Targeted flight opportunities with large area collectors

A major factor in the stratospheric collection process is the relative density of particles at the collection altitude. With current aircraft-borne collector plate geometries, one potential extraterrestrial particle of about 10 micron diameter is collected approximately every hour. However, a new design for the collector plate, termed the Large Area Collector (LAC), allows a factor of 10 improvement in collection efficiency over current conventional geometry. The implementation of LAC design on future stratospheric collection flights will provide many opportunities for additional data on both terrestrial and extraterrestrial phenomena. With the improvement in collection efficiency, LAC's may provide a suitable number of potential extraterrestrial particles in one short flight of between 4 and 8 hours duration. Alternatively, total collection periods of approximately 40 hours enhance the probability that rare particles can be retrieved from the stratosphere. This latter approach is of great value for the cosmochemist who may wish to perform sophisticated analyses on interplanetary dust greater than a picogram. The former approach, involving short duration flights, may also provide invaluable data on the source of many extraterrestrial particles. The time dependence of particle entry to the collection altitude is an important parameter which may be correlated with specific global events (e.g., meteoroid streams) provided the collection time is known to an accuracy of 2 hours.

Expander graph based key distribution mechanisms in wireless sensor networks

Secure communications between large number of sensor nodes that are randomly scattered over a hostile territory, necessitate efficient key distribution schemes. However, due to limited resources at sensor nodes such schemes cannot be based on post deployment computations. Instead, pairwise (symmetric) keys are required to be pre-distributed by assigning a list of keys, (a.k.a. key-chain), to each sensor node. If a pair of nodes does not have a common key after deployment then they must find a key-path with secured links. The objective is to minimize the keychain size while (i) maximizing pairwise key sharing probability and resilience, and (ii) minimizing average key-path length. This paper presents a deterministic key distribution scheme based on Expander Graphs. It shows how to map the parameters (e.g., degree, expansion, and diameter) of a Ramanujan Expander Graph to the desired properties of a key distribution scheme for a physical network topology.

How activation, entanglement, and searching a semantic network contribute to event memory

Free association norms indicate that words are organized into semantic/associative neighborhoods within a larger network of words and links that bind the net together. We present evidence indicating that memory for a recent word event can depend on implicitly and simultaneously activating related words in its neighborhood. Processing a word during encoding primes its network representation as a function of the density of the links in its neighborhood. Such priming increases recall and recognition and can have long lasting effects when the word is processed in working memory. Evidence for this phenomenon is reviewed in extralist cuing, primed free association, intralist cuing, and single-item recognition tasks. The findings also show that when a related word is presented to cue the recall of a studied word, the cue activates it in an array of related words that distract and reduce the probability of its selection. The activation of the semantic network produces priming benefits during encoding and search costs during retrieval. In extralist cuing recall is a negative function of cue-to-distracter strength and a positive function of neighborhood density, cue-to-target strength, and target-to cue strength. We show how four measures derived from the network can be combined and used to predict memory performance. These measures play different roles in different tasks indicating that the contribution of the semantic network varies with the context provided by the task. We evaluate spreading activation and quantum-like entanglement explanations for the priming effect produced by neighborhood density.

The influence of neighbourhood disadvantage on smoking cessation and its contribution to inequalities in smoking status

Introduction and aims: Individual smokers from disadvantaged backgrounds are less likely to quit, which contributes to widening inequalities in smoking. Residents of disadvantaged neighbourhoods are more likely to smoke, and neighbourhood inequalities in smoking may also be widening because of neighbourhood differences in rates of cessation. This study examined the association between neighbourhood disadvantage and smoking cessation and its relationship with neighbourhood inequalities in smoking. Design and methods: A multilevel longitudinal study of mid-aged (40-67 years) residents (n=6915) of Brisbane, Australia, who lived in the same neighbourhoods (n=200) in 2007 and 2009. Neighbourhood inequalities in cessation and smoking were analysed using multilevel logistic regression and Markov chain Monte Carlo simulation. Results: After adjustment for individual-level socioeconomic factors, the probability of quitting smoking between 2007 and 2009 was lower for residents of disadvantaged neighbourhoods (9.0%-12.8%) than their counterparts in more advantaged neighbourhoods (20.7%-22.5%). These inequalities in cessation manifested in widening inequalities in smoking: in 2007 the between-neighbourhood variance in rates of smoking was 0.242 (p≤0.001) and in 2009 it was 0.260 (p≤0.001). In 2007, residents of the most disadvantaged neighbourhoods were 88% (OR 1.88, 95% CrI 1.41-2.49) more likely to smoke than residents in the least disadvantaged neighbourhoods: the corresponding difference in 2009 was 98% (OR 1.98 95% CrI 1.48-2.66). Conclusion: Fundamentally, social and economic inequalities at the neighbourhood and individual-levels cause smoking and cessation inequalities. Reducing these inequalities will require comprehensive, well-funded, and targeted tobacco control efforts and equity based policies that address the social and economic determinants of smoking.

Design and modeling of collaboration architecture for security

Threats against computer networks evolve very fast and require more and more complex measures. We argue that teams respectively groups with a common purpose for intrusion detection and prevention improve the measures against rapid propagating attacks similar to the concept of teams solving complex tasks known from field of work sociology. Collaboration in this sense is not easy task especially for heterarchical environments. We propose CIMD (collaborative intrusion and malware detection) as a security overlay framework to enable cooperative intrusion detection approaches. Objectives and associated interests are used to create detection groups for exchange of security-related data. In this work, we contribute a tree-oriented data model for device representation in the scope of security. We introduce an algorithm for the formation of detection groups, show realization strategies for the system and conduct vulnerability analysis. We evaluate the benefit of CIMD by simulation and probabilistic analysis.

Inferencing design styles using Baysian Networks

Reasoning with uncertain knowledge and belief has long been recognized as an important research issue in Artificial Intelligence (AI). Several methodologies have been proposed in the past, including knowledge-based systems, fuzzy sets, and probability theory. The probabilistic approach became popular mainly due to a knowledge representation framework called Bayesian networks. Bayesian networks have earned reputation of being powerful tools for modeling complex problem involving uncertain knowledge. Uncertain knowledge exists in domains such as medicine, law, geographical information systems and design as it is difficult to retrieve all knowledge and experience from experts. In design domain, experts believe that design style is an intangible concept and that its knowledge is difficult to be presented in a formal way. The aim of the research is to find ways to represent design style knowledge in Bayesian net works. We showed that these networks can be used for diagnosis (inferences) and classification of design style. The furniture design style is selected as an example domain, however the method can be used for any other domain.

Link discovery for Chinese/English cross-language web information retrieval

Nowadays people heavily rely on the Internet for information and knowledge. Wikipedia is an online multilingual encyclopaedia that contains a very large number of detailed articles covering most written languages. It is often considered to be a treasury of human knowledge. It includes extensive hypertext links between documents of the same language for easy navigation. However, the pages in different languages are rarely cross-linked except for direct equivalent pages on the same subject in different languages. This could pose serious difficulties to users seeking information or knowledge from different lingual sources, or where there is no equivalent page in one language or another. In this thesis, a new information retrieval task—cross-lingual link discovery (CLLD) is proposed to tackle the problem of the lack of cross-lingual anchored links in a knowledge base such as Wikipedia. In contrast to traditional information retrieval tasks, cross language link discovery algorithms actively recommend a set of meaningful anchors in a source document and establish links to documents in an alternative language. In other words, cross-lingual link discovery is a way of automatically finding hypertext links between documents in different languages, which is particularly helpful for knowledge discovery in different language domains. This study is specifically focused on Chinese / English link discovery (C/ELD). Chinese / English link discovery is a special case of cross-lingual link discovery task. It involves tasks including natural language processing (NLP), cross-lingual information retrieval (CLIR) and cross-lingual link discovery. To justify the effectiveness of CLLD, a standard evaluation framework is also proposed. The evaluation framework includes topics, document collections, a gold standard dataset, evaluation metrics, and toolkits for run pooling, link assessment and system evaluation. With the evaluation framework, performance of CLLD approaches and systems can be quantified. This thesis contributes to the research on natural language processing and cross-lingual information retrieval in CLLD: 1) a new simple, but effective Chinese segmentation method, n-gram mutual information, is presented for determining the boundaries of Chinese text; 2) a voting mechanism of name entity translation is demonstrated for achieving a high precision of English / Chinese machine translation; 3) a link mining approach that mines the existing link structure for anchor probabilities achieves encouraging results in suggesting cross-lingual Chinese / English links in Wikipedia. This approach was examined in the experiments for better, automatic generation of cross-lingual links that were carried out as part of the study. The overall major contribution of this thesis is the provision of a standard evaluation framework for cross-lingual link discovery research. It is important in CLLD evaluation to have this framework which helps in benchmarking the performance of various CLLD systems and in identifying good CLLD realisation approaches. The evaluation methods and the evaluation framework described in this thesis have been utilised to quantify the system performance in the NTCIR-9 Crosslink task which is the first information retrieval track of this kind.

Combinatorial design of key distribution mechanisms for wireless sensor networks

Key distribution is one of the most challenging security issues in wireless sensor networks where sensor nodes are randomly scattered over a hostile territory. In such a sensor deployment scenario, there will be no prior knowledge of post deployment configuration. For security solutions requiring pair wise keys, it is impossible to decide how to distribute key pairs to sensor nodes before the deployment. Existing approaches to this problem are to assign more than one key, namely a key-chain, to each node. Key-chains are randomly drawn from a key-pool. Either two neighbouring nodes have a key in common in their key-chains, or there is a path, called key-path, among these two nodes where each pair of neighbouring nodes on this path has a key in common. Problem in such a solution is to decide on the key-chain size and key-pool size so that every pair of nodes can establish a session key directly or through a path with high probability. The size of the key-path is the key factor for the efficiency of the design. This paper presents novel, deterministic and hybrid approaches based on Combinatorial Design for key distribution. In particular, several block design techniques are considered for generating the key-chains and the key-pools. Comparison to probabilistic schemes shows that our combinatorial approach produces better connectivity with smaller key-chain sizes.

Prediction of multilocus identity-by-descent

Previous studies have enabled exact prediction of probabilities of identity-by-descent (IBD) in randommating populations for a few loci (up to four or so), with extension to more using approximate regression methods. Here we present a precise predictor of multiple-locus IBD using simple formulas based on exact results for two loci. In particular, the probability of non-IBD X ABC at each of ordered loci A, B, and C can be well approximated by XABC = XABXBC/XB and generalizes to X123. . .k = X12X23. . .Xk-1,k/ Xk-2, where X is the probability of non-IBD at each locus. Predictions from this chain rule are very precise with population bottlenecks and migration, but are rather poorer in the presence of mutation. From these coefficients, the probabilities of multilocus IBD and non-IBD can also be computed for genomic regions as functions of population size, time, and map distances. An approximate but simple recurrence formula is also developed, which generally is less accurate than the chain rule but is more robust with mutation. Used together with the chain rule it leads to explicit equations for non-IBD in a region. The results can be applied to detection of quantitative trait loci (QTL) by computing the probability of IBD at candidate loci in terms of identity-by-state at neighboring markers.

Prediction of IBD based on population history for fine gene mapping

A novel multiple regression method (RM) is developed to predict identity-by-descent probabilities at a locus L (IBDL), among individuals without pedigree, given information on surrounding markers and population history. These IBDL probabilities are a function of the increase in linkage disequilibrium (LD) generated by drift in a homogeneous population over generations. Three parameters are sufficient to describe population history: effective population size (Ne), number of generations since foundation (T), and marker allele frequencies among founders (p). IBD L are used in a simulation study to map a quantitative trait locus (QTL) via variance component estimation. RM is compared to a coalescent method (CM) in terms of power and robustness of QTL detection. Differences between RM and CM are small but significant. For example, RM is more powerful than CM in dioecious populations, but not in monoecious populations. Moreover, RM is more robust than CM when marker phases are unknown or when there is complete LD among founders or Ne is wrong, and less robust when p is wrong. CM utilises all marker haplotype information, whereas RM utilises information contained in each individual marker and all possible marker pairs but not in higher order interactions. RM consists of a family of models encompassing four different population structures, and two ways of using marker information, which contrasts with the single model that must cater for all possible evolutionary scenarios in CM.

On the prediction of simultaneous inbreeding coefficients at multiple loci

A new deterministic method for predicting simultaneous inbreeding coefficients at three and four loci is presented. The method involves calculating the conditional probability of IBD (identical by descent) at one locus given IBD at other loci, and multiplying this probability by the prior probability of the latter loci being simultaneously IBD. The conditional probability is obtained applying a novel regression model, and the prior probability from the theory of digenic measures of Weir and Cockerham. The model was validated for a finite monoecious population mating at random, with a constant effective population size, and with or without selfing, and also for an infinite population with a constant intermediate proportion of selfing. We assumed discrete generations. Deterministic predictions were very accurate when compared with simulation results, and robust to alternative forms of implementation. These simultaneous inbreeding coefficients were more sensitive to changes in effective population size than in marker spacing. Extensions to predict simultaneous inbreeding coefficients at more than four loci are now possible.

Power of QTL detection using association tests with family controls

The power of testing for a population-wide association between a biallelic quantitative trait locus and a linked biallelic marker locus is predicted both empirically and deterministically for several tests. The tests were based on the analysis of variance (ANOVA) and on a number of transmission disequilibrium tests (TDT). Deterministic power predictions made use of family information, and were functions of population parameters including linkage disequilibrium, allele frequencies, and recombination rate. Deterministic power predictions were very close to the empirical power from simulations in all scenarios considered in this study. The different TDTs had very similar power, intermediate between one-way and nested ANOVAs. One-way ANOVA was the only test that was not robust against spurious disequilibrium. Our general framework for predicting power deterministically can be used to predict power in other association tests. Deterministic power calculations are a powerful tool for researchers to plan and evaluate experiments and obviate the need for elaborate simulation studies.

Hydrogen spillover mechanism on a pd-doped mg surface as revealed by ab initio density functional calculation

The hydrogenation kinetics of Mg is slow, impeding its application for mobile hydrogen storage. We demonstrate by ab initio density functional theory (DFT) calculations that the reaction path can be greatly modified by adding transition metal catalysts. Contrasting with Ti doping, a Pd dopant will result in a very small activation barrier for both dissociation of molecular hydrogen and diffusion of atomic H on the Mg surface. This new computational finding supports for the first time by ab initio simulationthe proposed hydrogen spillover mechanism for rationalizing experimentally observed fast hydrogenation kinetics for Pd-capped Mg materials.

Comparing child product safety concerns with injury incidents : does the evidence support the response?

Background Efficient effective child product safety (PS) responses require data on hazards, injury severity and injury probability. PS responses in Australia largely rely on reports from manufacturers/retailers, other jurisdictions/regulators, or consumers. The extent to which reactive responses reflect actual child injury priorities is unknown. Aims/Objectives/Purpose This research compared PS issues for children identified using data compiled from PS regulatory data and data compiled from health data sources in Queensland, Australia. Methods PS regulatory documents describing issues affecting children in Queensland in 2008–2009 were compiled and analysed to identify frequent products and hazards. Three health data sources (ED, injury surveillance and hospital data) were analysed to identify frequent products and hazards. Results/Outcomes Projectile toys/squeeze toys were the priority products for PS regulators with these toys having the potential to release small parts presenting choking hazards. However, across all health datasets, falls were the most common mechanism of injury, and several of the products identified were not subject to a PS system response. While some incidents may not require a response, a manual review of injury description text identified child poisonings and burns as common mechanisms of injuries in the health data where there was substantial documentation of product-involvement, yet only 10% of PS system responses focused on these two mechanisms combined. Significance/contribution to the field Regulatory data focused on products that fail compliance checks with ‘potential’ to cause harm, and health data identified actual harm, resulting in different prioritisation of products/mechanisms. Work is needed to better integrate health data into PS responses in Australia.