Effects of a nurse-led, clinic and home-based intervention on recurrent hospital use in chronic heart failure

Background: Few studies have examined the potential benefits of specialist nurse-led programs of care involving home and clinic-based follow-up to optimise the post-discharge management of chronic heart failure (CHF). Objective: To determine the effectiveness of a hybrid program of clinic plus home-based intervention (C+HBI) in reducing recurrent hospitalisation in CHF patients. Methods: CHF patients with evidence of left ventricular systolic dysfunction admitted to two hospitals in Northern England were assigned to a C+HBI lasting 6 months post-discharge (n=58) or to usual, post-discharge care (UC: n=48) via a cluster randomization protocol. The co-primary endpoints were death or unplanned readmission (event-free survival) and rate of recurrent, all-cause readmission within 6 months of hospital discharge. Results: During study follow-up, more UC patients had an unplanned readmission for any cause (44% vs. 22%: P=0.0191 OR 1.95 95% CI 1.10-3.48) whilst 7 (15%) versus 5 (9%) UC and C+HBI patients, respectively, died (P=NS). Overall, 15 (26%) C+HBI versus 21 (44%) UC patients experienced a primary endpoint. C+HBI was associated with a non-significant, 45% reduction in the risk of death or readmission when adjusting for potential confounders (RR 0.55, 95% CI 0.28-1.08: P=0.08). Overall, C+HBI patients accumulated significantly fewer unplanned readmissions (15 vs. 45: P

Dynamic rupture in a 3-D particle-based simulation of a rough planar fault

An appreciation of the physical mechanisms which cause observed seismicity complexity is fundamental to the understanding of the temporal behaviour of faults and single slip events. Numerical simulation of fault slip can provide insights into fault processes by allowing exploration of parameter spaces which influence microscopic and macroscopic physics of processes which may lead towards an answer to those questions. Particle-based models such as the Lattice Solid Model have been used previously for the simulation of stick-slip dynamics of faults, although mainly in two dimensions. Recent increases in the power of computers and the ability to use the power of parallel computer systems have made it possible to extend particle-based fault simulations to three dimensions. In this paper a particle-based numerical model of a rough planar fault embedded between two elastic blocks in three dimensions is presented. A very simple friction law without any rate dependency and no spatial heterogeneity in the intrinsic coefficient of friction is used in the model. To simulate earthquake dynamics the model is sheared in a direction parallel to the fault plane with a constant velocity at the driving edges. Spontaneous slip occurs on the fault when the shear stress is large enough to overcome the frictional forces on the fault. Slip events with a wide range of event sizes are observed. Investigation of the temporal evolution and spatial distribution of slip during each event shows a high degree of variability between the events. In some of the larger events highly complex slip patterns are observed.

Improved algorithms for rare event simulation with heavy tails

The estimation of P(S-n > u) by simulation, where S, is the sum of independent. identically distributed random varibles Y-1,..., Y-n, is of importance in many applications. We propose two simulation estimators based upon the identity P(S-n > u) = nP(S, > u, M-n = Y-n), where M-n = max(Y-1,..., Y-n). One estimator uses importance sampling (for Y-n only), and the other uses conditional Monte Carlo conditioning upon Y1,..., Yn-1. Properties of the relative error of the estimators are derived and a numerical study given in terms of the M/G/1 queue in which n is replaced by an independent geometric random variable N. The conclusion is that the new estimators compare extremely favorably with previous ones. In particular, the conditional Monte Carlo estimator is the first heavy-tailed example of an estimator with bounded relative error. Further improvements are obtained in the random-N case, by incorporating control variates and stratification techniques into the new estimation procedures.

Prolonged effects of a home-based intervention in patients with chronic illness

Background: Data on the long-term benefits of nonspecific disease management programs are limited. We performed a long-term follow-up of a previously published randomized trial. Methods: We compared all-cause mortality and recurrent hospitalization during median follow-up of 7.5 years in a heterogeneous cohort of patients with chronic illness initially exposed to a multidisciplinary, homebased intervention (HBI) (n = 260) or to usual postdischarge care (n = 268). Results: During follow-up, HBI had no impact on all-cause mortality (relative risk, 1.04; 95% confidence interval, 0.80-1.35) or event-free survival from death or unplanned hospitalization (relative risk, 1.03; 95% confidence interval, 0.86-1.24). Initial analysis suggested that HBI had only a marginal impact in reducing unplanned hospitalization, with 677 readmissions vs 824 for the usual care group (mean +/- SD rate, 0.72 +/- 0.96 vs 0.84 +/- 1.20 readmissions/patient per year; P = .08). When accounting for increased hospital activity in HBI patients with chronic obstructive pulmonary disease during follow-up for 2 years, post hoc analyses showed that HBI reduced readmissions by 14% within 2 years in patients without this condition (mean +/- SD rate, 0.54 +/- 0.72 vs 0.63 +/- 0.88 readmission/patient per year; P =. 04) and by 21% in all surviving patients within 3 to 8 years (mean +/- SD rate, 0.64 +/- 1.26 vs 0.81 +/- 1.61 readmissions/ patient per year; P =. 03). Overall, recurrent hospital costs were significantly lower ( 14%) in the HBI group (mean +/- SD, $ 823 +/- $ 1642 vs $ 960 +/- $ 1376 per patient per year; P =. 045). Conclusion: This unique study suggests that a nonspecific HBI provides long-term cost benefits in a range of chronic illnesses, except for chronic obstructive pulmonary disease.

Physiologically based synthetic models of hepatic disposition

Current Physiologically based pharmacokinetic (PBPK) models are inductive. We present an additional, different approach that is based on the synthetic rather than the inductive approach to modeling and simulation. It relies on object-oriented programming A model of the referent system in its experimental context is synthesized by assembling objects that represent components such as molecules, cells, aspects of tissue architecture, catheters, etc. The single pass perfused rat liver has been well described in evaluating hepatic drug pharmacokinetics (PK) and is the system on which we focus. In silico experiments begin with administration of objects representing actual compounds. Data are collected in a manner analogous to that in the referent PK experiments. The synthetic modeling method allows for recognition and representation of discrete event and discrete time processes, as well as heterogeneity in organization, function, and spatial effects. An application is developed for sucrose and antipyrine, administered separately and together PBPK modeling has made extensive progress in characterizing abstracted PK properties but this has also been its limitation. Now, other important questions and possible extensions emerge. How are these PK properties and the observed behaviors generated? The inherent heuristic limitations of traditional models have hindered getting meaningful, detailed answers to such questions. Synthetic models of the type described here are specifically intended to help answer such questions. Analogous to wet-lab experimental models, they retain their applicability even when broken apart into sub-components. Having and applying this new class of models along with traditional PK modeling methods is expected to increase the productivity of pharmaceutical research at all levels that make use of modeling and simulation.

Finding negative event oriented patterns in long temporal sequences

Pattern discovery in a long temporal event sequence is of great importance in many application domains. Most of the previous work focuses on identifying positive associations among time stamped event types. In this paper, we introduce the problem of defining and discovering negative associations that, as positive rules, may also serve as a source of knowledge discovery. In general, an event-oriented pattern is a pattern that associates with a selected type of event, called a target event. As a counter-part of previous research, we identify patterns that have a negative relationship with the target events. A set of criteria is defined to evaluate the interestingness of patterns associated with such negative relationships. In the process of counting the frequency of a pattern, we propose a new approach, called unique minimal occurrence, which guarantees that the Apriori property holds for all patterns in a long sequence. Based on the interestingness measures, algorithms are proposed to discover potentially interesting patterns for this negative rule problem. Finally, the experiment is made for a real application.

Introducing uncertainty into pattern discovery in temporal event sequences

Pattern discovery in temporal event sequences is of great importance in many application domains, such as telecommunication network fault analysis. In reality, not every type of event has an accurate timestamp. Some of them, defined as inaccurate events may only have an interval as possible time of occurrence. The existence of inaccurate events may cause uncertainty in event ordering. The traditional support model cannot deal with this uncertainty, which would cause some interesting patterns to be missing. A new concept, precise support, is introduced to evaluate the probability of a pattern contained in a sequence. Based on this new metric, we define the uncertainty model and present an algorithm to discover interesting patterns in the sequence database that has one type of inaccurate event. In our model, the number of types of inaccurate events can be extended to k readily, however, at a cost of increasing computational complexity.

Genetic algorithm based distance spectrum technique for performance union bound of space-time trellis coded OFDM

This paper derives the performance union bound of space-time trellis codes in orthogonal frequency division multiplexing system (STTC-OFDM) over quasi-static frequency selective fading channels based on the distance spectrum technique. The distance spectrum is the enumeration of the codeword difference measures and their multiplicities by exhausted searching through all the possible error event paths. Exhaustive search approach can be used for low memory order STTC with small frame size. However with moderate memory order STTC and moderate frame size the computational cost of exhaustive search increases exponentially, and may become impractical for high memory order STTCs. This requires advanced computational techniques such as Genetic Algorithms (GAS). In this paper, a GA with sharing function method is used to locate the multiple solutions of the distance spectrum for high memory order STTCs. Simulation evaluates the performance union bound and the complexity comparison of non-GA aided and GA aided distance spectrum techniques. It shows that the union bound give a close performance measure at high signal-to-noise ratio (SNR). It also shows that GA sharing function method based distance spectrum technique requires much less computational time as compared with exhaustive search approach but with satisfactory accuracy.

A wavelet-based adaptive technique for adsorption problems involving steep gradients

A general, fast wavelet-based adaptive collocation method is formulated for heat and mass transfer problems involving a steep moving profile of the dependent variable. The technique of grid adaptation is based on sparse point representation (SPR). The method is applied and tested for the case of a gas–solid non-catalytic reaction in a porous solid at high Thiele modulus. Accurate and convergent steep profiles are obtained for Thiele modulus as large as 100 for the case of slab and found to match the analytical solution.

A matching pursuit-based signal complexity measure for the analysis of newborn EEG

This paper presents a new relative measure of signal complexity, referred to here as relative structural complexity, which is based on the matching pursuit (MP) decomposition. By relative, we refer to the fact that this new measure is highly dependent on the decomposition dictionary used by MP. The structural part of the definition points to the fact that this new measure is related to the structure, or composition, of the signal under analysis. After a formal definition, the proposed relative structural complexity measure is used in the analysis of newborn EEG. To do this, firstly, a time-frequency (TF) decomposition dictionary is specifically designed to compactly represent the newborn EEG seizure state using MP. We then show, through the analysis of synthetic and real newborn EEG data, that the relative structural complexity measure can indicate changes in EEG structure as it transitions between the two EEG states; namely seizure and background (non-seizure).

A hybrid probabilistic criterion for market-based transmission expansion planning

Market-based transmission expansion planning gives information to investors on where is the most cost efficient place to invest and brings benefits to those who invest in this grid. However, both market issue and power system adequacy problems are system planers’ concern. In this paper, a hybrid probabilistic criterion of Expected Economical Loss (EEL) is proposed as an index to evaluate the systems’ overall expected economical losses during system operation in a competitive market. It stands on both investors’ and planner’s point of view and will further improves the traditional reliability cost. By applying EEL, it is possible for system planners to obtain a clear idea regarding the transmission network’s bottleneck and the amount of losses arises from this weak point. Sequentially, it enables planners to assess the worth of providing reliable services. Also, the EEL will contain valuable information for moneymen to undertake their investment. This index could truly reflect the random behaviors of power systems and uncertainties from electricity market. The performance of the EEL index is enhanced by applying Normalized Coefficient of Probability (NCP), so it can be utilized in large real power systems. A numerical example is carried out on IEEE Reliability Test System (RTS), which will show how the EEL can predict the current system bottleneck under future operational conditions and how to use EEL as one of planning objectives to determine future optimal plans. A well-known simulation method, Monte Carlo simulation, is employed to achieve the probabilistic characteristic of electricity market and Genetic Algorithms (GAs) is used as a multi-objective optimization tool.

DR-NEGOTIATE - A system for automated agent negotiation with defeasible logic-based strategies

This paper reports on a system for automated agent negotiation, based on a formal and executable approach to capture the behavior of parties involved in a negotiation. It uses the JADE agent framework, and its major distinctive feature is the use of declarative negotiation strategies. The negotiation strategies are expressed in a declarative rules language, defeasible logic, and are applied using the implemented system DR-DEVICE. The key ideas and the overall system architecture are described, and a particular negotiation case is presented in detail.

Foil based atom chip for Bose-Einstein condensates

We describe a novel method of fabricating atom chips that are well suited to the production and manipulation of atomic Bose–Einstein condensates. Our chip was created using a silver foil and simple micro-cutting techniques without the need for photolithography. It can sustain larger currents than conventional chips, and is compatible with the patterning of complex trapping potentials. A near pure Bose–Einstein condensate of 4 × 104 87Rb atoms has been created in a magnetic microtrap formed by currents through wires on the chip. We have observed the fragmentation of atom clouds in close proximity to the silver conductors. The fragmentation has different characteristic features to those seen with copper conductors.

Molecular phylogeny of Wolbachia endosymbionts in southeast asian mosquitoes (Diptera: Culicidae) based on wsp gene sequences

Wolbachia are maternally inherited intracellular bacteria that infect a wide range of arthropods and nematodes and are associated with various reproductive abnormalities in their hosts. Insect-associated Wolbachia form a monophyletic clade in the α-Proteobacteria and recently have been separated into two supergroups (A and B) and 19 groups. Our recent polymerase chain reaction (PCR) survey using wsp specific primers indicated that various strains of Wolbachia were present in mosquitoes collected from Southeast Asia. Here, we report the phylogenetic relationship of the Wolbachia strains found in these mosquitoes using wsp gene sequences. Our phylogenetic analysis revealed eight new Wolbachia strains, five in the A supergroup and three in the B supergroup. Most of the Wolbachia strains present in Southeast Asian mosquitoes belong to the established Mors, Con, and Pip groups.