939 resultados para Shrimps - Classification - Molecular aspects


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This paper makes a formal security analysis of the current Australian e-passport implementation using model checking tools CASPER/CSP/FDR. We highlight security issues in the current implementation and identify new threats when an e-passport system is integrated with an automated processing system like SmartGate. The paper also provides a security analysis of the European Union (EU) proposal for Extended Access Control (EAC) that is intended to provide improved security in protecting biometric information of the e-passport bearer. The current e-passport specification fails to provide a list of adequate security goals that could be used for security evaluation. We fill this gap; we present a collection of security goals for evaluation of e-passport protocols. Our analysis confirms existing security weaknesses that were previously identified and shows that both the Australian e-passport implementation and the EU proposal fail to address many security and privacy aspects that are paramount in implementing a secure border control mechanism. ACM Classification C.2.2 (Communication/Networking and Information Technology – Network Protocols – Model Checking), D.2.4 (Software Engineering – Software/Program Verification – Formal Methods), D.4.6 (Operating Systems – Security and Privacy Protection – Authentication)

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The Brain Research Institute (BRI) uses various types of indirect measurements, including EEG and fMRI, to understand and assess brain activity and function. As well as the recovery of generic information about brain function, research also focuses on the utilisation of such data and understanding to study the initiation, dynamics, spread and suppression of epileptic seizures. To assist with the future focussing of this aspect of their research, the BRI asked the MISG 2010 participants to examine how the available EEG and fMRI data and current knowledge about epilepsy should be analysed and interpreted to yield an enhanced understanding about brain activity occurring before, at commencement of, during, and after a seizure. Though the deliberations of the study group were wide ranging in terms of the related matters considered and discussed, considerable progress was made with the following three aspects. (1) The science behind brain activity investigations depends crucially on the quality of the analysis and interpretation of, as well as the recovery of information from, EEG and fMRI measurements. A number of specific methodologies were discussed and formalised, including independent component analysis, principal component analysis, profile monitoring and change point analysis (hidden Markov modelling, time series analysis, discontinuity identification). (2) Even though EEG measurements accurately and very sensitively record the onset of an epileptic event or seizure, they are, from the perspective of understanding the internal initiation and localisation, of limited utility. They only record neuronal activity in the cortical (surface layer) neurons of the brain, which is a direct reflection of the type of electrical activity they have been designed to record. Because fMRI records, through the monitoring of blood flow activity, the location of localised brain activity within the brain, the possibility of combining fMRI measurements with EEG, as a joint inversion activity, was discussed and examined in detail. (3) A major goal for the BRI is to improve understanding about ``when'' (at what time) an epileptic seizure actually commenced before it is identified on an eeg recording, ``where'' the source of this initiation is located in the brain, and ``what'' is the initiator. Because of the general agreement in the literature that, in one way or another, epileptic events and seizures represent abnormal synchronisations of localised and/or global brain activity the modelling of synchronisations was examined in some detail. References C. M. Michel, G. Thut, S. Morand, A. Khateb, A. J. Pegna, R. Grave de Peralta, S. Gonzalez, M. Seeck and T. Landis, Electric source imaging of human brain functions, Brain Res. 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In this paper, we propose a new multi-class steganalysis for binary image. The proposed method can identify the type of steganographic technique used by examining on the given binary image. In addition, our proposed method is also capable of differentiating an image with hidden message from the one without hidden message. In order to do that, we will extract some features from the binary image. The feature extraction method used is a combination of the method extended from our previous work and some new methods proposed in this paper. Based on the extracted feature sets, we construct our multi-class steganalysis from the SVM classifier. We also present the empirical works to demonstrate that the proposed method can effectively identify five different types of steganography.

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Background Timely diagnosis and reporting of patient symptoms in hospital emergency departments (ED) is a critical component of health services delivery. However, due to dispersed information resources and a vast amount of manual processing of unstructured information, accurate point-of-care diagnosis is often difficult. Aims The aim of this research is to report initial experimental evaluation of a clinician-informed automated method for the issue of initial misdiagnoses associated with delayed receipt of unstructured radiology reports. Method A method was developed that resembles clinical reasoning for identifying limb abnormalities. The method consists of a gazetteer of keywords related to radiological findings; the method classifies an X-ray report as abnormal if it contains evidence contained in the gazetteer. A set of 99 narrative reports of radiological findings was sourced from a tertiary hospital. Reports were manually assessed by two clinicians and discrepancies were validated by a third expert ED clinician; the final manual classification generated by the expert ED clinician was used as ground truth to empirically evaluate the approach. Results The automated method that attempts to individuate limb abnormalities by searching for keywords expressed by clinicians achieved an F-measure of 0.80 and an accuracy of 0.80. Conclusion While the automated clinician-driven method achieved promising performances, a number of avenues for improvement were identified using advanced natural language processing (NLP) and machine learning techniques.

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Background Cancer monitoring and prevention relies on the critical aspect of timely notification of cancer cases. However, the abstraction and classification of cancer from the free-text of pathology reports and other relevant documents, such as death certificates, exist as complex and time-consuming activities. Aims In this paper, approaches for the automatic detection of notifiable cancer cases as the cause of death from free-text death certificates supplied to Cancer Registries are investigated. Method A number of machine learning classifiers were studied. Features were extracted using natural language techniques and the Medtex toolkit. The numerous features encompassed stemmed words, bi-grams, and concepts from the SNOMED CT medical terminology. The baseline consisted of a keyword spotter using keywords extracted from the long description of ICD-10 cancer related codes. Results Death certificates with notifiable cancer listed as the cause of death can be effectively identified with the methods studied in this paper. A Support Vector Machine (SVM) classifier achieved best performance with an overall F-measure of 0.9866 when evaluated on a set of 5,000 free-text death certificates using the token stem feature set. The SNOMED CT concept plus token stem feature set reached the lowest variance (0.0032) and false negative rate (0.0297) while achieving an F-measure of 0.9864. The SVM classifier accounts for the first 18 of the top 40 evaluated runs, and entails the most robust classifier with a variance of 0.001141, half the variance of the other classifiers. Conclusion The selection of features significantly produced the most influences on the performance of the classifiers, although the type of classifier employed also affects performance. In contrast, the feature weighting schema created a negligible effect on performance. Specifically, it is found that stemmed tokens with or without SNOMED CT concepts create the most effective feature when combined with an SVM classifier.

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Background The epidemiology of dengue in the South Pacific has been characterized by transmission of a single dominant serotype for 3–5 years, with subsequent replacement by another serotype. From 2001 to 2008 only DENV-1 was reported in the Pacific. In 2008, DENV-4 emerged and quickly displaced DENV-1 in the Pacific, except in New Caledonia (NC) where DENV-1 and DENV-4 co-circulated in 2008–2009. During 2012–2013, another DENV-1 outbreak occurred in NC, the third DENV-1 outbreak in a decade. Given that dengue is a serotype-specific immunizing infection, the recurrent outbreaks of a single serotype within a 10-year period was unexpected. Findings This study aimed to inform this phenomenon by examining the phylogenetic characteristics of the DENV-1 viruses in NC and other Pacific islands between 2001 and 2013. As a result, we have demonstrated that NC experienced introductions of viruses from both the Pacific (genotype IV) and South-east Asia (genotype I). Moreover, whereas genotype IV and I were co-circulating at the beginning of 2012, we observed that from the second half of 2012, i.e. during the major DENV-1 outbreak, all analyzed viruses were genotype I suggesting that a genotype switch occurred. Conclusions Repeated outbreaks of the same dengue serotype, as observed in NC, is uncommon in the Pacific islands. Why the earlier DENV-1 outbreaks did not induce sufficient herd immunity is unclear, and likely multifactorial, but the robust vector control program may have played a role by limiting transmission and thus maintaining a large susceptible pool in the population. Keywords: Dengue; Phylogeny; Genotype; Epidemics; New Caledonia

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An ongoing challenge in chemistry and crystal engineering is the synthesis of functional materials with predictable structures and customisable properties. This may be achieved by crystallising mixtures of different compounds. Co-crystals formed through this method have predictable structures and their properties may be tuned by varying the ratio of the compounds in the crystallising solution. This thesis examines single crystals formed by the co-crystallisation of metal complexes that have similar structures but different physical or chemical properties. A variety of new compounds with interesting properties were prepared, characterised and their significance in the context of crystal engineering was explored.

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Two lecture notes describe recent developments of evolutionary multi objective optimization (MO) techniques in detail and their advantages and drawbacks compared to traditional deterministic optimisers. The role of Game Strategies (GS), such as Pareto, Nash or Stackelberg games as companions or pre-conditioners of Multi objective Optimizers is presented and discussed on simple mathematical functions in Part I , as well as their implementations on simple aeronautical model optimisation problems on the computer using a friendly design framework in Part II. Real life (robust) design applications dealing with UAVs systems or Civil Aircraft and using the EAs and Game Strategies combined material of Part I & Part II are solved and discussed in Part III providing the designer new compromised solutions useful to digital aircraft design and manufacturing. Many details related to Lectures notes Part I, Part II and Part III can be found by the reader in [68].

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In 2010 there has again been an increase in the number of papers published involving piezoelectric acoustic sensors, or quartz crystal microbalances (QCM), when compared to the last period reviewed 2006-2009. The average number of QCM publications per annum was 124 in the period 2001-2005, 223 in the period 2006-9, and 273 in 2010. There are trends towards increasing use of QCM in the study of protein adsorption to surfaces (93% increase), homeostasis (67% increase), protein-protein interactions (40% increase), and carbohydrates (43% increase). New commercial systems have been released that are driving the uptake of the technology for characterisation of binding specificities, affinities, kinetics and conformational changes associated with a molecular recognition event. This article highlights theoretical and practical aspects of the principals that underpin acoustic analysis, then reviews exemplary papers in key application areas involving small molecular weight ligands, carbohydrates, proteins, nucleic acids, viruses, bacteria, cells, and membrane interfaces.

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Siphons have been used since ancient times, but exactly how they work is still a matter of debate. In order to elucidate the modus operandi of a siphon, a 1.5 m high siphon was set up in a hypobaric chamber to explore siphon behaviour in a low-pressure environment. When the pressure in the chamber was reduced to about 0.18 atmospheres, a curious waterfall-like feature appeared downstream from the apex of the siphon. A hypothesis is presented to explain the waterfall phenomenon. When the pressure was reduced further the siphon broke into two columns - in effect becoming two back-to-back barometers. This experiment demonstrates the role of atmospheric pressure in explaining the hydrostatic characteristics of a siphon and the role of molecular cohesion in explaining the hydrodynamic aspects.

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Some minerals are colloidal and show no X-ray diffraction patterns. Vibrational spectroscopy offers one of the few methods for the assessment of the structure of these types of mineral. Among this group of minerals is pitticite simply described as Fe, AsO4, SO4, H2O. The objective of this research is to determine the molecular structure of the mineral pitticite using vibrational spectroscopy. Raman microscopy offers a useful method for the analysis of such colloidal minerals. Raman and infrared bands are attributed to the , and water stretching vibrations. The Raman spectrum is dominated by a very intense sharp band at 983 cm−1 assigned to the symmetric stretching mode. A strong Raman band at 1041 cm−1 is observed and is assigned to the antisymmetric stretching mode. Low intensity Raman bands at 757 and 808 cm−1 may be assigned to the antisymmetric and symmetric stretching modes. Raman bands observed at 432 and 465 cm−1 are attributable to the doubly degenerate ν2(SO4)2- bending mode.

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The motion response of marine structures in waves can be studied using finite-dimensional linear-time-invariant approximating models. These models, obtained using system identification with data computed by hydrodynamic codes, find application in offshore training simulators, hardware-in-the-loop simulators for positioning control testing, and also in initial designs of wave-energy conversion devices. Different proposals have appeared in the literature to address the identification problem in both time and frequency domains, and recent work has highlighted the superiority of the frequency-domain methods. This paper summarises practical frequency-domain estimation algorithms that use constraints on model structure and parameters to refine the search of approximating parametric models. Practical issues associated with the identification are discussed, including the influence of radiation model accuracy in force-to-motion models, which are usually the ultimate modelling objective. The illustration examples in the paper are obtained using a freely available MATLAB toolbox developed by the authors, which implements the estimation algorithms described.

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Medroxyprogesterone acetate (MPA) has widely been used in hormone replacement therapy (HRT), and is associated with an increased risk of breast cancer, possibly due to disruption of androgen receptor (AR) signaling. In contrast, the synthetic HRT Tibolone does not increase breast density, and is rapidly metabolized to estrogenic 3α-OH-tibolone and 3β-OH-tibolone, and a delta-4 isomer (Δ4-TIB) that has both androgenic and progestagenic properties. Here, we show that 5α-dihydrotestosterone (DHT) and Δ4-TIB, but not MPA, stabilize AR protein levels, initiate specific AR intramolecular interactions critical for AR transcriptional regulation, and increase proliferation of AR positive MDA-MB-453 breast cancer cells. Structural modeling and molecular dynamic simulation indicate that Δ4-TIB induces a more stable AR structure than does DHT, and MPA a less stable one. Microarray expression analyses confirms that the molecular actions of Δ4-TIB more closely resembles DHT in breast cancer cells than either ligand does to MPA.

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As the level of autonomy in Unmanned Aircraft Systems (UAS) increases, there is an imperative need for developing methods to assess robust autonomy. This paper focuses on the computations that lead to a set of measures of robust autonomy. These measures are the probabilities that selected performance indices related to the mission requirements and airframe capabilities remain within regions of acceptable performance.

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The aim of the current study was to examine the associations between a number of individual factors (demographic factors (age and gender), personality factors, risk-taking propensity, attitudes towards drink driving, and perceived legitimacy of drink driving enforcement) and how they influence the self-reported likelihood of drink driving. The second aim of this study was to examine the potential of attitudes mediating the relationship between risk-taking and self-reported likelihood of drink driving. In total, 293 Queensland drivers volunteered to participate in an online survey that assessed their self-reported likelihood to drink drive in the next month, demographics, traffic-related demographics, personality factors, risk-taking propensity, attitudes towards drink driving, and perceived legitimacy of drink driving enforcement. An ordered logistic regression analysis was utilised to evaluate the first aim of the study; at the first step the demographic variables were entered; at step two the personality and risk-taking were entered; at the third step, the attitudes and perceptions of legitimacy variables were entered. Being a younger driver and having a high risk-taking propensity were related to self-reported likelihood of drink driving. However, when the attitudes variable was entered, these individual factors were no longer significant; with attitudes being the most important predictor of self-reported drink driving likelihood. A significant mediation model was found with the second aim of the study, such that attitudes mediated the relationship between risk-taking and self-reported likelihood of drink driving. Considerable effort and resources are utilised by traffic authorities to reducing drink driving on the Australian road network. Notwithstanding these efforts, some participants still had some positive attitudes towards drink driving and reported that they were likely to drink drive in the future. These findings suggest that more work is needed to address attitudes regarding the dangerousness of drink driving.