Secondary prevention of cardiovascular disease in different primary healthcare systems with and without pay-for-performance

Objective: To compare baseline cardiovascular risk management between people recruited from two different healthcare systems, to a research trial of an intervention to optimize secondary prevention. Design: Cross-sectional study. Setting: General practices, randomly selected: 16 in Northern Ireland (NI) (UK NHS, ‘strong’ infrastructure); 32 in Republic of Ireland (RoI) (mixed healthcare economy, less infrastructure). Patients: 903 (mean age 67.5 years; 69.9% male); randomly selected, known coronary heart disease. Main outcome measures: Blood pressure, cholesterol, medications; validated questionnaires for diet (DINE), exercise (Godin), quality of life (SF12); healthcare usage. Results: More RoI than NI participants had systolic BP>140 mmHg (37% v 28%, p=0.01) and cholesterol >5mmol/l (24% v 17%, p=0.02): RoI mean systolic BP was higher (139 v 132 mm Hg). More RoI participants reported a high fibre intake (35% v 23%), higher levels of physical activity (62% v 44%), and better physical and mental health (SF12); they had more GP (5.6 v 4.4) and fewer nurse visits (1.6 v 2.1) in the previous year. Fewer in RoI (55% v 70%) were prescribed B blockers. Both groups’ ACE inhibitor (41%; 48%) prescribing was similar; high proportions were prescribed statins (84%; 85%) and aspirin (83%; 77%). Conclusions Blood pressure and cholesterol are better controlled among patients in a primary healthcare system with a ‘strong’ infrastructure supporting computerization and rewarding measured performance but this is not associated with healthier lifestyle or better quality of life. Further exploration of differences in professionals’ and patients’ engagement in secondary prevention in different healthcare systems is needed.

Optimization of an open-ended microwave oven for microelectronics packaging

A physically open, but electrically shielded, microwave open oven can be produced by virtue of the evanescent fields in a waveguide below cutoff. The below cutoff heating chamber is fed by a transverse magnetic resonance established in a dielectric-filled section of the waveguide exploiting continuity of normal electric flux. In order to optimize the fields and the performance of the oven, a thin layer of a dielectric material with higher permittivity is inserted at the interface. Analysis and synthesis of an optimized open oven predicts field enhancement in the heating chamber up to 9.4 dB. Results from experimental testing on two fabricated prototypes are in agreement with the simulated predictions, and demonstrate an up to tenfold improvement in the heating performance. The open-ended oven allows for simultaneous precision alignment, testing, and efficient curing of microelectronic devices, significantly increasing productivity gains.

A programmable architecture for layered multimedia streams in IPv6 networks

A new configurable architecture is presented that offers multiple levels of video playback by accommodating variable levels of network utilization and bandwidth. By utilizing scalable MPEG-4 encoding at the network edge and using specific video delivery protocols, media streaming components are merged to fully optimize video playback for IPv6 networks, thus improving QoS. This is achieved by introducing “programmable network functionality” (PNF) which splits layered video transmission and distributes it evenly over available bandwidth, reducing packet loss and delay caused by out-of-profile DiffServ classes. An FPGA design is given which gives improved performance, e.g. link utilization, end-to-end delay, and that during congestion, improves on-time delivery of video frames by up to 80% when compared to current “static” DiffServ.

Imperfect assessment and limited information preclude optimal strategies in male-male fights in the orb-weaving spider Metellina mengei

Agonistic behaviour between male orb-web spiders Metellina mengei competing for access to female webs was examined in field experiments to test the major predictions of game theory. Winners of fights were significantly larger than losers, particularly with respect to the length of the first pair of legs, which are sexually dimorphic in this species and used extensively in agonistic encounters. The size of the winning male had no influence on contest intensity or duration, and neither did relative size. However, fight intensity and duration were both positively correlated with the size of the losing male. Resident males won significantly more contests than intruders. Winning intruders were significantly larger than winning residents and it was these winning intruders that tended to produce the longer fights. Female weight and hence reproductive value had a marked influence on fight intensity and duration of fights won by the intruder but not those won by the resident. This indicates that only the resident obtains information about the female. These data are discussed with reference to the discrepancy with theory and a failure of some contestants to obtain information on resource value and relative contestant size necessary to optimize fight strategy.

Kinematic modeling of Exechon parallel kinematic machine

The studies on PKMs have attracted a great attention to robotics community. By deploying a parallel kinematic structure, a parallel kinematic machine (PKM) is expected to possess the advantages of heavier working load, higher speed, and higher precision. Hundreds of new PKMs have been proposed. However, due to the considerable gaps between the desired and actual performances, the majorities of the developed PKMs were the prototypes in research laboratories and only a few of them have been practically applied for various applications; among the successful PKMs, the Exechon machine tool is recently developed. The Exechon adopts unique over-constrained structure, and it has been improved based on the success of the Tricept parallel kinematic machine. Note that the quantifiable theoretical studies have yet been conducted to validate its superior performances, and its kinematic model is not publically available. In this paper, the kinematic characteristics of this new machine tool is investigated, the concise models of forward and inverse kinematics have been developed. These models can be used to evaluate the performances of an existing Exechon machine tool and to optimize new structures of an Exechon machine to accomplish some specific tasks.

Phase-Transfer Catalysis in Segmented Flow in a Microchannel: Fluidic Control of Selectivity and Productivity

Precise control over the interfacial area of aqueous and organic slugs in segmented flow in a microchannel reactor provides an attractive means to optimize the yield and productivity of a phase-transfer-catalyzed reaction. Herein, we report the selective alkylation of phenylacetonitrile to the monoalkylated product in a microchannel of 250-mu m internal diameter operated in a continuous and solvent-free manner in the slug-flow regime. The conversion of phenylacetonitrile increased from 40% to 99% as a result of a 97% larger slug surface-to-volume ratio when the volumetric aqueous-to-organic phase flow ratio was raised from 1.0 to 6.1 at the same residence time. The larger surface-to-volume ratio significantly promoted catalyst phase transfer but decreased selectivity because of the simultaneous increase of the rate of the consecutive reaction to the dialkylated product. There exists all Optimum flow ratio with a maximum productivity. Conversion and selectivity in the microchannel reactor were both found to be significantly larger than in a stirred reactor.

Macronutrient balance mediates trade-offs between immune function and life history traits

1. Diet and health are intimately linked and recent studies have found that caloric restriction can affect immune function. However, when given a choice between diets that differ in their macronutrient composition, pathogen-infected individuals can select a diet that improves their survival, suggesting that the nutritional composition of the diet, as well as its calorie content, can play a role in defence against disease. Moreover, as individuals change their diet when infected, it suggests that a diet that is optimal for growth is not optimal for immunity, leading to trade-offs.
2. Currently, our knowledge of the effects of diet on immunity is limited because previous experiments have manipulated either single nutrients or the calorie content of the diet without considering their interactive effects. By simultaneously manipulating both the diet composition (quality) and its caloric density (quantity), in both naive and immune-challenged insects, we asked how do diet quality and quantity influence an individual's ability to mount an immune response? And to what extent are allocation trade-offs driven by quantity- versus quality-based constraints?
3. We restricted individuals to 20 diets varying in their protein and carbohydrate content and used 3D response surfaces to visualize dietary effects on larval growth and immune traits. Our results show that both constitutive and induced immune responses are not limited by the total quantity of nutrients consumed, but rather different traits respond differently to variation in the ratios of macronutrients (diet quality), and peak in different regions of macronutrient space. The preferred dietary composition therefore represents a compromise between the nutritional requirements of growth and immune responses. We also show that a non-pathogenic immune challenge does not affect diet choice, rather immune-challenged insects modify their allocation of nutrients to improve their immune response.
4. Our results indicate that immune traits are affected by the macronutrient content of the diet and that no diet can simultaneously optimize all components of the immune system. To date the emphasis has been on the effects of micronutrients in improving immunity, our findings indicate that this must be widened to include the neglected impact of macronutrients on defence against disease.

Evaluation of Random Delay Insertion against DPA on FPGAs

Side-channel attacks (SCA) threaten electronic cryptographic devices and can be carried out by monitoring the physical characteristics of security circuits. Differential Power Analysis (DPA) is one the most widely studied side-channel attacks. Numerous countermeasure techniques, such as Random Delay Insertion (RDI), have been proposed to reduce the risk of DPA attacks against cryptographic devices. The RDI technique was first proposed for microprocessors but it was shown to be unsuccessful when implemented on smartcards as it was vulnerable to a variant of the DPA attack known as the Sliding-Window DPA attack.Previous research by the authors investigated the use of the RDI countermeasure for Field Programmable Gate Array (FPGA) based cryptographic devices. A split-RDI technique wasproposed to improve the security of the RDI countermeasure. A set of critical parameters wasalso proposed that could be utilized in the design stage to optimize a security algorithm designwith RDI in terms of area, speed and power. The authors also showed that RDI is an efficientcountermeasure technique on FPGA in comparison to other countermeasures.In this article, a new RDI logic design is proposed that can be used to cost-efficiently implementRDI on FPGA devices. Sliding-Window DPA and realignment attacks, which were shown to beeffective against RDI implemented on smartcard devices, are performed on the improved RDIFPGA implementation. We demonstrate that these attacks are unsuccessful and we also proposea realignment technique that can be used to demonstrate the weakness of RDI implementations.

Cholinesterase Inhibitor and Memantine Use in Newly Admitted Nursing Home Residents with Dementia

OBJECTIVES: To quantify the use of cholinesterase inhibitors (ChEIs) and memantine in nursing home (NH) residents with dementia upon NH admission and 3 months later and to examine factors associated with reduction in therapy.

DESIGN: Retrospective cohort study.

SETTING: Nationwide sample of U.S. NHs.

PARTICIPANTS: Three thousand ?ve hundred six NH residents with dementia newly admitted in 2006.

MEASUREMENTS: Data from pharmacy dispensing records were used to determine ChEI and memantine medication use upon NH admission and at 3-month follow-up. The Minimum Data Set was used to determine resident- and facility-level characteristics. Severity of dementia was de?ned using the Cognitive Performance Scale (CPS).

RESULTS: Overall, 40.1% (n51,407) of newly admitted NH residents with dementia received ChEIs and memantine on NH admission. Use of ChEIs and memantine on admission was significantly greater in residents with mild to moderately severe dementia (41.2%) than in those with advanced dementia (33.3%, P5.001). After 3 months, ChEI and memantine use decreased by about half in both groups (48.6% with mild to moderately severe dementia vs 57.0% with advanced dementia, Po.05). NH residents with advanced dementia were significantly more likely reduce their use of ChEIs and memantine than those with mild to moderately severe dementia (odds ratio 51.44, 95% con?dence interval 51.03–2.01, P5.04).

CONCLUSION: Many NH residents with advanced dementia receive ChEIs and memantine upon NH admission, and approximately half of these decrease their medication use over the ensuing months. Further study is required to optimize use of ChEIs and memantine in NH populations and to determine the effects of withdrawing therapy on resident outcomes.

Optimal control of atom transport for quantum gates in optical lattices

By means of optimal control techniques we model and optimize the manipulation of the external quantum state (center-of-mass motion) of atoms trapped in adjustable optical potentials. We consider in detail the cases of both noninteracting and interacting atoms moving between neighboring sites in a lattice of a double-well optical potentials. Such a lattice can perform interaction-mediated entanglement of atom pairs and can realize two-qubit quantum gates. The optimized control sequences for the optical potential allow transport faster and with significantly larger fidelity than is possible with processes based on adiabatic transport.

Fast automatic two-stage nonlinear model identification based on the extreme learning machine

It is convenient and effective to solve nonlinear problems with a model that has a linear-in-the-parameters (LITP) structure. However, the nonlinear parameters (e.g. the width of Gaussian function) of each model term needs to be pre-determined either from expert experience or through exhaustive search. An alternative approach is to optimize them by a gradient-based technique (e.g. Newton’s method). Unfortunately, all of these methods still need a lot of computations. Recently, the extreme learning machine (ELM) has shown its advantages in terms of fast learning from data, but the sparsity of the constructed model cannot be guaranteed. This paper proposes a novel algorithm for automatic construction of a nonlinear system model based on the extreme learning machine. This is achieved by effectively integrating the ELM and leave-one-out (LOO) cross validation with our two-stage stepwise construction procedure [1]. The main objective is to improve the compactness and generalization capability of the model constructed by the ELM method. Numerical analysis shows that the proposed algorithm only involves about half of the computation of orthogonal least squares (OLS) based method. Simulation examples are included to confirm the efficacy and superiority of the proposed technique.

Adaptive Code Allocation for Interference Management on the Downlink of DS-CDMA Systems

A new technique based on adaptive code-to-user allocation for interference management on the downlink of BPSK based TDD DS-CDMA systems is presented. The principle of the proposed technique is to exploit the dependency of multiple access interference on the instantaneous symbol values of the active users. The objective is to adaptively allocate the available spreading sequences to users on a symbol-by-symbol basis to optimize the decision variables at the downlink receivers. The presented simulations show an overall system BER performance improvement of more than an order of a magnitude with the proposed technique while the adaptation overhead is kept less than 10% of the available bandwidth.

One Dimensional Modeling of a Turbogenerating Spark Ignition Engine Operating on Biogas

Turbocompounding is generally regarded as the process of recovering a proportion of the exhaust gas energy from a reciprocating engine and applying it to the output power of the crankshaft. In conventional turbocompounding, the power turbine has been mechanically connected to the crankshaft but now a new method has emerged. Recent advances in high speed electrical machines have enabled the power turbine to be coupled to an electric generator. Decoupling the power turbine from the crankshaft and coupling it to a generator allows the power electronics to control the turbine speed independently in order to optimize the turbine efficiency for different engine operating conditions.

Working Memory and Postural Control: Adult Age Differences in Potential for Improvement, Task Priority, and Dual Tasking

We investigate dynamic posture control and working memory (NBack) retest practice in young and older adults, focusing on older adults' potential for improvement in the component tasks but more importantly in dual-task performance. Participants performed the 2 tasks in 11 sessions under single- and dual-task conditions. Posture improvement was observed with retest practice for both groups. Increase in cognitive load after initial practice led to greater dual-task costs in both tasks in older adults and higher costs in memory in young adults. With continued practice, costs were reduced by both groups; however, the 2 groups focused improvement on different tasks: Older adults focused on posture but young adults on cognition. These results emphasize older adults' potential for improvement in dual-task performance and their flexibility to utilize the practice gains in posture to optimize cognitive performance.

Prediction-Based Power-Performance Adaptation of Multithreaded Scientific Codes

Computing has recently reached an inflection point with the introduction of multicore processors. On-chip thread-level parallelism is doubling approximately every other year. Concurrency lends itself naturally to allowing a program to trade performance for power savings by regulating the number of active cores; however, in several domains, users are unwilling to sacrifice performance to save power. We present a prediction model for identifying energy-efficient operating points of concurrency in well-tuned multithreaded scientific applications and a runtime system that uses live program analysis to optimize applications dynamically. We describe a dynamic phase-aware performance prediction model that combines multivariate regression techniques with runtime analysis of data collected from hardware event counters to locate optimal operating points of concurrency. Using our model, we develop a prediction-driven phase-aware runtime optimization scheme that throttles concurrency so that power consumption can be reduced and performance can be set at the knee of the scalability curve of each program phase. The use of prediction reduces the overhead of searching the optimization space while achieving near-optimal performance and power savings. A thorough evaluation of our approach shows a reduction in power consumption of 10.8 percent, simultaneous with an improvement in performance of 17.9 percent, resulting in energy savings of 26.7 percent.