Large-scale 3-D modeling by integration of resistivity models and borehole data through inversion

We present an automatic method for parameterization of a 3-D model of the subsurface, integrating lithological information from boreholes with resistivity models through an inverse optimization, with the objective of further detailing of geological models, or as direct input into groundwater models. The parameter of interest is the clay fraction, expressed as the relative length of clay units in a depth interval. The clay fraction is obtained from lithological logs and the clay fraction from the resistivity is obtained by establishing a simple petrophysical relationship, a translator function, between resistivity and the clay fraction. Through inversion we use the lithological data and the resistivity data to determine the optimum spatially distributed translator function. Applying the translator function we get a 3-D clay fraction model, which holds information from the resistivity data set and the borehole data set in one variable. Finally, we use k-means clustering to generate a 3-D model of the subsurface structures. We apply the procedure to the Norsminde survey in Denmark, integrating approximately 700 boreholes and more than 100 000 resistivity models from an airborne survey in the parameterization of the 3-D model covering 156 km2. The final five-cluster 3-D model differentiates between clay materials and different high-resistivity materials from information held in the resistivity model and borehole observations, respectively

An automated method to build groundwater model hydrostratigraphy from airborne electromagnetic data and lithological borehole logs

Abstract. Large-scale integrated hydrological models are important decision support tools in water resources management. The largest source of uncertainty in such models is the hydrostratigraphic model. Geometry and configuration of hydrogeological units are often poorly determined from hydrogeological data alone. Due to sparse sampling in space, lithological borehole logs may overlook structures that are important for groundwater flow at larger scales. Good spatial coverage along with high spatial resolution makes airborne time-domain electromagnetic (AEM) data valuable for the structural input to large-scale groundwater models. We present a novel method to automatically integrate large AEM data-sets and lithological information into large-scale hydrological models. Clay-fraction maps are produced by translating geophysical resistivity into clay-fraction values using lithological borehole information. Voxel models of electrical resistivity and clay fraction are classified into hydrostratigraphic zones using k-means clustering. Hydraulic conductivity values of the zones are estimated by hydrological calibration using hydraulic head and stream discharge observations. The method is applied to a Danish case study. Benchmarking hydrological performance by comparison of simulated hydrological state variables, the cluster model performed competitively. Calibrations of 11 hydrostratigraphic cluster models with 1–11 hydraulic conductivity zones showed improved hydrological performance with increasing number of clusters. Beyond the 5-cluster model hydrological performance did not improve. Due to reproducibility and possibility of method standardization and automation, we believe that hydrostratigraphic model generation with the proposed method has important prospects for groundwater models used in water resources management.</jats:p

Biosensor Integration Development ExMC/Canadian Space Agency Collaboration

In support of the NASA Human Research Program Exploration Medical Capability (ExMC) Element, NASA Ames Research Center (ARC) established a collaborative effort with the Canadian Space Agency (CSA). The collaboration focuses on leveraging CSA capability in the areas of biosensors and decision support that will augment future development of such components for Exploration Missions. The CSA advancement of biosensors enables NASA to focus on the integration and data management associated with these types of components through the system currently under development by the Medical Data Architecture (MDA) project. This approach has enabled the establishment of a successful collaborative working relationship between ExMC and CSA.Applying lessons learned from the fiscal year 2016 (FY16) Human Exploration Research Analog (HERA) campaign, CSA and NASA ARC developed a solution to provide real-time feedback to researchers who monitor the collection of vital signs data from a wearable Astroskin garment. The advances in the interfaces included the development of an iPad application (by CSA) to wirelessly forward the vital signs data to the MDA system, which collected the vital signs data through a receiver developed by NASA ARC. The development of these interfaces aims to provide communications between the Astroskin and the MDA system such that data may be seamlessly collected, stored and retrieved by the MDA. The first steps towards this goal were demonstrated in FY16. In FY17, ExMC will complete the first in a series of test beds that establishes a system to automate collection and management of vital sign data from the Astroskin, and other sources of data, to provide information for a crewmember to make medical decisions. In addition, the MDA Test Bed 1 will enable CSA to evaluate and optimize biosensor advancement and facilitate decision support algorithm development

Magma-driven, high-grade metamorphism in the Sveconorwegian Province, southwest Norway, during the terminal stages of Fennoscandian Shield evolution

Recently it has been argued that the Sveconorwegian orogeny in southwest Fennoscandia comprised a series of accretionary events between 1140 and 920 Ma, behind a long-lived, active continental margin characterized by voluminous magmatism and high-grade metamorphism. Voluminous magnesian granitic magmatism is recorded between 1070 and 1010 Ma (Sirdal Magmatic Belt, SMB), with an apparent drop in activity ca. 1010-1000 Ma. Granitic magmatism resumed ca. 1000-990 Ma, but with more ferroan (A type) compositions (hornblende-biotite granites). This ferroan granitic magmatism was continuous until 920 Ma, and included emplacement of an AMCG (anorthosite-mangerite-charnockite-granite) complex (Rogaland Igneous Complex). Mafic rocks with ages corresponding to the spatially associated granites suggest that heat from underplated mafic magma was the main driving force for lower crustal melting and long-lived granitic magmatism. The change from magnesian to ferroan compositions may reflect an increasingly depleted and dehydrated lower crustal source. High-grade metamorphic rocks more than ~20 km away from the Rogaland Igneous Complex yield metamorphic ages of 1070-1015 Ma, corresponding to SMB magmatism, whereas similar rocks closer to the Rogaland Igneous Complex yield ages between 1100 and 920 Ma, with an apparent age peak ca. 1000 Ma. Ti-in-zircon temperatures from these rocks increase from ~760 to 820 °C ca. 970 Ma, well before the inferred emplacement age of the Rogaland Igneous Complex (930 Ma), suggesting that long-lived, high-grade metamorphism was not directly linked to the emplacement of the latter, but rather to the same mafic underplating that was driving lower crustal melting. Structural data suggest that the present-day regional distribution of high- and low-grade rocks reflects late-stage orogenic doming

Constructible motivic functions and motivic integration

We introduce a direct image formalism for constructible motivic functions. One deduces a very general version of motivic integration for which a change of variables theorem is proved. These constructions are generalized to the relative framework, in which we develop a relative version of motivic integration. These results have been announced in math.AG/0403349 and math.AG/0403350. Main results and statements unchanged. Many minor slips corrected and some details added.Comment: Final versio

Medical Data Architecture Project Status

The Medical Data Architecture (MDA) project supports the Exploration Medical Capability (ExMC) risk to minimize or reduce the risk of adverse health outcomes and decrements in performance due to in-flight medical capabilities on human exploration missions. To mitigate this risk, the ExMC MDA project addresses the technical limitations identified in ExMC Gap Med 07: We do not have the capability to comprehensively process medically-relevant information to support medical operations during exploration missions. This gap identifies that the current in-flight medical data management includes a combination of data collection and distribution methods that are minimally integrated with on-board medical devices and systems. Furthermore, there are a variety of data sources and methods of data collection. For an exploration mission, the seamless management of such data will enable a more medically autonomous crew than the current paradigm. The medical system requirements are being developed in parallel with the exploration mission architecture and vehicle design. ExMC has recognized that in order to make informed decisions about a medical data architecture framework, current methods for medical data management must not only be understood, but an architecture must also be identified that provides the crew with actionable insight to medical conditions. This medical data architecture will provide the necessary functionality to address the challenges of executing a self-contained medical system that approaches crew health care delivery without assistance from ground support. Hence, the products supported by current prototype development will directly inform exploration medical system requirements

Personalized practice dosages may improve motor learning in older adults compared to standard of care practice dosages: A randomized controlled trial

Standard dosages of motor practice in clinical physical rehabilitation are insufficient to optimize motor learning, particularly for older patients who often learn at a slower rate than younger patients. Personalized practice dosing (i.e., practicing a task to or beyond one\u27s plateau in performance) may provide a clinically feasible method for determining a dose of practice that is both standardized and individualized, and may improve motor learning. The purpose of this study was to investigate whether personalized practice dosages

Psychoimmunological effects of dioscorea in ovariectomized rats: role of anxiety level

<p>Abstract</p> <p>Background</p> <p>Anxiety levels in rats are correlated with interleukin-2 (IL-2) levels in the brain. The aim of the present study was to investigate the effects of dioscorea (wild yam), a Chinese medicine, on emotional behavior and IL-2 levels in the brain of ovariectomized (OVX) rats.</p> <p>Methods</p> <p>One month after ovariectomy, female Wistar rats were screened in the elevated plus-maze (EPM) test to measure anxiety levels and divided into low anxiety (LA) and high anxiety (HA) groups, which were then given dioscorea (250, 750, or 1500 mg/kg/day) by oral gavage for 27 days and were tested in the EPM on day 23 of administration and in the forced swim test (FST) on days 24 and 25, then 3 days later, the brain was removed and IL-2 levels measured.</p> <p>Results</p> <p>Compared to sham-operated rats, anxiety behavior in the EPM was increased in half of the OVX rats. After chronic dioscorea treatment, a decrease in anxiety and IL-2 levels was observed in the HA OVX rats. Despair behavior in the FST was inhibited by the highest dosage of dioscorea.</p> <p>Conclusion</p> <p>These results show that OVX-induced anxiety and changes in neuroimmunological function in the cortex are reversed by dioscorea treatment. Furthermore, individual differences need to be taken into account when psychoneuroimmunological issues are measured and the EPM is a useful tool for determining anxiety levels when examining anxiety-related issues.</p