MERRA/AS: The MERRA Analytic Services Project Interim Report

MERRA AS is a cyberinfrastructure resource that will combine iRODS-based Climate Data Server (CDS) capabilities with Coudera MapReduce to serve MERRA analytic products, store the MERRA reanalysis data collection in an HDFS to enable parallel, high-performance, storage-side data reductions, manage storage-side driver, mapper, reducer code sets and realized objects for users, and provide a library of commonly used spatiotemporal operations that can be composed to enable higher-order analyses

Boolean Dynamics with Random Couplings

This paper reviews a class of generic dissipative dynamical systems called N-K models. In these models, the dynamics of N elements, defined as Boolean variables, develop step by step, clocked by a discrete time variable. Each of the N Boolean elements at a given time is given a value which depends upon K elements in the previous time step. We review the work of many authors on the behavior of the models, looking particularly at the structure and lengths of their cycles, the sizes of their basins of attraction, and the flow of information through the systems. In the limit of infinite N, there is a phase transition between a chaotic and an ordered phase, with a critical phase in between. We argue that the behavior of this system depends significantly on the topology of the network connections. If the elements are placed upon a lattice with dimension d, the system shows correlations related to the standard percolation or directed percolation phase transition on such a lattice. On the other hand, a very different behavior is seen in the Kauffman net in which all spins are equally likely to be coupled to a given spin. In this situation, coupling loops are mostly suppressed, and the behavior of the system is much more like that of a mean field theory. We also describe possible applications of the models to, for example, genetic networks, cell differentiation, evolution, democracy in social systems and neural networks.Comment: 69 pages, 16 figures, Submitted to Springer Applied Mathematical Sciences Serie

Smart Aerospace eCommerce: Using Intelligent Agents in a NASA Mission Services Ordering Application

This paper describes how intelligent agent technology was successfully prototyped and then deployed in a smart eCommerce application for NASA. An intelligent software agent called the Intelligent Service Validation Agent (ISVA) was added to an existing web-based ordering application to validate complex orders for spacecraft mission services. This integration of intelligent agent technology with conventional web technology satisfies an immediate NASA need to reduce manual order processing costs. The ISVA agent checks orders for completeness, consistency, and correctness, and notifies users of detected problems. ISVA uses NASA business rules and a knowledge base of NASA services, and is implemented using the Java Expert System Shell (Jess), a fast rule-based inference engine. The paper discusses the design of the agent and knowledge base, and the prototyping and deployment approach. It also discusses future directions and other applications, and discusses lessons-learned that may help other projects make their aerospace eCommerce applications smarter

Association of free androgen index and sex hormone–binding globulin and left ventricular hypertrophy in postmenopausal hypertensive women

The aim of the present study was to explore the relationship between androgen and LVH in postmenopausal hypertensive women. Enrolled in this study were 378 postmenopausal hypertensive women who were admitted to the department of cardiology between December 2018 and December 2020. According to left ventricular mass index (LVMI) evaluated by echocardiography, the patients were divided into LVH group (n = 172) and non‐LVH group (n = 206). Their clinical characteristics were collected. Based on the result of propensity score matching analysis, 160 cases in each group were matched successfully. After correcting for confounding factors by various models, the results showed that free androgen index (FAI) and sex hormone–binding globulin (SHBG) were the influencing factors of LVH in postmenopausal women with hypertension. Patients with elevated SHBG were 5% less likely to develop LVH than those without elevated SHBG (OR: 0.950, 95% CI 0.922‐1.578). Postmenopausal hypertensive patients with elevated FAI were 16% more likely to have LVH than those without elevated FAI (OR: 1.608, 95% CI 0.807‐3.202). Multiple linear regression showed that LVMI increased by 61.82g/m(2) for every 1 unit increase in FAI. In addition, SHBG decreased by 1 nmol/l, and LVMI increased by 0.177g/m(2). Subgroup analysis showed that patients in the controlled BP group had a lower risk of LVH for every additional unit of SHBG compared with the uncontrolled BP group. The risk of LVH for each additional unit of FAI in the uncontrolled BP group was higher than that in the controlled BP group. The results of this present study showed that the occurrence of LVH was positively correlated with FAI and negatively correlated with SHBG in postmenopausal women with hypertension. The increase in FAI level and the decrease in SHBG level may be related to the occurrence and development of LVH in postmenopausal hypertension