Specsim: The MIRI Medium Resolution Spectrometer Simulator

MIRI, the Mid-InfraRed Instrument, is one of four instruments being built for the James Webb Space Telescope, and is developed jointly between an EuropeanConsortium and the US. In this paper we present a software data simulator for one of MIRI's four instruments: the Integral Field Unit (IFU) Medium Resolution Spectrometer (MIRI-MRS), the first mid-infrared IFU spectrograph, and one of the first IFUs to be used in a space mission. To give the MIRI community a preview of the properties of the MIRI-MRS data products before the telescope is operational, the Specsim tool has been developed to model, in software, the operation of the spectrometer. Specsim generates synthetic data frames approximating those which will be taken by the instrument in orbit. The program models astronomical sources and generates detector frames using the predicted and measured optical properties of the telescope and MIRI. These frames can then be used to illustrate and inform a range of operational activities, including data calibration strategies and the development and testing of the data reduction software for the MIRI-MRS. Specsim will serve as a means of communication between the many consortium members by providing a way to easily illustrate the performance of the spectrometer under different circumstances, tolerances of components and design scenarios.Comment: 8 pages, 5 figures; A high resolution version is available at http://www.roe.ac.uk/~npfl/Publications/lgw+06.ps.gz (Changed URL of high-res version

Efeito das mudanças climáticas para cana-de-açúcar com base no modelo APSIM/Sugarcane.

O objetivo deste trabalho foi avaliar a sensibilidade do modelo Agricultural production simulator - sugarcane (APSIM/Sugarcane) (Keating et al. 1998; Thorburn et al., 2005) quanto aos parâmetros climáticos [CO2], temperatura e precipitação, e analisar cenários futuros de mudança climática para a cultura de cana-de-açúcar

Estimativa das temperaturas máximas, mínimas e médias mensais para o Brasil.

O trabalho gerou equações para estimativa das temperaturas médias, máximas e mínimas, por meio de análise de regressão linear múltipla, obtidas na escala mensal e anual para as cinco regiões brasileiras

Thermal and electrical modelling of polymer cored BGA interconnects

Polymer cored BGA/CSP balls have been proposed as a more reliable alternative to solid solder balls for demanding application environments. Their potential advantages are dependant on their increased compliance compared with a solid solder ball, thereby reducing the level of stress imposed on the solder joints during exposure to cyclic thermal loads and impacts. The latter is of particular importance for hand held products assembled using lead free solders, which are much more brittle than traditional tin-lead alloys, but this may also be important for harsh environment applications where tinlead solders are still being used, such as in aerospace and defence electronics applications. The increased compliance of a polymer cored ball may reduce the requirement for underfilling of components in hand held products, and allow adoption of BGA/CSP for safety critical applications in harsh environments. Such polymer cored interconnects are however likely to provide a reduced thermal and electrical conductivity and it is important to ensure any such effects do not impact upon the thermal and electrical performance of the product. This paper utilises analytical and computational modelling techniques to achieve an understanding of the effect of conductor particle geometry and properties on thermal and electrical performance. Such models offer a route to appropriate materials selection for the polymer spheres and their conductive coatings, and for establishing optimum design parameters such as ball diameter, conductive coating thickness, solder pad diameter, and solder volumes. The results confirm that the introduction of polymer cored BGA balls will result in some increases in thermal and electrical resistance, but that these changes will have minor impacts on the overall performance of products

Outcomes associated with bacteremia in the setting of methicillin-resistant Staphylococcus aureus pneumonia: A retrospective cohort study

INTRODUCTION: Methicillin-resistant Staphylococcus aureus (MRSA) remains an important pathogen in pneumonia. Bacteremia may secondarily complicate MRSA pneumonia. The epidemiology and outcomes associated with bacteremia in the setting of MRSA pneumonia are unknown. We sought to describe the prevalence of bacteremia in MRSA pneumonia and its impact on hospital mortality and length of stay (LOS). METHODS: We conducted a single-center retrospective cohort study (2008–2013) including adult patients hospitalized with pneumonia caused by MRSA. We defined pneumonia based on clinical criteria and all cases were culture confirmed. MRSA bacteremia was identified based on positive blood cultures. Pneumonia was categorized as either community-onset (CO, occurring at presentation or within 2 days of admission) or hospital-onset (HO, occurring > 2 days after admission). We compared bacteremic and non-bacteremic groups with respect to their demographic and clinical characteristics and outcomes. A logistic regression and a generalized linear model (GLM) were constructed to examine the impact of bacteremia on hospital mortality and post-pneumonia onset LOS, respectively. RESULTS: Among the 765 patients with MRSA pneumonia (33.1 % CO), 93 (12.2 %) had concurrent bacteremia (37.6 % CO). Patients with bacteremia were similar to non-bacteremic subjects based on demographic and clinical characteristics with the exception of frequency of a hospitalization within prior 180 days (48.4 % bacteremic and 37.7 % non-bacteremic, p = 0.047), prevalence of chronic liver disease (17.2 % vs. 9.5 %, p = 0.030), and the mean APACHE II score at the onset of pneumonia (17.5 ± 6.0 vs. 16.1 ± 6.0, p = 0.045). Both unadjusted mortality (33.7 % vs. 23.8 %, p = 0.067) and median post-pneumonia LOS (18.2 vs. 12.2 days, p < 0.001) were greater in the bacteremic than the non-bacteremic group. In a logistic regression, bacteremia showed a trend toward an association with increased mortality (odds ratio 1.56, 95 % confidence interval 0.93 to 2.61). Concomitant bacteremia was independently associated with a 10.3-day increase in the post-pneumonia hospital LOS (95 % confidence interval 6.7 to 13.9 days). CONCLUSIONS: Concurrent bacteremia occurred with moderate frequency in the setting of hospitalization with MRSA pneumonia. Although bacteremia did not appear to independently impact mortality, this was likely due to our study’s limited sample size. However, bacteremia complicating MRSA pneumonia added between 1 and 2 weeks to the hospital LOS

Efeito das mudanças climáticas para cana-de-açúcar com base no modelo APSIM-Sugarcane.

O objetivo deste trabalho foi simular os efeitos das alterações climáticas no crescimento e produtividade da cana-de-açúcar. O modelo APSIM-Sugarcane foi utilizado para a simulação, e para tanto, foi necessária a calibração para cultivar SP 80-1842, utilizando dados experimentais. A sensibilidade do modelo foi testada para os elementos climáticos [CO2], precipitação e temperatura do ar, com dados climáticos de Piracicaba-SP. Quatro cenários climáticos futuros foram simulados, além do atual. Com o aumento da concentração de CO 2 e precipitação, a produção de colmos aumentou em relação ao cenário atual. No entanto, mudanças de temperatura e diminuição da precipitação não beneficiaram a cultura. Apenas os cenários de mudanças climáticas CSIRO A2 e B2 mostraram um aumento na produtividade, enquanto PRECIS A2 e B2 indicaram uma diminuição em relação ao atual.CIIC 2012. No 12614

A risk score for identifying methicillin-resistant Staphylococcus aureus in patients presenting to the hospital with pneumonia.

Background Methicillin-resistant Staphylococcus aureus (MRSA) represents an important pathogen in healthcare-associated pneumonia (HCAP). The concept of HCAP, though, may not perform well as a screening test for MRSA and can lead to overuse of antibiotics. We developed a risk score to identify patients presenting to the hospital with pneumonia unlikely to have MRSA. Methods We identified patients admitted with pneumonia (Apr 2005 – Mar 2009) at 62 hospitals in the US. We only included patients with lab evidence of bacterial infection (e.g., positive respiratory secretions, blood, or pleural cultures or urinary antigen testing). We determined variables independently associated with the presence of MRSA based on logistic regression (two-thirds of cohort) and developed a risk prediction model based on these factors. We validated the model in the remaining population. Results The cohort included 5975 patients and MRSA was identified in 14%. The final risk score consisted of eight variables and a potential total score of 10. Points were assigned as follows: two for recent hospitalization or ICU admission; one each for age \u3c 30 or \u3e 79 years, prior IV antibiotic exposure, dementia, cerebrovascular disease, female with diabetes, or recent exposure to a nursing home/long term acute care facility/skilled nursing facility. This study shows how the prevalence of MRSA rose with increasing score after stratifying the scores into Low (0 to 1 points), Medium (2 to 5 points) and High (6 or more points) risk. When the score was 0 or 1, the prevalence of MRSA was \u3c 10% while the prevalence of MRSA climbed to \u3e 30% when the score was 6 or greater. Conclusions MRSA represents a cause of pneumonia presenting to the hospital. This simple risk score identifies patients at low risk for MRSA and in whom anti-MRSA therapy might be withheld

PPFL: privacy-preserving federated learning with trusted execution environments

We propose and implement a Privacy-preserving Federated Learning (PPFL) framework for mobile systems to limit privacy leakages in federated learning. Leveraging the widespread presence of Trusted Execution Environments (TEEs) in high-end and mobile devices, we utilize TEEs on clients for local training, and on servers for secure aggregation, so that model/gradient updates are hidden from adversaries. Challenged by the limited memory size of current TEEs, we leverage greedy layer-wise training to train each model's layer inside the trusted area until its convergence. The performance evaluation of our implementation shows that PPFL can significantly improve privacy while incurring small system overheads at the client-side. In particular, PPFL can successfully defend the trained model against data reconstruction, property inference, and membership inference attacks. Furthermore, it can achieve comparable model utility with fewer communication rounds (0.54x) and a similar amount of network traffic (1.002x) compared to the standard federated learning of a complete model. This is achieved while only introducing up to ~15% CPU time, ~18% memory usage, and ~21% energy consumption overhead in PPFL's client-side