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At least 343 records · Page 19

Crew Health and Performance Improvements with Reduced Carbon Dioxide Levels and the Resource Impact to Accomplish Those Reductions

Carbon dioxide (CO2) removal is one of the primary functions of the International Space Station (ISS) atmosphere revitalization systems. Primary CO2 removal is via the ISS s two Carbon Dioxide Removal Assemblies (CDRAs) and the Russian carbon dioxide removal assembly (Vozdukh); both of these systems are regenerable, meaning that their CO2 removal capacity theoretically remains constant as long as the system is operating. Contingency CO2 removal capability is provided by lithium hydroxide (LiOH) canisters, which are consumable, meaning that their CO2 removal capability disappears once the resource is used. With the advent of 6 crew ISS operations, experience showing that CDRA failures are not uncommon, and anecdotal association of crew symptoms with CO2 values just above 4 mmHg, the question arises: How much lower do we keep CO2 levels to minimize the risk to crew health and performance, and what will the operational cost to the CDRAs be to do it? The primary crew health concerns center on the interaction of increased intracranial pressure from fluid shifts and the increased intracranial blood flow induced by CO2. Typical acute symptoms include headache, minor visual disturbances, and subtle behavioral changes. The historical database of CO2 exposures since the beginning of ISS operations has been compared to the incidence of crew symptoms reported in private medical conferences. We have used this database in an attempt to establish an association between the CO2 levels and the risk of crew symptoms. This comparison will answer the question of the level needed to protect the crew from acute effects. As for the second part of the question, operation of the ISS s regenerable CO2 removal capability reduces the limited life of constituent parts. It also consumes limited electrical power and thermal control resources. Operation of consumable CO2 removal capability (LiOH) uses finite consumable materials, which must be replenished in the long term. Therefore, increased CO2 removal means increased resource use, with increased logistical capability to maintain necessary resources on board ISS. We must strike a balance between sufficiently low CO2 levels to maintain crew health and CO2 levels which are operationally feasible for the ISS program

James, John T.↗

Oxidative Stress and the Neuroconsequences of Spaceflight Environment - Immune Dysregulation and Antioxidant Dietary Countermeasure Efficacy

In this project, we will test the hypothesis that Ionizing Radiation (IR), microgravity and social isolation combine synergistically to trigger an oxidative stress response that alters immune homeostasis, brain structure and function, and neurobehavioral and cognitive performance. Specific Aims for this project are: (1) Determine dose-response curves for acute ‘Five-Ion GCR Simulation’ exposure for immune, brain and performance responses in crew age-matched adult male and female mice; (2) Determine effects of acute ‘Five-Ion GCR Simulation’ exposure singly and in combination with simulated microgravity and social isolation, on immune, brain and performance responses in crew age-matched male and female mice mimicking deep space missions; and (3) Determine efficacy of the dietary antioxidant, Nicotinamide Mononucleotide (NMN), a key intermediate in nicotinamide adenine dinucleotide (NAD+) biosynthesis. The project relies on established and highly translatable ground-based mouse models and assays with IR exposures to be performed at the NASA Space Radiation Laboratory (NSRL). The experimental approach will provide definitive data on the timing and mechanisms involved in the oxidative stress response, immune and brain changes, and ensuing functional (behavioral/cognitive) impairments expected during human transit to Mars. This project will identify potential biomarkers for, and mechanisms underlying, structural and functional changes in the immune and nervous systems leading to behavioral/cognitive performance deficits, and its potential application to develop effective countermeasures to mitigate negative health effects of long duration space habitation. The project will address NASA’s efforts to rapidly advance the characterization of risks and identify appropriate countermeasures in anticipation of future deep space missions. Ensuring crew health and performance during extended transits necessitates that sensorimotor and cognitive abilities remain strong to avoid potentially catastrophic health and safety outcomes. Further, despite historically low numbers of female astronauts, the two most recent NASA Astronaut Corps class selections, comprised of ~50% women as compared to men, signal the need to understand how sex differences affect physiological adaptation and health in the space environment. Here, we will determine how key features of the deep space environment may interact to increase risk to crewmembers by negatively impacting health and performance, and identify and develop strategies to characterize and mitigate the potential risks via countermeasures. Supported by the NASA Human Research Program (HRP) Human Factors Behavioral Performance Element Grant 18-18FLAG_2-0028.

radiation↗

Utilization of Machine Learning Techniques for Managing the Tracking and Data Relay Satellite Constellation

National Aeronautics and Space Administration’s (NASA) Goddard Space Flight Center (GSFC) operates a constellation of ten geosynchronous Tracking and Data Relay Satellites (TDRS). The TDRS constellation consists of multiple geosynchronous communication relay satellites located around the equator so they can provide continual coverage of any mission in low earth orbit. The TDRS are located primarily in three oceanic regions around the earth. NASA’s White Sands Complex provides the ground communication support for TDRS located over the Atlantic and Pacific Oceans. Another TDRS ground station in Guam supports the TDRS over the Indian Ocean. With these satellites the TDRS network can provide continuous coverage of satellites in low-earth orbit. The NASA Space Network (SN) project office at GSFC manages the constellation of spacecraft. Major customers of the TDRS constellation include, but are not limited to, the International Space Station and the Hubble Space Telescope. The TDRS constellation has three generations of satellites and has been active for over 30 years providing reliable communication links between customer satellites and corresponding ground stations. However, one of the major concerns for TDRS, and in any space mission, is to ensure the health and safety of the spacecraft. Generally, engineers use telemetry data to monitor and analyze the performance and state of health of the spacecraft. Telemetry data contains hundreds of parameters that monitor each important component in the spacecraft, which can be utilized to recognize and characterize the behavior of the spacecraft. Each parameter contains considerable information to represent time-dependent properties of each spacecraft subsystem and component. During the entire life of a TDRS spacecraft, thousands of gigabytes of telemetry data are transmitted in real-time from the spacecraft to the ground station at the White Sands Complex in Las Cruces, New Mexico, and recorded as historical data sets for engineers to process and analyze the events that occurred on-orbit. These parameters contain the function of multiple spacecraft subsystems, such as the attitude control system (ACS), Thermal, Electrical Power Subsystem (EPS), etc. . The first and second generations have exceeded their required lifetime and NASA is keen to manage these spacecrafts carefully in order to maximize the remaining life using the spacecraft telemetry. The challenge is to know when the risk of losing a spacecraft in geosynchronous orbit exceeds the benefit of continued operations for customer support. In the TDRS fleet, the EPS is the most critical subsystem related to spacecraft operations. Failure of the EPS would strand a spacecraft in geosynchronous orbit. Since EPS provides power to the spacecraft, component failures ultimately lead to the inability to support the spacecraft loads and the communications payload. For instance, TDRS-8 has several anomalies in EPS including the Bus Voltage Limiter (BVL) shunt current, solar array loss of circuits, and failed battery cells. Any of these anomalies can cause critical issues to the spacecraft. Therefore, developing a system to analyze and perform early detection of a potential anomaly is an important issue in telemetry data analysis. In recent years, Telemetry Mining (TM) has been proposed to process telemetry data by using Data Mining (DM) techniques such as classification, clustering, regression and anomaly detection. Anomaly detection, also known as outlier detection, has been widely used in many data mining areas such as remote sensing, medical data processing and digital image processing. The goal of anomaly detection is to detect abnormal data, which contains a relatively low probability of occurrence among the entire data set. Early detection of anomalies is one of the most significant issues in managing the spacecraft configuration. If anomalies can be detected early enough, then the redundant resources can be used to extend the life of the operational spacecraft. We present an unsupervised anomaly detection method to process the EPS data extracted from TDRS-8. This is different from traditional analytical methods, which use telemetry data to illustrate behavior and physical meaning of each spacecraft component. TM connects multiple parameters as a vector and then conducts data analysis on this high dimension telemetry vector. This method is looking at the properties of a high dimensional vector that is able to consider the relationship between different parameters in the anomaly detection problem. This kind of method performs much better than the traditional limit checking method. In addition, we propose a new approach of real-time anomaly detection to process telemetry data in real-time, which can then be applied to spacecraft monitoring with high reliability, low cost and high accuracy.

Machine Learning (ML)↗

Research activities at the Loma Linda University and Proton Treatment Facility--an overview

The Loma Linda University (LLU) Radiobiology Program coordinates basic research and proton beam service activities for the university and extramural communities. The current focus of the program is on the biological and physical properties of protons and the operation of radiobiology facilities for NASA-sponsored projects. The current accelerator, supporting facilities and operations are described along with a brief review of extramural research projects supported by the program. These include space craft electronic parts and shielding testing as well as tumorigenesis and animal behavior experiments. An overview of research projects currently underway at LLU is also described. These include: 1) acute responses of the C57Bl/6 mouse immune system, 2) modulation of gene expression in the nematode C. elegans and rat thyroid cells, 3) quantitation of dose tolerance in rat CNS microvasculature, 4) behavioral screening of whole body proton and iron ion-irradiated C57Bl/6 mice, and 5) investigation of the role of cell integration into epithelial structures on responses to radiation.

Non-NASA Center↗

Integrated Systems Health Management for Space Exploration

Integrated Systems Health Management (ISHM) is a system engineering discipline that addresses the design, development, operation, and lifecycle management of components, subsystems, vehicles, and other operational systems with the purpose of maintaining nominal system behavior and function and assuring mission safety and effectiveness under off-nominal conditions. NASA missions are often conducted in extreme, unfamiliar environments of space, using unique experimental spacecraft. In these environments, off-nominal conditions can develop with the potential to rapidly escalate into mission- or life-threatening situations. Further, the high visibility of NASA missions means they are always characterized by extraordinary attention to safety. ISHM is a critical element of risk mitigation, mission safety, and mission assurance for exploration. ISHM enables: In-space maintenance and repair; a) Autonomous (and automated) launch abort and crew escape capability; b) Efficient testing and checkout of ground and flight systems; c) Monitoring and trending of ground and flight system operations and performance; d) Enhanced situational awareness and control for ground personnel and crew; e) Vehicle autonomy (self-sufficiency) in responding to off-nominal conditions during long-duration and distant exploration missions; f) In-space maintenance and repair; and g) Efficient ground processing of reusable systems. ISHM concepts and technologies may be applied to any complex engineered system such as transportation systems, orbital or planetary habitats, observatories, command and control systems, life support systems, safety-critical software, and even the health of flight crews. As an overarching design and operational principle implemented at the system-of-systems level, ISHM holds substantial promise in terms of affordability, safety, reliability, and effectiveness of space exploration missions.

Uckun, Serdar↗

INDUCTIVE SYSTEM HEALTH MONITORING WITH STATISTICAL METRICS

Model-based reasoning is a powerful method for performing system monitoring and diagnosis. Building models for model-based reasoning is often a difficult and time consuming process. The Inductive Monitoring System (IMS) software was developed to provide a technique to automatically produce health monitoring knowledge bases for systems that are either difficult to model (simulate) with a computer or which require computer models that are too complex to use for real time monitoring. IMS processes nominal data sets collected either directly from the system or from simulations to build a knowledge base that can be used to detect anomalous behavior in the system. Machine learning and data mining techniques are used to characterize typical system behavior by extracting general classes of nominal data from archived data sets. In particular, a clustering algorithm forms groups of nominal values for sets of related parameters. This establishes constraints on those parameter values that should hold during nominal operation. During monitoring, IMS provides a statistically weighted measure of the deviation of current system behavior from the established normal baseline. If the deviation increases beyond the expected level, an anomaly is suspected, prompting further investigation by an operator or automated system. IMS has shown potential to be an effective, low cost technique to produce system monitoring capability for a variety of applications. We describe the training and system health monitoring techniques of IMS. We also present the application of IMS to a data set from the Space Shuttle Columbia STS-107 flight. IMS was able to detect an anomaly in the launch telemetry shortly after a foam impact damaged Columbia's thermal protection system.

Iverson, David L.↗

Risk of Adverse Cognitive or Behavioral Conditions and Psychiatric Disorders

The NASA commitment to human space flight includes continuing to fly astronauts on the ISS until it is decommissioned as well as possibly returning astronauts to the moon or having astronauts venture to an asteroid or Mars. As missions leave low Earth orbit and explore deeper space, BHP supports and conducts research to enable a risk posture that considers the risk of adverse cognitive or behavioral conditions and psychiatric disorders “acceptable given mitigations,” for pre-, in, and post-flight.The Human System Risk Board (HSRB) determines the risk of various mission scenarios using a likelihood (per person per year) by consequences matrix examining those risks across two categories—long term health and operational (within mission). Colors from a stoplight signal are used by HSRB and quickly provide a means of assessing overall perceived risk for a particular mission scenario. Risk associated with the current six month missions on the ISS are classified as “accepted with monitoring” while planetary missions, such as a mission to Mars, are recognized to be a “red” risk that requires mitigation to ensure mission success.Currently, the HSRB deems that the risk of adverse cognitive or behavioral conditions and psychiatric outcomes requires mitigation for planetary missions owing to long duration isolation and radiation exposure (see Table 1). While limited research evidence exists from spaceflight, it is well known anecdotally that the shift from the two week shuttle missions to the six month ISS missions renders the psychological stressors of space as more salient over longer duration missions. Shuttle astronauts were expected just to tolerate any stressors that arose during their mission and were successful at doing so (Whitmire et al, 2013). While it is possible to deal with stressors such as social isolation and to live with incompatible crewmembers for two weeks on shuttle, “ignoring it” is much less likely to be a successful coping mechanism on station. For the longer missions of the ISS, astronauts require a larger, more robust set of coping skills and more psychological support. Evidence of this are the number of BHP’s Operational Psychology (Op Psy) staff who have been awarded silver Snoopys by long duration astronauts†, in the statements of praise for the Op Psy and Family Support Office teams, and in the written and oral statements from flown astronauts regarding difficulty of longer missions and how much Op Psy helped.

Slack, Kelley J.↗

Deciphering the Effects of Microgravity Cell by Cell

Forces generated by gravity have a profound impact on the behavior of cells in tissues affecting the course of the cell cycle and differentiation fate of progenitors in mammalian tissues. These cells are contributing to normal tissue regenerative health and defence against disease. In Human space exploration context, it is extremely important to determine spaceflight provoked changes in tissue's regenerational capabilities. Microgravity experienced during spaceflight causes unloading and mechanical disuse on all orthostatic support tissues, therefore impacting stem cell fate and lineage commitment decisions. Investigating how ESCs respond to mechanical stimulation is a platform for fundamental developmental and regeneration research applicable for spaceflight. However, the gene expression programs associatiated with early committment stem cell pathways in response to physical stimulation are not readily known. Single-cell RNA-seq technologies have recently revolutionized the world of molecular biology by providing the capability to assess gene expression pattern within a single cell. Our method isolates and separately barcodes mRNAs from thousands of single cells and sequences their expressomes. Understanding regenerative processes on a molecular level would not only help reduce long-term spaceflight impact on health, but also may enable the development of novel tissue regenerative approaches to tissue degeneration on Earth.

Single cell sequencing↗

Health Monitoring and Prognostics in Li-ion Batteries

Space applications need to overcome a very critical challenge of predicting remaining useful life of its critical systems/subsystems, with batteries being one of them. Batteries, power electronics conditioning system and motors and one of the most critical systems. Similarly in case of electric aircrafts, computing remaining flying time is safety-critical, since an aircraft that runs out of power (battery charge) while in the air will eventually lose control leading to catastrophe. To tackle and solve the prediction problem, it is essential to have awareness of the current state and health of the system, especially since it is necessary to perform condition-based predictions. To be able to accurately predict the future state of any system, it is required to possess knowledge of its current and future operations. Given models of the current and future system behavior, the general approach of model-based prognostics can be employed as a solution to the prior stated prediction problem. Two approaches are presented with battery prognostics application. The first approach presentation covers a physics based-modeling approach implemented for battery prognostics. Given models of the current and future system behavior, a general approach of model-based prognostics can be employed as a solution to the prediction problem and further for decision making. A second hybrid framework for fusing information from physics-based performance models along with deep learning algorithms for prognostics of complex safety critical systems i.e. batteries is presented. In this framework, physics-based performance models infer unobservable model parameters related to the system's components health solving a calibration problem in the deep learning approach.

Batteries↗

Health Monitoring and Prognostics in Li-ion Batteries

Space applications need to overcome a very critical challenge of predicting remaining useful life of its critical systems/subsystems, with batteries being one of them. Batteries, power electronics conditioning system and motors and one of the most critical systems. Similarly in case of electric aircrafts, computing remaining flying time is safety-critical, since an aircraft that runs out of power (battery charge) while in the air will eventually lose control leading to catastrophe. To tackle and solve the prediction problem, it is essential to have awareness of the current state and health of the system, especially since it is necessary to perform condition-based predictions. To be able to accurately predict the future state of any system, it is required to possess knowledge of its current and future operations. Given models of the current and future system behavior, the general approach of model-based prognostics can be employed as a solution to the prior stated prediction problem. Two approaches are presented with battery prognostics application. The first approach presentation covers a physics based-modeling approach implemented for battery prognostics. Given models of the current and future system behavior, a general approach of model-based prognostics can be employed as a solution to the prediction problem and further for decision making. A second hybrid framework for fusing information from physics-based performance models along with deep learning algorithms for prognostics of complex safety critical systems i.e. batteries is presented. In this framework, physics-based performance models infer unobservable model parameters related to the system's components health solving a calibration problem in the deep learning approach.

Battery Prognostics↗

Electronic Health Management

Accelerated aging methodologies for electrolytic components have been designed and accelerated aging experiments have been carried out. The methodology is based on imposing electrical and/or thermal overstresses via electrical power cycling in order to mimic the real world operation behavior. Data are collected in-situ and offline in order to periodically characterize the devices' electrical performance as it ages. The data generated through these experiments are meant to provide capability for the validation of prognostic algorithms (both model-based and data-driven). Furthermore, the data allow validation of physics-based and empirical based degradation models for this type of capacitor. A first set of models and algorithms has been designed and tested on the data.

Celaya, Jose R.↗

Physics in NASA Exploration

The primary focus of the workshop was NASA's new concentration on sending crewed missions to the Moon by 2020, and then on to Mars and beyond. Several speakers, including JPL s Fred O Callaghan and NASA's Mark Lee, broached the problem that there is now a serious reduction of capability to perform experiments in the ISS, or to fly significant mass in microgravity by other means. By 2010, the shuttle fleet will be discontinued and Russian craft will provide the only access to the ISS. O Callaghan stated that the Fundamental Physics budget is being reduced by 70%. LTMPF and LCAP are slated for termination. However, ground-based experiments are continuing to be funded at present, and it will be possible to compete for $80-90 million in new money from the Human Research Initiative (HRI). The new program thrust is for exploration, not fundamental physics. Fundamental, we were told by Lee, does not ring well in Washington these days. Investigators were advised to consider how their work can benefit missions to the Moon and Mars. Work such as that regarding atomic clocks is looked upon with favor, for example, because it is considered important to navigation and planetary GPS. Mark Lee stressed that physicists must convey to NASA senior management that they are able and willing to contribute to the new exploration research programs. The new mentality must be we deliver products, not do research. This program needs to be able to say that it is doing at least 50% exploration-related research. JPL s Ulf Israelsson discussed the implications to OBPR, which will deliver methods and technology to assure human health and performance in extraterrestrial settings. The enterprise will provide advanced life-support systems and technology that are reliable, capable, simpler, less massive, smaller, and energy-efficient, and it may offer other necessary expertise in areas such as low-gravity behavior. Like Dr. Lee, he stated that the focus must be on products, not research. While there is not yet a formal direction, he said, LTMPF and PARCS ISS flight projects are slated to terminate in October 2004. All flight investigations are being returned to ground programs and phased out by the end of FY07. Physics ground programs are intact for now, but to survive we must shift about 50% of research to supporting exploration. Basic research programs in other disciplines are being cancelled. Product lines will support human health, safety and life-support, including countermeasures against radiation and other hazards, as well as advances in time-keeping, navigation and communications technologies. Israelsson said that the new Fundamental Physics for Exploration Roadmap points to how fundamental physics research can and does support exploration. JPL will use the roadmap to argue for support for fundamental physics research under several codes. Nicholas Bigelow of the University of Rochester encouraged attendees not to become discouraged, but rather to embrace the opportunities presented by NASA's new direction.

O'Callaghan, Fred↗

Cygnus X-1: A Case for a Magnetic Accretion Disk?

With the advent of Rossi X-ray Timing Explorer (RXTE), which is capable of broad spectral coverage and fast timing, as well as other instruments which are increasingly being used in multi-wavelength campaigns (via both space-based and ground-based observations), we must demand more of our theoretical models. No current model mimics all facets of a system as complex as an x-ray binary. However, a modern theory should qualitatively reproduce - or at the very least not fundamentally disagree with - all of Cygnus X-l's most basic average properties: energy spectrum (viewed within a broader framework of black hole candidate spectral behavior), power spectrum (PSD), and time delays and coherence between variability in different energy bands. Below we discuss each of these basic properties in turn, and we assess the health of one of the currently popular theories: Comptonization of photons from a cold disk. We find that the data pose substantial challenges for this theory, as well as all other in currently discussed models.

Nowak, Michael A.↗

Accelerated Aging with Electrical Overstress and Prognostics for Power MOSFETs

Power electronics play an increasingly important role in energy applications as part of their power converter circuits. Understanding the behavior of these devices, especially their failure modes as they age with nominal usage or sudden fault development is critical in ensuring efficiency. In this paper, a prognostics based health management of power MOSFETs undergoing accelerated aging through electrical overstress at the gate area is presented. Details of the accelerated aging methodology, modeling of the degradation process of the device and prognostics algorithm for prediction of the future state of health of the device are presented. Experiments with multiple devices demonstrate the performance of the model and the prognostics algorithm as well as the scope of application. Index Terms Power MOSFET, accelerated aging, prognostics

Saha, Sankalita↗

Cognitive deficits induced by 56Fe radiation exposure

Exposing rats to particles of high energy and charge (e.g., 56Fe) disrupts neuronal systems and the behaviors mediated by them; these adverse behavioral and neuronal effects are similar to those seen in aged animals. Because cognition declines with age, and our previous study showed that radiation disrupted Morris water maze spatial learning and memory performance, the present study used an 8-arm radial maze (RAM) to further test the cognitive behavioral consequences of radiation exposure. Control rats or rats exposed to whole-body irradiation with 1.0 Gy of 1 GeV/n high-energy 56Fe particles (delivered at the alternating gradient synchrotron at Brookhaven National Laboratory) were tested nine months following exposure. Radiation adversely affected RAM performance, and the changes seen parallel those of aging. Irradiated animals entered baited arms during the first 4 choices significantly less than did controls, produced their first error sooner, and also tended to make more errors as measured by re-entries into non-baited arms. These results show that irradiation with high-energy particles produces age-like decrements in cognitive behavior that may impair the ability of astronauts to perform critical tasks during long-term space travel beyond the magnetosphere. Published by Elsevier Science Ltd on behalf of COSPAR.

Non-NASA Center↗

Prognostics and Health Monitoring in Li-Ion Batteries and Capacitors Using Physics-Based Modeling Approach

In order to tackle and solve the prediction problem of the lifetime of Li-ion batteries, it is essential to have awareness of the current state and health of the battery pack. To be able to accurately predict the future state of any system, one must possess knowledge of its current and future operations. Using derived models of the current and future system behavior, a model-based prognostics approach can be implemented as a solution to the prediction problem. As more and more autonomous electric vehicles progressively emerge in our daily life, a very critical challenge lies in accurate prediction of remaining useful life of the systems/subsystems. Batteries, power electronics conditioning systems, and motors are integrated to form the powertrain in electric vehicles; one of the most critical systems. In the case of electric aircrafts, computing remaining flying time is critical for safety, since an aircraft that runs out of power (battery charge) while in the air will eventually lose control leading to catastropheThis presentation covers a physics-based modeling approach implemented for case studies in capacitor and battery prognostics which are an integral part of an electrical powertrain system. The general approach of model-based prognostics will be examined as a potential solution for safety critical problems related to battery state of charge and state of health.

Physics based modeling↗

SAMZ: Satellite-Derived Management Zones

The term "satellite-derived management zones" (SAMZ) denotes agricultural management zones that are subdivisions of large fields and that are derived from images of the fields acquired by instruments aboard Earth orbiting satellites during approximately the past 15 years. "SAMZ" also denotes the methodology and the software that implements the methodology for creating such zones. The SAMZ approach is one of several products of continuing efforts to realize a concept of precision agriculture, which involves optimal variations in seeding, in application of chemicals, and in irrigation, plus decisions to farm or not to farm certain portions of fields, all in an effort to maximize profitability in view of spatial and temporal variations in the growth and health of crops and in the chemical and physical conditions of soils. As used here, "management zone" signifies, more precisely, a subdivision of a field within which the crop production behavior is regarded as homogeneous. From the perspective of precision agriculture, management zones are the smallest subdivisions between which the seeding, application of chemicals, and other management parameters are to be varied. In the SAMZ approach, the main sources of data are the archives of satellite imagery that have been collected over the years for diverse purposes. One of the main advantages afforded by the SAMZ approach is that the data in these archives can be reused for purposes of precision agriculture at low cost. De facto, these archives contain information on all sources of variability within a field, including weather, crop types, crop management, soil types, and water drainage patterns. The SAMZ methodology involves the establishment of a Web-based interface based on an algorithm that generates management zones automatically and quickly from archival satellite image data in response to requests from farmers. A farmer can make a request by either uploading data describing a field boundary to the Web site or else drawing the boundary on a reference image. Hence, a farmer can start to engage in precision farming shortly after gaining access to the Web site, without need for incurring the high costs of conventional precision-agriculture data-collection practices that include collecting soil samples, mapping electrical conductivity of soil, and compiling multi-year crop-yield data. Given the boundary of a field, a SAMZ server computes the zones within the field in a three-stage process. In the first stage, a vector-valued image of the field is constructed by assembling, from the archives, the equivalent of a stack of the available images of the field (see figure). In the second stage, the vector-valued image is analyzed by use of a wavelet transform that detects spatial variations considered significant for precision farming while suppressing small-scale heterogeneities that are regarded as insignificant. In the third stage, a segmentation algorithm assembles the zones from smaller regions that have been identified in the wavelet analysis.

Source record↗

Effects of exposure to 56Fe particles on the acquisition of a conditioned place preference in rats

Exposure to low doses of 56Fe particles produces changes in neural function and behavior. The present experiments were designed to examine the effects of irradiation on the acquisition of a dopamine-mediated conditioned place preference (CPP). In the CPP procedure, rats are given an injection of the dopamine agonist amphetamine in one distinctive compartment and a saline injection in a different compartment of a three-compartment apparatus. Control rats develop a preference for the amphetamine-paired compartment. In contrast, rats exposed to 1 Gy of 56Fe particles fail to develop a similar preference. The results of the experiment indicate that exposure to low doses of heavy particles can disrupt the neural mechanisms that mediate the reinforcement of behavior.

Non-NASA Center↗