Tensile strained InxGa1−xPIn_{x}Ga_{1-x}P membranes for cavity optomechanics

We investigate the optomechanical properties of tensile-strained ternary InGaP nanomembranes grown on GaAs. This material system combines the benefits of highly strained membranes based on stoichiometric silicon nitride, with the unique properties of thin-film semiconductor single crystals, as previously demonstrated with suspended GaAs. Here we employ lattice mismatch in epitaxial growth to impart an intrinsic tensile strain to a monocrystalline thin film (approximately 30 nm thick). These structures exhibit mechanical quality factors of 2*10^6 or beyond at room temperature and 17 K for eigenfrequencies up to 1 MHz, yielding Q*f products of 2*10^12 Hz for a tensile stress of ~170 MPa. Incorporating such membranes in a high finesse Fabry-Perot cavity, we extract an upper limit to the total optical loss (including both absorption and scatter) of 40 ppm at 1064 nm and room temperature. Further reductions of the In content of this alloy will enable tensile stress levels of 1 GPa, with the potential for a significant increase in the Q*f product, assuming no deterioration in the mechanical loss at this composition and strain level. This materials system is a promising candidate for the integration of strained semiconductor membrane structures with low-loss semiconductor mirrors and for realizing stacks of membranes for enhanced optomechanical coupling.Comment: 10 pages, 3 figure

The Effect of Individual Movements and Interventions on the Spread of Influenza in Long-Term Care Facilities

Background. Nosocomial influenza poses a serious risk among residents of long-term care facilities (LTCFs). Objective. We sought to evaluate the effect of resident and staff movements and contact patterns on the outcomes of various intervention strategies for influenza control in an LTCF. Methods. We collected contact frequency data in Canada's largest veterans' LTCF by enroling residents and staff into a study that tracked their movements through wireless tags and signal receivers. We analyzed and fitted the data to an agent-based simulation model of influenza infection, and performed Monte-Carlo simulations to evaluate the benefit of antiviral prophylaxis and patient isolation added to standard (baseline) infection control practice (i.e., vaccination of residents and staff, plus antiviral treatment of residents with symptomatic infection). Results. We calibrated the model to attack rates of 20%, 40%, and 60% for the baseline scenario. For data-driven movements, we found that the largest reduction in attack rates (12.5% to 27%; ANOVA P 0.2) among residents. In contrast, parameterizing the model with random movements yielded different results, suggesting that the highest benefit was achieved through patient isolation (69.6% to 79.6%; ANOVA P <0.001) while the additional benefit of prophylaxis was negligible in reducing the cumulative number of infections. Conclusions. Our study revealed a highly structured contact and movement patterns within the LTCF. Accounting for this structureinstead of assuming randomnessin decision analytic methods can result in substantially different predictions

Wear in metal-on-metal total disc arthroplasty

The wear of a model metal-on-metal ball-and-socket total disc arthroplasty was measured in a simulator. The ball had a radius of 10 mm, and there was a radial clearance between ball and socket of 0.015 mm. The model was subjected to simultaneous flexion–extension, lateral bending, axial rotation (frequency: 1 Hz) and compression (frequency: 2 Hz, maximum load: 2 kN). Throughout the tests, the models were immersed in calf serum diluted to a concentration of 15 g protein per litre, at a controlled temperature of 37 °C. Tests were performed on three models. At regular intervals (0, 0.5, 1, 2, 3, 4 and 5 million cycles), mass and surface roughness were determined; mass measurements were converted into the volume lost as a result of wear. All measurements were repeated six times. Wear occurred in two stages. In the first stage (duration about 1 million cycles), there was a linear wear rate of 2.01 ± 0.04 mm3 per million cycles; in the second stage, there was a linear wear rate of 0.76 ± 0.02 mm3 per million cycles. Surface roughness increased linearly in the first million cycles and then continued to increase linearly but more slowly. </jats:p

How to Minimize the Attack Rate during Multiple Influenza Outbreaks in a Heterogeneous Population

<div><h3>Background</h3><p>If repeated interventions against multiple outbreaks are not feasible, there is an optimal level of control during the first outbreak. Any control measures above that optimal level will lead to an outcome that may be as sub-optimal as that achieved by an intervention that is too weak. We studied this scenario in more detail.</p> <h3>Method</h3><p>An age-stratified ordinary-differential-equation model was constructed to study infectious disease outbreaks and control in a population made up of two groups, adults and children. The model was parameterized using influenza as an example. This model was used to simulate two consecutive outbreaks of the same infectious disease, with an intervention applied only during the first outbreak, and to study how cumulative attack rates were influenced by population composition, strength of inter-group transmission, and different ways of triggering and implementing the interventions. We assumed that recovered individuals are fully immune and the intervention does not confer immunity.</p> <h3>Results/Conclusion</h3><p>The optimal intervention depended on coupling between the two population sub-groups, the length, strength and timing of the intervention, and the population composition. Population heterogeneity affected intervention strategies only for very low cross-transmission between groups. At more realistic values, coupling between the groups led to synchronization of outbreaks and therefore intervention strategies that were optimal in reducing the attack rates for each subgroup and the population overall coincided. For a sustained intervention of low efficacy, early intervention was found to be best, while at high efficacies, a delayed start was better. For short interventions, a delayed start was always advantageous, independent of the intervention efficacy. For most scenarios, starting the intervention after a certain cumulative proportion of children were infected seemed more robust in achieving close to optimal outcomes compared to a strategy that used a specified duration after an outbreak’s beginning as the trigger.</p> </div

Modelers' Perception of Mathematical Modeling in Epidemiology: A Web-Based Survey

International audienceBackground: Mathematical modeling in epidemiology (MME) is being used increasingly. However, there are many uncertainties in terms of definitions, uses and quality features of MME. Methodology/Principal Findings: To delineate the current status of these models, a 10-item questionnaire on MME was devised. Proposed via an anonymous internet-based survey, the questionnaire was completed by 189 scientists who had published in the domain of MME. A small minority (18%) of respondents claimed to have in mind a concise definition of MME. Some techniques were identified by the researchers as characterizing MME (e.g. Markov models), while others–at the same level of sophistication in terms of mathematics–were not (e.g. Cox regression). The researchers' opinions were also contrasted about the potential applications of MME, perceived as higly relevant for providing insight into complex mechanisms and less relevant for identifying causal factors. The quality criteria were those of good science and were not related to the size and the nature of the public health problems addressed. Conclusions/Significance: This study shows that perceptions on the nature, uses and quality criteria of MME are contrasted, even among the very community of published authors in this domain. Nevertheless, MME is an emerging discipline in epidemiology and this study underlines that it is associated with specific areas of application and methods. The development of this discipline is likely to deserve a framework providing recommendations and guidance at various steps of the studies, from design to report

Impact of Emerging Antiviral Drug Resistance on Influenza Containment and Spread: Influence of Subclinical Infection and Strategic Use of a Stockpile Containing One or Two Drugs

BACKGROUND: Wide-scale use of antiviral agents in the event of an influenza pandemic is likely to promote the emergence of drug resistance, with potentially deleterious effects for outbreak control. We explored factors promoting resistance within a dynamic infection model, and considered ways in which one or two drugs might be distributed to delay the spread of resistant strains or mitigate their impact. METHODS AND FINDINGS: We have previously developed a novel deterministic model of influenza transmission that simulates treatment and targeted contact prophylaxis, using a limited stockpile of antiviral agents. This model was extended to incorporate subclinical infections, and the emergence of resistant virus strains under the selective pressure imposed by various uses of one or two antiviral agents. For a fixed clinical attack rate, R(0) rises with the proportion of subclinical infections thus reducing the number of infections amenable to treatment or prophylaxis. In consequence, outbreak control is more difficult, but emergence of drug resistance is relatively uncommon. Where an epidemic may be constrained by use of a single antiviral agent, strategies that combine treatment and prophylaxis are most effective at controlling transmission, at the cost of facilitating the spread of resistant viruses. If two drugs are available, using one drug for treatment and the other for prophylaxis is more effective at preventing propagation of mutant strains than either random allocation or drug cycling strategies. Our model is relatively straightforward, and of necessity makes a number of simplifying assumptions. Our results are, however, consistent with the wider body of work in this area and are able to place related research in context while extending the analysis of resistance emergence and optimal drug use within the constraints of a finite drug stockpile. CONCLUSIONS: Combined treatment and prophylaxis represents optimal use of antiviral agents to control transmission, at the cost of drug resistance. Where two drugs are available, allocating different drugs to cases and contacts is likely to be most effective at constraining resistance emergence in a pandemic scenario

Nutrition and lung cancer: a case control study in Iran

Background: Despite many prospective and retrospective studies about the association of dietary habit and lung cancer, the topic still remains controversial. So, this study aims to investigate the association of lung cancer with dietary factors. Method: In this study 242 lung cancer patients and their 484 matched controls on age, sex, and place of residence were enrolled between October 2002 to 2005. Trained physicians interviewed all participants with standardized questionnaires. The middle and upper third consumer groups were compared to the lower third according to the distribution in controls unless the linear trend was significant across exposure groups. Result: Conditional logistic regression was used to evaluate the association with lung cancer. In a multivariate analysis fruit (Ptrend < 0.0001), vegetable (P = 0.001) and sunflower oil (P = 0.006) remained as protective factors and rice (P = 0.008), bread (Ptrend = 0.04), liver (P = 0.004), butter (Ptrend = 0.04), white cheese (Ptrend < 0.0001), beef (Ptrend = 0.005), vegetable ghee (P < 0.0001) and, animal ghee (P = 0.015) remained as risk factors of lung cancer. Generally, we found positive trend between consumption of beef (P = 0.002), bread (P < 0.0001), and dairy products (P < 0.0001) with lung cancer. In contrast, only fruits were inversely related to lung cancer (P < 0.0001). Conclusion: It seems that vegetables, fruits, and sunflower oil could be protective factors and bread, rice, beef, liver, dairy products, vegetable ghee, and animal ghee found to be possible risk factors for the development of lung cancer in Iran