Hierarchical Bayesian modelling of early detection surveillance for plant pest invasions

Early detection surveillance programs aim to find invasions of exotic plant pests and diseases before they are too widespread to eradicate. However, the value of these programs can be difficult to justify when no positive detections are made. To demonstrate the value of pest absence information provided by these programs, we use a hierarchical Bayesian framework to model estimates of incursion extent with and without surveillance. A model for the latent invasion process provides the baseline against which surveillance data are assessed. Ecological knowledge and pest management criteria are introduced into the model using informative priors for invasion parameters. Observation models assimilate information from spatio-temporal presence/absence data to accommodate imperfect detection and generate posterior estimates of pest extent. When applied to an early detection program operating in Queensland, Australia, the framework demonstrates that this typical surveillance regime provides a modest reduction in the estimate that a surveyed district is infested. More importantly, the model suggests that early detection surveillance programs can provide a dramatic reduction in the putative area of incursion and therefore offer a substantial benefit to incursion management. By mapping spatial estimates of the point probability of infestation, the model identifies where future surveillance resources can be most effectively deployed.

DNA technology for the detection of common genetic variants that predispose to thrombophilia

With the identification of common single locus point mutations as risk factors for thrombophilia, many DNA testing methodologies have been described for detecting these variations. Traditionally, functional or immunological testing methods have been used to investigate quantitative anticoagulant deficiencies. However, with the emergence of the genetic variations, factor V Leiden, prothrombin 20210 and, to a lesser extent, the methylene tetrahydrofolate reductase (MTHFR677) and factor V HR2 haplotype, traditional testing methodologies have proved to be less useful and instead DNA technology is more commonly employed in diagnostics. This review considers many of the DNA techniques that have proved to be useful in the detection of common genetic variants that predispose to thrombophilia. Techniques involving gel analysis are used to detect the presence or absence of restriction sites, electrophoretic mobility shifts, as in single strand conformation polymorphism or denaturing gradient gel electrophoresis, and product formation in allele-specific amplification. Such techniques may be sensitive, but are unwielding and often need to be validated objectively. In order to overcome some of the limitations of gel analysis, especially when dealing with larger sample numbers, many alternative detection formats, such as closed tube systems, microplates and microarrays (minisequencing, real-time polymerase chain reaction, and oligonucleotide ligation assays) have been developed. In addition, many of the emerging technologies take advantage of colourimetric or fluorescence detection (including energy transfer) that allows qualitative and quantitative interpretation of results. With the large variety of DNA technologies available, the choice of methodology will depend on several factors including cost and the need for speed, simplicity and robustness. © 2000 Lippincott Williams & Wilkins.

Use of first nucleotide change technology to determine the frequency of factor V Leiden in a population of Australian blood donors

Activated protein C resistance (APCR), the most common risk factor for venous thrombosis, is the result of a G to A base substitution at nucleotide 1691 (R506Q) in the factor V gene. Current techniques to detect the factor V Leiden mutation, such as determination of restriction length polymorphisms, do not have the capacity to screen large numbers of samples in a rapid, cost- effective test. The aim of this study was to apply the first nucleotide change (FNC) technology, to the detection of the factor V Leiden mutation. After preliminary amplification of genomic DNA by polymerase chain reaction (PCR), an allele-specific primer was hybridised to the PCR product and extended using fluorescent terminating dideoxynucleotides which were detected by colorimetric assay. Using this ELISA-based assay, the prevalence of the factor V Leiden mutation was determined in an Australian blood donor population (n = 500). A total of 18 heterozygotes were identified (3.6%) and all of these were confirmed with conventional MnlI restriction digest. No homozygotes for the variant allele were detected. We conclude from this study that the frequency of 3.6% is compatible with others published for Caucasian populations. In addition, the FNC technology shows promise as the basis for a rapid, automated DNA based test for factor V Leiden.

A spoofing detection method for civilian L1 GPS and the E1-B Galileo Safety of Life service

This paper describes an effective method for signal-authentication and spoofing detection for civilian GNSS receivers using the GPS L1 C/A and the Galileo E1-B Safety of Life service. The paper discusses various spoofing attack profiles and how the proposed method is able to detect these attacks. This method is relatively low-cost and can be suitable for numerous mass-market applications. This paper is the subject of a pending patent.

Gap analysis of intrusion detection in smart grids

Given the recent emergence of the smart grid and smart grid related technologies, their security is a prime concern. Intrusion detection provides a second line of defense. However, conventional intrusion detection systems (IDSs) are unable to adequately address the unique requirements of the smart grid. This paper presents a gap analysis of contemporary IDSs from a smart grid perspective. This paper highlights the lack of adequate intrusion detection within the smart grid and discusses the limitations of current IDSs approaches. The gap analysis identifies current IDSs as being unsuited to smart grid application without significant changes to address smart grid specific requirements.

A plasmonic 'ac Wheatstone bridge' circuit for high-sensitivity phase measurement and single-molecule detection

In this paper, a plasmonic “ac Wheatstone bridge” circuit is proposed and theoretically modeled for the first time. The bridge circuit consists of three metallic nanoparticles, shaped as rectangular prisms, with two nanoparticles acting as parallel arms of a resonant circuit and the third bridging nanoparticle acting as an optical antenna providing an output signal. Polarized light excites localized surface plasmon resonances in the two arms of the circuit, which generate an optical signal dependent on the phase-sensitive excitations of surface plasmons in the antenna. The circuit is analyzed using a plasmonic coupling theory and numerical simulations. The analyses show that the plasmonic circuit is sensitive to phase shifts between the arms of the bridge and has the potential to detect the presence of single molecules.

Proactive detection of high collision concentration locations on highways

In previous research (Chung et al., 2009), the potential of the continuous risk profile (CRP) to proactively detect the systematic deterioration of freeway safety levels was presented. In this paper, this potential is investigated further, and an algorithm is proposed for proactively detecting sites where the collision rate is not sufficiently high to be classified as a high collision concentration location but where a systematic deterioration of safety level is observed. The approach proposed compares the weighted CRP across different years and uses the cumulative sum (CUSUM) algorithm to detect the sites where changes in collision rate are observed. The CRPs of the detected sites are then compared for reproducibility. When high reproducibility is observed, a growth factor is used for sequential hypothesis testing to determine if the collision profiles are increasing over time. Findings from applying the proposed method using empirical data are documented in the paper together with a detailed description of the method.

High-Order Concept Associations Mining and Inferential Language Modeling for Online Review Spam Detection

Despite many incidents about fake online consumer reviews have been reported, very few studies have been conducted to date to examine the trustworthiness of online consumer reviews. One of the reasons is the lack of an effective computational method to separate the untruthful reviews (i.e., spam) from the legitimate ones (i.e., ham) given the fact that prominent spam features are often missing in online reviews. The main contribution of our research work is the development of a novel review spam detection method which is underpinned by an unsupervised inferential language modeling framework. Another contribution of this work is the development of a high-order concept association mining method which provides the essential term association knowledge to bootstrap the performance for untruthful review detection. Our experimental results confirm that the proposed inferential language model equipped with high-order concept association knowledge is effective in untruthful review detection when compared with other baseline methods.

Data preprocessing for anomaly based network intrusion detection : a review

Data preprocessing is widely recognized as an important stage in anomaly detection. This paper reviews the data preprocessing techniques used by anomaly-based network intrusion detection systems (NIDS), concentrating on which aspects of the network traffic are analyzed, and what feature construction and selection methods have been used. Motivation for the paper comes from the large impact data preprocessing has on the accuracy and capability of anomaly-based NIDS. The review finds that many NIDS limit their view of network traffic to the TCP/IP packet headers. Time-based statistics can be derived from these headers to detect network scans, network worm behavior, and denial of service attacks. A number of other NIDS perform deeper inspection of request packets to detect attacks against network services and network applications. More recent approaches analyze full service responses to detect attacks targeting clients. The review covers a wide range of NIDS, highlighting which classes of attack are detectable by each of these approaches. Data preprocessing is found to predominantly rely on expert domain knowledge for identifying the most relevant parts of network traffic and for constructing the initial candidate set of traffic features. On the other hand, automated methods have been widely used for feature extraction to reduce data dimensionality, and feature selection to find the most relevant subset of features from this candidate set. The review shows a trend toward deeper packet inspection to construct more relevant features through targeted content parsing. These context sensitive features are required to detect current attacks.

Towards the biofortification of banana fruit for enhanced micronutrient content

In Uganda, vitamin A deficiency (VAD) and iron deficiency anaemia (IDA) are major public health problems with between 15-32% of children under 5 years of age showing VAD and 73% being anaemic. This is largely due to the fact that the staple food crop of the country, banana, is low in pro-vitamin A and iron, therefore leading to dietary deficiencies. Although worldwide progress has been made to control VAD and IDA through supplementation, food fortification and diet diversification, their long term sustainability and impact in developing countries such as Uganda is limited. The approach taken by researchers at Queensland University of Technology (QUT), Australia, in collaboration with the National Agricultural Research Organization (NARO), Uganda, to address this problem, is to generate consumer acceptable banana varieties with significantly increased levels of pro-vitamin A and iron in the fruit using genetic engineering techniques. Such an approach requires the use of suitable, well characterised genes and promoters for targeted transgene expression. Recently, a new banana phytoene synthase gene (APsy2a) involved in the synthesis of pro-vitamin A (pVA) carotenoids was isolated from a high â-carotene banana (F’ei cv Asupina). In addition, sequences of banana ferritin, an iron storage protein, have been isolated from Cavendish banana. The aim of the research described in this thesis was to evaluate the function of these genes to assess their suitability for the biofortification of banana fruit. In addition, a range of banana-derived promoters were characterised to determine their suitability for controlling the expression of transgenes in banana fruit. Due to the time constraints involved with generating transgenic banana fruit, rice was used as the model crop to investigate the functionality of the banana-derived APsy2a and ferritin genes. Using Agrobacterium-mediated transformation, rice callus was transformed with APsy2a +/- the bacterial-derived carotene desaturase gene (CrtI) each under the control of the constitutive maize poly-ubiquitin promoter (ZmUbi) or seed-specific rice glutelin1 (Gt1) promoter. The maize phytoene synthase (ZmPsy1) gene was included as a control. On selective media, with the exception of ZmUbi-CrtI-transgenic callus, all antibiotic resistant callus displayed a yellow-orange colour from which the presence of â-carotene was demonstrated using Raman spectroscopy. Although the regeneration of plants from yellow-orange callus was difficult, 16 transgenic plants were obtained and characterised from callus transformed with ZmUbi-APys2a alone. At least 50% of the T1 seeds developed a yellow-orange coloured callus which was found to contain levels of â-carotene ranging from 4.6-fold to 72-fold higher than that in non-transgenic rice callus. Using the seed-specific Gt1 promoter, 38 transgenic rice plants were generated from APsy2a-CrtI-transformed callus while 32 plants were regenerated from ZmPsy1-CrtI-transformed callus. However, when analysed for presence of transgene by PCR, all transgenic plants contained the APsy2a, ZmPsy1 or CrtI transgene, with none of the plants found to be co-transformed. Using Raman spectroscopy, no â-carotene was detected in-situ in representative T1 seeds. To investigate the potential of the banana-derived ferritin gene (BanFer1) to enhance iron content, rice callus was transformed with constitutively expressed BanFer1 using the soybean ferritin gene (SoyFer) as a control. A total of 12 and 11 callus lines independently transformed with BanFer1 and SoyFer, respectively, were multiplied and transgene expression was verified by RT-PCR. Pearl’s Prussian blue staining for in-situ detection of ferric iron showed a stronger blue colour in rice callus transformed with BanFer1 compared to SoyFer. Using flame atomic absorption spectrometry, the highest mean amount of iron quantified in callus transformed with BanFer1 was 30-fold while that obtained using the SoyFer was 14-fold higher than the controls. In addition, ~78% of BanFer1-transgenic callus lines and ~27% of SoyFer-transgenic callus lines had significantly higher iron content than the non-transformed controls. Since the genes used for enhancing micronutrient content need to be expressed in banana fruit, the activity of a range of banana-derived, potentially fruit-active promoters in banana was investigated. Using uidA (GUS) as a reporter gene, the function of the Expansin1 (MaExp1), Expansin1 containing the rice actin intron (MaExp1a), Expansin4 (MaExp4), Extensin (MaExt), ACS (MaACS), ACO (MaACO), Metallothionein (MaMT2a) and phytoene synthase (APsy2a) promoters were transiently analysed in intact banana fruit using two transformation methods, particle bombardment and Agrobacterium-mediated infiltration (agro-infiltration). Although a considerable amount of variation in promoter activity was observed both within and between experiments, similar trends were obtained using both transformation methods. The MaExp1 and MaExp1a directed high levels of GUS expression in banana fruit which were comparable to those observed from the ZmUbi and Banana bunchy top virus-derived BT4 promoters that were included as positive controls. Lower levels of promoter activity were obtained in both methods using the MaACO and MaExt promoters while the MaExp4, MaACS, and APsy2a promoters directed the lowest GUS activity in banana fruit. An attempt was subsequently made to use agro-infiltration to assess the expression of pVA biosynthesis genes in banana fruit by infiltrating fruit with constructs in which the ZmUbi promoter controlled the expression of APsy2a +/- CrtI, and with the maize phytoene synthase gene (ZmPsy1) included as a control. Unfortunately, the large amount of variation and inconsistency observed within and between experiments precluded any meaningful conclusions to be drawn. The final component of this research was to assess the level of promoter activity and specificity in non-target tissue. These analyses were done on leaves obtained from glasshouse-grown banana plants stably transformed with MaExp1, MaACO, APsy2a, BT4 and ZmUbi promoters driving the expression of the GUS gene in addition to leaves from a selection of the same transgenic plants which were growing in a field trial in North Queensland. The results from both histochemical and fluorometric GUS assays showed that the MaExp1 and MaACO promoters directed very low GUS activities in leaves of stably transformed banana plants compared to the constitutive ZmUbi and BT4 promoters. In summary, the results from this research provide evidence that the banana phytoene synthase gene (APsy2a) and the banana ferritin gene (BanFer1) are functional, since the constitutive over-expression of each of these transgenes led to increased levels of pVA carotenoids (for APsy2a) and iron content (for BanFer1) in transgenic rice callus. Further work is now required to determine the functionality of these genes in stably-transformed banana fruit. This research also demonstrated that the MaExp1 and MaACO promoters are fruit-active but have low activity in non-target tissue (leaves), characteristics that make them potentially useful for the biofortification of banana fruit. Ultimately, however, analysis of fruit from field-grown transgenic plants will be required to fully evaluate the suitability of pVA biosynthesis genes and the fruit-active promoters for fruit biofortification.

CAT Detect (Computer Activity Timeline Detection) : a tool for detecting inconsistency in computer activity timelines

The construction of timelines of computer activity is a part of many digital investigations. These timelines of events are composed of traces of historical activity drawn from system logs and potentially from evidence of events found in the computer file system. A potential problem with the use of such information is that some of it may be inconsistent and contradictory thus compromising its value. This work introduces a software tool (CAT Detect) for the detection of inconsistency within timelines of computer activity. We examine the impact of deliberate tampering through experiments conducted with our prototype software tool. Based on the results of these experiments, we discuss techniques which can be employed to deal with such temporal inconsistencies.