RT_BUILD: An expert programmer for implementing and simulating Ada real-time control software

The RT BUILD is an expert control system programmer that creates real-time Ada code from block-diagram descriptions of control systems. Since RT BUILD embodies substantial knowledge about the implementation of real-time control systems, it can perform many, if not most of the functions normally performed by human real-time programmers. Though much basic research was done in automatic programming, RT BUILD appears to be the first application of this research to an important problem in flight control system development. In particular, RT BUILD was designed to directly increase productivity and reliability for control implementations of large complex systems

Discharge rate of cryogens in microgravity - What ground based experimentation cannot resolve

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/76407/1/AIAA-1991-3545-390.pd

Transient cryogenic liquid discharge in normal and micro-gravity

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/76393/1/AIAA-1991-486-786.pd

High serum osteopontin levels are associated with prevalent fractures and worse lipid profile in post-menopausal women with type 2 diabetes

Purpose: Patients with type 2 diabetes (T2DM) have increased fracture risk. Osteopontin (OPN) is a protein involved in bone remodeling and inflammation. The aim of this study was to evaluate the association of OPN with fracture prevalence and with metabolic parameters in post-menopausal women with T2DM. Methods: Sixty-four post-menopausal women with T2DM (age 67.0 ± 7.8 years, diabetes duration 8.9 ± 6.7 years), enrolled in a previous study, were followed up (3.6 ± 0.9 years). Previous fragility fractures were recorded. The FRAX score (without BMD) was calculated and biochemical parameters (plasma glucose, HbA1c, lipid profile and renal function) were assessed. Serum 25OH-vitamin D, calcium, PTH and OPN were evaluated at baseline. The association between OPN and fracture prevalence at baseline was evaluated by a logistic model. Results: OPN levels were higher in patients with previous fractures (n.25) than in patients without previous fractures at baseline (n.39) (p = 0.006). The odds of having fractures at baseline increased by 6.7 (1.9–31.4, 95% CI, p = 0.007) for each increase of 1 ng/ml in OPN levels, after adjustment for vitamin D and HbA1c levels. Fracture incidence was 4.7%. Higher OPN associated with a decrease in HDL-cholesterol (p = 0.048), after adjustment for age, basal HDL-cholesterol, basal and follow-up HbA1c and follow-up duration. 25OH-vitamin D associated with an increase in FRAX-estimated probability of hip fracture at follow-up (p = 0.029), after adjustment for age, 25OH-vitamin D and time. Conclusions: In post-menopausal women with T2DM, OPN might be a useful marker of fracture and worse lipid profile

Bayesian inference of hydraulic properties in and around a white fir using a process-based ecohydrologic model

We present a parameter estimation study of the Soil-Tree-Atmosphere Continuum (STAC) model, a process-based model that simulates water flow through an individual tree and its surrounding root zone. Parameters are estimated to optimize the model fit to observations of sap flux, stem water potential, and soil water storage made for a white fir (Abies concolor) in the Sierra Nevada, California. Bayesian inference is applied with a likelihood function that considers temporal correlation of the model errors. Key vegetation properties are estimated, such as the tree\u27s root distribution, tolerance to drought, and hydraulic conductivity and retention functions. We find the model parameters are relatively non-identifiable when considering just soil water storage. Overall, by utilizing multiple processes (e.g. sap flow, stem water potential, and soil water storage) during the parameter estimation, we find the simulations of the soil and tree water properties to be more accurate when compared to observed data

Tumor type M2-pyruvate-kinase levels in pleural fluid versus plasma in cancer patients: a further tool to define the need for invasive procedures

Pleural effusion is a common diagnostic problem and a challenge to the thoracic surgeon. The analysis of serum and body fluids for tumor markers is an established diagnostic procedure. Among various markers, tumors are linked to the overexpression of a glycolytic isoenzyme, M2-pyruvate-kinase (M2-PK). This preliminary study evaluated this enzyme as a tumor marker to differentiate malignant from benign pleural effusion

Optimising oceanic rainfall estimates for increased lead time of stream level forecasting: A case study of GPM IMERG estimates application in the UK

Among the three main rainfall data sources (rain gauge stations, rainfall radar stations and weather satellites), satellites are often the most appropriate for longer lead times in real-time flood forecasting [1]. This is particularly relevant in the UK, where severe rainfall events often originate over the Atlantic Ocean, distant from land-based instruments although it can also limit the effectiveness of satellite data for long-term predictions [2]. The Global Precipitation Measurement (GPM) Integrated Multi-satellitE Retrievals for GPM (IMERG) estimates can be used as an alternative source for rainfall information in real-time flood forecasting models. However, the challenge lies in monitoring the vast oceanic region around the UK and integrating this extensive data into hydrological or data-driven models, which presents computational and time constraints. Identifying key monitoring area for obtaining these estimates is essential to address these challenges and to effectively use this use for water level forecasting in urban drainage systems (UDS). This study introduced an optimised data-driven model for streamline the collection and use of GPM IMERG rainfall estimates for water level forecasting in UDS. The model’s effectiveness was demonstrated using a 20-year satellite data set from the Atlantic Ocean, west of the UK, focusing on water level forecasting for a specific UDS point in London. This data helped identify the most probable path of rainfall from the Atlantic that impacts UDS water levels. We conducted a cross-correlation analysis between the water level records and each IMERG data pixel within the selected oceanic area. The analysis successfully pinpointed the most influential rainfall points/pixels along the Atlantic path and their respective lag times between rainfall occurrence and water level changes at any satellite-monitored point until it reaches the mainland and joins the river system. This research enhances understanding of long-distance rainfall patterns while optimising the use of GPM IMERG data. It also aids in reducing data volume and processing time for stream-level forecasting models, aiming for longer lead times.Peer reviewe