Geographies of children, youth and families: an international perspective

This edited collection brings together international experts from the vibrant and growing field of geographies of children, youth and families. The book provides an overview of current conceptual and theoretical debates, and gives a wide range of examples of cutting-edge research from a variety of national contexts across the globe. The theme of 'disentangling the socio-spatial contexts of young people and/or their families' advances debates in geographies and social studies of young people and families by emphasising the context of young people's social agency. The book is designed to provide an introduction to the topic of geographies of children, youth and families and is an invaluable course text for undergraduate and postgraduate students of geography and the social sciences. This interdisciplinary text is also of likely interest to students and practitioners of education, youth work, social policy and social work.

Construction management research: a field of application

Research in construction management is diverse in content and in quality. There is much to be learned from more fundamental disciplines. Construction is a sub-set of human experience rather than a completely separate phenomenon. Therefore, it is likely that there are few problems in construction requiring the invention of a completely new theory. If construction researchers base their work only on that of other construction researchers, our academic community will become less relevant to the world at large. The theories that we develop or test must be of wider applicability to be of any real interest. In undertaking research, researchers learn a lot about themselves. Perhaps the only difference between research and education is that if we are learning about something which no-one else knows, then it is research, otherwise it is education. Self-awareness of this will help to reduce the chances of publishing work which only reveals a researcher’s own learning curve. Scientific method is not as simplistic as non-scientists claim and is the only real way of overcoming methodological weaknesses in our work. The reporting of research may convey the false impression that it is undertaken in the sequence in which it is written. Construction is not so unique and special as to require a completely different set of methods from other fields of enquiry. Until our research is reported in mainstream journals and conferences, there is little chance that we will influence the wider academic community and a concomitant danger that it will become irrelevant. The most useful insights will come from research which challenges the current orthodoxy rather than research which merely reports it.

The heliospheric magnetic field over the Hale cycle

The concept that open magnetic flux of the Sun (rooted with one and only one footpoint at the Sun) is a conserved quantity is taking root in the heliospheric community. Observations show that the Sun's open magnetic flux returns to the baseline from one solar minimum to the next. The temporary enhancement in the 1 AU heliospheric magnetic flux near solar maximum can be accounted for by the temporary creation of closed magnetic flux (with two footpoints at the Sun) during the ejection of coronal mass ejections (CMEs), which are more frequent near solar maximum. As a part of the International Heliophysical Year activities, this paper reviews two recently discussed consequences of open flux conservation: the reversal of open magnetic flux over the solar cycle driven by Coronal Mass Ejections and the impacts of open flux conservation on the global structure of the heliospheric magnetic field. These studies demonstrate the inherent linkages between coronal mass ejections, footpoint motions back at the Sun, and the global structure and evolution of the heliospheric magnetic field.

Comparative and international education: policy transfer, context sensitivity and professional development

This paper examines the intellectual and professional contribution of comparative and international studies to the field of education. It explores the nature of the challenges that are currently being faced, and assesses its potential for the advancement of future teaching, research and professional development. Attention is paid to the place of comparative and international education (CIE)-past and present-in teacher education, in postgraduate studies, and in the realms of policy and practice, theory and research. Consideration is first given to the nature and history of CIE, to its initial contributions to the field of education in the UK, and to its chief mechanisms and sites of production. Influential methodological and theoretical developments are examined, followed by an exploration of emergent questions, controversies and dilemmas that could benefit from sustained comparative analysis in the future. Conclusions consider implications for the place of CIE in the future of educational studies as a whole; for relations between and beyond the 'disciplines of education'; and for the development of sustainable research capacity in this field.

Fifty years of international business theory and beyond

As the field of international business has matured, there have been shifts in the core unit of analysis. First, there was analysis at country level, using national statistics on trade and foreign direct investment (FDI). Next, the focus shifted to the multinational enterprise (MNE) and the parent’s firm specific advantages (FSAs). Eventually the MNE was analysed as a network and the subsidiary became a unit of analysis. We untangle the last fifty years of international business theory using a classification by these three units of analysis. This is the country-specific advantage (CSA) and firm-specific advantage (FSA) matrix. Will this integrative framework continue to be useful in the future? We demonstrate that this is likely as the CSA/FSA matrix permits integration of potentially useful alternative units of analysis, including the broad region of the triad. Looking forward, we develop a new framework, visualized in two matrices, to show how distance really matters and how FSAs function in international business. Key to this are the concepts of compounded distance and resource recombination barriers facing MNEs when operating across national borders.

Molecular modelling studies of binding of DACD derivatives into G-Quadruplex DNA: comparison of force field and quantum polarized ligand docking methods

The DNA G-qadruplexes are one of the targets being actively explored for anti-cancer therapy by inhibiting them through small molecules. This computational study was conducted to predict the binding strengths and orientations of a set of novel dimethyl-amino-ethyl-acridine (DACA) analogues that are designed and synthesized in our laboratory, but did not diffract in Synchrotron light.Thecrystal structure of DNA G-Quadruplex(TGGGGT)4(PDB: 1O0K) was used as target for their binding properties in our studies.We used both the force field (FF) and QM/MM derived atomic charge schemes simultaneously for comparing the predictions of drug binding modes and their energetics. This study evaluates the comparative performance of fixed point charge based Glide XP docking and the quantum polarized ligand docking schemes. These results will provide insights on the effects of including or ignoring the drug-receptor interfacial polarization events in molecular docking simulations, which in turn, will aid the rational selection of computational methods at different levels of theory in future drug design programs. Plenty of molecular modelling tools and methods currently exist for modelling drug-receptor or protein-protein, or DNA-protein interactionssat different levels of complexities.Yet, the capasity of such tools to describevarious physico-chemical propertiesmore accuratelyis the next step ahead in currentresearch.Especially, the usage of most accurate methods in quantum mechanics(QM) is severely restricted by theirtedious nature. Though the usage of massively parallel super computing environments resulted in a tremendous improvement in molecular mechanics (MM) calculations like molecular dynamics,they are still capable of dealing with only a couple of tens to hundreds of atoms for QM methods. One such efficient strategy that utilizes thepowers of both MM and QM are the QM/MM hybrid methods. Lately, attempts have been directed towards the goal of deploying several different QM methods for betterment of force field based simulations, but with practical restrictions in place. One of such methods utilizes the inclusion of charge polarization events at the drug-receptor interface, that is not explicitly present in the MM FF.

Features for detection of Parkinson's disease tremor from local field potentials of the subthalamic nucleus

Deep Brain Stimulation (DBS) is a treatment routinely used to alleviate the symptoms of Parkinson's disease (PD). In this type of treatment, electrical pulses are applied through electrodes implanted into the basal ganglia of the patient. As the symptoms are not permanent in most patients, it is desirable to develop an on-demand stimulator, applying pulses only when onset of the symptoms is detected. This study evaluates a feature set created for the detection of tremor - a cardinal symptom of PD. The designed feature set was based on standard signal features and researched properties of the electrical signals recorded from subthalamic nucleus (STN) within the basal ganglia, which together included temporal, spectral, statistical, autocorrelation and fractal properties. The most characterized tremor related features were selected using statistical testing and backward algorithms then used for classification on unseen patient signals. The spectral features were among the most efficient at detecting tremor, notably spectral bands 3.5-5.5 Hz and 0-1 Hz proved to be highly significant. The classification results for determination of tremor achieved 94% sensitivity with specificity equaling one.

PDM 2006: Proceedings of the International Workshop on Data Mining

Recently major processor manufacturers have announced a dramatic shift in their paradigm to increase computing power over the coming years. Instead of focusing on faster clock speeds and more powerful single core CPUs, the trend clearly goes towards multi core systems. This will also result in a paradigm shift for the development of algorithms for computationally expensive tasks, such as data mining applications. Obviously, work on parallel algorithms is not new per se but concentrated efforts in the many application domains are still missing. Multi-core systems, but also clusters of workstations and even large-scale distributed computing infrastructures provide new opportunities and pose new challenges for the design of parallel and distributed algorithms. Since data mining and machine learning systems rely on high performance computing systems, research on the corresponding algorithms must be on the forefront of parallel algorithm research in order to keep pushing data mining and machine learning applications to be more powerful and, especially for the former, interactive. To bring together researchers and practitioners working in this exciting field, a workshop on parallel data mining was organized as part of PKDD/ECML 2006 (Berlin, Germany). The six contributions selected for the program describe various aspects of data mining and machine learning approaches featuring low to high degrees of parallelism: The first contribution focuses the classic problem of distributed association rule mining and focuses on communication efficiency to improve the state of the art. After this a parallelization technique for speeding up decision tree construction by means of thread-level parallelism for shared memory systems is presented. The next paper discusses the design of a parallel approach for dis- tributed memory systems of the frequent subgraphs mining problem. This approach is based on a hierarchical communication topology to solve issues related to multi-domain computational envi- ronments. The forth paper describes the combined use and the customization of software packages to facilitate a top down parallelism in the tuning of Support Vector Machines (SVM) and the next contribution presents an interesting idea concerning parallel training of Conditional Random Fields (CRFs) and motivates their use in labeling sequential data. The last contribution finally focuses on very efficient feature selection. It describes a parallel algorithm for feature selection from random subsets. Selecting the papers included in this volume would not have been possible without the help of an international Program Committee that has provided detailed reviews for each paper. We would like to also thank Matthew Otey who helped with publicity for the workshop.