Vitamin D receptor gene variants and esophageal adenocarcinoma risk:A population-based case-control study

Purpose: Polymorphisms in the vitamin D receptor (VDR) gene may be of etiological importance in determining cancer risk. The aim of this study was to assess the association between common VDR gene polymorphisms and esophageal adenocarcinoma (EAC) risk in an all-Ireland population-based case-control study. Methods: EAC cases and frequency-matched controls by age and gender recruited between March 2002 and December 2004 throughout Ireland were included. Participants were interviewed, and a blood sample collected for DNA extraction. Twenty-seven single nucleotide polymorphisms in the VDR gene were genotyped using Sequenom or TaqMan assays while the poly(A) microsatellite was genotyped by fluorescent fragment analysis. Unconditional logistic regression was applied to assess the association between VDR polymorphisms and EAC risk. Results: A total of 224 cases of EAC and 256 controls were involved in analyses. After adjustment for potential confounders, TT homozygotes at rs2238139 and rs2107301 had significantly reduced risks of EAC compared with CC homozygotes. In contrast, SS alleles of the poly(A) microsatellite had significantly elevated risks of EAC compared with SL/LL alleles. However, following permutation analyses to adjust for multiple comparisons, no significant associations were observed between any VDR gene polymorphism and EAC risk. Conclusions: VDR gene polymorphisms were not significantly associated with EAC development in this Irish population. Confirmation is required from larger studies. © Springer Science+Business Media, LLC 2011.

Socio-economic status and lifestyle factors are associated with achalasia risk: a population-based case-control study.

AIM: To evaluate the association between various lifestyle factors and achalasia risk.

METHODS: A population-based case-control study was conducted in Northern Ireland, including n= 151 achalasia cases and n = 117 age- and sex-matched controls. Lifestyle factors were assessed via a face-to-face structured interview. The association between achalasia and lifestyle factors was assessed by unconditional logistic regression, to produce odds ratios (OR) and 95% confidence interval (CI).

RESULTS: Individuals who had low-class occupations were at the highest risk of achalasia (OR = 1.88, 95%CI: 1.02-3.45), inferring that high-class occupation holders have a reduced risk of achalasia. A history of foreign travel, a lifestyle factor linked to upper socio-economic class, was also associated with a reduced risk of achalasia (OR = 0.59, 95%CI: 0.35-0.99). Smoking and alcohol consumption carried significantly reduced risks of achalasia, even after adjustment for socio-economic status. The presence of pets in the house was associated with a two-fold increased risk of achalasia (OR = 2.00, 95%CI: 1.17-3.42). No childhood household factors were associated with achalasia risk.

CONCLUSION: Achalasia is a disease of inequality, and individuals from low socio-economic backgrounds are at highest risk. This does not appear to be due to corresponding alcohol and smoking behaviours. An observed positive association between pet ownership and achalasia risk suggests an interaction between endotoxin and viral infection exposure in achalasia aetiology.

Co-operative tensegrity-based formation control algorithm for a multi-aircraft system

This paper presents a tensegrity-based co-operative control algorithm for an aircraft formation. The 6 degrees-of-freedom model of the well-known Aerosonde unmanned aerial vehicle (UAV), is integrated with the model of the tensegrity structure and a decentralised control scheme is proposed. The strategy is shown to be scalable for 2n number of UAVs and is able to maintain a firm geometry whilst allowing flexible shape transformations. Simulation results demonstrate the effectiveness and stability of the proposed tensegrity-based formation control algorithm in 3D.

Threat Analysis of BlackEnergy Malware for Synchrophasor based Real-time Control and Monitoring in Smart Grid

The BlackEnergy malware targeting critical infrastructures has a long history. It evolved over time from a simple DDoS platform to a quite sophisticated plug-in based malware. The plug-in architecture has a persistent malware core with easily installable attack specific modules for DDoS, spamming, info-stealing, remote access, boot-sector formatting etc. BlackEnergy has been involved in several high profile cyber physical attacks including the recent Ukraine power grid attack in December 2015. This paper investigates the evolution of BlackEnergy and its cyber attack capabilities. It presents a basic cyber attack model used by BlackEnergy for targeting industrial control systems. In particular, the paper analyzes cyber threats of BlackEnergy for synchrophasor based systems which are used for real-time control and monitoring functionalities in smart grid. Several BlackEnergy based attack scenarios have been investigated by exploiting the vulnerabilities in two widely used synchrophasor communication standards: (i) IEEE C37.118 and (ii) IEC 61850-90-5. Specifically, the paper addresses reconnaissance, DDoS, man-in-the-middle and replay/reflection attacks on IEEE C37.118 and IEC 61850-90-5. Further, the paper also investigates protection strategies for detection and prevention of BlackEnergy based cyber physical attacks.

Performance analysis of an improved power-saving medium access protocol for IEEE 802.11 point coordination function WLAN

Wireless enabled portable devices must operate with the highest possible energy efficiency while still maintaining a minimum level and quality of service to meet the user's expectations. The authors analyse the performance of a new pointer-based medium access control protocol that was designed to significantly improve the energy efficiency of user terminals in wireless local area networks. The new protocol, pointer controlled slot allocation and resynchronisation protocol (PCSAR), is based on the existing IEEE 802.11 point coordination function (PCF) standard. PCSAR reduces energy consumption by removing the need for power saving stations to remain awake and listen to the channel. Using OPNET, simulations were performed under symmetric channel loading conditions to compare the performance of PCSAR with the infrastructure power saving mode of IEEE 802.11, PCF-PS. The simulation results demonstrate a significant improvement in energy efficiency without significant reduction in performance when using PCSAR. For a wireless network consisting of an access point and 8 stations in power saving mode, the energy saving was up to 31% while using PCSAR instead of PCF-PS, depending upon frame error rate and load. The results also show that PCSAR offers significantly reduced uplink access delay over PCF-PS while modestly improving uplink throughput.

Improved power-saving medium access protocol for IEEE 802.11e QoS-enabled wireless networks

The performance of a new pointer-based medium-access control protocol that was designed to significantly improve the energy efficiency of user terminals in quality-of-service-enabled wireless local area networks was analysed. The new protocol, pointer-controlled slot allocation and resynchronisation protocol (PCSARe), is based on the hybrid coordination function-controlled channel access mode of the IEEE 802.11e standard. PCSARe reduces energy consumption by removing the need for power-saving stations to remain awake for channel listening. Discrete event network simulations were performed to compare the performance of PCSARe with the non-automatic power save delivery (APSD) and scheduled-APSD power-saving modes of IEEE 802.11e. The simulation results show a demonstrable improvement in energy efficiency without significant reduction in performance when using PCSARe. For a wireless network consisting of an access point and eight stations in power-saving mode, the energy saving was up to 39% when using PCSARe instead of IEEE 802.11e non-APSD. The results also show that PCSARe offers significantly reduced uplink access delay over IEEE 802.11e non-APSD, while modestly improving the uplink throughput. Furthermore, although both had the same energy consumption, PCSARe gave a 25% reduction in downlink access delay compared with IEEE 802.11e S-APSD.

Plant-wide predictive control for a thermal power plant based on a physical plant model

A constrained non-linear, physical model-based, predictive control (NPMPC) strategy is developed for improved plant-wide control of a thermal power plant. The strategy makes use of successive linearisation and recursive state estimation using extended Kalman filtering to obtain a linear state-space model. The linear model and a quadratic programming routine are used to design a constrained long-range predictive controller One special feature is the careful selection of a specific set of plant model parameters for online estimation, to account for time-varying system characteristics resulting from major system disturbances and ageing. These parameters act as nonstationary stochastic states and help to provide sufficient degrees-of-freedom to obtain unbiased estimates of controlled outputs. A 14th order non-linear plant model, simulating the dominant characteristics of a 200 MW oil-fired pou er plant has been used to test the NPMPC algorithm. The control strategy gives impressive simulation results, during large system disturbances and extremely high rate of load changes, right across the operating range. These results compare favourably to those obtained with the state-space GPC method designed under similar conditions.

A Population-Based Study of IGF Axis Polymorphisms and the Esophageal Inflammation, Metaplasia, Adenocarcinoma Sequence

BACKGROUND & AIMS: Insulin-like growth factor (IGF) axis plays a key role in cell development, proliferation, and survival and is implicated in the etiology of several cancers. Few studies have examined the relationship between genetic variation of this axis and esophageal adenocarcinoma (EAC) or its precursors. METHODS: In a population-based case-control study, we investigated the association of common polymorphisms of IGF-1, IGF-2, IGF-1 receptor, IGF binding protein -3, growth hormones (GH) 1 and GH2, and GH receptor with reflux esophagitis (RE), Barrett esophagus (BE), and EAC. Two hundred and thirty RE, 224 BE, 227 EAC cases, and 260 controls were studied. Gene polymorphisms were identified using publicly available online resources; 102 IGF axis tag and putatively functional single-nucleotide polymorphisms (SNPs) were analyzed using MassARRAY iPLEX and Taqman assays. Results were analyzed using Haploview.
RESULTS: Three polymorphisms were disease-associated. IGF1 SNP rs6214 was associated with BE (adjusted P = .039). Using GG genotype as reference, odds ratio for BE in AA (wild-type) was 0.43 (95% confidence interval [CI], 0.24-0.75). GH receptor SNP rs6898743 was associated with EAC (adjusted P = .0112). With GG as reference, odds ratio for EAC in CC (wildtype) genotype was 0.42 (95% CI, 0.23-0.76). IGF1 (CA)(17) 185-bp allele was associated with RE (adjusted P = .0116). Using IGF1(non17) as reference, odds ratio for RE in IGF1(17) carriers was 7.29 (95% CI, 1.57-46.7).
CONCLUSIONS: In this study, 3 polymorphisms of IGF genes were associated with EAC or its precursors. These polymorphisms may be markers of disease risk; independent validation of our findings is required. These results suggest the IGF pathway is involved in EAC development.

Cross-layer Energy-Efficiency Optimization of Packet Based Wireless MIMO Communication Systems

Energy in today's short-range wireless communication is mostly spent on the analog- and digital hardware rather than on radiated power. Hence,purely information-theoretic considerations fail to achieve the lowest energy per information bit and the optimization process must carefully consider the overall transceiver. In this paper, we propose to perform cross-layer optimization, based on an energy-aware rate adaptation scheme combined with a physical layer that is able to properly adjust its processing effort to the data rate and the channel conditions to minimize the energy consumption per information bit. This energy proportional behavior is enabled by extending the classical system modes with additional configuration parameters at the various layers. Fine grained models of the power consumption of the hardware are developed to provide awareness of the physical layer capabilities to the medium access control layer. The joint application of the proposed energy-aware rate adaptation and modifications to the physical layer of an IEEE802.11n system, improves energy-efficiency (averaged over many noise and channel realizations) in all considered scenarios by up to 44%.

Cross-layer Framework for Fine-grained Channel Access in Next Generation High-density WiFi Networks

Densely deployed WiFi networks will play a crucial role in providing the capacity for next generation mobile internet. However, due to increasing interference, overlapped channels in WiFi networks and throughput efficiency degradation, densely deployed WiFi networks is not a guarantee to obtain higher throughput. An emergent challenge is how to efficiently utilize scarce spectrum resources, by matching physical layer resources to traffic demand. In this aspect, access control allocation strategies play a pivotal role but remain too coarse-grained. As a solution, this research proposes a flexible framework for fine-grained channel width adaptation and multi-channel access in WiFi networks. This approach, named SFCA (Sub-carrier Fine-grained Channel Access), adopts DOFDM (Discontinuous Orthogonal Frequency Division Multiplexing) at the PHY layer. It allocates the frequency resource with a sub-carrier granularity, which facilitates the channel width adaptation for multi-channel access and thus brings more flexibility and higher frequency efficiency. The MAC layer uses a frequency-time domain backoff scheme, which combines the popular time-domain BEB scheme with a frequency-domain backoff to decrease access collision, resulting in higher access probability for the contending nodes. SFCA is compared with FICA (an established access scheme) showing significant outperformance. Finally we present results for next generation 802.11ac WiFi networks.

Multidimensional Intrusion Detection System for IEC 61850 based SCADA Networks

Emerging cybersecurity vulnerabilities in supervisory control and data acquisition (SCADA) systems are becoming urgent engineering issues for modern substations. This paper proposes a novel intrusion detection system (IDS) tailored for cybersecurity of IEC 61850 based substations. The proposed IDS integrates physical knowledge, protocol specifications and logical behaviours to provide a comprehensive and effective solution that is able to mitigate various cyberattacks. The proposed approach comprises access control detection, protocol whitelisting, model-based detection, and multi-parameter based detection. This SCADA-specific IDS is implemented and validated using a comprehensive and realistic cyber-physical test-bed and data from a real 500kV smart substation.

No association between hOGG1, XRCC1, and XPD polymorphisms and risk of reflux esophagitis, Barrett's Esophagus, or esophageal adenocarcinoma: Results from the factors influencing the Barrett's adenocarcinoma relationship case-control study

Reflux of gastric contents can lead to development of reflux esophagitis and Barrett's esophagus. Barrett's esophagus is a risk factor for esophageal adenocarcinoma. Damage to DNA may lead to carcinogenesis but is repaired through activation of pathways involving polymorphic enzymes, including human 8-oxoguanine glycosylase 1 (hOGG1), X-ray repair cross-complementing 1 (XRCC1), and xeroderma pigmentosum group D (XPD). Of the single nucleotide polymorphisms identified in these genes, hOGG1 Ser 326Cys, XRCC1 Arg 399Gln, and XPD Lys 751Gln are particularly common in Caucasians and have been associated with lower DNA repair capacity. Small studies have reported associations with XPD Lys 751Gln and esophageal adenocarcinoma. XRCC1 Arg 399Gln has been linked to Barrett's esophagus and reflux esophagitis. In a population-based case-control study, we examined associations of the hOGG1 Ser 326Cys, XRCC1 Arg 399Gln, and XPD Lys 751Gln polymorphisms with risk of esophageal adenocarcinoma, Barrett's esophagus, and reflux esophagitis. Genomic DNA was extracted from blood samples collected from cases of esophageal adenocarcinoma (n = 210), Barrett's esophagus (n = 212), reflux esophagitis (n = 230), and normal population controls frequency matched for age and sex (n = 248). Polymorphisms were genotyped using Taq-Man allelic discrimination assays. Odds ratios and 95% confidence intervals were obtained from logistic regression models adjusted for potential confounding factors. There were no statistically significant associations between these polymorphisms and risk of esophageal adenocarcinoma, Barrett's esophagus, or reflux esophagitis.

Improved fault diagnosis in multivariate systems using regression-based reconstruction

Subspace monitoring has recently been proposed as a condition monitoring tool that requires considerably fewer variables to be analysed compared to dynamic principal component analysis (PCA). This paper analyses subspace monitoring in identifying and isolating fault conditions, which reveals that the existing work suffers from inherent limitations if complex fault senarios arise. Based on the assumption that the fault signature is deterministic while the monitored variables are stochastic, the paper introduces a regression-based reconstruction technique to overcome these limitations. The utility of the proposed fault identification and isolation method is shown using a simulation example and the analysis of experimental data from an industrial reactive distillation unit.

Extruder Melt Temperature Control with Fuzzy Logic

In polymer extrusion, the delivery of a melt which is homogenous in composition and temperature is paramount for achieving high quality extruded products. However, advancements in process control are required to reduce temperature variations across the melt flow which can result in poor product quality. The majority of thermal monitoring methods provide only low accuracy point/bulk melt temperature measurements and cause poor controller performance. Furthermore, the most common conventional proportional-integral-derivative controllers seem to be incapable of performing well over the nonlinear operating region. This paper presents a model-based fuzzy control approach to reduce the die melt temperature variations across the melt flow while achieving desired average die melt temperature. Simulation results confirm the efficacy of the proposed controller.