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Extremism and Intelligence: A Threat Analysis
Get PDFContemporary extremist threats encompass a widening spectrum, whereby long-standing threats are supplemented by the stubborn persistence of historical threats, and by the emergence of new threats and Violent Transnational Social Movements (VTSMs). For security and intelligence agencies, the management challenges posed by the evolving picture are complex and multi-faceted. Probably the most difficult challenge is that of prioritisation and the allocation of resources across the spectrum of investigation. Other challenges include those of recruiting and retaining staff with the right cutting-edge skills, especially in such fields of social media exploitation; and a fundamental definitional question of how to define some of the newly-emerging threats, avoiding questions of surveillance crossing-over into inappropriate suppression of legitimate dissent in a liberal democracy
Vehicle Activity Recognition Using DCNN
Get PDFAbstract. This paper presents a novel Deep Convolutional Neural Net
work (DCNN) method for vehicle activity classification. We extend our
previous approach to be able to classify a larger number of vehicle trajec
tories in a single network.We also highlight the fl
exibility of our approach
in integrating further scenarios to our classifier. Firstly, a spatiotempo
ral calculus method is used to encode the relative movement between
vehicles as a trajectory of QTC states. We then map the encoded trajectory to a 2D matrix using the one-hot vector mapping, this preserves
the important positional data and order for each QTC state. To do this
we associate the QTC sequences with pixels to form a 2D image tex
ture. Afterwards, we adapted trained CNN architecture into our vehicles
activity recognition task. Two separate types of driving data sets are
used to evaluate our method. We demonstrate that the proposed method
out-performs existing techniques. Along with the proposed approach we
created a new dataset of vehicles interactions. Although the focus of this
paper is on the automated analysis of vehicle interactions, the proposed
technique is general and can be applied for pairwise analysis for moving
objects
High fat-fed GPR55 null mice display impaired glucose tolerance without concomitant changes in energy balance or insulin sensitivity but are less responsive to the effects of the cannabinoids rimonabant or Δ(9)-tetrahydrocannabivarin on weight gain
Get PDFBackground
The insulin-sensitizing phytocannabinoid, Δ(9)-tetrahydrocannabivarin (THCV) can signal partly via G protein coupled receptor-55 (GPR55 behaving as either an agonist or an antagonist depending on the assay). The cannabinoid receptor type 1 (CB1R) inverse agonist rimonabant is also a GPR55 agonist under some conditions. Previous studies have shown varied effects of deletion of GPR55 on energy balance and glucose homeostasis in mice. The contribution of signalling via GPR55 to the metabolic effects of THCV and rimonabant has been little studied.
Methods
In a preliminary experiment, energy balance and glucose homeostasis were studied in GPR55 knockout and wild-type mice fed on both standard chow (to 20 weeks of age) and high fat diets (from 6 to 15 weeks of age). In the main experiment, all mice were fed on the high fat diet (from 6 to 14 weeks of age). In addition to replicating the preliminary experiment, the effects of once daily administration of THCV (15 mg.kg-1 po) and rimonabant (10 mg.kg-1 po) were compared in the two genotypes.
Results
There was no effect of genotype on absolute body weight or weight gain, body composition measured by either dual-energy X-ray absorptiometry or Nuclear Magnetic Resonance (NMR), fat pad weights, food intake, energy expenditure, locomotor activity, glucose tolerance or insulin tolerance in mice fed on chow. When the mice were fed a high fat diet, there was again no effect of genotype on these various aspects of energy balance. However, in both experiments, glucose tolerance was worse in the knockout than the wild-type mice. Genotype did not affect insulin tolerance in either experiment. Weight loss in rimonabant- and THCV-treated mice was lower in knockout than in wild-type mice, but surprisingly there was no detectable effect of genotype on the effects of the drugs on any aspect of glucose homeostasis after taking into account the effect of genotype in vehicle-treated mice.
Conclusions
Our two experiments differ from those reported by others in finding impaired glucose tolerance in GPR55 knockout mice in the absence of any effect on body weight, body composition, locomotor activity or energy expenditure. Nor could we detect any effect of genotype on insulin tolerance, so the possibility that GPR55 regulates glucose-stimulated insulin secretion merits further investigation. By contrast with the genotype effect in untreated mice, we found that THCV and rimonabant reduced weight gain, and this effect was in part mediated by GPR55
Psychological outcomes of MRSA isolation in spinal cord injury rehabilitation
Get PDFStudy design Retrospective secondary analysis with a quantitative, matched-pairs design. Patients isolated due to methicillin- Resistant Staphylococcus aureus (MRSA) were matched with controls without MRSA infection admitted to a multi-bedded ward, based on: gender, injury level, injury severity (AIS grade), age at the time of injury and year of admission. Objectives Determine the implications of MRSA-related infection isolation on spinal cord injury patients’ anxiety, depression, appraisals of disability, perceived manageability and pain intensity. Hypotheses predicted patients who were isolated due to MRSA during inpatient stay would demonstrate poorer psychological health outcomes at discharge in comparison with non-isolated matched controls.
Setting National Spinal Injuries Centre, England, UK.
Methods Secondary analyses were conducted on pre-existing data based on patients’ first admission for primary rehabili- tation. Psychometric scales were used to measure outcome variables. Assessments were repeated at the time of admission and discharge.
Results Nonparametric longitudinal analyses using the nparLD package in R were conducted. Relative treatment effects demonstrated that there were no significant differences between groups across all outcome measures. There was a significant effect of time (admission vs discharge) on perceived manageability and pain intensity, indicating improved outcomes at discharge. There was no difference in the overall length of stay between the isolated and non-isolated groups. Conclusions Isolation experienced by rehabilitation inpatients with spinal cord injury with MRSA had no effect on a series of psychological outcomes. Engaging with rehabilitation had a positive impact in reducing pain unpleasantness and increasing perceived manageability of spinal cord injury, irrespective of infection isolation
Private Purpose Trusts and the Re Denley Trust 50 Years On
Get PDFWithin England and Wales, it is well-known that a trust cannot be for a purpose unless it is charitable. Yet this assertion is often caveated by the so-called
‘exceptions’ to the rule; one such exception is that of the Re Denley trust. Though some have advocated that it should never have been permitted, the consensus seems to be that the Re Denley trust is yet another form of permissible non-charitable purpose trust. It has now been five decades since the High Court handed down its controversial judgment in Re Denley and notwithstanding the controversy, the decision remains ‘good law’. Though perhaps tempting, it would be naïve to “[place it] on one side in a pile…marked ‘not to be looked at again’”. And to simply dismiss the case as sui generis would likewise trivialise the decision. Indeed, the case requires revisiting not least because it appears to contravene orthodox trust law principles, but also because the decision has been positively cited and relied upon in recent caselaw. So returning to the decision 50 years later is more than just an historically felicitous foray; it is an opportune moment to reconsider our understanding of the fundamental rules and principles governing this area of the law. It may, consequently, require us to reassess those cases which have taken Re Denley as gospel. This article will set out the law in relation to private purpose trusts within England and Wales, and provide a much-needed, up to date critique on the current state of the law. Concomitantly, it will re-examine Re Denley in light of these considerations to establish to what extent, if any, its ostensible departure from the orthodoxy can be justified. Finally, the article will go on to consider possible recognised, alternate methods which could have been employed in Re Denley to achieve the same ends, thus avoiding the creation of this novel, controversial type of trust
Persistent Homology Tools for Image Analysis
Get PDFTopological Data Analysis (TDA) is a new field of mathematics emerged rapidly since the first decade of the century from various works of algebraic topology and
geometry. The goal of TDA and its main tool of persistent homology (PH) is to provide topological insight into complex and high dimensional datasets. We take this
premise onboard to get more topological insight from digital image analysis and quantify tiny low-level distortion that are undetectable except possibly by highly trained persons. Such image distortion could be caused intentionally (e.g. by morphing and steganography) or naturally in abnormal human tissue/organ scan images as a result of onset of cancer or other diseases.
The main objective of this thesis is to design new image analysis tools based on persistent homological invariants representing simplicial complexes on sets of pixel landmarks over a sequence of distance resolutions. We first start by proposing innovative automatic techniques to select image pixel landmarks to build a variety of
simplicial topologies from a single image. Effectiveness of each image landmark selection demonstrated by testing on different image tampering problems such as morphed face detection, steganalysis and breast tumour detection.
Vietoris-Rips simplicial complexes constructed based on the image landmarks at an increasing distance threshold and topological (homological) features computed at each threshold and summarized in a form known as persistent barcodes. We vectorise the space of persistent barcodes using a technique known as persistent binning where we demonstrated the strength of it for various image analysis purposes. Different machine learning approaches are adopted to develop automatic detection of tiny
texture distortion in many image analysis applications. Homological invariants used in this thesis are the 0 and 1 dimensional Betti numbers. We developed an innovative approach to design persistent homology (PH) based
algorithms for automatic detection of the above described types of image distortion. In particular, we developed the first PH-detector of morphing attacks on passport face biometric images. We shall demonstrate significant accuracy of 2 such morph detection algorithms with 4 types of automatically extracted image landmarks: Local Binary patterns (LBP), 8-neighbour super-pixels (8NSP), Radial-LBP (R-LBP) and centre-symmetric LBP (CS-LBP). Using any of these techniques yields several persistent barcodes that summarise persistent topological features that help gaining insights into complex hidden structures not amenable by other image analysis methods. We shall also demonstrate significant success of a similarly developed PH-based universal steganalysis tool capable for the detection of secret messages hidden inside digital images. We also argue through a pilot study that building PH records from digital images can differentiate breast malignant tumours from benign tumours using digital mammographic images. The research presented in this thesis creates new opportunities to build real applications based on TDA and demonstrate many research challenges in a variety of image processing/analysis tasks. For example, we describe a TDA-based exemplar image inpainting technique (TEBI), superior to existing exemplar algorithm, for the reconstruction of missing image regions
The Impacts of Energy Consumption, Energy Prices and Energy Import-Dependency on Gross and Sectoral Value-Added in Sri Lanka
Get PDFDrifting away from the neoclassical growth conjecture of economic growth being solely dependent on capital and labor inputs, this paper aimed to evaluate the dynamic impacts of energy consumption, energy prices and imported energy-dependency on both gross and sectoral value added figures of Sri Lanka. The analysis has particularly used the robust econometric methods that can account for structural break issues in the data. The results, in a nutshell, indicated that energy consumption homogeneously contributes to gross, agricultural, industrial and services valueadditions
in Sri Lanka. However, positive oil price shocks and greater shares of imported energy in the total energy consumption figures are found to dampen the growth figures, especially in the context of the gross, industrial and services value additions. Besides, the joint growth-inhibiting impacts of oil price movements and energy import-dependency are also ascertained. On the other hand, the causality estimates reveal bidirectional causal associations between energy consumption gross value-added and energy consumption-industrial value-added. In contrast, no causal impact
of energy consumption on the agricultural and services value-added is evidenced. Hence, these findings impose key policy implications for constructing crucial energy policy reforms to make sure that the economic growth performances of Sri Lanka are sustained in the future
The Disruptive Effect of Distributed Ledger Technology and Blockchain in the over the counter derivatives market
Get PDFThe market for derivatives has endured a substantial transformation and scrutiny since the 2007/08 financial crisis. This subprime or credit crunch disaster seriously undermined what fuels business ‘Trust’, therefore customers lost faith in financial institutions. Banks’ ledger manipulation reached unacceptable levels by moving debt off the books during auditing times and assigning speculative high values to hard-to-value assets, which ultimately had not value at all. All of these led to serious concerns about financial services integrity. Understandably, the market was hurt thus; sharp expressions like ‘Lehman Brothers is often Exhibit A in the breakdown of trust in the twenty-first century’ are used. At the heart of the subprime crisis laid collateralised debt obligations (CDO’s), credit default swaps (CDS’s) and the derivative financial instruments created and privately traded over the counter. There were three main features in the over the counter derivatives market (OTC), namely Deregulation, Secrecy and Descentralisation which added to or triggered the crisis.
The unregulated (OTC) market operated under the premise that banks would design products and adapt to the incumbent demands of the financial ecosystem therefore develop their own rules. Sadly, excessive unethical profit driven practices infested this liberalised segment of the market. Secrecy on the other hand exacerbated the problem because OTC derivatives traded bilaterally or privately and did not need to go through any central clearing counterparty so the system was mainly uncontrollable. This explains why governments could not exactly assess from the onset the magnitude of the financial crisis.
The question at that time was whether stakeholders including Fintech startups, should remain passive or proactive hence, the ‘Dichotomy’ faced by financial innovators, was to insist with a system based on trust in financial institutions, or explore others more transparent where neither trust nor were banks, as intermediaries, indispensable for the successful and safe completion of financial transactions.
The latter idea prevailed and developed a series of important platforms, which came to disrupt or incrementally benefit financial services thus changing not only the payments landscape, but also the structure of the service itself. The OTC market is experiencing these changes and it is gradually becoming a smart system.
One could look at the smart OTC market from three different angles: as depository or record keeping of transactions (Blockchain), as contract executing system (Smart Contracts) and regulatory (Regulation).
The aim of this piece of research is to analyse to what extent innovative technology such Blockchain with embedded smart contracts, may affect the way the ‘Over the Counter’ (OTC) market operates, by providing investors with a trustworthy platform for the efficient assessment of the risk behind certain financial instruments. Consequently, the market will be more resilient when another financial crisis strikes. It approaches the problem from a pure practical or investment perspective namely how to deliver the OTC service to consumers. Albeit this article touches upon regulatory matters and the desirable use of central counterparties (CCP’s) for clearing, regulation per se will be the subject matter of the author’s future research outputs. It is necessary to emphasise indeed that the over the counter derivative market still softly regulated therefore, identifying some advantages and disadvantages of using Blockchain may help future legislation
A common risk factor and the correlation between equity and corporate bond returns
Get PDFA growing body of literature documents that security prices within and across asset classes behave similarly highlighting the importance of investors’ common expectations about future risk and returns in the asset pricing. Consequently, variations in the common expectations of investors have a major role in determining the correlation among asset prices. We examine the role of these common expectations in determining the relationship between firm-level equity and bond returns. We use a novel measure of the common expectations defined as the difference in relative frequencies of words signalling excitement and anxiety in a large dataset of articles published by Reuters. Further, we also consider the VIX index and the indices of Baker and Wurgler (2006) and Huang et al. (2015) as potential common factors. The results show that changes in common expectations, proxied by our index and the VIX, are significant in predicting variations in the correlation between equity and bond returns. An improvement in investors’ optimism about future risk and returns causes a weaker correlation. The effect is stronger for the riskiest firms and flattens as firms’ credit risk improves. By decomposing our index into the excitement and anxiety components, we find that this predictive power is due to changes in the anxiety component