Topical Review: The current understanding on the diamond machining of silicon carbide

The Glenn Research Centre of NASA, USA (www.grc.nasa.gov/WWW/SiC/, silicon carbide electronics) is in pursuit of realizing bulk manufacturing of silicon carbide (SiC), specifically by mechanical means. Single point diamond turning (SPDT) technology which employs diamond (the hardest naturally-occurring material realized to date) as a cutting tool to cut a workpiece is a highly productive manufacturing process. However, machining SiC using SPDT is a complex process and, while several experimental and analytical studies presented to date aid in the understanding of several critical processes of machining SiC, the current knowledge on the ductile behaviour of SiC is still sparse. This is due to a number of simultaneously occurring physical phenomena that may take place on multiple length and time scales. For example, nucleation of dislocation can take place at small inclusions that are of a few atoms in size and once nucleated, the interaction of these nucleations can manifest stresses on the micrometre length scales. The understanding of how stresses manifest during fracture in the brittle range, or dislocations/phase transformations in the ductile range, is crucial in understanding the brittle–ductile transition in SiC. Furthermore, there is a need to incorporate an appropriate simulation-based approach in the manufacturing research on SiC, owing primarily to the number of uncertainties in the experimental research that includes wear of the cutting tool, poor controllability of the nano-regime machining scale (effective thickness of cut), and coolant effects (interfacial phenomena between the tool, workpiece/chip and coolant), etc. In this review, these two problems are combined together to posit an improved understanding on the current theoretical knowledge on the SPDT of SiC obtained from molecular dynamics simulation.

Big Society as Big Government: Cameron's Governmentality Agenda

Cameron’s flagship policy of the ‘Big Society’ rests on a society/government dichotomy, diagnosing a ‘broken society’ caused by ‘big government’ having assumed the role communities once played. The remedy is greater social responsibility and the ‘Big Society’. This article argues that the dichotomy is
deceptive. We aim to show that the Big Society is big government, as it employs techniques for managing the conduct of individuals and communities such that the mentality of government, far from being removed or reduced, is bettered and made more efficient. To illustrate this, we explore two major initiatives: the National Citizen Service and the Community Resilience programme. These
projects demonstrate how practices of informing and guiding the conduct of individuals both produce agents and normalise certain values, resulting in the population being better known and controlled. Thus, far from lessening government and empowering people, the Big Society extends governmentality
throughout the social body.

Autoecological Approaches to Resolve Subjective Taxonomic Divisions within Arcellacea

Arcellacea (testate lobose amoebae) are important lacustrine environmental indicators that have been used in paleoclimatic reconstructions, assessing the effectiveness of mine tailings pond reclamation projects and for studying the effects of land use change in rural, industrial and urban settings. Recognition of ecophenotypically significant infra-specific ‘strains’ within arcellacean assemblages has the potential to enhance the utility of the group in characterizing contemporary and paleoenvironments. We present a novel approach which employs statistical tools to investigate the environmental and taxonomic significance of proposed strains. We test this approach on two identified strains: Difflugia protaeiformis Lamarck strain ‘acuminata’ (DPA), characterized by fine grained agglutination, and Difflugia protaeiformis Lamarck strain ‘claviformis’ (DPC), characterized by coarse grained agglutination. Redundancy analysis indicated that both organisms are associated with similar environmental variables. No relationship was observed between substrate particle size and abundance of DPC, indicating that DPC has a size preference for xenosomes during test construction. Thus DPC should not be designated as a distinct strain but rather form a species complex with DPA. This study elucidates the need to justify the designation of strains based on their autecology in addition to morphological stability.

Selective High Impedance Surface Active Region Loading of Archimedean Spiral Antenna

We show that a significant increase in the gain and front-to-back ratio is obtained when different high impedance surface (HIS) sections are placed below the active regions of an Archimedean spiral antenna. The principle of operation is demonstrated at 3, 6, and 9 GHz for an antenna design that employs a ground plane composed of two dissimilar HISs. The unit cells of the HISs are collocated and resonant at the same frequency as the 3- and 6-GHz active regions of the wideband spiral. It is shown that the former HIS must also be designed to resonate at 9 GHz to avoid the generation of a boresight null that occurs because the structure is physically large enough to support higher-order modes. The improvement that is obtained at each of the three frequencies investigated is shown by comparing the predicted and measured radiation patterns for the free space and HIS-backed antenna.

Optimization through quantum annealing: theory and some applications

Quantum annealing is a promising tool for solving optimization problems, similar in some ways to the traditional ( classical) simulated annealing of Kirkpatrick et al. Simulated annealing takes advantage of thermal fluctuations in order to explore the optimization landscape of the problem at hand, whereas quantum annealing employs quantum fluctuations. Intriguingly, quantum annealing has been proved to be more effective than its classical counterpart in many applications. We illustrate the theory and the practical implementation of both classical and quantum annealing - highlighting the crucial differences between these two methods - by means of results recently obtained in experiments, in simple toy-models, and more challenging combinatorial optimization problems ( namely, Random Ising model and Travelling Salesman Problem). The techniques used to implement quantum and classical annealing are either deterministic evolutions, for the simplest models, or Monte Carlo approaches, for harder optimization tasks. We discuss the pro and cons of these approaches and their possible connections to the landscape of the problem addressed.

Optimised extraction of heterocyclic aromatic amines from blood using hollow fibre membrane liquid-phase microextraction and triple quadrupole mass spectrometry

Heterocyclic aromatic amines (HCA) are carcinogenic mutagens formed during cooking of proteinaceous foods, particularly meat. To assist in the ongoing search for biomarkers of HCA exposure in blood, a method is described for the extraction from human plasma of the most abundant HCAs: 2-Amino-1-methyl-6-phenylimidazo(4,5-b)pyridine (PhIP), 2-amino-3,8-dimethylimidazo[4,5-f]quinoxaline (MeIQx) and 2-amino-3,4,8-trimethylimidazo[4,5-f]quinoxaline (4,8-DiMeIQx) (and its isomer 7,8-DiMeIQx), using Hollow Fibre Membrane Liquid-Phase Microextraction. This technique employs 2.5 cm lengths of porous polypropylene fibres impregnated with organic solvent to facilitate simultaneous extraction from an alkaline aqueous sample into a low volume acidic acceptor phase. This low cost protocol is extensively optimised for fibre length, extraction time, sample pH and volume. Detection is by UPLC-MS/MS using positive mode electrospray ionisation with a 3.4 min runtime, with optimum peak shape, sensitivity and baseline separation being achieved at pH 9.5. To our knowledge this is the first description of HCA chromatography under alkaline conditions. Application of fixed ion ratio tolerances for confirmation of analyte identity is discussed. Assay precision is between 4.5 and 8.8% while lower limits of detection between 2 and 5 pg/mL are below the concentrations postulated for acid-labile HCA-protein adducts in blood.

Epstein-Barr Virus Large Tegument Protein BPLF1 Contributes to Innate Immune Evasion through Interference with Toll-Like Receptor Signaling

Viral infection triggers an early host response through activation of pattern recognition receptors, including Toll-like receptors (TLR). TLR signaling cascades induce production of type I interferons and proinflammatory cytokines involved in establishing an anti-viral state as well as in orchestrating ensuing adaptive immunity. To allow infection, replication, and persistence, (herpes)viruses employ ingenious strategies to evade host immunity. The human gamma-herpesvirus Epstein-Barr virus (EBV) is a large, enveloped DNA virus persistently carried by more than 90% of adults worldwide. It is the causative agent of infectious mononucleosis and is associated with several malignant tumors. EBV activates TLRs, including TLR2, TLR3, and TLR9. Interestingly, both the expression of and signaling by TLRs is attenuated during productive EBV infection. Ubiquitination plays an important role in regulating TLR signaling and is controlled by ubiquitin ligases and deubiquitinases (DUBs). The EBV genome encodes three proteins reported to exert in vitro deubiquitinase activity. Using active site-directed probes, we show that one of these putative DUBs, the conserved herpesvirus large tegument protein BPLF1, acts as a functional DUB in EBV-producing B cells. The BPLF1 enzyme is expressed during the late phase of lytic EBV infection and is incorporated into viral particles. The N-terminal part of the large BPLF1 protein contains the catalytic site for DUB activity and suppresses TLR-mediated activation of NF-κB at, or downstream of, the TRAF6 signaling intermediate. A catalytically inactive mutant of this EBV protein did not reduce NF-κB activation, indicating that DUB activity is essential for attenuating TLR signal transduction. Our combined results show that EBV employs deubiquitination of signaling intermediates in the TLR cascade as a mechanism to counteract innate anti-viral immunity of infected hosts.

BER evaluation of a low complexity transmit diversity scheme and its application to MIMO-BICM

In this paper, we first provide a theoretical validation for a low-complexity transmit diversity algorithm which employs only one RF chain and a low-complexity switch for transmission. Our theoretical analysis is compared to the simulation results and proved to be accurate. We then apply the transmit diversity scheme to multiple-input and multiple-output (MIMO) systems with bit-interleaved coded modulation (BICM). © 2012 IEEE.

An Adaptive Machine Learning Decision System for Flexible Predictive Maintenance

Process monitoring and Predictive Maintenance (PdM) are gaining increasing attention in most manufacturing environments as a means of reducing maintenance related costs and downtime. This is especially true in industries that are data intensive such as semiconductor manufacturing. In this paper an adaptive PdM based flexible maintenance scheduling decision support system, which pays particular attention to associated opportunity and risk costs, is presented. The proposed system, which employs Machine Learning and regularized regression methods, exploits new information as it becomes available from newly processed components to refine remaining useful life estimates and associated costs and risks. The system has been validated on a real industrial dataset related to an Ion Beam Etching process for semiconductor manufacturing.

Rapid quantification of microRNAs in plasma using a fast real time PCR system

The ability to rapidly detect circulating small RNAs, in particular microRNAs (miRNAs), would further increase their already established potential as biomarkers in a range of conditions. One rate-limiting factor is the time taken to perform quantitative real time PCR amplification. We therefore evaluated the ability of a novel thermal cycler to perform this step in less than 10 minutes. Quantitative PCR was performed on an xxpress® thermal cycler (BJS Biotechnologies, Perivale, UK), which employs a resistive heating system and forced air cooling to achieve thermal ramp rates of 10 °C/s, and a conventional peltier-controlled LightCycler 480 system (Roche, Basel, Switzerland) ramping at 4.8 °C/s. The threshold cycle (Ct) for detection of 18S rDNA from a standard genomic DNA sample was significantly more variable across the block (F-test, p=2.4x10-25) for the xxpress (20.01±0.47SD) than the LightCycler (19.87±0.04SD). RNA was extracted from human plasma, reverse transcribed and a panel of miRNAs amplified and detected using SYBR green (Kapa Biosystems, Wilmington, Ma, USA). The sensitivity of both systems was broadly comparable and both detected a panel of miRNAs reliably and indicated similar relative abundances. The xxpress thermal cycler facilitates rapid qPCR detection of small RNAs and brings point-of care diagnostics based upon circulating miRNAs a step closer to reality.

Evidence reasoning for event inference in smart transport video surveillance

In this paper we present a new event recognition framework, based on the Dempster-Shafer theory of evidence, which combines the evidence from multiple atomic events detected by low-level computer vision analytics. The proposed framework employs evidential network modelling of composite events. This approach can effectively handle the uncertainty of the detected events, whilst inferring high-level events that have semantic meaning with high degrees of belief. Our scheme has been comprehensively evaluated against various scenarios that simulate passenger behaviour on public transport platforms such as buses and trains. The average accuracy rate of our method is 81% in comparison to 76% by a standard rule-based method.

Belief Updating and Learning in Semi-Qualitative Probabilistic Networks

This paper explores semi-qualitative probabilistic networks (SQPNs) that combine numeric and qualitative information. We first show that exact inferences with SQPNs are NPPP-Complete. We then show that existing qualitative relations in SQPNs (plus probabilistic logic and imprecise assessments) can be dealt effectively through multilinear programming. We then discuss learning: we consider a maximum likelihood method that generates point estimates given a SQPN and empirical data, and we describe a Bayesian-minded method that employs the Imprecise Dirichlet Model to generate set-valued estimates.

An official American thoracic society research statement: Comparative effectiveness research in pulmonary, critical care, and sleep medicine

Background: Comparative effectiveness research (CER) is intended to inform decision making in clinical practice, and is central to patientcentered outcomes research (PCOR). Purpose: To summarize key aspects of CER definitions and provide examples highlighting the complementary nature of efficacy and CER studies in pulmonary, critical care, and sleep medicine. Methods: An ad hoc working group of the American Thoracic Society with experience in clinical trials, health services research, quality improvement, and behavioral sciences in pulmonary, critical care, and sleepmedicinewas convened. The group used an iterative consensus process, including a reviewbyAmerican Thoracic Society committees and assemblies. Results: The traditional efficacy paradigm relies on clinical trials with high internal validity to evaluate interventions in narrowly defined populations and in research settings. Efficacy studies address the question, "Can it work in optimal conditions?" The CER paradigm employs a wide range of study designs to understand the effects of interventions in clinical settings. CER studies address the question, "Does it work in practice?" The results of efficacy and CER studies may or may not agree. CER incorporates many attributes of outcomes research and health services research, while placing greater emphasis on meeting the expressed needs of nonresearcher stakeholders (e.g., patients, clinicians, and others). Conclusions: CER complements traditional efficacy research by placing greater emphasis on the effects of interventions in practice, and developing evidence to address the needs of the many stakeholders involved in health care decisions. Stakeholder engagement is an important component of CER. Copyright © 2013 by the American Thoracic Society.

Hybrid probabilistic wind power forecasting using temporally local Gaussian process

The demand for sustainable development has resulted in a rapid growth in wind power worldwide. Despite various approaches have been proposed to improve the accuracy and to overcome the uncertainties associated with traditional methods, the stochastic and variable nature of wind still remains the most challenging issue in accurately forecasting wind power. This paper presents a hybrid deterministic-probabilistic method where a temporally local ‘moving window’ technique is used in Gaussian Process to examine estimated forecasting errors. This temporally local Gaussian Process employs less measurement data while faster and better predicts wind power at two wind farms, one in the USA and the other in Ireland. Statistical analysis on the results shows that the method can substantially reduce the forecasting error while more likely generate Gaussian-distributed residuals, particularly for short-term forecast horizons due to its capability to handle the time-varying characteristics of wind power.

Novel decentralised formation control for unmanned vehicles

This paper proposes a new methodology for solving the unmanned multi-vehicle formation control problem. It employs a unique “extension-decomposition-aggregation” scheme to transform the overall complex formation control problem to a group of sub-problems which work via boundary interactions. The H∞ robust control strategy is applied to design the decentralised formation controllers to reject the interactions and work jointly to maintain the stability of the overall formation. Simulation studies have been performed to verify its performance and effectiveness.