Impact response and parametric studies of reinforced concrete circular columns

This paper presents a detailed description of the influence of critical parameters that govern the vulnerability of columns under lateral impact loads. Numerical simulations are conducted by using the Finite Element program LS-DYNA, incorporating steel reinforcement, material models and strain rate effects. A simplified method based on impact pulse generated from full scale impact tests is used for impact reconstruction and effects of the various pulse loading parameters are investigated under low to medium velocity impacts. A constitutive material model which can simulate failures under tri-axial state of stresses is used for concrete. Confinement effects are also introduced to the numerical simulation and columns of Grade 30 to 50 concrete under pure axial loading are analysed in detail. This research confirmed that the vulnerability of the axially loaded columns can be mitigated by reducing the slenderness ratio and concrete grade, and by choosing the design option with a minimal amount of longitudinal steel. Additionally, it is evident that approximately a 50% increase in impact capacity can be gained for columns in medium rise buildings by enhancing the confinement effects alone. Results also indicated that the ductility as well as the mode of failure under impact can be changed with the volumetric ratio of lateral steel. Moreover, to increase the impact capacity of the vulnerable columns, a higher confining stress is required. The general provisions of current design codes do not sufficiently cover this aspect and hence this research will provide additional guidelines to overcome the inadequacies of code provisions.

Parametric building development during early design stage

Objectives The objectives of this project were two-fold: • Assess the ease with which current architectural CAD systems supported the use ofparametric descriptions in defining building shape, engineering system performance and cost at the early stages of building design; • Assess the feasibility of implementing a software decision support system that allowed designers to trade-off the characteristics and configuration of various engineering systems to move towards a “global optimum” rather than considering each system in isolation and expecting humans to weigh up all of the costs and benefits. The first stage of the project consisted of using four different CAD systems to define building shells (envelopes) with different usages. These models were then exported into a shared database using the IFC information exchange specifications. The second stage involved the implementation of small computer programs that were able to estimate relevant system parameters based on performance requirements and the constraints imposed by the other systems. These are presented in a unified user interface that extracts the appropriate building shape parameters from the shared database Note that the term parametric in this context refers to the relationships among and between all elements of the building model - not just geometric associations - which will enable the desired coordination.

Mining trading partners’ preferences for efficient multi-issue bargaining in E‑business

Classical negotiation models are weak in supporting real-world business negotiations because these models often assume that the preference information of each negotiator is made public. Although parametric learning methods have been proposed for acquiring the preference information of negotiation opponents, these methods suffer from the strong assumptions about the specific utility function and negotiation mechanism employed by the opponents. Consequently, it is difficult to apply these learning methods to the heterogeneous negotiation agents participating in e‑marketplaces. This paper illustrates the design, development, and evaluation of a nonparametric negotiation knowledge discovery method which is underpinned by the well-known Bayesian learning paradigm. According to our empirical testing, the novel knowledge discovery method can speed up the negotiation processes while maintaining negotiation effectiveness. To the best of our knowledge, this is the first nonparametric negotiation knowledge discovery method developed and evaluated in the context of multi-issue bargaining over e‑marketplaces.

The impact of child sexual abuse on victims/survivors: Exploring posttraumatic outcomes as a function of childhood sexual abuse

There is sparse systematic examination of the potential for growth as well as distress that may occur for some adult survivors of childhood sexual abuse. The presented study explored posttraumatic growth and its relationship with negative posttrauma outcomes within the specific population of survivors of childhood sexual abuse (N = 40). Results showed that 95% of the participants experienced clinically significant post-traumatic stress disorder symptomatology related to their childhood sexual abuse. In conjunction with these high levels of negative symptoms, the population evidenced posttraumatic growth levels that were comparable to other trauma samples. This research has clinical relevance in terms of adding to the knowledge base on sexual abuse and the usefulness of this knowledge in therapeutic interventions and relationships.

Molecular architecture of the human sinus node: insights into the function of the cardiac pacemaker.

BACKGROUND: Although we know much about the molecular makeup of the sinus node (SN) in small mammals, little is known about it in humans. The aims of the present study were to investigate the expression of ion channels in the human SN and to use the data to predict electrical activity. METHODS AND RESULTS: Quantitative polymerase chain reaction, in situ hybridization, and immunofluorescence were used to analyze 6 human tissue samples. Messenger RNA (mRNA) for 120 ion channels (and some related proteins) was measured in the SN, a novel paranodal area, and the right atrium (RA). The results showed, for example, that in the SN compared with the RA, there was a lower expression of Na(v)1.5, K(v)4.3, K(v)1.5, ERG, K(ir)2.1, K(ir)6.2, RyR2, SERCA2a, Cx40, and Cx43 mRNAs but a higher expression of Ca(v)1.3, Ca(v)3.1, HCN1, and HCN4 mRNAs. The expression pattern of many ion channels in the paranodal area was intermediate between that of the SN and RA; however, compared with the SN and RA, the paranodal area showed greater expression of K(v)4.2, K(ir)6.1, TASK1, SK2, and MiRP2. Expression of ion channel proteins was in agreement with expression of the corresponding mRNAs. The levels of mRNA in the SN, as a percentage of those in the RA, were used to estimate conductances of key ionic currents as a percentage of those in a mathematical model of human atrial action potential. The resulting SN model successfully produced pacemaking. CONCLUSIONS: Ion channels show a complex and heterogeneous pattern of expression in the SN, paranodal area, and RA in humans, and the expression pattern is appropriate to explain pacemaking.

Intelligent prognostics of machinery health utilising suspended condition monitoring data

The ability to forecast machinery failure is vital to reducing maintenance costs, operation downtime and safety hazards. Recent advances in condition monitoring technologies have given rise to a number of prognostic models for forecasting machinery health based on condition data. Although these models have aided the advancement of the discipline, they have made only a limited contribution to developing an effective machinery health prognostic system. The literature review indicates that there is not yet a prognostic model that directly models and fully utilises suspended condition histories (which are very common in practice since organisations rarely allow their assets to run to failure); that effectively integrates population characteristics into prognostics for longer-range prediction in a probabilistic sense; which deduces the non-linear relationship between measured condition data and actual asset health; and which involves minimal assumptions and requirements. This work presents a novel approach to addressing the above-mentioned challenges. The proposed model consists of a feed-forward neural network, the training targets of which are asset survival probabilities estimated using a variation of the Kaplan-Meier estimator and a degradation-based failure probability density estimator. The adapted Kaplan-Meier estimator is able to model the actual survival status of individual failed units and estimate the survival probability of individual suspended units. The degradation-based failure probability density estimator, on the other hand, extracts population characteristics and computes conditional reliability from available condition histories instead of from reliability data. The estimated survival probability and the relevant condition histories are respectively presented as “training target” and “training input” to the neural network. The trained network is capable of estimating the future survival curve of a unit when a series of condition indices are inputted. Although the concept proposed may be applied to the prognosis of various machine components, rolling element bearings were chosen as the research object because rolling element bearing failure is one of the foremost causes of machinery breakdowns. Computer simulated and industry case study data were used to compare the prognostic performance of the proposed model and four control models, namely: two feed-forward neural networks with the same training function and structure as the proposed model, but neglected suspended histories; a time series prediction recurrent neural network; and a traditional Weibull distribution model. The results support the assertion that the proposed model performs better than the other four models and that it produces adaptive prediction outputs with useful representation of survival probabilities. This work presents a compelling concept for non-parametric data-driven prognosis, and for utilising available asset condition information more fully and accurately. It demonstrates that machinery health can indeed be forecasted. The proposed prognostic technique, together with ongoing advances in sensors and data-fusion techniques, and increasingly comprehensive databases of asset condition data, holds the promise for increased asset availability, maintenance cost effectiveness, operational safety and – ultimately – organisation competitiveness.

The statistics of refractive error maps : managing wavefront aberration analysis without Zernike polynomials

The refractive error of a human eye varies across the pupil and therefore may be treated as a random variable. The probability distribution of this random variable provides a means for assessing the main refractive properties of the eye without the necessity of traditional functional representation of wavefront aberrations. To demonstrate this approach, the statistical properties of refractive error maps are investigated. Closed-form expressions are derived for the probability density function (PDF) and its statistical moments for the general case of rotationally-symmetric aberrations. A closed-form expression for a PDF for a general non-rotationally symmetric wavefront aberration is difficult to derive. However, for specific cases, such as astigmatism, a closed-form expression of the PDF can be obtained. Further, interpretation of the distribution of the refractive error map as well as its moments is provided for a range of wavefront aberrations measured in real eyes. These are evaluated using a kernel density and sample moments estimators. It is concluded that the refractive error domain allows non-functional analysis of wavefront aberrations based on simple statistics in the form of its sample moments. Clinicians may find this approach to wavefront analysis easier to interpret due to the clinical familiarity and intuitive appeal of refractive error maps.

Mathematical modelling of muscle recruitment and function in the lumbar spine

Low back pain is an increasing problem in industrialised countries and although it is a major socio-economic problem in terms of medical costs and lost productivity, relatively little is known about the processes underlying the development of the condition. This is in part due to the complex interactions between bone, muscle, nerves and other soft tissues of the spine, and the fact that direct observation and/or measurement of the human spine is not possible using non-invasive techniques. Biomechanical models have been used extensively to estimate the forces and moments experienced by the spine. These models provide a means of estimating the internal parameters which can not be measured directly. However, application of most of the models currently available is restricted to tasks resembling those for which the model was designed due to the simplified representation of the anatomy. The aim of this research was to develop a biomechanical model to investigate the changes in forces and moments which are induced by muscle injury. In order to accurately simulate muscle injuries a detailed quasi-static three dimensional model representing the anatomy of the lumbar spine was developed. This model includes the nine major force generating muscles of the region (erector spinae, comprising the longissimus thoracis and iliocostalis lumborum; multifidus; quadratus lumborum; latissimus dorsi; transverse abdominis; internal oblique and external oblique), as well as the thoracolumbar fascia through which the transverse abdominis and parts of the internal oblique and latissimus dorsi muscles attach to the spine. The muscles included in the model have been represented using 170 muscle fascicles each having their own force generating characteristics and lines of action. Particular attention has been paid to ensuring the muscle lines of action are anatomically realistic, particularly for muscles which have broad attachments (e.g. internal and external obliques), muscles which attach to the spine via the thoracolumbar fascia (e.g. transverse abdominis), and muscles whose paths are altered by bony constraints such as the rib cage (e.g. iliocostalis lumborum pars thoracis and parts of the longissimus thoracis pars thoracis). In this endeavour, a separate sub-model which accounts for the shape of the torso by modelling it as a series of ellipses has been developed to model the lines of action of the oblique muscles. Likewise, a separate sub-model of the thoracolumbar fascia has also been developed which accounts for the middle and posterior layers of the fascia, and ensures that the line of action of the posterior layer is related to the size and shape of the erector spinae muscle. Published muscle activation data are used to enable the model to predict the maximum forces and moments that may be generated by the muscles. These predictions are validated against published experimental studies reporting maximum isometric moments for a variety of exertions. The model performs well for fiexion, extension and lateral bend exertions, but underpredicts the axial twist moments that may be developed. This discrepancy is most likely the result of differences between the experimental methodology and the modelled task. The application of the model is illustrated using examples of muscle injuries created by surgical procedures. The three examples used represent a posterior surgical approach to the spine, an anterior approach to the spine and uni-lateral total hip replacement surgery. Although the three examples simulate different muscle injuries, all demonstrate the production of significant asymmetrical moments and/or reduced joint compression following surgical intervention. This result has implications for patient rehabilitation and the potential for further injury to the spine. The development and application of the model has highlighted a number of areas where current knowledge is deficient. These include muscle activation levels for tasks in postures other than upright standing, changes in spinal kinematics following surgical procedures such as spinal fusion or fixation, and a general lack of understanding of how the body adjusts to muscle injuries with respect to muscle activation patterns and levels, rate of recovery from temporary injuries and compensatory actions by other muscles. Thus the comprehensive and innovative anatomical model which has been developed not only provides a tool to predict the forces and moments experienced by the intervertebral joints of the spine, but also highlights areas where further clinical research is required.

A comparison of executive function in very preterm and term infants at 8 months corrected age

Executive function (EF) emerges in infancy and continues to develop throughout childhood. Executive dysfunction is believed to contribute to learning and attention problems in children at school age. Children born very preterm are more prone to these problems than their full-term peers.

A parametric study of imaging subsurface objects using ground penetrating radar

A parametric study was carried out to investigate the effects on reconstructed images from a ground penetrating radar (GPR) due to (a) the centre frequency of the GPR excitation pulse, (b) the height of transmitting and receiving antennas above ground level, and (c) the proximity of the buried objects. An integrated software package was developed to streamline the computer simulation based on synthetic data generated by GPRMax.

Re-conceptualising IS function's support performance : a preliminary model

While IS function has gained widespread attention for over two decades, there is little consensus among information systems (IS) researchers and practitioners on how best to evaluate IS function's support performance. This paper reports on preliminary findings of a larger research effort proceeds from a central interest in the importance of evaluating IS function's support in organisations. This study is the first that attempts to re-conceptualise and conceive evaluate IS function's support as a multi- dimensional formative construct. We argue that a holistic measure for evaluating evaluate IS function's support should consist of dimensions that together assess the variety of the support functions and the quality of the support services provided to end-users. Thus, the proposed model consists of two halves, "Variety" and "Quality" within which resides seven dimensions. The Variety half includes five dimensions: Training; Documentation; Data- related Support, Software-related Support; and Hardware-related Support. The Quality half includes two dimensions: IS Support Staff and Support Services Performance. The proposed model is derived using a directed content analysis of 83 studies; from top IS outlets, employing the characteristics of the analytic theory and consistent with formative construct development procedures.

Coding speech signals at very low rates (below 1 kb/s) with high intelligibility

This thesis presents an original approach to parametric speech coding at rates below 1 kbitsjsec, primarily for speech storage applications. Essential processes considered in this research encompass efficient characterization of evolutionary configuration of vocal tract to follow phonemic features with high fidelity, representation of speech excitation using minimal parameters with minor degradation in naturalness of synthesized speech, and finally, quantization of resulting parameters at the nominated rates. For encoding speech spectral features, a new method relying on Temporal Decomposition (TD) is developed which efficiently compresses spectral information through interpolation between most steady points over time trajectories of spectral parameters using a new basis function. The compression ratio provided by the method is independent of the updating rate of the feature vectors, hence allows high resolution in tracking significant temporal variations of speech formants with no effect on the spectral data rate. Accordingly, regardless of the quantization technique employed, the method yields a high compression ratio without sacrificing speech intelligibility. Several new techniques for improving performance of the interpolation of spectral parameters through phonetically-based analysis are proposed and implemented in this research, comprising event approximated TD, near-optimal shaping event approximating functions, efficient speech parametrization for TD on the basis of an extensive investigation originally reported in this thesis, and a hierarchical error minimization algorithm for decomposition of feature parameters which significantly reduces the complexity of the interpolation process. Speech excitation in this work is characterized based on a novel Multi-Band Excitation paradigm which accurately determines the harmonic structure in the LPC (linear predictive coding) residual spectra, within individual bands, using the concept 11 of Instantaneous Frequency (IF) estimation in frequency domain. The model yields aneffective two-band approximation to excitation and computes pitch and voicing with high accuracy as well. New methods for interpolative coding of pitch and gain contours are also developed in this thesis. For pitch, relying on the correlation between phonetic evolution and pitch variations during voiced speech segments, TD is employed to interpolate the pitch contour between critical points introduced by event centroids. This compresses pitch contour in the ratio of about 1/10 with negligible error. To approximate gain contour, a set of uniformly-distributed Gaussian event-like functions is used which reduces the amount of gain information to about 1/6 with acceptable accuracy. The thesis also addresses a new quantization method applied to spectral features on the basis of statistical properties and spectral sensitivity of spectral parameters extracted from TD-based analysis. The experimental results show that good quality speech, comparable to that of conventional coders at rates over 2 kbits/sec, can be achieved at rates 650-990 bits/sec.