Acoustic features for multi-level classification of Australian frogs

Over past few decades, frog species have been experiencing dramatic decline around the world. The reason for this decline includes habitat loss, invasive species, climate change and so on. To better know the status of frog species, classifying frogs has become increasingly important. In this study, acoustic features are investigated for multi-level classification of Australian frogs: family, genus and species, including three families, eleven genera and eighty five species which are collected from Queensland, Australia. For each frog species, six instances are selected from which ten acoustic features are calculated. Then, the multicollinearity between ten features are studied for selecting non-correlated features for subsequent analysis. A decision tree (DT) classifier is used to visually and explicitly determine which acoustic features are relatively important for classifying family, which for genus, and which for species. Finally, a weighted support vector machines (SVMs) classifier is used for the multi- level classification with three most important acoustic features respectively. Our experiment results indicate that using different acoustic feature sets can successfully classify frogs at different levels and the average classification accuracy can be up to 85.6%, 86.1% and 56.2% for family, genus and species respectively.

Stress analysis of carotid plaque based on in vivo MRI of acute symptomatic and asymptomatic patients

Stress analysis within carotid plaques based on in vivo MR imaging has shown to be useful for the identification of vulnerable atheroma. This study is to investigate whether magnetic resonance imaging (MRI) based-biomechanical stress analysis of carotid plaques can differentiate acute symptomatic and asymptomatic patients. 54 asymptomatic and 45 acute symptomatic patients underwent in vivo multi-contrast MRI of the carotid arteries. Plaque geometry used for finite element analysis was derived from in vivo MR images at the site of maximum and minimum plaque burden. In total 198 slices were used for the computational simulations. A pre shrink technique was used to refine the simulation. Maximum principle stress at the vulnerable plaque sites (i.e. critical stress) was extracted for the selected slices and a comparison was performed between the two groups. Critical stress at the site of maximum plaque burden is significantly higher in acute symptomatic patients as compared to asymptomatic patients [median: 198.0kPa (inter quartile range (IQR) = (119.8 - 359.0) vs. 138.4kPa (83.8, 242.6), p=0.04]. No significant difference was found at the minimum plaque burden site between the two groups [196.7kPa (133.3- 282.7) vs. 182.4kPa (117.2 - 310. 6), p=0.82). Stress analysis at the site of maximal plaque burden can be effectively used for differentiating acute symptomatic carotid plaques from asymptomatic plaques. This maybe potentially used for development of biomechanical risk stratification criteria based on plaque burden in future studies.

Stress analysis on human arterial plaques by fluid structure interactions - Multi-case study

Atherosclerotic plaque rupture has been extensively considered as the leading cause of death in the world. It is believed that high stress within plaque can be an important factor which can trigger the rupture of the plaque. High resolution multi-spectral magnetic resonance imaging (MRI) has allowed the plaque components (arterial wall, lipids, and fibrous cap) to be visualized in vivo [1]. The patient specific finite element model can be generated from the image data to perform stress analysis and provide critical information on understanding plaque rupture mechanisms [2]. The present work is to apply the procedure to a total of 14 patients (S1 ∼ S14), to study the stress distributions on carotid artery plaque reconstructed from multi-spectral magnetic resonance images, and the possible relationships between stress and plaque burdens.

Intra-cluster correlation structure in longitudinal data analysis: Selection criteria and misspecification tests

Selection criteria and misspecification tests for the intra-cluster correlation structure (ICS) in longitudinal data analysis are considered. In particular, the asymptotical distribution of the correlation information criterion (CIC) is derived and a new method for selecting a working ICS is proposed by standardizing the selection criterion as the p-value. The CIC test is found to be powerful in detecting misspecification of the working ICS structures, while with respect to the working ICS selection, the standardized CIC test is also shown to have satisfactory performance. Some simulation studies and applications to two real longitudinal datasets are made to illustrate how these criteria and tests might be useful.

Recent emergence of the wheat Lr34 multi-pathogen resistance: insights from haplotype analysis in wheat, rice, sorghum and Aegilops tauschii

Spontaneous sequence changes and the selection of beneficial mutations are driving forces of gene diversification and key factors of evolution. In highly dynamic co-evolutionary processes such as plant-pathogen interactions, the plant's ability to rapidly adapt to newly emerging pathogens is paramount. The hexaploid wheat gene Lr34, which encodes an ATP-binding cassette (ABC) transporter, confers durable field resistance against four fungal diseases. Despite its extensive use in breeding and agriculture, no increase in virulence towards Lr34 has been described over the last century. The wheat genepool contains two predominant Lr34 alleles of which only one confers disease resistance. The two alleles, located on chromosome 7DS, differ by only two exon-polymorphisms. Putatively functional homoeologs and orthologs of Lr34 are found on the B-genome of wheat and in rice and sorghum, but not in maize, barley and Brachypodium. In this study we present a detailed haplotype analysis of homoeologous and orthologous Lr34 genes in genetically and geographically diverse selections of wheat, rice and sorghum accessions. We found that the resistant Lr34 haplotype is unique to the wheat D-genome and is not found in the B-genome of wheat or in rice and sorghum. Furthermore, we only found the susceptible Lr34 allele in a set of 252 Ae. tauschii genotypes, the progenitor of the wheat D-genome. These data provide compelling evidence that the Lr34 multi-pathogen resistance is the result of recent gene diversification occurring after the formation of hexaploid wheat about 8,000 years ago.

Multi-user resource-sharing problem for the Internet

In this thesis we study a series of multi-user resource-sharing problems for the Internet, which involve distribution of a common resource among participants of multi-user systems (servers or networks). We study concurrently accessible resources, which for end-users may be exclusively accessible or non-exclusively. For all kinds we suggest a separate algorithm or a modification of common reputation scheme. Every algorithm or method is studied from different perspectives: optimality of protocols, selfishness of end users, fairness of the protocol for end users. On the one hand the multifaceted analysis allows us to select the most suited protocols among a set of various available ones based on trade-offs of optima criteria. On the other hand, the future Internet predictions dictate new rules for the optimality we should take into account and new properties of the networks that cannot be neglected anymore. In this thesis we have studied new protocols for such resource-sharing problems as the backoff protocol, defense mechanisms against Denial-of-Service, fairness and confidentiality for users in overlay networks. For backoff protocol we present analysis of a general backoff scheme, where an optimization is applied to a general-view backoff function. It leads to an optimality condition for backoff protocols in both slot times and continuous time models. Additionally we present an extension for the backoff scheme in order to achieve fairness for the participants in an unfair environment, such as wireless signal strengths. Finally, for the backoff algorithm we suggest a reputation scheme that deals with misbehaving nodes. For the next problem -- denial-of-service attacks, we suggest two schemes that deal with the malicious behavior for two conditions: forged identities and unspoofed identities. For the first one we suggest a novel most-knocked-first-served algorithm, while for the latter we apply a reputation mechanism in order to restrict resource access for misbehaving nodes. Finally, we study the reputation scheme for the overlays and peer-to-peer networks, where resource is not placed on a common station, but spread across the network. The theoretical analysis suggests what behavior will be selected by the end station under such a reputation mechanism.

Statistical methods for analysis of multi-harvest data from perennial pasture variety selection trials

Variety selection in perennial pasture crops involves identifying best varieties from data collected from multiple harvest times in field trials. For accurate selection, the statistical methods for analysing such data need to account for the spatial and temporal correlation typically present. This paper provides an approach for analysing multi-harvest data from variety selection trials in which there may be a large number of harvest times. Methods are presented for modelling the variety by harvest effects while accounting for the spatial and temporal correlation between observations. These methods provide an improvement in model fit compared to separate analyses for each harvest, and provide insight into variety by harvest interactions. The approach is illustrated using two traits from a lucerne variety selection trial. The proposed method provides variety predictions allowing for the natural sources of variation and correlation in multi-harvest data.

A cyclostationary multi-domain analysis of fluid instability in Kaplan turbines

Hydraulic instabilities represent a critical problem for Francis and Kaplan turbines, reducing their useful life due to increase of fatigue on the components and cavitation phenomena. Whereas an exhaustive list of publications on computational fluid-dynamic models of hydraulic instability is available, the possibility of applying diagnostic techniques based on vibration measurements has not been investigated sufficiently, also because the appropriate sensors seldom equip hydro turbine units. The aim of this study is to fill this knowledge gap and to exploit fully, for this purpose, the potentiality of combining cyclostationary analysis tools, able to describe complex dynamics such as those of fluid-structure interactions, with order tracking procedures, allowing domain transformations and consequently the separation of synchronous and non-synchronous components. This paper will focus on experimental data obtained on a full-scale Kaplan turbine unit, operating in a real power plant, tackling the issues of adapting such diagnostic tools for the analysis of hydraulic instabilities and proposing techniques and methodologies for a highly automated condition monitoring system. © 2015 Elsevier Ltd.

Negotiation schemes for multi-agent cooperative search

Because of limited sensor and communication ranges, designing efficient mechanisms for cooperative tasks is difficult. In this article, several negotiation schemes for multiple agents performing a cooperative task are presented. The negotiation schemes provide suboptimal solutions, but have attractive features of fast decision-making, and scalability to large number of agents without increasing the complexity of the algorithm. A software agent architecture of the decision-making process is also presented. The effect of the magnitude of information flow during the negotiation process is studied by using different models of the negotiation scheme. The performance of the various negotiation schemes, using different information structures, is studied based on the uncertainty reduction achieved for a specified number of search steps. The negotiation schemes perform comparable to that of optimal strategy in terms of uncertainty reduction and also require very low computational time, similar to 7 per cent to that of optimal strategy. Finally, analysis on computational and communication requirement for the negotiation schemes is carried out.

Splitting Algorithms for Fast Relay Selection: Generalizations, Analysis, and a Unified View

Relay selection for cooperative communications promises significant performance improvements, and is, therefore, attracting considerable attention. While several criteria have been proposed for selecting one or more relays, distributed mechanisms that perform the selection have received relatively less attention. In this paper, we develop a novel, yet simple, asymptotic analysis of a splitting-based multiple access selection algorithm to find the single best relay. The analysis leads to simpler and alternate expressions for the average number of slots required to find the best user. By introducing a new contention load' parameter, the analysis shows that the parameter settings used in the existing literature can be improved upon. New and simple bounds are also derived. Furthermore, we propose a new algorithm that addresses the general problem of selecting the best Q >= 1 relays, and analyze and optimize it. Even for a large number of relays, the scalable algorithm selects the best two relays within 4.406 slots and the best three within 6.491 slots, on average. We also propose a new and simple scheme for the practically relevant case of discrete metrics. Altogether, our results develop a unifying perspective about the general problem of distributed selection in cooperative systems and several other multi-node systems.

Income Inequality and Healt: A Multi-Country Analysis

This paper investigates the effect of income inequality on health status. A model of health status was specified in which the main variables were income level, income inequality, the level of savings and the level of education. The model was estimated using a panel data set for 44 countries covering six time periods. The results indicate that income inequality (measured by the Gini coefficient) has a significant effect on health status when we control for the levels of income, savings and education. The relationship is consistent regardless of the specification of health status and income. Thus, the study results provide some empirical support for the income inequality hypothesis.

The challenge of LC/MS/MS multi-mycotoxin analysis - Heracles battling the Hydra?

Mycotoxins are secondary metabolites of filamentous fungi. They pose a health risk to humans and animals due to their harmful biological properties and common occurrence in food and feed. Liquid chromatography/mass spectrometry (LC/MS) has gained popularity in the trace analysis of food contaminants. In this study, the applicability of the technique was evaluated in multi-residue methods of mycotoxins aiming at simultaneous detection of chemically diverse compounds. Methods were developed for rapid determination of toxins produced by fungal genera of Aspergillus, Fusarium, Penicillium and Claviceps from cheese, cereal based agar matrices and grains. Analytes were extracted from these matrices with organic solvents. Minimal sample clean-up was carried out before the analysis of the mycotoxins with reversed phase LC coupled to tandem MS (MS/MS). The methods were validated and applied for investigating mycotoxins in cheese and ergot alkaloid occurrence in Finnish grains. Additionally, the toxin production of two Fusarium species predominant in northern Europe was studied. Nine mycotoxins could be determined from cheese with the method developed. The limits of quantification (LOQ) allowed the quantification at concentrations varying from 0.6 to 5.0 µg/kg. The recoveries ranged between 96 and 143 %, and the within-day repeatability (as relative standard deviation, RSDr) between 2.3 and 12.1 %. Roquefortine C and mycophenolic acid could be detected at levels of 300 up to 12000 µg/kg in the mould cheese samples analysed. A total of 29 or 31 toxins could be analysed with the method developed for agar matrices and grains, with the LOQs ranging overall from 0.1 to 1250 µg/kg. The recoveries ranged generally between 44 and 139 %, and the RSDr between 2.0 and 38 %. Type-A trichothecenes and beauvericin were determined from the cereal based agar and grain cultures of F. sporotrichioides and F. langsethiae. T-2 toxin was the main metabolite, the average levels reaching 22000 µg/kg in the grain cultures after 28 days of incubation. The method developed for ten ergot alkaloids from grains allowed their quantification at levels varying from 0.01 to 10 µg/kg. The recoveries ranged from 51 to 139 %, and the RSDr from 0.6 to 13.9 %. Ergot alkaloids were measured in barley and rye at average levels of 59 and 720 µg/kg, respectively. The two most prevalent alkaloids were ergocornine and ergocristine. The LC/MS methods developed enabled rapid detection of mycotoxins in such applications where several toxins co-occurred. Generally, the performance of the methods was good, allowing reliable analysis of the mycotoxins of interest with sufficiently low quantification limits. However, the variation in validation results highlighted the challenges related to optimising this type of multi-residue methods. New data was obtained about the occurrence of mycotoxins in mould cheeses and of ergot alkaloids in Finnish grains. In addition, the study revealed the high mycotoxin-producing potential of two common fungi in Finnish crops. The information can be useful when risks related to fungal and mycotoxin contamination will be assessed.

Multi-Agent Rendezvous Algorithm with Rectilinear Decision Domain

The aim of this paper is to develop a computationally efficient decentralized rendezvous algorithm for a group of autonomous agents. The algorithm generalizes the notion of sensor domain and decision domain of agents to enable implementation of simple computational algorithms. Specifically, the algorithm proposed in this paper uses a rectilinear decision domain (RDD) as against the circular decision domain assumed in earlier work. Because of this, the computational complexity of the algorithm reduces considerably and, when compared to the standard Ando's algorithm available in the literature, the RDD algorithm shows very significant improvement in convergence time performance. Analytical results to prove convergence and supporting simulation results are presented in the paper.

Positional Consensus of Multi-Agent Systems Using Linear Programming Based Decentralized Control with Rectilinear Decision Domain

In this paper we develop a Linear Programming (LP) based decentralized algorithm for a group of multiple autonomous agents to achieve positional consensus. Each agent is capable of exchanging information about its position and orientation with other agents within their sensing region. The method is computationally feasible and easy to implement. Analytical results are presented. The effectiveness of the approach is illustrated with simulation results.

The actor-critic algorithm as multi-time-scale stochastic approximation

The actor-critic algorithm of Barto and others for simulation-based optimization of Markov decision processes is cast as a two time Scale stochastic approximation. Convergence analysis, approximation issues and an example are studied.