Asthma control and exacerbations: two different sides of the same coin.

Purpose of review: Optimal asthma management includes both the control of asthma symptoms and reducing the risk of future asthma exacerbations. Traditionally, treatment has been adjusted largely on the basis of symptoms and lung function and for many patients, this approach delivers both excellent symptom control and reduced risk. However, the relationship between these two key components of the disease may vary between different asthmatic phenotypes and disease severities and there is increasing recognition of the need for more individualized treatment approaches.

Recent findings: A number of factors which predict exacerbation risk have been identified including demographic and behavioural features and specific inflammatory biomarkers. Type-2 cytokine-driven eosinophilic airways inflammation predisposes to frequent exacerbations and predicts response to corticosteroids, and the usefulness of sputum eosinophilia as both a marker of exacerbation risk and biomarker for adjustment of corticosteroid treatment has been established for some time. However, attempts to develop surrogate markers, which would be more straightforward to deliver in the clinic, have been challenging.

Summary: Some patients with asthma have persistent symptoms in the absence of type-2 cytokine driven-eosinophilic airways inflammation due to noncorticosteroid responsive mechanisms (T2-low disease). Composite biomarker strategies using easily measured surrogate indicators of type-2 inflammation (such as fractional exhaled nitric oxide, blood eosinophil count and serum periostin levels) may predict exacerbation risk better but it is unclear if they can be used to adjust corticosteroid treatment. Biomarkers will be used to target novel biologic treatments but additionally may be used to optimize corticosteroid treatment dose and act as prognostics for exacerbation risk and potentially other important longer term asthma outcomes.

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.

Implementation and Evaluation of Measurement-Based Admission Control Schemes Within a Converged Networks QoS Management Framework

Policy-based network management (PBNM) paradigms provide an effective tool for end-to-end resource
management in converged next generation networks by enabling unified, adaptive and scalable solutions
that integrate and co-ordinate diverse resource management mechanisms associated with heterogeneous
access technologies. In our project, a PBNM framework for end-to-end QoS management in converged
networks is being developed. The framework consists of distributed functional entities managed within a
policy-based infrastructure to provide QoS and resource management in converged networks. Within any
QoS control framework, an effective admission control scheme is essential for maintaining the QoS of
flows present in the network. Measurement based admission control (MBAC) and parameter basedadmission control (PBAC) are two commonly used approaches. This paper presents the implementationand analysis of various measurement-based admission control schemes developed within a Java-based
prototype of our policy-based framework. The evaluation is made with real traffic flows on a Linux-based experimental testbed where the current prototype is deployed. Our results show that unlike with classic MBAC or PBAC only schemes, a hybrid approach that combines both methods can simultaneously result in improved admission control and network utilization efficiency

Feasibility Assessment of Plug and Play Model Predictive Control for use in DC Grids

Distributed control techniques can allow Transmission System Operators (TSOs) to coordinate their responses via TSO-TSO communication, providing a level of control that lies between that of centralised control and communication free decentralised control of interconnected power systems. Recently the Plug and Play Model Predictive Control (PnPMPC) toolbox has been developed in order to allow practitioners to design distributed controllers based on tube-MPC techniques. In this paper, some initial results using the PnPMPC toolbox for the design of distributed controllers to enhance AGC in AC areas connected to Multi-Terminal HVDC (MTDC) grids, are illustrated, in order to evaluate the feasibility of applying PnPMPC for this purpose.

The role of BRCA1 in transcriptional regulation and cell cycle control

The exact functions of BRCA1 have not been fully described but it now seems apparent that it has roles in DNA damage repair, transcriptional regulation, cell cycle control and most recently in ubiquitylation. These functions of BRCA1 are most likely interdependent but this review will focus on the role of BRCA1 in relation to transcriptional regulation and in particular how this impacts upon cell cycle control. We will (i) describe the structure of BRCA1 and how it may contribute to its transcription function; (ii) describe the interaction of BRCA1 with the core transcriptional machinery (RNA polII); (iii) describe how BRCA1 may regulate transcription at an epigenetic level through chromatin modification; (iv) discuss the role of BRCA1 in modulating transcription through its association with sequence-specific transcription factors. Finally, we will discuss the possible effects of BRCA1 transcriptional regulation on downstream targets with known roles in cell cycle control.

Power-law behaviour, heterogeneity, and trend chasing

Long-range dependence in volatility is one of the most prominent examples in financial market research involving universal power laws. Its characterization has recently spurred attempts to provide some explanations of the underlying mechanism. This paper contributes to this recent line of research by analyzing a simple market fraction asset pricing model with two types of traders---fundamentalists who trade on the price deviation from estimated fundamental value and trend followers whose conditional mean and variance of the trend are updated through a geometric learning process. Our analysis shows that agent heterogeneity, risk-adjusted trend chasing through the geometric learning process, and the interplay of noisy fundamental and demand processes and the underlying deterministic dynamics can be the source of power-law distributed fluctuations. In particular, the noisy demand plays an important role in the generation of insignificant autocorrelations (ACs) on returns, while the significant decaying AC patterns of the absolute returns and squared returns are more influenced by the noisy fundamental process. A statistical analysis based on Monte Carlo simulations is conducted to characterize the decay rate. Realistic estimates of the power-law decay indices and the (FI)GARCH parameters are presented.

Special issue on design and programming of signal processors for multimedia communication:Special issue on design and programming of signal processors for multimedia communication

The technical challenges in the design and programming of signal processors for multimedia communication are discussed. The development of terminal equipment to meet such demand presents a significant technical challenge, considering that it is highly desirable that the equipment be cost effective, power efficient, versatile, and extensible for future upgrades. The main challenges in the design and programming of signal processors for multimedia communication are, general-purpose signal processor design, application-specific signal processor design, operating systems and programming support and application programming. The size of FFT is programmable so that it can be used for various OFDM-based communication systems, such as digital audio broadcasting (DAB), digital video broadcasting-terrestrial (DVB-T) and digital video broadcasting-handheld (DVB-H). The clustered architecture design and distributed ping-pong register files in the PAC DSP raise new challenges of code generation.

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.

Coordinated Control of DFIG and FSIG-based Wind Farms under Unbalanced Grid Conditions

This paper investigates the control and operation of doubly-fed induction generator (DFIG) and fixed-speed induction generator (FSIG) based wind farms under unbalanced grid conditions. A DFIG system model suitable for analyzing unbalanced operation is developed, and used to assess the impact of an unbalanced supply on DFIG and FSIG operation. Unbalanced voltage at DFIG and FSIG terminals can cause unequal heating on the stator windings, extra mechanical stresses and output power fluctuations. These problems are particularly serious for the FSIG-based wind farm without a power electronic interface to the grid. To improve the stability of a wind energy system containing both DFIG and FSIG based wind farms during network unbalance, a control strategy of unbalanced voltage compensation by the DFIG systems is proposed. The DFIG system compensation ability and the impact of transmission network impedance are illustrated. The simulation results implemented in Matlab/Simulink show that the proposed DFIG control system improves not only its own performance, but also the stability of the FSIG system with the same grid connection point during network unbalance.

Methadone as Social Control: Institutionalized Stigma and the Prospect of Recovery

Methadone maintenance treatment (MMT) is an intervention used to treat opioid (heroin) dependence. Several investigators have found that MMT is effective in reducing heroin use and other behaviors; however, a disproportionate number of MMT clients leave treatment prematurely. Moreover, MMT outcome variables are often limited in terms of their measurement. Utilizing an integrated theoretical framework of social control and stigma, we focused on the experiences of methadone maintenance from the perspective of clients. We pooled interview data from four qualitative studies in two jurisdictions and found linkages between social control and institutional stigma that serve to reinforce "addict" identities, expose undeserving customers to the public gaze, and encourage clients to be passive recipients of treatment. We discuss the implications for recovery and suggest recommendations for change.