Subpicosecond carrier lifetime in GaAs grown by molecular beam epitaxy at low temperatures

Epitaxial GaAs grown by molecular beam epitaxy (MBE) at low substrate temperatures is observed to have a significantly shorter carrier lifetime than GaAs grown at normal substrate temperatures. Using femtosecond time‐resolved‐reflectance techniques, a sub‐picosecond (<0.4 ps) carrier lifetime has been measured for GaAs grown by MBE at ∼200°C and annealed at 600 °C. With the same material as a photoconductive switch we have measured electrical pulses with a full‐width at half‐maximum of 0.6 ps using the technique of electro‐optic sampling. Good responsivity for a photoconductive switch is observed, corresponding to a mobility of the photoexcited carriers of ∼120–150 cm2/V s. GaAs grown by MBE at 200 °C and annealed at 600 °C is also semi‐insulating, which results in a low dark current in the switch application. The combination of fast recombination lifetime, high carrier mobility, and high resistivity makes this material ideal for a number of subpicosecond photoconductive applications.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/71318/2/APPLAB-59-25-3276-1.pd

Ultrahigh-bandwidth vector network analyzer based on external electro-optic sampling

We report the development of an ultrahigh-bandwidth vector network analyzer useful for small-signal characterization of high-speed semiconductor devices. It employs 100-fs optical pulses for making terahertz-bandwidth electro-optic measurements of electrical signals, as well as for sub-picosecond, photoconductive, electrical-stimulus-signal generation. High-bandwidth coplanar strip transmission lines are used for signal transmission. A 0.15 x 50 [mu]m gate AlGaAs/InGaAs/GaAs HFET has been characterized over a bandwidth of 100 GHz using this network analyzer. A comparison with conventional RF network analyzer measurements performed to 40 GHz demonstrated good agreement throughout this bandwidth. Such measurements of the actual device characteristics across their entire operating frequency range should improve device development and incorporation into active circuits.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/30189/1/0000574.pd

Impact of Diabetes on Work Cessation: Data from the GAZEL cohort study

International audienceOBJECTIVE: To measure the impact of diabetes on work cessation, i.e., on the risks of work disability, early retirement, and death while in the labor force. RESEARCH DESIGN AND METHODS: We used data from the GAZEL prospective cohort of 20,625 employees of the French national gas and electricity company "EDF-GDF." We identified 506 employees with diabetes and randomly selected 2,530 nondiabetic employed control subjects matched for major sociodemographic and occupational characteristics. Using a multistate Cox model, we estimated hazard ratios (HRs) comparing the risks of transition from employment to disability, retirement, and death over time between participants with versus without diabetes. RESULTS: Employment rate decreased more rapidly in participants with diabetes (51.9 and 10.1% at 55 and 60 years, respectively) compared with nondiabetic participants (66.5 and 13.4%, respectively). Participants with diabetes had significantly increased risks of transition from employment to disability (HR 1.7 [95% CI 1.0-2.9]), retirement (HR 1.6 [1.5-1.8]), and death (HR 7.3 [3.6-14.6]) compared with participants without diabetes. Between 35 and 60 years, each participant with diabetes lost an estimated mean time of 1.1 year in the workforce (95% CI 0.99-1.14) compared with a nondiabetic participant. CONCLUSIONS: Our results provide evidence for a profound negative impact of diabetes on workforce participation in France. Social and economic consequences are major for patients, employers, and society-a burden that is likely to increase as diabetes becomes more and more common in the working-aged population

Latent cluster analysis of ALS phenotypes identifies prognostically differing groups

BACKGROUND Amyotrophic lateral sclerosis (ALS) is a degenerative disease predominantly affecting motor neurons and manifesting as several different phenotypes. Whether these phenotypes correspond to different underlying disease processes is unknown. We used latent cluster analysis to identify groupings of clinical variables in an objective and unbiased way to improve phenotyping for clinical and research purposes. METHODS Latent class cluster analysis was applied to a large database consisting of 1467 records of people with ALS, using discrete variables which can be readily determined at the first clinic appointment. The model was tested for clinical relevance by survival analysis of the phenotypic groupings using the Kaplan-Meier method. RESULTS The best model generated five distinct phenotypic classes that strongly predicted survival (p<0.0001). Eight variables were used for the latent class analysis, but a good estimate of the classification could be obtained using just two variables: site of first symptoms (bulbar or limb) and time from symptom onset to diagnosis (p<0.00001). CONCLUSION The five phenotypic classes identified using latent cluster analysis can predict prognosis. They could be used to stratify patients recruited into clinical trials and generating more homogeneous disease groups for genetic, proteomic and risk factor research

Expression determinants of mammalian argonaute proteins in mediating gene silencing

RNA interference occurs by two main processes: mRNA site-specific cleavage and non-cleavage-based mRNA degradation or translational repression. Site-specific cleavage is carried out by argonaute-2 (Ago2), while all four mammalian argonaute proteins (Ago1–Ago4) can carry out non-cleavage-mediated inhibition, suggesting that Ago1, Ago3 and Ago4 may have similar but potentially redundant functions. It has been observed that in mammalian tissues, expression of Ago3 and Ago4 is dramatically lower compared with Ago1; however, an optimization of the Ago3 and Ago4 coding sequences to include only the most common codon at each amino acid position was able to augment the expression of Ago3 and Ago4 to levels comparable to that of Ago1 and Ago2. Thus, we examined whether particular sequence features exist in the coding region of Ago3 and Ago4 that may prevent a high level of expression. Swapping specific sub-regions of wild-type and optimized Ago sequence identified the portion of the coding region (nucleotides 1–1163 for Ago-3 and 1–1494 for Ago-4) that is most influential for expression. This finding has implications for the evolutionary conservation of Ago proteins in the mammalian lineage and the biological role that potentially redundant Ago proteins may have

Assessing the Relative Performance of Nurses Using Data Envelopment Analysis Matrix (DEAM)

Assessing employee performance is one of the most important issue in healthcare management services. Because of their direct relationship with patients, nurses are also the most influential hospital staff who play a vital role in providing healthcare services. In this paper, a novel Data Envelopment Analysis Matrix (DEAM) approach is proposed for assessing the performance of nurses based on relative efficiency. The proposed model consists of five input variables (including type of employment, work experience, training hours, working hours and overtime hours) and eight output variables (the outputs are amount of hours each nurse spend on each of the eight activities including documentation, medical instructions, wound care and patient drainage, laboratory sampling, assessment and control care, follow-up and counseling and para-clinical measures, attendance during visiting and discharge suction) have been tested on 30 nurses from the heart department of a hospital in Iran. After determining the relative efficiency of each nurse based on the DEA model, the nurses’ performance were evaluated in a DEAM format. As results the nurses were divided into four groups; superstars, potential stars, those who are needed to be trained effectively and question marks. Finally, based on the proposed approach, we have drawn some recommendations to policy makers in order to improve and maintain the performance of each of these groups. The proposed approach provides a practical framework for hospital managers so that they can assess the relative efficiency of nurses, plan and take steps to improve the quality of healthcare delivery