Observations related to chronologic and gynecologic age in pregnant adolescents.

A low chronologic age (less than or equal to 15 years) and low gynecologic age (less than or equal to 2 years) have been considered factors that increase medical complications among adolescent pregnant women. Gynecologic age (GA) is defined in this study as age in years at conception minus age at menarche. Two hundred twelve consecutive pregnant teenagers were followed prospectively in the Teen OB Clinic at the University of California, San Diego Medical Center, between August 1978 and July 1981. The clinic population consisted of 37.3 percent Whites, 35.8 percent Hispanics, 20.8 percent Blacks, and 6.1 percent other (mostly Indochinese). Sixty-eight percent of the patients were funded by MediCal. The patient population was divided by chronological age (CA) at conception into those 15 years or less or 16 years or older. A low chronological age was found to be a significant risk factor for premature rupture of membranes. Teenagers with a low gynecologic age (less than or equal to 2) had a lower mean pre-pregnancy weight and body mass index (Kg/M2) than teenagers with a higher gynecologic age. In this study, we did not find that a low CA or GA was correlated with a higher frequency of pregnancy-induced hypertension, prenatal medical problems, obstetrical problems at labor or delivery, or an excessive number of low-birthweight infants

A study of the feasibility of using sea and wind information from the ERS-1 satellite. Part 1: Wind scatterometer data

The use of scatterometer and altimeter data in wind and wave assimilation, and the benefits this offers for quality assurance and validation of ERS-1 data were examined. Real time use of ERS-1 data was simulated through assimilation of Seasat scatterometer data. The potential for quality assurance and validation is demonstrated by documenting a series of substantial problems with the scatterometer data, which are known but took years to establish, or are new. A data impact study, and an analysis of the performance of ambiguity removal algorithms on real and simulated data were conducted. The impact of the data on analyses and forecasts is large in the Southern Hemisphere, generally small in the Northern Hemisphere, and occasionally large in the Tropics. Tests with simulated data give more optimistic results than tests with real data. Errors in ambiguity removal results occur in clusters. The probabilities which can be calculated for the ambiguous wind directions on ERS-1 contain more information than is given by a simple ranking of the directions

Coz: Finding Code that Counts with Causal Profiling

Improving performance is a central concern for software developers. To locate optimization opportunities, developers rely on software profilers. However, these profilers only report where programs spent their time: optimizing that code may have no impact on performance. Past profilers thus both waste developer time and make it difficult for them to uncover significant optimization opportunities. This paper introduces causal profiling. Unlike past profiling approaches, causal profiling indicates exactly where programmers should focus their optimization efforts, and quantifies their potential impact. Causal profiling works by running performance experiments during program execution. Each experiment calculates the impact of any potential optimization by virtually speeding up code: inserting pauses that slow down all other code running concurrently. The key insight is that this slowdown has the same relative effect as running that line faster, thus "virtually" speeding it up. We present Coz, a causal profiler, which we evaluate on a range of highly-tuned applications: Memcached, SQLite, and the PARSEC benchmark suite. Coz identifies previously unknown optimization opportunities that are both significant and targeted. Guided by Coz, we improve the performance of Memcached by 9%, SQLite by 25%, and accelerate six PARSEC applications by as much as 68%; in most cases, these optimizations involve modifying under 10 lines of code.Comment: Published at SOSP 2015 (Best Paper Award

Dynamic Resource Allocation for Efficient Sharing of Services from Heterogeneous Autonomous Vehicles

A novel dynamic resource allocation model is introduced for efficient sharing of services provided by ad hoc assemblies of heterogeneous autonomous vehicles. A key contribution is the provision of capability to dynamically select sensors and platforms within constraints imposed by time dependencies, refueling, and transportation services. The problem is modeled as a connected network of nodes and formulated as an integer linear program. Solution fitness is prioritized over computation time. Simulation results of an illustrative scenario are used to demonstrate the ability of the model to plan for sensor selection, refueling, collaboration, and cooperation between heterogeneous resources. Prioritization of operational cost leads to missions that use cheaper resources but take longer to complete. Prioritization of completion time leads to shorter missions at the expense of increased overall resource cost. Missions can be successfully replanned through dynamic reallocation of new requests during a mission. Monte Carlo studies on systems of increasing complexity show that good solutions can be obtained using low time resolutions, with small time windows at a relatively low computational cost. In comparison with other approaches, the developed integer linear program model provides best solutions at the expense of longer computation time

And Then Suddenly Seattle University Was On Its Way To A Parallel, Integrative Curriculum

This is a story of change so sudden that it surprised even those who most fervently sought it. For nearly a decade, Seattle University School of Law has offered an extensive typical skills curriculum. All students are involved in an intensive two year writing program. The simulated Comprehensive Pretrial and Trial Advocacy Program trains over 150 students a year, while in the Law Practice Clinic, 60 students a year represent domestic and criminal clients. Course offerings that fill out the lawyering skills supports are offerings such as ADR, Negotiations, and Appellate Advocacy, along with judicial and public service externships and an array of student competitions. All was well done, well-conceived, staple clinical fare. Then something happened. These programs remain, but woven throughout the course offerings is what we call a Parallel, Integrative Curriculum: One-credit live-client and simulated course components running parallel to related upper-level substantive courses. This article is about that curriculum and, as importantly, how it came into being

Gi- and Gs-coupled GPCRs show different modes of G-protein binding.

More than two decades ago, the activation mechanism for the membrane-bound photoreceptor and prototypical G protein-coupled receptor (GPCR) rhodopsin was uncovered. Upon light-induced changes in ligand-receptor interaction, movement of specific transmembrane helices within the receptor opens a crevice at the cytoplasmic surface, allowing for coupling of heterotrimeric guanine nucleotide-binding proteins (G proteins). The general features of this activation mechanism are conserved across the GPCR superfamily. Nevertheless, GPCRs have selectivity for distinct G-protein family members, but the mechanism of selectivity remains elusive. Structures of GPCRs in complex with the stimulatory G protein, Gs, and an accessory nanobody to stabilize the complex have been reported, providing information on the intermolecular interactions. However, to reveal the structural selectivity filters, it will be necessary to determine GPCR-G protein structures involving other G-protein subtypes. In addition, it is important to obtain structures in the absence of a nanobody that may influence the structure. Here, we present a model for a rhodopsin-G protein complex derived from intermolecular distance constraints between the activated receptor and the inhibitory G protein, Gi, using electron paramagnetic resonance spectroscopy and spin-labeling methodologies. Molecular dynamics simulations demonstrated the overall stability of the modeled complex. In the rhodopsin-Gi complex, Gi engages rhodopsin in a manner distinct from previous GPCR-Gs structures, providing insight into specificity determinants

Treatment and outcomes in necrotising autoimmune myopathy: an australian perspective

Necrotising Autoimmune Myopathy (NAM) presents as a subacute proximal myopathy with high creatine kinase levels. It is associated with statin exposure, 3-hydroxy-3-methylglutaryl-CoA reductase (HMGCR) antibody, connective tissue diseases, signal recognition particle (SRP) antibody and malignancy. This case series presents our Western Australian NAM patient cohort: comparing the subgroup presentations, biopsy appearance and treatment outcomes. We retrospectively collected data on patients diagnosed with NAM at the Western Australian Neuroscience Research Institute between the years 2000 and 2015. We identified 20 patients with Necrotising Autoimmune Myopathy: 14 with anti-HMGCR antibodies; two with anti-SRP antibodies; three with connective tissue disease; two as yet unspecified. Median creatine kinase level was 6047units/L (range 1000–17000). The statin naïve patients with HMGCR antibodies and patients with SRP antibodies were the most severely affected subgroups, with higher creatine kinase levels, and were more resistant to immunotherapy. Two or more immunotherapy agents were required in 90%; eight patients required IVIG and rituximab. Steroid weaning commonly precipitated relapses. Four patients had complete remission, and the remaining patients still require immunotherapy. Necrotising Autoimmune Myopathy is a potentially treatable myopathy, which can be precipitated by statin therapy and requires early, aggressive immunotherapy, usually requiring multiple steroid sparing agents for successful steroid weaning