Detecting Illegal Arms Trade

Illegal arms are responsible for thousands of deaths in civil wars every year. Yet, their trade is very hard to detect. We propose a method to statistically detect illegal arms trade based on the investor knowledge embedded in financial markets. We focus on eight countries under UN arms embargo in the period 1990-2005, and analyze eighteen events during the embargo that suddenly increase or decrease conflict intensity. If the weapon-making companies are not trading or are trading legally, an event worsening the hostilities should not affect their stock prices or affect them adversely, since it delays the removal of the embargo. Conversely, if the companies are trading illegally, the event may increase stock prices, since it increases the demand for illegal weapons. We detect no significant effect overall. However, we find a large and significant positive reaction for companies head-quartered in countries where the legal and reputation costs of illegal trades are likely to be lower. We identify such countries using measures of corruption and transparency in arms trade. We also suggest a method to detect potential embargo violations based on stock reactions by individual companies, including chains of reactions. The presumed violations are higher for conflicts with more UN investigations and for companies with more Internet stories regarding embargo.

Maternal Diet Intervention Before Pregnancy Primes Offspring Lipid Metabolism in Liver

Nonalcoholic fatty liver disease (NAFLD) has a developmental origin and is influenced in utero. We aimed to evaluate if maternal diet intervention before pregnancy would be beneficial to reduce the risk of offspring NAFLD. In our study, female mice were either on a normal-fat diet (NF group), or a high-fat diet for 12 weeks and continued on this diet throughout pregnancy and lactation (HF group), or switched from HF-to-NF diet 1 week (H1N group), or 9 weeks (H9N group) before pregnancy. Compared with the NF offspring, the H1N and HF, but not the H9N offspring, displayed more severe hepatic steatosis and glucose intolerance. More specifically, an abnormal blood lipid panel was seen in the H1N offspring and abnormal hepatic free fatty acid composition was present in both the HF and H1N offspring, while the H9N offspring displayed both at normal levels. These physiological changes were associated with desensitized hepatic insulin/AKT signaling, increased expression of genes and proteins for de novo lipogenesis and cholesterol synthesis, decreased expression of genes and proteins for fatty acid oxidation, increased Pcsk9 expression, and hypoactivation of 5' AMP-activated protein kinase (AMPK) signaling in the HF and H1N offspring. However, these effects were completely or partially rescued in the H9N offspring. In summary, we found that early maternal diet intervention is effective in reducing the risk of offspring NAFLD caused by maternal HF diet. These findings provide significant support to develop effective diet intervention strategies and policies for prevention of obesity and NAFLD to promote optimal health outcomes for mothers and children

Air Traffic Safety: continued evolution or a new Paradigm.

The context here is Transport Risk Management. Is the philosophy of Air Traffic Safety different from other modes of transport? – yes, in many ways, it is. The focus is on Air Traffic Management (ATM), covering (eg) air traffic control and airspace structures, which is the part of the aviation system that is most likely to be developed through new paradigms. The primary goal of the ATM system is to control accident risk. ATM safety has improved over the decades for many reasons, from better equipment to additional safety defences. But ATM safety targets, improving on current performance, are now extremely demanding. What are the past and current methodologies for ATM risk assessment; and will they work effectively for the kinds of future systems that people are now imagining and planning? The title contrasts ‘Continued Evolution’ and a ‘New Paradigm’. How will system designers/operators assure safety with traffic growth and operational/technical changes that are more than continued evolution from the current system? What are the design implications for ‘new paradigms’, such as the USA’s ‘Next Generation Air Transportation System’ (NextGen) and Europe’s Single European Sky ATM Research Programme (SESAR)? Achieving and proving safety for NextGen and SESAR is an enormously tough challenge. For example, it will need to cover system resilience, human/automation issues, software/hardware performance/ground/air protection systems. There will be a need for confidence building programmes regarding system design/resilience, eg Human-in-the-Loop simulations with ‘seeded errors’

Misconfiguration in Firewalls and Network Access Controls: Literature Review

Firewalls and network access controls play important roles in security control and protection. Those firewalls may create an incorrect sense or state of protection if they are improperly configured. One of the major configuration problems in firewalls is related to misconfiguration in the access control roles added to the firewall that will control network traffic. In this paper, we evaluated recent research trends and open challenges related to firewalls and access controls in general and misconfiguration problems in particular. With the recent advances in next-generation (NG) firewalls, firewall roles can be auto-generated based on networks and threats. Nonetheless, and due to the large number of roles in any medium to large networks, roles’ misconfiguration may occur for several reasons and will impact the performance of the firewall and overall network and protection efficiency

Distinctive Personality Traits and Neural Correlates Associated with Stimulant Drug Use Versus Familial Risk of Stimulant Dependence

BackgroundStimulant drugs such as cocaine and amphetamine have a high abuse liability, but not everyone who uses them develops dependence. However, the risk for dependence is increased for individuals with a family history of addiction. We hypothesized that individuals without a family history of dependence who have been using cocaine recreationally for several years but have not made the transition to dependence will differ in terms of personality traits and brain structure from individuals who are either dependent on stimulants or at risk for dependence.MethodsWe compared 27 individuals without a familial risk of dependence who had been using cocaine recreationally with 50 adults with stimulant dependence, their nondependent siblings (n = 50), and unrelated healthy volunteers (n = 52) who had neither a personal nor a family history of dependence. All participants underwent a magnetic resonance imaging brain scan and completed a selection of personality measures that have been associated with substance abuse.ResultsIncreased sensation-seeking traits and abnormal orbitofrontal and parahippocampal volume were shared by individuals who were dependent on stimulant drugs or used cocaine recreationally. By contrast, increased levels of impulsive and compulsive personality traits and limbic-striatal enlargement were shared by stimulant-dependent individuals and their unaffected siblings.ConclusionsWe provide evidence for distinct neurobiological phenotypes that are either associated with familial vulnerability for dependence or with regular stimulant drug use. Our findings further suggest that some individuals with high sensation-seeking traits but no familial vulnerability for dependence are likely to use cocaine but may have relatively low risk for developing dependence

CLUSTERED HIERARCHICAL ANOMALY AND OUTLIER DETECTION ALGORITHMS

Anomaly and outlier detection is a long-standing problem in machine learning. In some cases, anomaly detection is easy, such as when data are drawn from well-characterized distributions such as the Gaussian. However, when data occupy high-dimensional spaces, anomaly detection becomes more difficult. We present CLAM (Clustered Learning of Approximate Manifolds), a manifold mapping technique in any metric space. CLAM begins with a fast hierarchical clustering technique and then induces a graph from the cluster tree, based on overlapping clusters as selected using several geometric and topological features. Using these graphs, we implement CHAODA (Clustered Hierarchical Anomaly and Outlier Detection Algorithms), exploring various properties of the graphs and their constituent clusters to find outliers. CHAODA employs a form of transfer learning based on a training set of datasets, and applies this knowledge to a separate test set of datasets of different cardinalities, dimensionalities, and domains. On 24 publicly available datasets, we compare CHAODA (by measure of ROC AUC) to a variety of state-of-the-art unsupervised anomaly-detection algorithms. Six of the datasets are used for training. CHAODA outperforms other approaches on 16 of the remaining 18 datasets. CLAM and CHAODA scale to large, high-dimensional “big data” anomalydetection problems, and generalize across datasets and distance functions. Source code to CLAM and CHAODA are freely available on GitHub1

Air Traffic Management Safety Challenges

The primary goal of the Air Traffic Management (ATM) system is to control accident risk. ATM safety has improved over the decades for many reasons, from better equipment to additional safety defences. But ATM safety targets, improving on current performance, are now extremely demanding. Safety analysts and aviation decision-makers have to make safety assessments based on statistically incomplete evidence. If future risks cannot be estimated with precision, then how is safety to be assured with traffic growth and operational/technical changes? What are the design implications for the USA’s ‘Next Generation Air Transportation System’ (NextGen) and Europe’s Single European Sky ATM Research Programme (SESAR)? ATM accident precursors arise from (eg) pilot/controller workload, miscommunication, and lack of upto- date information. Can these accident precursors confidently be ‘designed out’ by (eg) better system knowledge across ATM participants, automatic safety checks, and machine rather than voice communication? Future potentially hazardous situations could be as ‘messy’ in system terms as the Überlingen mid-air collision. Are ATM safety regulation policies fit for purpose: is it more and more difficult to innovate, to introduce new technologies and novel operational concepts? Must regulators be more active, eg more inspections and monitoring of real operational and organisational practices