Characterization of nonlinear switching in a figure-of-eight fiber laser using frequency-resolved optical gating

The measurement technique of frequency-resolved optical gating is applied to determine the nonlinear switching characteristics of a passively modelocked figure-of-eight erbium-doped fiber laser. By completely characterizing the intensity and phase of the laser output pulses, the intracavity fields in the nonlinear amplifying loop mirror of the laser cavity are determined by numerical propagation using the nonlinear Schrodinger equation. Excellent switching of 95% can be achieved as a result of uniform phase characteristics developed by pulses propagating in the nonlinear amplifying loop mirror

Complete characterization of ultrashort pulse sources at 1550 nm

This paper reviews the use of frequency-resolved optical gating (FROG) to characterize mode-locked lasers producing ultrashort pulses suitable for high-capacity optical communications systems at wavelengths around 1550 nm, Second harmonic generation (SHG) FROG is used to characterize pulses from a passively mode-locked erbium-doped fiber laser, and both single-mode and dual-mode gain-switched semiconductor lasers. The compression of gain-switched pulses in dispersion compensating fiber is also studied using SHG-FROG, allowing optimal compression conditions to be determined without a priori assumptions about pulse characteristics. We also describe a fiber-based FROG geometry exploiting cross-phase modulation and show that it is ideally suited to pulse characterization at optical communications wavelengths. This technique has been used to characterize picosecond pulses with energy as low as 24 pJ, giving results in excellent agreement with SHG-FROG characterization, and without any temporal ambiguity in the retrieved puls

Acute kidney injury in the era of the AKI E-Alert

Background and objectivesOur aimwas to use a national electronicAKI alert to define the incidence and outcome of all episodes of community– and hospital–acquired adult AKI. Design, setting, participants, & measurements A prospective national cohort study was undertaken in a population of 3.06 million.Datawere collected betweenMarch of 2015 andAugust of 2015. All patients with adult ($18 years of age) AKI were identified to define the incidence and outcome of all episodes of community- and hospital-acquired AKI in adults. Mortality and renal outcomes were assessed at 90 days. Results There was a total of 31,601 alerts representing 17,689 incident episodes, giving an incidence of AKI of 577 per 100,000 population. Community-acquired AKI accounted for 49.3% of all incident episodes, and 42% occurred in the context of preexisting CKD (Chronic Kidney Disease Epidemiology Collaboration eGFR); 90-day mortality rate was 25.6%, and 23.7% of episodes progressed to a higher AKI stage than the stage associated with the alert. AKI electronic alert stage and peak AKI stage were associated with mortality, and mortality was significantly higher for hospital-acquired AKI compared with alerts generated in a community setting. Among patients who survived to 90 days after the AKI electronic alert, those who were not hospitalized had a lower rate of renal recovery and a greater likelihood of developing an eGFR,60 ml/min per 1.73m2 for the first time,which may be indicative of development of de novo CKD. Conclusions The reported incidence of AKI is far greater than the previously reported incidence in studies reliant on clinical identification of adult AKI or hospital coding data. Although an electronic alert systemis Information Technology driven and therefore, lacks intelligence and clinical context, these data can be used to identify deficiencies in care, guide the development of appropriate intervention strategies, and provide a baseline against which the effectiveness of these interventions may be measured

Identification of Complex Rumen Microbiome Interaction Within Diverse Functional Niches as Mechanisms Affecting the Variation of Methane Emissions in Bovine

A network analysis including relative abundances of all ruminal microbial genera (archaea, bacteria, fungi, and protists) and their genes was performed to improve our understanding of how the interactions within the ruminal microbiome affects methane emissions (CH 4). Metagenomics and CH 4 data were available from 63 bovines of a two-breed rotational cross, offered two basal diets. Co-abundance network analysis revealed 10 clusters of functional niches. The most abundant hydrogenotrophic Methanobacteriales with key microbial genes involved in methanogenesis occupied a different functional niche (i.e., "methanogenesis" cluster) than methylotrophic Methanomassiliicoccales (Candidatus Methanomethylophylus) and acetogens ( Blautia). Fungi and protists clustered together and other plant fiber degraders like Fibrobacter occupied a seperate cluster. A Partial Least Squares analysis approach to predict CH 4 variation in each cluster showed the methanogenesis cluster had the best prediction ability (57.3%). However, the most important explanatory variables in this cluster were genes involved in complex carbohydrate degradation, metabolism of sugars and amino acids and Candidatus Azobacteroides carrying nitrogen fixation genes, but not methanogenic archaea and their genes. The cluster containing Fibrobacter, isolated from other microorganisms, was positively associated with CH 4 and explained 49.8% of its variability, showing fermentative advantages compared to other bacteria and fungi in providing substrates (e.g., formate) for methanogenesis. In other clusters, genes with enhancing effect on CH 4 were related to lactate and butyrate ( Butyrivibrio and Pseudobutyrivibrio) production and simple amino acids metabolism. In comparison, ruminal genes negatively related to CH 4 were involved in carbohydrate degradation via lactate and succinate and synthesis of more complex amino acids by γ-Proteobacteria. When analyzing low- and high-methane emitters data in separate networks, competition between methanogens in the methanogenesis cluster was uncovered by a broader diversity of methanogens involved in the three methanogenesis pathways and larger interactions within and between communities in low compared to high emitters. Generally, our results suggest that differences in CH 4 are mainly explained by other microbial communities and their activities rather than being only methanogens-driven. Our study provides insight into the interactions of the rumen microbial communities and their genes by uncovering functional niches affecting CH 4, which will benefit the development of efficient CH 4 mitigation strategies

Mother-child histocompatibility and risk of rheumatoid arthritis and systemic lupus erythematosus among mothers.

The study objective was to test the hypothesis that having histocompatible children increases the risk of rheumatoid arthritis (RA) and systemic lupus erythematosus (SLE), possibly by contributing to the persistence of fetal cells acquired during pregnancy. We conducted a case control study using data from the UC San Francisco Mother Child Immunogenetic Study and studies at the Inova Translational Medicine Institute. We imputed human leukocyte antigen (HLA) alleles and minor histocompatibility antigens (mHags). We created a variable of exposure to histocompatible children. We estimated an average sequence similarity matching (SSM) score for each mother based on discordant mother-child alleles as a measure of histocompatibility. We used logistic regression models to estimate odds ratios (ORs) and 95% confidence intervals. A total of 138 RA, 117 SLE, and 913 control mothers were analyzed. Increased risk of RA was associated with having any child compatible at HLA-B (OR 1.9; 1.2-3.1), DPB1 (OR 1.8; 1.2-2.6) or DQB1 (OR 1.8; 1.2-2.7). Compatibility at mHag ZAPHIR was associated with reduced risk of SLE among mothers carrying the HLA-restriction allele B*07:02 (n = 262; OR 0.4; 0.2-0.8). Our findings support the hypothesis that mother-child histocompatibility is associated with risk of RA and SLE

Atomic Beam Research

Contains reports on one research project