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At least 199 records · Page 11

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NASA NTRS1989

Metal matrix composite micromechanics: In-situ behavior influence on composite properties

Recent efforts in computational mechanics methods for simulating the nonlinear behavior of metal matrix composites have culminated in the implementation of the Metal Matrix Composite Analyzer (METCAN) computer code. In METCAN material nonlinearity is treated at the constituent (fiber, matrix, and interphase) level where the current material model describes a time-temperature-stress dependency of the constituent properties in a material behavior space. The composite properties are synthesized from the constituent instantaneous properties by virtue of composite micromechanics and macromechanics models. The behavior of metal matrix composites depends on fabrication process variables, in situ fiber and matrix properties, bonding between the fiber and matrix, and/or the properties of an interphase between the fiber and matrix. Specifically, the influence of in situ matrix strength and the interphase degradation on the unidirectional composite stress-strain behavior is examined. These types of studies provide insight into micromechanical behavior that may be helpful in resolving discrepancies between experimentally observed composite behavior and predicted response.

Murthy, P. L. N.↗

NASA NTRS1988

Accelerated fatigue crack growth behavior of PWA 1480

An investigation of the fatigue crack growth (FCG) behavior of PWA 1480 single crystal nickel base superalloy was conducted. Typical Paris region behavior was observed above a delta K of 8 MPa sq rt of m. However, below that stress intensity range, the alloy exhibited highly unusual behavior. This behavior consisted of a region where the crack growth rate became essentially independent of the applied stress intensity. The transition in the FCG behavior was related to a change in the observed crack growth mechanisms. In the Paris region, fatigue failure occurred along (111) facets; however, at the lower stress intensities, (001) fatigue failure was observed. A mechanism was proposed, based on barriers to dislocation motion, to explain the changes in the observed FCG behavior. The FCG data were also evaluated in terms of a recently proposed stress intensity parameter, K sub rss. This parameter, based on the resolved shear stresses on the slip planes, quantified the crack driving force as well as the mode I delta K, and at the same time was also able to predict the microscopic crack path under different stress states.

Telesman, Jack↗

NASA NTRS1998

Behavior and Performance Project

Behavior is an overt manifestation of underlying biology. As such, alterations in biological systems that result from spaceflight would be expected to evidence themselves in subtle or even pronounced changes in the behavior of that organism. These alterations in visible behavior may then indicate or even be diagnostic of alterations in the physical well-being of humans and other animals as they adapt to space environments or readapt to Earth--alterations that might not otherwise be detected without relatively invasive and frequently expensive procedures. Moreover, behavior and performance constitute the central standard for evaluating the mission success of spaceflight ventures. The success or failure of any excursion into space is primarily indexed by the ability of astronauts and cosmonauts to perform the tasks and experiments of any particular mission, to land a re-entry vehicle after extended exposure to microgravity (as with the space shuttle), or to make time-critical and life-saving repairs or other decisions while in orbit (as with the recent Mir events). Thus, understanding the effects spaceflight on behavior and performance is inherently important, in addition to those insights that behavior can provide about the physiological consequences of space adaptation.

Washburn, David A.↗

NASA NTRS2014

Comprehension of Spacecraft Telemetry Using Hierarchical Specifications of Behavior

A key challenge in operating remote spacecraft is that ground operators must rely on the limited visibility available through spacecraft telemetry in order to assess spacecraft health and operational status. We describe a tool for processing spacecraft telemetry that allows ground operators to impose structure on received telemetry in order to achieve a better comprehension of system state. A key element of our approach is the design of a domain-specific language that allows operators to express models of expected system behavior using partial specifications. The language allows behavior specifications with data fields, similar to other recent runtime verification systems. What is notable about our approach is the ability to develop hierarchical specifications of behavior. The language is implemented as an internal DSL in the Scala programming language that synthesizes rules from patterns of specification behavior. The rules are automatically applied to received telemetry and the inferred behaviors are available to ground operators using a visualization interface that makes it easier to understand and track spacecraft state. We describe initial results from applying our tool to telemetry received from the Curiosity rover currently roving the surface of Mars, where the visualizations are being used to trend subsystem behaviors, in order to identify potential problems before they happen. However, the technology is completely general and can be applied to any system that generates telemetry such as event logs.

Runtime monitoring↗

NASA NTRS2017

Experimental Constraints on the Partitioning Behavior of F, Cl, and OH Between Apatite and Basaltic Melt

The mineral apatite is present in a wide range of planetary materials. The presence of volatiles (F, Cl, and OH) within its crystal structure (X-site) have motivated numerous studies to investigate the partitioning behavior of F, Cl, and OH between apatite and silicate melt with the end goal of using apatite to constrain the volatile contents of planetary magmas and mantle sources. A number of recent experimental studies have investigated the apatite-melt partitioning behavior of F, Cl, and OH in magmatic systems. Apatite-melt partitioning of volatiles are best described as exchange equilibria similar to Fe-Mg partitioning between olivine and silicate melt. However, the partitioning behavior is likely to change as a function of temperature, pressure, oxygen fugacity, apatite composition, and melt composition. In the present study, we have conducted experiments to assess the partitioning behavior of F, Cl, and OH between apatite and silicate melt over a pressure range of 0-6 gigapascals, a temperature range of 950-1500 degrees Centigrade, and a wide range of apatite ternary compositions. All of the experiments were conducted between iron-wustite oxidation potentials IW minus 1 and IW plus 2 in a basaltic melt composition. The experimental run products were analyzed by a combination of electron probe microanalysis and secondary ion mass spectrometry (NanoSIMS). Temperature, apatite crystal chemistry, and pressure all play important roles in the partitioning behavior of F, Cl, and OH between apatite and silicate melt. In portions of apatite ternary space that undergo ideal mixing of F, Cl, and OH, exchange coefficients remain constant at constant temperature and pressure. However, exchange coefficients vary at constant temperature (T) and pressure (P) in portions of apatite compositional space where F, Cl, and OH do not mix ideally in apatite. The variation in exchange coefficients exhibited by apatite that does not undergo ideal mixing far exceeds the variations induced by changes in temperature (T) or pressure (P) . In regions where apatite undergoes ideal mixing of F, Cl, and OH, temperature has a stronger effect than pressure on the partitioning behavior, but both are important. Furthermore, fluorine becomes less compatible in apatite with increasing pressure and temperature. We are still in the process of analyzing our experimental run products, but we plan to quantify the effects of P and T on apatite-melt partitioning of F, Cl, and OH.

McCubbin, Francis M.↗

NASA NTRS2017

Informing Rodent Behavior in Space: Gene Expression and Hyper-Emotionality Following Prenatal Stress

As space exploration pushes our boundaries further away from Earth and for longer durations, we will inevitably require the use of multi-generational studies to continue our expansion. Space is a stressful environment not only due to the deleterious effect of spaceflight on physiology, but also due to confinement, limited social interactions, inherently dangerous circumstances, and many other stresses of an unknown environment. Stress can alter the brain chemistry, and these alterations can affect behavior at all stages of development, but it is especially pronounced during the perinatal period and can have longstanding effects, even into adulthood, which manifest through augmented brain function and psychopathology. This study investigated the nexus of brain chemistry and brain function by observing behavior of adult rats whose mothers were exposed to unpredictable variable prenatal stress (UVPS) while they were in the womb. The UVPS consisted of strobe light, tube restraint, and white noise, and was administered at unpredictable times of the day and also varied in length, both of which were measures taken to prevent habituation to the stressor. The offspring rats were then allowed to reach adulthood and at 90 days were subjected to a series of behavioral tests including novel object, startle response, and an unknown intruder to quantify the adult rats stress response and anxiety. Here we report these results of the behavioral analysis and correlate adult behavioral measures with the expression of genes involved in the hypothalamic-pituitary-adrenal axis, which modulates the animals stress response. We hypothesized that hyper-expression of genes involved in the HPA axis would correlate with the observed anxiety-like behaviors associated with early stress.

Moyer, E. L.↗

NASA NTRS2018

The Use of MERRA-2 Near Surface Meteorology to Understand the Behavior of Planetary Boundary Layer Heights Derived from Wind Profiler Data over the US Great Plains

The atmospheric general circulation model (GCM) that underlies the MERRA-2 reanalysis includes a suite of physical parameterizations that describe the processes that occur in the planetary boundary layer (PBL). The data assimilation system assures that the atmospheric state variables used as input to these parameterizations are constrained to the best fit to all of the available observations. Many studies, however, have shown that the GCM-based estimates of MERRA-2 PBL heights are biased high, and so are not reliable for boundary layer studies.A 20-year record of PBL heights was derived from Wind Profiler (WP) backscatter data measured at a wide network of stations throughout the US Great Plains and has been validated against independent estimates. The behavior of these PBL heights shows geographical and temporal variations that are difficult to attribute to particular physical processes without additional information that are not part of the observational record.In the present study, we use information on physical processes from MERRA-2 to understand the behavior of the WP derived PBL heights. The behavior of the annual cycle of both MERRA-2 and WP PBL heights shows four classes of behavior: (i) canonical, characterized by a monthly progression in PBL height that follows the solar insolation, (ii) double peak, characterized by canonical behavior that is interrupted by a minimum in July, (iii) late peak, characterized by a suppressed heights in May and June, and return to canonical in July and August, and (iv) early peak where the PBL height rises with solar insolation but is suppressed later in the summer. The explanation for these behaviors and the relationship to local precipitation, temperature, sensible and latent heat fluxes, net radiation and aerosol load is articulated using information from MERRA-2.

Salmun, Haydee↗

NASA NTRSDate not supplied

Behavioral consequences of low dose radiation and sex differences in MCAT mouse model

Our study used 1-year old C57BL/6NJ male and female mice (astronaut-relevant age) that underwent exposure to 0.5 gray of gamma radiation and were euthanized 12 weeks after. In this study, we used an MCAT mouse model for mitochondrial ROS quenching, which overexpress human catalase. MCAT mice were shown to live longer and age better. Hence, in this study we determined whether quenching ROS in the mitochondria will mitigate the adverse effects of ionizing radiation exposure on spaceflight-relevant tissues. As part of the analysis, we have completed 5 different behavioral tests which focus on memory, physical stance, stress, anxiety, and other mission relevant behaviors. In the Neuro-score battery, performed after both 1and 8 weeks post IR we saw that all female groups had significantly higher scores compared to males. When comparing the baseline vs 8 weeks of radiation, we saw that all the male groups (including the sham) had lower neuro-score, pointing out to aging effect in addition to IR. In the female groups only the female IR group had lower neuro-score and the MCAT group was protected from this effect. In the Nestlet building test we saw similarly that only females were affected by radiation, having lower scores and this effect was mitigated in the MCAT animals as well. In the Catwalk test we saw that females were faster, had higher swing speed and stride length in all four paws. Males had higher stand, step cycle and max contact area. Aging is associated with slowing of gait speed, swing speed and shortening of stride length which we see in males, this is consistent with physical appearance where males look markedly older. In the Light-Dark Box test we saw that females were more frequently present in the light side and altered zones more frequently, pointing out to a more exploratory and less anxious pattern of behavior. Similarly, to what was detected in the Nest building and Neuro-score test, in the Barnes maze test, during the acquisition phase (learning) we saw that IR affected more the females who did not do better in the maze after 4 days. On the other hand, during the probe phase of the test (spatial memory) the females visited the target hole and the box quadrant more often, but also had more errors vs males, which points out to possible serial escape vs spatial escape strategy. Overall, we see that older females look physically better are faster and perform better almost in all behavioral tests compared to their male counterparts. On the other hand, they are more sensitive to low dose radiation in many cases, in some cases this effect was mitigated in the MCAT model pointing out to the importance of ROS in these stressors. In the near future we will focus on corelating these behavioral tests with molecular findings such as for example brain IHC, plasma and hippocampal cytokines in order to find specific biomarkers for behavioral deficits.

radiation↗

DOE OSTI2020

On-the fly scheduling of execution of dynamic hardware behaviors

Methods for dynamically executing computer code across multiple disparate processing unit architectures are disclosed. During execution of a first portion of computer code on a first processing unit, it is determined that a first dynamic hardware behavior of a plurality of dynamic hardware behaviors will occur at a subsequent point in time, based on a second dynamic hardware behavior that is occurring. The methods include determining to execute code corresponding to the first dynamic hardware behavior on a second processing unit, rather than the first processing unit, and scheduling computer program code corresponding to the first dynamic hardware behavior to execute on the second processing unit rather than the first processing unit. Upon completion of execution of the computer code corresponding to the first dynamic hardware behavior, a remaining portion of the computer code is scheduled to execute on the first processing unit.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2025

Data-driven modeling of dynamic occupant thermostat override behavior for demand response applications

Buildings consume nearly 40% of global energy and produce similar emissions. Whiletechnological advances address efficiency, occupant behavior causes energy use variations up to 300% between identical buildings. This gap between predicted and actual building performance impacts building design, operations, and grid demand management programs. Through analyses of smart thermostat data from 1,400 single-occupant homes, the researchdemonstrates that occupants respond to 8°F thermostat setpoint changes within a median of 15 minutes, while 2°F changes trigger responses within a median of 30 minutes. This highlights an understudied temporal relationship between thermostat setbacks and response time of occupant behaviors. Models of such behavior dynamics are required to incorporate occupant impacts into building performance simulation. A key contribution of this dissertation is the Thermal Frustration Theory (TFT), which positsthat thermal discomfort driven behaviors are caused by the time-accumulation of discomfort, not simply a temperature deviation threshold or a delay from an initiating event. Using a dataset of 634 thermostats, each with 25+ manual setpoint changes, a comparative analysis of TFT and comfort zone and a delayed response theories demonstrated that personalized TFT models better predict when manual setpoint change occur. This was measured by the area under the curve statistical measure (AUC); all three models perform similarly by a Matthews Correlation Coefficient measure. Higher AUC performance is especially important for modeling occupant behavior in demand response programs where false negatives of rare occupant interactions could adversely affect grid stability. EnergyPlus based simulations were conducted with TFT-derived occupant models, demonstrating the ability to identify parameters of known TFT models from only data observable with smart thermostats, even under the presence of noise from routine overrides. Overall, the dissertation highlights that thermostat interactions are neither static,instantaneous, nor driven solely by the environment. Instead, temporal accumulation of discomfort and routine-based behavior play important roles. The methodology and results offer a pathway towards more accurate modeling of human-building interactions for policy assessment, building design, and demand response programs.

Sharma, Kunind [Northeastern University] (ORCID:00↗

DOE OSTI2023

Evaluation of the critical behavior near ferromagnetic to paramagnetic phase transition in CrTe 1-x Se x alloys: An experimental study

For this study, we used the conventional solid-state reaction method to prepare stoichiometric samples of CrTe 1-x Se x , where 0 ≤ x ≤ 0.10, and investigated the structural and critical behavior of the prepared samples. Room temperature powder X-ray diffraction, along with Rietveld refinement, revealed the emergence of the NiAs structure with P6 3 /mmc (194) space group with increasing Se substitution. The high-temperature linear fit to inverse of the dc-susceptibility versus temperature for the mother sample resulted in an effective moment of 3.65μ B Cr with Curie-Weiss temperature near 335K, which is slightly higher than the Tc of ~332K obtained from the inflection point of magnetization versus temperature. Magnetization isotherms were employed to investigate the critical behavior of ferromagnetic CrTe 1-x Se x with 0.0 ≤ x ≤ 0.10 near their Curie temperatures (Tc). The magnetic behavior near Tc was found to follow 3D mean-field critical exponents with a second-order phase transition in all samples investigated. We fine-tuned the critical exponents (β, γ, and δ) using a combination of an iteration technique, the Kouvel-Fisher method, and modified Arrott plots. All samples follow a mean field behavior, with Tc ranging from 298 to 340K. The acquired values exhibit self-consistency, as indicated by the results from the Widom scaling relation. Furthermore, the magnetization isotherms exhibit a universal scaling behavior, providing additional credence to the calculated critical exponents.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2025

Microstructure-sensitive mechanical behavior of an additively manufactured psuedoelastic shape memory alloy

The additive manufacturing of shape memory alloys into complex geometries enables fabrication of advanced functional systems across a variety of fields and domains. This work presents results focused on the mechanical behavior of additively manufactured shape memory pseudoelastic NiTi. The deformation induced solid state phase transformation from austenite to martensite allows this system to accommodate large recoverable strains. This deformation behavior is fundamentally driven by crystal-scale transformation physics. Laser powder bed fusion processing reveals that the resulting microstructure, both grain morphology and crystallographic texture, is strongly dependent on the manufacturing processing history. Exhaustive mechanical testing demonstrates that these microstructural factors strongly impact both tensile and cyclic stress–strain behavior. Cyclic dissipative behavior, however, is similar across all tested microstructures following an initial transient period. Remarkably, analysis of spatial strain fields during tensile loading reveals two distinctly different localization “modes”. The first is initiation of localized deformation bands which continuously propagate through the tensile bar during loading. In the second mode localization is observed but lacks propagation; instead additional localization cites nucleate during subsequent loading. The latter phenomena is suspected to be driven by grain-scale deformation physics as the localized band morphologies coincide with grain morphologies. These phenomena strongly impact the resulting aggregate stress–strain behavior. Hence, manufacturers and designers of psuedoelastic functional components must at the very least consider the potential variability in properties when considering additive manufacturing processing. More ideally the process–structure–property relations can be used to further tailor and optimize final functional performance.

Additive manufacturing↗

DOE OSTI2022

Residential Demand Flexibility: Modeling Occupant Behavior using Sociodemographic Predictors

Demand flexibility (DF) has the potential to increase the saturation of renewables in the grid and reduce operating costs for both utilities and customers. However, less than 8% of U.S. residential electric customers are enrolled in DF programs. A major research gap on this topic is an uneven understanding of behavioral drivers of electricity use and DF program participation at the household level. In this study, we employ machine learning models to predict residential occupant behavior in activities relevant to DF. We model occupants' extensive decisions (i.e., choice of action) and intensive behaviors (i.e., amount of time spent) during peak and off-peak time periods using the publicly available American Time Use Survey, which includes activities data for approximately 200,000 respondents. In our machine learning models, predictions for both extensive and intensive behavior fell within a +/-20% error margin at the aggregate level. We identify 13 key sociodemographic predictors of DF-related intensive behavior using LASSO inference and beta coefficient ranking. However, these top predictors differ by activity, suggesting potential scope for differential user targeting for DF events and technologies during program design. This work also contributes to understanding when and who might adopt these DF technologies based on their daily routine activities.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2023

Bridging adsorption behavior of confined CH 4 -CO 2 binary mixtures across scales

An accurate understanding of the competitive adsorption of CH 4 -CO 2 binary mixtures in nano-confined systems is critical for engineering CO 2 storage in shale gas reservoirs. Due to difficulties in making reliable experimental observations in nano-scale, atomistic simulations (ASs), such as the Grand Canonical Monte Carlo (GCMC) method, provide a viable approach to studying the adsorption behavior of confined fluids. ASs are, however, limited in the size of the compositional domain due to the high computational cost. This work proposes a framework that combines AS and the lattice Boltzmann (LB) method to bridge the physics of confined fluids across scales. The Peng–Robinson equation of state (PR-EoS) produces fugacity coefficients, which serve as input for conducting multi-component GCMC simulations. These GCMC simulations explore the competitive adsorption behavior of CH 4 -CO 2 in nano-slits at various composition, pressure, and channel-width conditions. Both components generate adsorption layers with high densities near the walls with CO 2 preferentially adsorbing compared to CH 4 on the organic walls of carbon sheets. At the mesoscale, a pseudopotential model represents the intermolecular forces in multi-component, multiple-relaxation-time LB simulations. The LB simulations are in good agreement with the GCMC results, allowing us to obtain values for tunable LB parameters. We then extend the use of LB to simulate adsorption behavior in complex networks with nano-sized channels. The phase behavior and fluid properties in the complex geometries of nano-channels differ from nano-slits and bulk systems. Furthermore, the bridging of physics from GCMC (microscale) to LB (mesoscale) via the macroscale PR-EoS connects the adsorption behavior of binary systems across scales.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2021

Past agricultural land use affects multiple facets of ungulate antipredator behavior

Antipredator behavior affects prey fitness, prey demography, and the strength of ecological interactions. Although predator-prey interactions increasingly occur in habitats that experience multiple forms of human-generated disturbance, it is unclear how different forms of disturbance might affect antipredator behavior. Fire is a contemporary disturbance that has dramatic effects on terrestrial habitats. Such habitats may have also experienced past disturbances, like agricultural land use, that leave lasting legacies on habitat structure (e.g., overstory and understory composition). It is unclear how these past and present disturbances affect the use of different antipredator behaviors, like temporal avoidance and vigilance. We examined whether variation in disturbance regimes generates differences in ungulate antipredator behavior by using cameras to measure white-tailed deer vigilance and activity time across 24 longleaf pine woodlands that vary in past land use and contemporary fire regime. Regardless of land-use history, woodlands with high fire frequencies had 4 times less vegetation cover than low-fire woodlands, generating riskier habitats for deer; however, deer responded to fire with different antipredator strategies depending on land-use history. In nonagricultural woodlands, fire affected deer activity time such that activity was nocturnal in low-fire woodlands and crepuscular in high-fire woodlands. In post-agricultural woodlands, fire affected vigilance and not activity time such that deer were more vigilant in high-fire woodlands than in low-fire woodlands. Furthermore, these results suggest that ungulate antipredator behavior may vary spatially depending on past land use and contemporary fire regime, and such disturbances may generate “landscapes of fear” that persist for decades after agricultural use.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2024

Promoting Sustainable Transportation Modes: A Systematic Review of Behavior-Change Strategies

In previous studies, many travel-behavior-change strategies often relied on single behavior determinants or psychological theories, overlooking the incorporation of sociopsychological theories for guidance in their design. Integrating these theories could offer consistent guidance for program developers and enhance intervention effectiveness. This paper systematically reviews interventions targeting travel-behavior change, with a focus on self-determination theory and its principles of satisfying individuals’ competence, autonomy, and relatedness needs for enacting change. Additionally, experiment design methods, including randomized controlled trials and quasi-experimental designs, are reviewed and discussed. Key findings highlight the effectiveness of personalized interventions and integrating feedback with goal-setting strategies. Given the limited direct references to sociopsychological theories in existing studies, we explore relevant sociopsychological theories applicable to travel-behavior-change programs to provide examples of how strategies could be designed based on them. This review contributes valuable insights into the development of strategies for changing travel behavior, offering a theoretical framework for researchers and practitioners to guide intervention design, experimentation, and evaluation. In conclusion, leveraging these theories not only facilitates reproducibility but also provides a standardized approach for transportation demand management program developers.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2020

Empirical Study of Effect of Dynamic Travel Time Information on Driver Route Choice Behavior

The objective of this paper is to study the effect of travel time information on day-to-day driver route choice behavior. A real-world experimental study is designed to have participants repeatedly choose between two alternative routes for five origin-destination pairs over multiple days after providing them with dynamically updated travel time information (average travel time and travel time variability). The results demonstrate that historical travel time information enhances behavioral rationality by 10% on average and reduces inertial tendencies to increase risk seeking in the gain domain. Furthermore, expected travel time information is demonstrated to be more effective than travel time variability information in enhancing rational behavior when drivers have limited experiences. After drivers gain sufficient knowledge of routes, however, the difference in behavior associated with the two information types becomes insignificant. The results also demonstrate that, when drivers lack experience, the faster less reliable route is more attractive than the slower more reliable route. However, with cumulative experiences, drivers become more willing to take the more reliable route given that they are reluctant to become risk seekers once experience is gained. Furthermore, the effect of information on driver behavior differs significantly by participant and trip, which is, to a large extent, dependent on personal traits and trip characteristics.

99 GENERAL AND MISCELLANEOUS↗

NASA NTRS2004

Heavy particle irradiation, neurochemistry and behavior: thresholds, dose-response curves and recovery of function

Exposure to heavy particles can affect the functioning of the central nervous system (CNS), particularly the dopaminergic system. In turn, the radiation-induced disruption of dopaminergic function affects a variety of behaviors that are dependent upon the integrity of this system, including motor behavior (upper body strength), amphetamine (dopamine)-mediated taste aversion learning, and operant conditioning (fixed-ratio bar pressing). Although the relationships between heavy particle irradiation and the effects of exposure depend, to some extent, upon the specific behavioral or neurochemical endpoint under consideration, a review of the available research leads to the hypothesis that the endpoints mediated by the CNS have certain characteristics in common. These include: (1) a threshold, below which there is no apparent effect; (2) the lack of a dose-response relationship, or an extremely steep dose-response curve, depending on the particular endpoint; and (3) the absence of recovery of function, such that the heavy particle-induced behavioral and neural changes are present when tested up to one year following exposure. The current report reviews the data relevant to the degree to which these characteristics are common to neurochemical and behavioral endpoints that are mediated by the effects of exposure to heavy particles on CNS activity. c2004 COSPAR. Published by Elsevier Ltd. All rights reserved.

Review↗