least one construction to support FIPS 198 HMAC application. As part of its evaluation, NIST is aiming to select either a candidate hash function which is more resistant to known side channel attacks (SCA) when plugged into HMAC, or that has an alternative MAC mode which is more resistant to known SCA than the other submitted alternatives. In response to this, we perform differential power analysis (DPA) on the possible smart card implementations of some of the recently proposed MAC alternatives to NMAC (a fully analyzed variant of HMAC) and HMAC algorithms and NMAC/HMAC versions of some recently proposed hash and compression function modes. We show that the recently proposed BNMAC and KMDP MAC schemes are even weaker than NMAC/HMAC against the DPA attacks, whereas multi-lane NMAC, EMD MAC and the keyed wide-pipe hash have similar security to NMAC against the DPA attacks. Our DPA attacks do not work on the NMAC setting of MDC-2, Grindahl and MAME compression functions.

Frequency response function based damage identification using principal component analysis and pattern recognition technique

Pattern recognition is a promising approach for the identification of structural damage using measured dynamic data. Much of the research on pattern recognition has employed artificial neural networks (ANNs) and genetic algorithms as systematic ways of matching pattern features. The selection of a damage-sensitive and noise-insensitive pattern feature is important for all structural damage identification methods. Accordingly, a neural networks-based damage detection method using frequency response function (FRF) data is presented in this paper. This method can effectively consider uncertainties of measured data from which training patterns are generated. The proposed method reduces the dimension of the initial FRF data and transforms it into new damage indices and employs an ANN method for the actual damage localization and quantification using recognized damage patterns from the algorithm. In civil engineering applications, the measurement of dynamic response under field conditions always contains noise components from environmental factors. In order to evaluate the performance of the proposed strategy with noise polluted data, noise contaminated measurements are also introduced to the proposed algorithm. ANNs with optimal architecture give minimum training and testing errors and provide precise damage detection results. In order to maximize damage detection results, the optimal architecture of ANN is identified by defining the number of hidden layers and the number of neurons per hidden layer by a trial and error method. In real testing, the number of measurement points and the measurement locations to obtain the structure response are critical for damage detection. Therefore, optimal sensor placement to improve damage identification is also investigated herein. A finite element model of a two storey framed structure is used to train the neural network. It shows accurate performance and gives low error with simulated and noise-contaminated data for single and multiple damage cases. As a result, the proposed method can be used for structural health monitoring and damage detection, particularly for cases where the measurement data is very large. Furthermore, it is suggested that an optimal ANN architecture can detect damage occurrence with good accuracy and can provide damage quantification with reasonable accuracy under varying levels of damage.

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.

Analysis of a Genomic DNA Expression Library of Mycobacterium tuberculosis Using Tuberculosis Patient Sera: Evidence for Modulation of Host Immune Response

DNA obtained from a human sputum isolate of Mycobacterium tuberculosis, NTI-64719, which showed extensive dissemination in the guinea pig model resulting in a high score for virulence was used to construct an expression library in the lambda ZAP vector. The size of DNA inserts in the library ranged from 1 to 3 kb, and recombinants represented 60% of the total plaques obtained. When probed with pooled serum from chronically infected tuberculosis patients, the library yielded 176 recombinants with a range of signal intensities. Among these, 93 recombinants were classified into 12 groups on the basis of DNA hybridization experiments, The polypeptides synthesized by the recombinants were predominantly LacZ fusion proteins, Serum obtained from patients who were clinically diagnosed to be in the early phase of M. tuberculosis infection was used to probe the 176 recombinants obtained. interestingly, some recombinants that gave very strong signals in the original screen did not react with early-phase serum; conversely, others whose signals were extremely weak in the original screen gave very intense signals with serum from recently infected patients, This indicates the differential nature of either the expression of these antigens or the immune response elicited by them as a function of disease progression.

Finite element analysis of deep transverse metatarsal ligaments mechanical response during landing

The deep transverse metatarsal ligaments (DTML) play an important role in stabilizing the metatarsal bones and manipulating foot transverse arch deformation. However, the biomechanical research about DTML in the foot maneuver is quite few. Due to the difficulties and lack of better measurement technology for these ligaments experimental monitor, the load transfer mechanism and internal stress state also hadn't been well addressed. The purpose of this study was to develop a detailing foot finite element model including DTML tissues, to investigate the mechanical response of DTML during the landing condition. The DTML was considered as hyperelastic material model was used to represent the nonlinear and nearly incompressible nature of the ligament tissue. From the simulation results, it is clearly to find that the peak maiximal principal stress of DTML was between the third and fourth metatarsals. Meanwhile, it seems the DTML in the middle position experienced higher tension than the sides DTML.

Blast response and failure analysis of a segmented buried tunnel

Underground tunnels are vulnerable to terrorist attacks which can cause collapse of the tunnel structures or at least extensive damage, requiring lengthy repairs. This paper treats the blast impact on a reinforced concrete segmental tunnel buried in soil under a number of parametric conditions; soil properties, soil cover, distance of explosive from the tunnel centreline and explosive weight and analyses the possible failure patterns. A fully coupled Fluid Structure Interaction (FSI) technique incorporating the Arbitrary Lagrangian-Eulerian (ALE) method is used in this study. Results indicate that the tunnel in saturated soil is more vulnerable to severe damage than that buried in either partially saturated soil or dry soil. The tunnel is also more vulnerable to surface explosions which occur directly above the centre of the tunnel than those that occur at any equivalent distances in the ground away from the tunnel centre. The research findings provide useful information on modeling, analysis, overall tunnel response and failure patterns of segmented tunnels subjected to blast loads. This information will guide future development and application of research in this field.

Promoting articulated action from diverse stakeholders in response to public policy scenarios: A case analysis of the use of ‘scenario improvisation’ method

In this paper we present a novel application of scenario methods to engage a diverse constituency of senior stakeholders, with limited time availability, in debate to inform planning and policy development. Our case study project explores post-carbon futures for the Latrobe Valley region of the Australian state of Victoria. Our approach involved initial deductive development of two ‘extreme scenarios’ by a multi-disciplinary research team, based upon an extensive research programme. Over four workshops with the stakeholder constituency, these initial scenarios were discussed, challenged, refined and expanded through an inductive process, whereby participants took ‘ownership’ of a final set of three scenarios. These were both comfortable and challenging to them. The outcomes of this process subsequently informed public policy development for the region. Whilst this process did not follow a single extant structured, multi-stage scenario approach, neither was it devoid of form. Here, we seek to theorise and codify elements of our process – which we term ‘scenario improvisation’ – such that others may adopt it.