Effect of three surface conditioning methods to improve bond strength of particulate filler resin composites

The use of resin-based composite materials in operative dentistry is increasing, including applications in stress-bearing areas. However, composite restorations, in common with all restorations, suffer from deterioration and degradation in clinical service. Durable repair alternatives by layering a new composite onto such failed composite restorations, will eliminate unnecessary loss of tooth tissue and repeated insults to the pulp. The objective of this study was to evaluate the effect of three surface conditioning methods on the repair bond strength of a particulate filler resin-composite (PFC) to 5 PFC substrates. The specimens were randomly assigned to one of the following surface conditioning methods: (1) Hydrofluoric (HF) acid gel (9.5%) etching, (2) Air-borne particle abrasion (50 mum Al2O3), (3) Silica coating (30 mum SiOx, CoJet(R)-Sand). After each conditioning method, a silane coupling agent was applied. Adhesive resin was then applied in a thin layer and light polymerized. The low-viscosity diacrylate resin composite was bonded to the conditioned substrates in polyethylene molds. All specimens were tested in dry and thermocycled (6.000, 5-55 degreesC, 30 s) conditions. One-way ANOVA showed significant influence of the surface conditioning methods (p &lt;0.001), and the PFC types (p &lt;0.0001) on the shear bond strength values. Significant differences were observed in bond strength values between the acid etched specimens (5.7-14.3 MPa) and those treated with either air-borne particle abrasion (13.0-22.5 MPa) or silica coating (25.5-41.8 MPa) in dry conditions (ANOVA, p &lt;0.001). After thermocycling, the silica coating process resulted in the highest bond values in all material groups (17.2-30.3 MPa). (C) 2005 Springer Science + Business Media, Inc.</p

A controlled migration genetic algorithm operator for hardware-in-the-loop experimentation

In this paper, we describe the development of an extended migration operator, which combats the negative effects of noise on the effective search capabilities of genetic algorithms. The research is motivated by the need to minimize the num- ber of evaluations during hardware-in-the-loop experimentation, which can carry a significant cost penalty in terms of time or financial expense. The authors build on previous research, where convergence for search methods such as Simulated Annealing and Variable Neighbourhood search was accelerated by the implementation of an adaptive decision support operator. This methodology was found to be effective in searching noisy data surfaces. Providing that noise is not too significant, Genetic Al- gorithms can prove even more effective guiding experimentation. It will be shown that with the introduction of a Controlled Migration operator into the GA heuristic, data, which repre- sents a significant signal-to-noise ratio, can be searched with significant beneficial effects on the efficiency of hardware-in-the- loop experimentation, without a priori parameter tuning. The method is tested on an engine-in-the-loop experimental example, and shown to bring significant performance benefits

Search based software engineering: Trends, techniques and applications

© ACM, 2012. This is the author's version of the work. It is posted here by permission of ACM for your personal use. Not for redistribution. The definitive version is available from the link below.In the past five years there has been a dramatic increase in work on Search-Based Software Engineering (SBSE), an approach to Software Engineering (SE) in which Search-Based Optimization (SBO) algorithms are used to address problems in SE. SBSE has been applied to problems throughout the SE lifecycle, from requirements and project planning to maintenance and reengineering. The approach is attractive because it offers a suite of adaptive automated and semiautomated solutions in situations typified by large complex problem spaces with multiple competing and conflicting objectives. This article provides a review and classification of literature on SBSE. The work identifies research trends and relationships between the techniques applied and the applications to which they have been applied and highlights gaps in the literature and avenues for further research.EPSRC and E

The effects of probiotic bacteria on glycaemic control in overweight men and women: a randomised controlled trial

Background/Objectives: Evidence from animal and in vitro models suggest a role of probiotic bacteria in improving glycaemic control and delaying the onset of type 2 diabetes. However, the evidence from controlled trials in humans is limited. The objective was to determine if the probiotic bacteria L. acidophilus La5 and B. animalis subsp lactis Bb12, supplemented in a whole food (yoghurt) or isolated (capsules) form, can improve biomarkers of glycaemic control. Subjects/methods: Following a 3-week washout period, 156 overweight men and women over 55 years (mean age: 67±8 years; mean body mass index (31±4 kg/m2) were randomized to a 6-week double-blinded parallel study. The four intervention groups were: (A) probiotic yoghurt plus probiotic capsules; (B) probiotic yoghurt plus placebo capsules; (C) control milk plus probiotic capsules; and (D) control milk plus placebo capsules. Outcome measurements, including fasting glucose, insulin, glycated haemoglobin and Homoeostasis Model Assessment of Insulin Resistance (HOMA-IR), were performed at baseline and week 6. Results: Relative to the milk-control group, probiotic yoghurt resulted in a significantly higher HOMA-IR (0.32±0.15, P=0.038), but did not have a significant effect on the other three measures of glycaemic control (P>0.05). Relative to placebo capsules, probiotic capsules resulted in a significantly higher fasting glucose (0.15±0.07 mmol/l, P=0.037), with no significant effect on the other three measures of glycaemic control (P>0.05). Further analyses did not identify other variables as contributing to these adverse findings. Conclusions: Data from this study does not support the hypothesis that L. acidophilus La5 and B. animalis subsp lactis Bb12, either in isolated form or as part of a whole food, benefit short-term glycaemic control. Indeed, there is weak data for an adverse effect of these strains on glucose homoeostasis

GA-based multi-objective optimization of active nonlinear quarter car suspension system—PID and fuzzy logic control

Background The primary function of a suspension system is to isolate the vehicle body from road irregularities thus providing the ride comfort and to support the vehicle and provide stability. The suspension system has to perform conflicting requirements; hence, a passive suspension system is replaced by the active suspension system which can supply force to the system. Active suspension supplies energy to respond dynamically and achieve relative motion between body and wheel and thus improves the performance of suspension system. Methods This study presents modelling and control optimization of a nonlinear quarter car suspension system. A mathematical model of nonlinear quarter car is developed and simulated for control and optimization in Matlab/Simulink® environment. Class C road is selected as input road condition with the vehicle traveling at 80 kmph. Active control of the suspension system is achieved using FLC and PID control actions. Instead of guessing and or trial and error method, genetic algorithm (GA)-based optimization algorithm is implemented to tune PID parameters and FLC membership functions’ range and scaling factors. The optimization function is modeled as a multi-objective problem comprising of frequency weighted RMS seat acceleration, Vibration dose value (VDV), RMS suspension space, and RMS tyre deflection. ISO 2631-1 standard is adopted to assess the ride and health criterion. Results The nonlinear quarter model along with the controller is modeled and simulated and optimized in a Matlab/Simulink environment. It is observed that GA-optimized FLC gives better control as compared to PID and passive suspension system. Further simulations are validated on suspension system with seat and human model. Parameters under observation are frequency-weighted RMS head acceleration, VDV at the head, crest factor, and amplitude ratios at the head and upper torso (AR_h and AR_ut). Simulation results are presented in time and frequency domain. Conclusion Simulation results show that GA-based FLC and PID controller gives better ride comfort and health criterion by reducing RMS head acceleration, VDV at the head, CF, and AR_h and AR_ut over passive suspension system