Structural damage detection method using frequency response functions

Structural damage detection using measured dynamic data for pattern recognition is a promising approach. These pattern recognition techniques utilize artificial neural networks and genetic algorithm to match pattern features. In this study, an artificial neural network–based damage detection method using frequency response functions is presented, which can effectively detect nonlinear damages for a given level of excitation. The main objective of this article is to present a feasible method for structural vibration–based health monitoring, which reduces the dimension of the initial frequency response function data and transforms it into new damage indices and employs artificial neural network method for detecting different levels of nonlinearity using recognized damage patterns from the proposed algorithm. Experimental data of the three-story bookshelf structure at Los Alamos National Laboratory are used to validate the proposed method. Results showed that the levels of nonlinear damages can be identified precisely by the developed artificial neural networks. Moreover, it is identified that artificial neural networks trained with summation frequency response functions give higher precise damage detection results compared to the accuracy of artificial neural networks trained with individual frequency response functions. The proposed method is therefore a promising tool for structural assessment in a real structure because it shows reliable results with experimental data for nonlinear damage detection which renders the frequency response function–based method convenient for structural health monitoring.

Inorganic-organic composite particle as a staged delivery platform for plasmid DNA-based biopharmaceuticals

Infectious diseases such as SARS, influenza and bird flu may spread exponentially throughout communities. In fact, most infectious diseases remain major health risks due to the lack of vaccine or the lack of facilities to deliver the vaccines. Conventional vaccinations are based on damaged pathogens, live attenuated viruses and viral vectors. If the damage was not complete, the vaccination itself may cause adverse effects. Therefore, researchers have been prompted to prepare viable replacements for the attenuated vaccines that would be more effective and safer to use. DNA vaccines are generally composed of a double stranded plasmid that includes a gene encoding the target antigen under the transcriptional directory and control of a promoter region which is active in cells. Plasmid DNA (pDNA) vaccines allow the foreign genes to be expressed transiently in cells, mimicking intracellular pathogenic infection and inducing both humoral and cellular immune responses. Currently, because of their highly evolved and specialized components, viral systems are the most effective means for DNA delivery, and they achieve high efficiencies (generally >90%), for both DNA delivery and expression. As yet, viral-mediated deliveries have several limitations, including toxicity, limited DNA carrying capacity, restricted target to specific cell types, production and packing problems, and high cost. Thus, nonviral systems, particularly a synthetic DNA delivery system, are highly desirable in both research and clinical applications.

Effect of cell wall properties on porosity and shrinkage of dried apple

Water removal during drying depends on the pathway of water migration from food materials. Moreover, the water removal rate also depends on the characteristics of the cell wall of plant tissue. In this study, the influence of cell wall properties (such as moisture distribution, stiffness, thickness and cell dimension) on porosity and shrinkage of dried product was investigated. Cell wall stiffness depends on a complex combination of plant cell microstructure, composition of food materials and the water-holding capacity of the cell. In this work, a preliminary investigation of the cell wall properties of apple was conducted in order to predict changes of porosity and shrinkage during drying. Cell wall characteristics of two types of apple (Granny Smith and Red Delicious) were investigated under convective drying to correlate with porosity and shrinkage. A scanning electron microscope (SEM), 2kN Intron, pycnometer and ImageJ software were used in order to measure and analyse cell characteristics, water holding capacity of cell walls, porosity and shrinkage. The cell firmness of the Red Delicious apple was found to be higher than for Granny Smith apples. A remarkable relationship was observed between cell wall characteristics when compare with heat and mass transfer characteristics. It was also found that the evolution of porosity and shrinkage are noticeably influenced by the nature of the cell wall during convective drying. This study has revealed a better understanding of porosity and the shrinkage of dried food at microscopy (cell) level, and will provide better insights to attain energy-effective drying processes and improved quality of dried foods.

Marginal costs of hospital-acquired conditions : information for priority-setting for patient safety programmes and research

Objective: To estimate the relative inpatient costs of hospital-acquired conditions. Methods: Patient level costs were estimated using computerized costing systems that log individual utilization of inpatient services and apply sophisticated cost estimates from the hospital's general ledger. Occurrence of hospital-acquired conditions was identified using an Australian ‘condition-onset' flag for diagnoses not present on admission. These were grouped to yield a comprehensive set of 144 categories of hospital-acquired conditions to summarize data coded with ICD-10. Standard linear regression techniques were used to identify the independent contribution of hospital-acquired conditions to costs, taking into account the case-mix of a sample of acute inpatients (n = 1,699,997) treated in Australian public hospitals in Victoria (2005/06) and Queensland (2006/07). Results: The most costly types of complications were post-procedure endocrine/metabolic disorders, adding AU$21,827 to the cost of an episode, followed by MRSA (AU$19,881) and enterocolitis due to Clostridium difficile (AU$19,743). Aggregate costs to the system, however, were highest for septicaemia (AU$41.4 million), complications of cardiac and vascular implants other than septicaemia (AU$28.7 million), acute lower respiratory infections, including influenza and pneumonia (AU$27.8 million) and UTI (AU$24.7 million). Hospital-acquired complications are estimated to add 17.3% to treatment costs in this sample. Conclusions: Patient safety efforts frequently focus on dramatic but rare complications with very serious patient harm. Previous studies of the costs of adverse events have provided information on ‘indicators’ of safety problems rather than the full range of hospital-acquired conditions. Adding a cost dimension to priority-setting could result in changes to the focus of patient safety programmes and research. Financial information should be combined with information on patient outcomes to allow for cost-utility evaluation of future interventions.

Interrogating Creative Theory and Creative Work: Inside the Games Studio

The expansion of creative and cultural industries has provided a rich source for theoretical claims and commentary. Much of this reproduces and extends the idea that autonomy is the defining feature of both enterprises and workers. Drawing on evidence from research into Australian development studios in the global digital games industry, the article interrogates claims concerning autonomy and related issues of insecurity and intensity, skill and specialisation, work–play boundaries, identity and attachments. In seeking to reconnect changes in creative labour to the wider production environment and political economy, an argument is advanced that autonomy is deeply contextual and contested as a dimension of the processes of capturing value for firms and workers.

Injury narrative text classification using factorization model

Narrative text is a useful way of identifying injury circumstances from the routine emergency department data collections. Automatically classifying narratives based on machine learning techniques is a promising technique, which can consequently reduce the tedious manual classification process. Existing works focus on using Naive Bayes which does not always offer the best performance. This paper proposes the Matrix Factorization approaches along with a learning enhancement process for this task. The results are compared with the performance of various other classification approaches. The impact on the classification results from the parameters setting during the classification of a medical text dataset is discussed. With the selection of right dimension k, Non Negative Matrix Factorization-model method achieves 10 CV accuracy of 0.93.

Collective futures: How projections about the future of society are related to actions and attitudes supporting social change

We identified the active ingredients in people’s visions of society’s future (“collective futures”) that could drive political behavior in the present. In eight studies (N = 595), people imagined society in 2050 where climate change was mitigated (Study 1), abortion laws relaxed (Study 2), marijuana legalized (Study 3), or the power of different religious groups had increased (Studies 4-8). Participants rated how this future society would differ from today in terms of societal-level dysfunction and development (e.g., crime, inequality, education, technology), people’s character (warmth, competence, morality), and their values (e.g., conservation, self-transcendence). These measures were related to present-day attitudes/intentions that would promote/prevent this future (e.g., act on climate change, vote for a Muslim politician). A projection about benevolence in society (i.e., warmth/morality of people’s character) was the only dimension consistently and uniquely associated with present-day attitudes and intentions across contexts. Implications for social change theories, political communication, and policy design are discussed.

Self-regulation support through music

A critical dimension of early learning competence in the year prior to school is self-regulation. Self-regulation enables children to manage their emotions and direct their attention, thinking, and actions to meet adaptive goals. These skills enhance young children's readiness to learn.

Attributing and denying humanness to others

We review a programme of research on the attribution of humanness to people, and the ways in which lesser humanness is attributed to some compared to others. We first present evidence that humanness has two distinct senses, one representing properties that are unique to our species, and the other—human nature—those properties that are essential or fundamental to the human category. An integrative model of dehumanisation is then laid out, in which distinct forms of dehumanisation correspond to the denial of the two senses of humanness, and the likening of people to particular kinds of nonhuman entities (animals and machines). Studies demonstrating that human nature attributes are ascribed more to the self than to others are reviewed, along with evidence of the phenomenon’s cognitive and motivational basis. Research also indicates that both kinds of humanness are commonly denied to social groups, both explicitly and implicitly, and that they may cast a new light on the study of stereotype content. Our approach to the study of dehumanisation complements the tradition of research on infrahumanisation, and indicates new directions for exploring the importance of humanness as a dimension of social perception.

Theorizing why in digital learning: Opening frontiers for inquiry and innovation with technology

Asking why is an important foundation of inquiry and fundamental to the development of reasoning skills and learning. Despite this, and despite the relentless and often disruptive nature of innovations in information and communications technology (ICT), sophisticated tools that directly support this basic act of learning appear to be undeveloped, not yet recognized, or in the very early stages of development. Why is this so? To this question, there is no single factual answer. In response, however, plausible explanations and further questions arise, and such responses are shown to be typical consequences of why-questioning. A range of contemporary scenarios are presented to highlight the problem. Consideration of the various inputs into the evolution of digital learning is introduced to provide historical context and this serves to situate further discussion regarding innovation that supports inquiry-based learning. This theme is further contextualized by narratives on openness in education, in which openness is also shown to be an evolving construct. Explanatory and descriptive contents are differentiated in order to scope out the kinds of digital tools that might support inquiry instigated by why-questioning and which move beyond the search paradigm. Probing why from a linguistic perspective reveals versatile and ambiguous semantics. The why dimension—asking, learning, knowing, understanding, and explaining why—is introduced as a construct that highlights challenges and opportunities for ICT innovation. By linking reflective practice and dialogue with cognitive engagement, this chapter points to specific frontiers for the design and development of digital learning tools, frontiers in which inquiry may find new openings for support.

Peace education

Peace education can be most simply thought of as educating students to create a more peaceful world. However, just as peace needs to be thought of as more than merely the absence of war, so too peace education needs to be thought of as being more than educating students to understand the importance of avoiding war. Peace is the presence of justice, and thus a fuller definition of peace education is educating students to create a more just and harmonious world. Peace education may thought of as having an international dimension, that is, educating for peace and social justice between nation-states; as having a domestic dimension, that is, educating for peace and social justice within societies, groups and families; and as having a personal dimension, that is, educating for peace and justice in our individual personal relationships and educating for inner peace. Moreover, many writers now also see peace education as encompassing our inter-relationship with our natural environment. All these dimensions of peace education can be seen to be inter-related...

Exploring how adults who work with young children conceptualise sustainability and describe their practice initiatives

The development of early Childhood Education for Sustainability (ECEfS) practices with young children from birth to eight years is an emerging area in academic and professional literature. ECEfS practices reflect growing awareness of the imperative for twenty-first century societies to respond to the pressures of unsustainable patterns of living. This article contributes to the growing area of ECEfS research by exploring sustainability conceptualisations and practice initiatives as reported by early childhood teachers, educators, pre-service educators and parents in Tasmania. We do this by analysing data collected from participants who attended ECEfS professional learning workshops, entitled Living and learning about sustainability in the early years. Findings show that environmental (nature/natural) aspects of sustainability dominate these adults' practice initiatives and understandings. While many of the reported educational initiatives are to be celebrated, the authors contend that there is much work to be done to extend thinking and practice beyond the natural/environmental dimension in order to embrace holistic notions of sustainability incorporating social, economic and political dimensions.

Application of higher-order spectra for automated grading of diabetic maculopathy

Diabetic macular edema (DME) is one of the most common causes of visual loss among diabetes mellitus patients. Early detection and successive treatment may improve the visual acuity. DME is mainly graded into non-clinically significant macular edema (NCSME) and clinically significant macular edema according to the location of hard exudates in the macula region. DME can be identified by manual examination of fundus images. It is laborious and resource intensive. Hence, in this work, automated grading of DME is proposed using higher-order spectra (HOS) of Radon transform projections of the fundus images. We have used third-order cumulants and bispectrum magnitude, in this work, as features, and compared their performance. They can capture subtle changes in the fundus image. Spectral regression discriminant analysis (SRDA) reduces feature dimension, and minimum redundancy maximum relevance method is used to rank the significant SRDA components. Ranked features are fed to various supervised classifiers, viz. Naive Bayes, AdaBoost and support vector machine, to discriminate No DME, NCSME and clinically significant macular edema classes. The performance of our system is evaluated using the publicly available MESSIDOR dataset (300 images) and also verified with a local dataset (300 images). Our results show that HOS cumulants and bispectrum magnitude obtained an average accuracy of 95.56 and 94.39 % for MESSIDOR dataset and 95.93 and 93.33 % for local dataset, respectively.

Teachers-as-writers: Writing information texts in English and vernacular

Our contribution to this volume is not on the work of the teacher who inspires the child writer, but the teacher as the writer and illustrator of multilingual texts for classroom use that inspires the child reader. This chapter focuses on a first time teacher writer from Fiji, Bereta , who participated in a two day writing workshop known as the Information Text Awareness Project (hereafter ITAP). This chapter commences with an overview of the ITAP which was conducted in Nadi, Fiji, in 2012 with Bereta and 17 teachers from urban, semi-urban and rural contexts within the Nadi educational district. The politics of presenting Western ways of knowing to teachers from diverse cultural and linguistic contexts via a Western pedagogical approach is explored in the second section. We believe that this work involves a moral dimension that needs careful consideration. The third section outlines the eight stages of ITAP where teacher writers such as Bereta produced an English and a vernacular information text for use in their classrooms. The outline of the eight stages of ITAP is justified with links to the research literature. The final section recounts Bereta’s interview data where she talks about using the newly created English and vernacular information texts in the classroom and the community’s response to her inaugural publications. The findings may be of interest to those seeking to establish an adult writing cooperative to produce English and vernacular information texts for classroom use.

Transdimensional sequential Monte Carlo using variational Bayes — SMCVB

A new transdimensional Sequential Monte Carlo (SMC) algorithm called SM- CVB is proposed. In an SMC approach, a weighted sample of particles is generated from a sequence of probability distributions which ‘converge’ to the target distribution of interest, in this case a Bayesian posterior distri- bution. The approach is based on the use of variational Bayes to propose new particles at each iteration of the SMCVB algorithm in order to target the posterior more efficiently. The variational-Bayes-generated proposals are not limited to a fixed dimension. This means that the weighted particle sets that arise can have varying dimensions thereby allowing us the option to also estimate an appropriate dimension for the model. This novel algorithm is outlined within the context of finite mixture model estimation. This pro- vides a less computationally demanding alternative to using reversible jump Markov chain Monte Carlo kernels within an SMC approach. We illustrate these ideas in a simulated data analysis and in applications.