Cartels: the Probability of Getting Caught in the European Union. Bruges European Economic Research (BEER) Papers 12/March 2008

In 1991, Bryant and Eckard estimated the annual probability that a cartel would be detected by the US Federal authorities, conditional on being detected, to be at most between 13 % and 17 %. 15 years later, we estimated the same probability over a European sample and we found an annual probability that falls between 12.9 % and 13.3 %. We also develop a detection model to clarify this probability. Our estimate is based on detection durations, calculated from data reported for all the cartels convicted by the European Commission from 1969 to the present date, and a statistical birth and death process model describing the onset and detection of cartels.

Phosphoregulators: Protein kinases and protein phosphatases of mouse

With the completion of the human and mouse genome sequences, the task now turns to identifying their encoded transcripts and assigning gene function. In this study, we have undertaken a computational approach to identify and classify all of the protein kinases and phosphatases present in the mouse gene complement. A nonredundant set of these sequences was produced by mining Ensembl gene predictions and publicly available cDNA sequences with a panel of InterPro domains. This approach identified 561 candidate protein kinases and 162 candidate protein phosphatases. This cohort was then analyzed using TribeMCL protein sequence similarity clustering followed by CLUSTALV alignment and hierarchical tree generation. This approach allowed us to (1) distinguish between true members of the protein kinase and phosphatase families and enzymes of related biochemistry, (2) determine the structure of the families, and (3) suggest functions for previously uncharacterized members. The classifications obtained by this approach were in good agreement with previous schemes and allowed us to demonstrate domain associations with a number of clusters. Finally, we comment on the complementary nature of cDNA and genome-based gene detection and the impact of the FANTOM2 transcriptome project.

Effects of CO2 and iron availability on rbcL gene expression in Bering Sea diatoms

Iron (Fe) can limit phytoplankton productivity in approximately 40% of the global ocean, including in high-nutrient, low-chlorophyll (HNLC) waters. However, there is little information available on the impact of CO2-induced seawater acidification on natural phytoplankton assemblages in HNLC regions. We therefore conducted an on-deck experiment manipulating CO2 and Fe using Fe-deficient Bering Sea water during the summer of 2009. The concentrations of CO2 in the incubation bottles were set at 380 and 600 ppm in the non-Fe-added (control) bottles and 180, 380, 600, and 1000 ppm in the Fe-added bottles. The phytoplankton assemblages were primarily composed of diatoms followed by haptophytes in all incubation bottles as estimated by pigment signatures throughout the 5-day (control) or 6-day (Fe-added treatment) incubation period. At the end of incubation, the relative contribution of diatoms to chlorophyll a biomass was significantly higher in the 380 ppm CO2 treatment than in the 600 ppm treatment in the controls, whereas minimal changes were found in the Fe-added treatments. These results indicate that, under Fe-deficient conditions, the growth of diatoms could be negatively affected by the increase in CO2 availability. To further support this finding, we estimated the expression and phylogeny of rbcL (which encodes the large subunit of RuBisCO) mRNA in diatoms by quantitative reverse transcription polymerase chain reaction (PCR) and clone library techniques, respectively. Interestingly, regardless of Fe availability, the transcript abundance of rbcL decreased in the high CO2 treatments (600 and 1000 ppm). The present study suggests that the projected future increase in seawater pCO2 could reduce the RuBisCO transcription of diatoms, resulting in a decrease in primary productivity and a shift in the food web structure of the Bering Sea.

Intrusion detection techniques in wireless local area networks

This research investigates wireless intrusion detection techniques for detecting attacks on IEEE 802.11i Robust Secure Networks (RSNs). Despite using a variety of comprehensive preventative security measures, the RSNs remain vulnerable to a number of attacks. Failure of preventative measures to address all RSN vulnerabilities dictates the need for a comprehensive monitoring capability to detect all attacks on RSNs and also to proactively address potential security vulnerabilities by detecting security policy violations in the WLAN. This research proposes novel wireless intrusion detection techniques to address these monitoring requirements and also studies correlation of the generated alarms across wireless intrusion detection system (WIDS) sensors and the detection techniques themselves for greater reliability and robustness. The specific outcomes of this research are: A comprehensive review of the outstanding vulnerabilities and attacks in IEEE 802.11i RSNs. A comprehensive review of the wireless intrusion detection techniques currently available for detecting attacks on RSNs. Identification of the drawbacks and limitations of the currently available wireless intrusion detection techniques in detecting attacks on RSNs. Development of three novel wireless intrusion detection techniques for detecting RSN attacks and security policy violations in RSNs. Development of algorithms for each novel intrusion detection technique to correlate alarms across distributed sensors of a WIDS. Development of an algorithm for automatic attack scenario detection using cross detection technique correlation. Development of an algorithm to automatically assign priority to the detected attack scenario using cross detection technique correlation.

Experimenting with an intrusion detection system for encrypted networks

Network-based Intrusion Detection Systems (NIDSs) analyse network traffic to detect instances of malicious activity. Typically, this is only possible when the network traffic is accessible for analysis. With the growing use of Virtual Private Networks (VPNs) that encrypt network traffic, the NIDS can no longer access this crucial audit data. In this paper, we present an implementation and evaluation of our approach proposed in Goh et al. (2009). It is based on Shamir's secret-sharing scheme and allows a NIDS to function normally in a VPN without any modifications and without compromising the confidentiality afforded by the VPN.

Intrusion detection system for encrypted networks using secret-sharing schemes

Secret-sharing schemes describe methods to securely share a secret among a group of participants. A properly constructed secret-sharing scheme guarantees that the share belonging to one participant does not reveal anything about the shares of others or even the secret itself. Besides the obvious feature which is to distribute a secret, secret-sharing schemes have also been used in secure multi-party computations and redundant residue number systems for error correction codes. In this paper, we propose that the secret-sharing scheme be used as a primitive in a Network-based Intrusion Detection System (NIDS) to detect attacks in encrypted networks. Encrypted networks such as Virtual Private Networks (VPNs) fully encrypt network traffic which can include both malicious and non-malicious traffic. Traditional NIDS cannot monitor encrypted traffic. Our work uses a combination of Shamir's secret-sharing scheme and randomised network proxies to enable a traditional NIDS to function normally in a VPN environment. In this paper, we introduce a novel protocol that utilises a secret-sharing scheme to detect attacks in encrypted networks.

Accurate silhouettes for surveillance : improved motion segmentation using graph cuts

Silhouettes are common features used by many applications in computer vision. For many of these algorithms to perform optimally, accurately segmenting the objects of interest from the background to extract the silhouettes is essential. Motion segmentation is a popular technique to segment moving objects from the background, however such algorithms can be prone to poor segmentation, particularly in noisy or low contrast conditions. In this paper, the work of [3] combining motion detection with graph cuts, is extended into two novel implementations that aim to allow greater uncertainty in the output of the motion segmentation, providing a less restricted input to the graph cut algorithm. The proposed algorithms are evaluated on a portion of the ETISEO dataset using hand segmented ground truth data, and an improvement in performance over the motion segmentation alone and the baseline system of [3] is shown.

Towards the implementation of vision-based UAS sense-and-avoid

Machine vision represents a particularly attractive solution for sensing and detecting potential collision-course targets due to the relatively low cost, size, weight, and power requirements of the sensors involved. This paper describes the development of detection algorithms and the evaluation of a real-time flight ready hardware implementation of a vision-based collision detection system suitable for fixed-wing small/medium size UAS. In particular, this paper demonstrates the use of Hidden Markov filter to track and estimate the elevation (β) and bearing (α) of the target, compares several candidate graphic processing hardware choices, and proposes an image based visual servoing approach to achieve collision avoidance

Molecular characterisation of six badnavirus species associated with leaf streak disease of banana in East Africa

Banana leaf streak disease, caused by several species of Banana streak virus (BSV), is widespread in East Africa. We surveyed for this disease in Uganda and Kenya, and used rolling-circle amplification (RCA) to detect the presence of BSV in banana. Six distinct badnavirus sequences, three from Uganda and three from Kenya, were amplified for which only partial sequences were previously available. The complete genomes were sequenced and characterised. The size and organisation of all six sequences was characteristic of other badnaviruses, including conserved functional domains present in the putative polyprotein encoded by open reading frame (ORF) 3. Based on nucleotide sequence analysis within the reverse transcriptase/ribonuclease H-coding region of open reading frame 3, we propose that these sequences be recognised as six new species and be designated as Banana streak UA virus, Banana streak UI virus, Banana streak UL virus, Banana streak UM virus, Banana streak CA virus and Banana streak IM virus. Using PCR and species-specific primers to test for the presence of integrated sequences, we demonstrated that sequences with high similarity to BSIMV only were present in several banana cultivars which had tested negative for episomal BSV sequences.

Intrusion detection framework for encrypted networks

Network-based Intrusion Detection Systems (NIDSs) monitor network traffic for signs of malicious activities that have the potential to disrupt entire network infrastructures and services. NIDS can only operate when the network traffic is available and can be extracted for analysis. However, with the growing use of encrypted networks such as Virtual Private Networks (VPNs) that encrypt and conceal network traffic, a traditional NIDS can no longer access network traffic for analysis. The goal of this research is to address this problem by proposing a detection framework that allows a commercial off-the-shelf NIDS to function normally in a VPN without any modification. One of the features of the proposed framework is that it does not compromise on the confidentiality afforded by the VPN. Our work uses a combination of Shamir’s secret-sharing scheme and randomised network proxies to securely route network traffic to the NIDS for analysis. The detection framework is effective against two general classes of attacks – attacks targeted at the network hosts or attacks targeted at framework itself. We implement the detection framework as a prototype program and evaluate it. Our evaluation shows that the framework does indeed detect these classes of attacks and does not introduce any additional false positives. Despite the increase in network overhead in doing so, the proposed detection framework is able to consistently detect intrusions through encrypted networks.

Fusion of morphological images for airborne target detection

Several track-before-detection approaches for image based aircraft detection have recently been examined in an important automated aircraft collision detection application. A particularly popular approach is a two stage processing paradigm which involves: a morphological spatial filter stage (which aims to emphasize the visual characteristics of targets) followed by a temporal or track filter stage (which aims to emphasize the temporal characteristics of targets). In this paper, we proposed new spot detection techniques for this two stage processing paradigm that fuse together raw and morphological images or fuse together various different morphological images (we call these approaches morphological reinforcement). On the basis of flight test data, the proposed morphological reinforcement operations are shown to offer superior signal to-noise characteristics when compared to standard spatial filter options (such as the close-minus-open and adaptive contour morphological operations). However, system operation characterised curves, which examine detection verses false alarm characteristics after both processing stages, illustrate that system performance is very data dependent.

Creating gold nanoprisms directly on quartz crystal microbalance electrodes for mercury vapor sensing

A novel electrochemical route is used to form highly {111}-oriented and size-controlled Au nanoprisms directly onto the electrodes of quartz crystal microbalances (QCMs) which are subsequently used as mercury vapor sensors. The Au nanoprism loaded QCM sensors exhibited excellent response–concentration linearity with a response enhancement of up to ~ 800% over a non-modified sensor at an operating temperature of 28 °C. The increased surface area and atomic-scale features (step/defect sites) introduced during the growth of nanoprisms are thought to play a significant role in enhancing the sensing properties of the Au nanoprisms toward Hg vapor. The sensors are shown to have excellent Hg sensing capabilities in the concentration range of 0.123–1.27 ppmv (1.02–10.55 mg m − 3), with a detection limit of 2.4 ppbv (0.02 mg m − 3) toward Hg vapor when operating at 28 °C, and 17 ppbv (0.15 mg m − 3) at 89 °C, making them potentially useful for air monitoring applications or for monitoring the efficiency of Hg emission control systems in industries such as mining and waste incineration. The developed sensors exhibited excellent reversible behavior (sensor recovery) within 1 h periods, and crucially were also observed to have high selectivity toward Hg vapor in the presence of ethanol, ammonia and humidity, and excellent long-term stability over a 33 day operating period.

Practical Modbus flooding attack and detection

The Modicon Communication Bus (Modbus) protocol is one of the most commonly used protocols in industrial control systems. Modbus was not designed to provide security. This paper confirms that the Modbus protocol is vulnerable to flooding attacks. These attacks involve injection of commands that result in disrupting the normal operation of the control system. This paper describes a set of experiments that shows that an anomaly-based change detection algorithm and signature-based Snort threshold module are capable of detecting Modbus flooding attacks. In comparing these intrusion detection techniques, we find that the signature-based detection requires a carefully selected threshold value, and that the anomaly-based change detection algorithm may have a short delay before detecting the attacks depending on the parameters used. In addition, we also generate a network traffic dataset of flooding attacks on the Modbus control system protocol.

Child sexual abuse in China : a meta-analysis of 27 studies

Objective: To examine whether Chinese studies of child sexual abuse (CSA) in the general population show lower prevalence rates than other international studies, and whether certain features of these studies may help to account for variation in estimates. Methods: A meta-analysis and meta-regression were conducted on 27 studies found in the English and Chinese language peer reviewed journals that involved general populations of students or residents, estimated CSA prior to age 18, and specified rates for males or females individually. Results: Estimates for Chinese females were lower than the international composites. For total CSA for females, the Chinese pooled estimate was 15.3% (95% CI = 12.6–18.0) based on the meta-analysis of 24 studies, lower than the international estimate (Stoltenborgh, van IJzendoorn, Euser, & Bakermans-Kranenburg, 2011) but not significantly. For contact CSA for females, the pooled estimate was 9.5% (95% CI = 7.5–11.5), based on 16 studies, significantly lower than the international prevalence. For penetrative CSA for females, the pooled estimate was 1% (95% CI = 0.7–1.3), based on 15 studies, significantly lower than the international estimate of 15.1%. Chinese men reported significantly less penetrative CSA but significantly more total CSA than international estimates; while contact CSA reported by Chinese and international males appeared to be roughly equivalent. Chinese CSA prevalence estimates were lower in studies from urban areas and non-mainland areas (Hong Kong and Taiwan), and in surveys with larger and probability samples, multiple sites, face-to-face interview method and when using less widely used instruments. Conclusions: The findings to date justify further research into possible cultural and sociological reasons for lower risk of contact and penetrative sexual abuse of girls and less penetrative abuse of boys in China. Future research should examine sociological explanations, including patterns of supervision, sexual socialization and attitudes related to male sexual prowess. Practice implications: The findings suggest that future general population studies in China should use well validated instruments, avoid face-to-face interview formats and be careful to maintain methodological standards when sampling large populations over multiple sites.

Size dependent photodegradation of CdS particles deposited onto TiO2 mesoporous films by SILAR method

The properties of CdS nanoparticles incorporated onto mesoporous TiO2 films by a successive ionic layer adsorption and reaction (SILAR) method were investigated by Raman spectroscopy, UV-visible spectroscopy, transmission electron microscopy (TEM) and X-ray photoelectron spectroscopy (XPS). High resolution TEM indicated that the synthesized CdS particles were hexagonal phase and the particle sizes were less than 5 nm when SILAR cycles were fewer than 9. Quantum size effect was found with the CdS sensitized TiO2 films prepared with up to 9 SILAR cycles. The band gap of CdS nanoparticles decreased from 2.65 eV to 2.37 eV with the increase of the SILAR cycles from 1 to 11. The investigation of the stability of the CdS/TiO2 films in air under illumination (440.6 µW/cm2) showed that the photodegradation rate was up to 85% per day for the sample prepared with 3 SILAR cycles. XPS analysis indicated that the photodegradation was due to the oxidation of CdS, leading to the transformation from sulphide to sulphate (CdSO4). Furthermore, the degradation rate was strongly dependent upon the particle size of CdS. Smaller particles showed faster degradation rate. The size-dependent photo-induced oxidization was rationalized with the variation of size-dependent distribution of surface atoms of CdS particles. Molecular Dynamics (MD) simulation has indicated that the surface sulphide anion of a large CdS particle such as CdS made with 11 cycles (CdS11, particle size = 5.6 nm) accounts for 9.6% of the material whereas this value is increased to 19.2% for (CdS3) based smaller particles (particle size: 2.7 nm). Nevertheless, CdS nanoparticles coated with ZnS material showed a significantly enhanced stability under illumination in air. A nearly 100% protection of CdS from photon induced oxidation with a ZnS coating layer prepared using four SILAR cycles, suggesting the formation of a nearly complete coating layer on the CdS nanoparticles.