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Incremental exposure facilitates adaptation to sensory rearrangement

Visual-target pointing experiments were performed on 24 adult volunteers in order to compare the relative effectiveness of incremental (stepwise) and single-step exposure conditions on adaptation to visual rearrangement. The differences between the preexposure and postexposure scores served as an index of the adaptation elicited during the exposure period. It is found that both single-step and stepwise exposure to visual rearrangement elicit compensatory changes in sensorimotor coordination. However, stepwise exposure, when compared to single-step exposur in terms of the average magnitude of visual displacement over the exposure period, clearly enhances the rate of adaptation. It seems possible that the enhancement of adaptation to unusual patterns of sensory stimulation produced by incremental exposure reflects a general principle of sensorimotor function.

Lackner, J. R.↗

FAIRness and Usability for Open-access Omics Data Systems

Omics data sharing is crucial to the biological research community, and the last decade or two has seen a huge rise in collaborative analysis systems, databases, and knowledge bases for omics and other systems biology data. We assessed the "FAIRness" of NASA's GeneLab Data Systems (GLDS) along with four similar kinds of systems in the research omics data domain, using 14 FAIRness metrics. The range of overall FAIRness scores was 6-12 (out of 14), average 10.1, and standard deviation 2.4. The range of Pass ratings for the metrics was 29-79%, Partial Pass 0-21%, and Fail 7-50%. The systems we evaluated performed the best in the areas of data findability and accessibility, and worst in the area of data interoperability. Reusability of metadata, in particular, was frequently not well supported. We relate our experiences implementing semantic integration of omics data from some of the assessed systems for federated querying and retrieval functions, given their shortcomings in data interoperability. Finally, we propose two new principles that Big Data system developers, in particular, should consider for maximizing data accessibility.

Berrios, Daniel C.↗

FAIRness and Usability for Open-access Omics Data Systems

Omics data sharing is crucial to the biological research community, and the last decade or two has seen a huge rise in collaborative analysis systems, databases, and knowledge bases for omics and other systems biology data. We assessed the “FAIRness” of NASA’s GeneLab Data Systems (GLDS) along with four similar kinds of systems in the research omics data domain, using 14 FAIRness metrics. The range of overall FAIRness scores was 6-12 (out of 14), average 10.1, and standard deviation 2.4. The range of Pass ratings for the metrics was 29-79%, Partial Pass 0-21%, and Fail 7-50%. The systems we evaluated performed the best in the areas of data findability and accessibility, and worst in the area of data interoperability. Reusability of metadata, in particular, was frequently not well supported. We relate our experiences implementing semantic integration of omics data from some of the assessed systems for federated querying and retrieval functions, given their shortcomings in data interoperability. Finally, we propose two new principles that Big Data system developers, in particular, should consider for maximizing data accessibility.

Berrios, Daniel C.↗

Heart Rhythm Monitoring in the Constellation Lunar and Launch/Landing EVA Suit: Recommendations from an Expert Panel

Currently there are several physiological monitoring requirements for Extravehicular Activity (EVA) in the Human-Systems Interface Requirements (HSIR) document, including continuous heart rhythm monitoring. However, it is not known whether heart rhythm monitoring in the lunar surface space suit is a necessary capability for lunar surface operations or in launch/landing suit the event of a cabin depressurization enroute to or from the moon. Methods: Current US astronaut corps demographic information was provided to an expert panel of cardiovascular medicine experts, including specialists in electrophysiology, exercise physiology, interventional cardiology and arrhythmia. This information included averages for male/female age, body mass index (BMI), blood pressure, cholesterol, inflammatory markers, echocardiogram, ranges for coronary artery calcium (CAC) scores for long duration astronauts, and ranges for heart rate (HR) and metabolic (MET) rates obtained during microgravity and lunar EVA. Results: The panel determined that no uncontrolled hazard was likely to occur in the suit during lunar surface or contingency microgravity ops that would require ECG monitoring in the highly screened US astronaut population. However having the capability for rhythm monitoring inside the vehicle (IVA) was considered critical to manage an astronaut in distress. Discussion: Heart rate (HR) monitoring alone allows effective monitoring of astronaut health and function. Consequently, electrocardiographic (ECG) monitoring capability as a clinical tool is not essential in the lunar or launch/landing space suit. However, the panel considered that rhythm monitoring could be useful in certain clinical situations, it was not considered required for safe operations. Also, lunar vehicles should be required to have ECG monitoring capability with a minimum of 5-lead ECG (derived 12- lead) for IVA medical assessments.

Scheuring, Richard A.↗

Understanding software faults and their role in software reliability modeling

This study is a direct result of an on-going project to model the reliability of a large real-time control avionics system. In previous modeling efforts with this system, hardware reliability models were applied in modeling the reliability behavior of this system. In an attempt to enhance the performance of the adapted reliability models, certain software attributes were introduced in these models to control for differences between programs and also sequential executions of the same program. As the basic nature of the software attributes that affect software reliability become better understood in the modeling process, this information begins to have important implications on the software development process. A significant problem arises when raw attribute measures are to be used in statistical models as predictors, for example, of measures of software quality. This is because many of the metrics are highly correlated. Consider the two attributes: lines of code, LOC, and number of program statements, Stmts. In this case, it is quite obvious that a program with a high value of LOC probably will also have a relatively high value of Stmts. In the case of low level languages, such as assembly language programs, there might be a one-to-one relationship between the statement count and the lines of code. When there is a complete absence of linear relationship among the metrics, they are said to be orthogonal or uncorrelated. Usually the lack of orthogonality is not serious enough to affect a statistical analysis. However, for the purposes of some statistical analysis such as multiple regression, the software metrics are so strongly interrelated that the regression results may be ambiguous and possibly even misleading. Typically, it is difficult to estimate the unique effects of individual software metrics in the regression equation. The estimated values of the coefficients are very sensitive to slight changes in the data and to the addition or deletion of variables in the regression equation. Since most of the existing metrics have common elements and are linear combinations of these common elements, it seems reasonable to investigate the structure of the underlying common factors or components that make up the raw metrics. The technique we have chosen to use to explore this structure is a procedure called principal components analysis. Principal components analysis is a decomposition technique that may be used to detect and analyze collinearity in software metrics. When confronted with a large number of metrics measuring a single construct, it may be desirable to represent the set by some smaller number of variables that convey all, or most, of the information in the original set. Principal components are linear transformations of a set of random variables that summarize the information contained in the variables. The transformations are chosen so that the first component accounts for the maximal amount of variation of the measures of any possible linear transform; the second component accounts for the maximal amount of residual variation; and so on. The principal components are constructed so that they represent transformed scores on dimensions that are orthogonal. Through the use of principal components analysis, it is possible to have a set of highly related software attributes mapped into a small number of uncorrelated attribute domains. This definitively solves the problem of multi-collinearity in subsequent regression analysis. There are many software metrics in the literature, but principal component analysis reveals that there are few distinct sources of variation, i.e. dimensions, in this set of metrics. It would appear perfectly reasonable to characterize the measurable attributes of a program with a simple function of a small number of orthogonal metrics each of which represents a distinct software attribute domain.

Munson, John C.↗

Cognitive Performance in ISS Astronauts on 6-Month Low Earth Orbit Missions

Introduction: Current and future astronauts will endure prolonged exposure to spaceflight hazards and environmental stressors that could compromise cognitive functioning, yet cognitive performance in current missions to the International Space Station remains critically under-characterized. We systematically assessed cognitive performance across 10 cognitive domains in astronauts on 6-month missions to the ISS. Methods: Twenty-five professional astronauts were administered the Cognition Battery as part of National Aeronautics and Space Administration (NASA) Human Research Program Standard Measures Cross-Cutting Project. Cognitive performance data were collected at five mission phases: pre-flight, early flight, late flight, early post-flight, and late post-flight. We calculated speed and accuracy scores, corrected for practice effects, and derived z-scores to represent deviations in cognitive performance across mission phases from the sample’s mean baseline (i.e., pre-flight) performance. Linear mixed models with random subject intercepts and pairwise comparisons examined the relationships between mission phase and cognitive performance. Results: Cognitive performance was generally stable over time with some differences observed across mission phases for specific subtests. There was slowed performance observed in early flight on tasks of processing speed, visual working memory, and sustained attention. We observed a decrease in risk-taking propensity during late flight and post-flight mission phases. Beyond examining group differences, we inspected scores that represented a significant shift from the sample’s mean baseline score, revealing that 11.8% of all flight and post-flight scores were at or below 1.5 standard deviations below the sample’s baseline mean. Finally, exploratory analyses yielded no clear pattern of associations between cognitive performance and either sleep or ratings of alertness. Conclusions: There was no evidence for a systematic decline in cognitive performance for astronauts on a 6-month missions to the ISS. Some differences were observed for specific subtests at specific mission phases, suggesting that processing speed, visual working memory, sustained attention, and risk-taking propensity may be the cognitive domains most susceptible to change in Low Earth Orbit for high performing, professional astronauts. We provide descriptive statistics of pre-flight cognitive performance from 25 astronauts, the largest published preliminary normative database of its kind to date, to help identify significant performance decrements in future samples.

Data curation↗

Integrated Medical Model (IMM) Optimization Version 4.0 Functional Improvements

The IMMs ability to assess mission outcome risk levels relative to available resources provides a unique capability to provide guidance on optimal operational medical kit and vehicle resources. Post-processing optimization allows IMM to optimize essential resources to improve a specific model outcome such as maximization of the Crew Health Index (CHI), or minimization of the probability of evacuation (EVAC) or the loss of crew life (LOCL). Mass and or volume constrain the optimized resource set. The IMMs probabilistic simulation uses input data on one hundred medical conditions to simulate medical events that may occur in spaceflight, the resources required to treat those events, and the resulting impact to the mission based on specific crew and mission characteristics. Because IMM version 4.0 provides for partial treatment for medical events, IMM Optimization 4.0 scores resources at the individual resource unit increment level as opposed to the full condition-specific treatment set level, as done in version 3.0. This allows the inclusion of as many resources as possible in the event that an entire set of resources called out for treatment cannot satisfy the constraints. IMM Optimization version 4.0 adds capabilities that increase efficiency by creating multiple resource sets based on differing constraints and priorities, CHI, EVAC, or LOCL. It also provides sets of resources that improve mission-related IMM v4.0 outputs with improved performance compared to the prior optimization. The new optimization represents much improved fidelity that will improve the utility of the IMM 4.0 for decision support.

risk assessment↗

Trusted Communication: Utilizing Speech Communication to Enhance Human-Machine Teaming Success

An area of increasing interest for the next generation of aircraft is autonomy and the integration of increasingly autonomous systems into the national airspace. Such an integration requires humans to work closely with autonomous systems, forming teams. Our hypothesis is that a team composed of both humans and autonomous systems will operate better than either entity alone. We have existing procedures for certifying pilots to operate in the national airspace and are currently working on methods for validating the function of autonomous systems, however we have no method in place for assessing the interaction of these two disparate systems. Communication is one avenue. This paper will examine the use of language as a metric for ascertaining human-machine teaming effectiveness. A proof-of-concept of the application of two communication-based analysis techniques, Linguistic Inquiry and Word Count (LIWC) and Latent Semantic Analysis (LSA), for the prediction of success in human/chatbot teaming was conducted. By running these analyses over data from the 2014 and 2015 Loebner Prize competitions of human/chatbot teaming, numerical scores were obtained that can be associated with scores provided by human judges during the competition. Correlating their LIWC and LSA data with the scores provided by the judges, and using linear regression over this correlation, formulae were obtained that predict the score of human/chatbot interaction. These formulae were tested over the 2013 Loebner Prize transcripts, determining that, though there was strong correlation between predicted and actual scores, the predictive success of this method was not strong. However, with specialized topic spaces and lexica, as well as larger data sets, the predictive power of these metrics will improve. Given the importance of providing metrics for human-machine system team success and given the promise shown by the communication-basedLIWCand LSAmethods, continuing research in this area is necessary. After examining the potential for using communication and spoken language as a metric for the success of human/autonomous system teaming, this paper then examines aspects inherent to communication systems that may contribute to unreliability and reduced trust. Modern natural language processing tools rely on deep learning algorithms to create language rules that produce accurate results, but these rules are uninterpretable. The resulting blackbox system lacks transparency necessary for full validation and complete trust. Additionally, speech-based interfaces pose other difficulties to developing coordinated teamwork between humans and autonomous systems. Human communication is infrequently limited to speech only, instead usually relying on a combination of verbal, gestural, and general body language communication. Reducing an analysis of team effectiveness to a study of spoken language alone is problematic as it leaves these other equally important forms of communication out. This paper will examine these problems and the general deficiencies in speech-based metrics for human-machine teaming.

E L Meszaros↗

Upward appraisal as a means for improving supervisory performance and promoting process improvement, with long-term implications for organizational change

This study represents the implementation phase of an organizational development project which was initiated last year in the Management Support Division (MSD) at Langley Research Center to diagnose organizational functioning. As a result of MSD survey data from last year's effort, a Quality Action Team was created to address the responses compiled from the MSD Organizational Assessment Questionnaire and Follow-Up Questionnaire. The team was officially named the MSD Employee Relations Improvement Team (MERIT). MERIT's goal was to analyze major concerns generated by the questionnaires and to present feasible solutions to management which would improve supervisory performance, promote process improvement; and ultimately, lead to a better organization. The team met weekly and was very disciplined in following guidelines needed to ensure a fully functioning team. Several TQM tools were used during the team process, including brainstorming and the cause and effect diagram. One of the products produced by MERIT was a 'report card', more formally known as an upward appraisal system, to evaluate supervisory performance in the division office, its three branches, and in teams. Major areas of emphasis on the 47 item report card were those identified by employees through the previously administered questionnaires as needing to be improved; specifically, training, recognition, teamwork, supervision and leadership, and communication. MERIT created an enlarged and modified version of the report card which enabled scores for each individual supervisor to be recorded on a separate form, along with summary results and employee comments. Report card results have been compiled and fed back to the Division Chief and Assistant Division Chief. These individuals will in turn, feed the results back to the remaining supervisors and the team leaders. Although results differ among supervisors, some similarities exist. Communication generally appears to be adequate, which represents an improvement over last year. In contrast, recognition and teamwork are the two major areas where improvement in supervisory performance seems to be most needed. The initial report card results will serve as a baseline against which future performance ratings will be compared. Once supervisors have been presented with their data and given an opportunity to analyze and discus the results, they will be assisted in developing an action plan for improving their performance and work processes. They will be provided with ongoing support from management in following through with the action plan.

Siegfeldt, Denise V.↗

Monte Carlo mixture model of lifetime cancer incidence risk from radiation exposure on shuttle and international space station

Estimating uncertainty in lifetime cancer risk for human exposure to space radiation is a unique challenge. Conventional risk assessment with low-linear-energy-transfer (LET)-based risk from Japanese atomic bomb survivor studies may be inappropriate for relativistic protons and nuclei in space due to track structure effects. This paper develops a Monte Carlo mixture model (MCMM) for transferring additive, National Institutes of Health multiplicative, and multiplicative excess cancer incidence risks based on Japanese atomic bomb survivor data to determine excess incidence risk for various US astronaut exposure profiles. The MCMM serves as an anchor point for future risk projection methods involving biophysical models of DNA damage from space radiation. Lifetime incidence risks of radiation-induced cancer for the MCMM based on low-LET Japanese data for nonleukemia (all cancers except leukemia) were 2.77 (90% confidence limit, 0.75-11.34) for males exposed to 1 Sv at age 45 and 2.20 (90% confidence limit, 0.59-10.12) for males exposed at age 55. For females, mixture model risks for nonleukemia exposed separately to 1 Sv at ages of 45 and 55 were 2.98 (90% confidence limit, 0.90-11.70) and 2.44 (90% confidence limit, 0.70-10.30), respectively. Risks for high-LET 200 MeV protons (LET=0.45 keV/micrometer), 1 MeV alpha-particles (LET=100 keV/micrometer), and 600 MeV iron particles (LET=180 keV/micrometer) were scored on a per particle basis by determining the particle fluence required for an average of one particle per cell nucleus of area 100 micrometer(2). Lifetime risk per proton was 2.68x10(-2)% (90% confidence limit, 0.79x10(-3)%-0. 514x10(-2)%). For alpha-particles, lifetime risk was 14.2% (90% confidence limit, 2.5%-31.2%). Conversely, lifetime risk per iron particle was 23.7% (90% confidence limit, 4.5%-53.0%). Uncertainty in the DDREF for high-LET particles may be less than that for low-LET radiation because typically there is very little dose-rate dependence. Probability density functions for high-LET radiation quality and dose-rate may be preferable to conventional risk assessment approaches. Nuclear reactions and track structure effects in tissue may not be properly estimated by existing data using in vitro models for estimating RBEs. The method used here is being extended to estimate uncertainty in spacecraft shielding effectiveness in various space radiation environments.

NASA Center LaRC↗

Development of an Objective Space Suit Mobility Performance Metric Using Metabolic Cost and Functional Tasks

Existing methods for evaluating EVA suit performance and mobility have historically concentrated on isolated joint range of motion and torque. However, these techniques do little to evaluate how well a suited crewmember can actually perform during an EVA. An alternative method of characterizing suited mobility through measurement of metabolic cost to the wearer has been evaluated at Johnson Space Center over the past several years. The most recent study involved six test subjects completing multiple trials of various functional tasks in each of three different space suits; the results indicated it was often possible to discern between different suit designs on the basis of metabolic cost alone. However, other variables may have an effect on real-world suited performance; namely, completion time of the task, the gravity field in which the task is completed, etc. While previous results have analyzed completion time, metabolic cost, and metabolic cost normalized to system mass individually, it is desirable to develop a single metric comprising these (and potentially other) performance metrics. This paper outlines the background upon which this single-score metric is determined to be feasible, and initial efforts to develop such a metric. Forward work includes variable coefficient determination and verification of the metric through repeated testing.

Norcross, J. R.↗

Development of an Objective Space Suit Mobility Performance Metric Using Metabolic Cost and Functional Tasks

Existing methods for evaluating EVA suit performance and mobility have historically concentrated on isolated joint range of motion and torque. However, these techniques do little to evaluate how well a suited crewmember can actually perform during an EVA. An alternative method of characterizing suited mobility through measurement of metabolic cost to the wearer has been evaluated at Johnson Space Center over the past several years. The most recent study involved six test subjects completing multiple trials of various functional tasks in each of three different space suits; the results indicated it was often possible to discern between different suit designs on the basis of metabolic cost alone. However, other variables may have an effect on real-world suited performance; namely, completion time of the task, the gravity field in which the task is completed, etc. While previous results have analyzed completion time, metabolic cost, and metabolic cost normalized to system mass individually, it is desirable to develop a single metric comprising these (and potentially other) performance metrics. This paper outlines the background upon which this single-score metric is determined to be feasible, and initial efforts to develop such a metric. Forward work includes variable coefficient determination and verification of the metric through repeated testing.

McFarland, Shane M.↗

Anthropomorphic teleoperation: Controlling remote manipulators with the DataGlove

A two phase effort was conducted to assess the capabilities and limitations of the DataGlove, a lightweight glove input device that can output signals in real-time based on hand shape, orientation, and movement. The first phase was a period for system integration, checkout, and familiarization in a virtual environment. The second phase was a formal experiment using the DataGlove as input device to control the protoflight manipulator arm (PFMA) - a large telerobotic arm with an 8-ft reach. The first phase was used to explore and understand how the DataGlove functions in a virtual environment, build a virtual PFMA, and consider and select a reasonable teleoperation control methodology. Twelve volunteers (six males and six females) participated in a 2 x 3 (x 2) full-factorial formal experiment using the DataGlove to control the PFMA in a simple retraction, slewing, and insertion task. Two within-subjects variables, time delay (0, 1, and 2 seconds) and PFMA wrist flexibility (rigid/flexible), were manipulated. Gender served as a blocking variable. A main effect of time delay was found for slewing and total task times. Correlations among questionnaire responses, and between questionnaire responses and session mean scores and gender were computed. The experimental data were also compared with data collected in another study that used a six degree-of-freedom handcontroller to control the PFMA in the same task. It was concluded that the DataGlove is a legitimate teleoperations input device that provides a natural, intuitive user interface. From an operational point of view, it compares favorably with other 'standard' telerobotic input devices and should be considered in future trades in teleoperation systems' designs.

Hale, J. P., II↗

Developing Tests of Visual Dependency

Astronauts develop neural adaptive responses to microgravity during space flight. Consequently these adaptive responses cause maladaptive disturbances in balance and gait function when astronauts return to Earth and are re-exposed to gravity. Current research in the Neuroscience Laboratories at NASA-JSC is focused on understanding how exposure to space flight produces post-flight disturbances in balance and gait control and developing training programs designed to facilitate the rapid recovery of functional mobility after space flight. In concert with these disturbances, astronauts also often report an increase in their visual dependency during space flight. To better understand this phenomenon, studies were conducted with specially designed training programs focusing on visual dependency with the aim to understand and enhance subjects ability to rapidly adapt to novel sensory situations. The Rod and Frame test (RFT) was used first to assess an individual s visual dependency, using a variety of testing techniques. Once assessed, subjects were asked to perform two novel tasks under transformation (both the Pegboard and Cube Construction tasks). Results indicate that head position cues and initial visual test conditions had no effect on an individual s visual dependency scores. Subjects were also able to adapt to the manual tasks after several trials. Individual visual dependency correlated with ability to adapt manual to a novel visual distortion only for the cube task. Subjects with higher visual dependency showed decreased ability to adapt to this task. Ultimately, it was revealed that the RFT may serve as an effective prediction tool to produce individualized adaptability training prescriptions that target the specific sensory profile of each crewmember.

Kindrat, Alexandra N.↗

Leveraging Automated Fiber Placement Computer Aided Process Planning Framework for Defect Validation and Dynamic Layup Strategies

Process planning represents an essential stage of the Automated Fiber Placement (AFP) workflow. It develops useful and efficient machine processes based upon the working material, composite design, and manufacturing resources. The current state of process planning requires a high degree of interaction from the process planner and could greatly benefit from increased automation. Therefore, a list of key steps and functions are created to identify the more difficult and time-consuming phases of process planning. Additionally, a set of metrics must exist by which to evaluate the effectiveness of the manufactured laminate from the machine code created during the Process Planning stage. Layup strategies, in addition to dog ears, stagger shifts, steering constraints, and starting points, represented the group of functions labeled as process optimization and ranked the highest in terms of priority for automation. The laminates resulting from the selected parameters are evaluated through the occurrences of principal defect metrics such as fiber gaps, overlaps, angle deviation and steering violations. This document presents an automated software solution to the layup strategy and starting point selection phase of process planning. A series of ply scenarios are generated with variations of these ply parameters and evaluated according to a set of metrics entered by the Process Planner. These metrics are generated through use of the Analytical Hierarchy Process (AHP), where relative importance between each of the fiber features are defined. The ply scenarios are selected which reduce the overall fiber feature scores based on the defects the Process Planner wishes to minimize.

HiCAM↗

Functional Mobility Performance and Balance Confidence in Older Adults after Sensorimotor Adaptation Training

Research indicates a main contributor of injury in older adults is from falling. The decline in sensory systems limits information needed to successfully maneuver through the environment. The objective of this study was to determine if prolonged exposure to the realignment of perceptual-motor systems increases adaptability of balance, and if balance confidence improves after training. A total of 16 older adults between ages 65-85 were randomized to a control group (walking on a treadmill while viewing a static visual scene) and an experimental group (walking on a treadmill while viewing a rotating visual scene). Prior to visual exposure, participants completed six trials of walking through a soft foamed obstacle course. Participants came in twice a week for 4 weeks to complete training of walking on a treadmill and viewing the visual scene for 20 minutes each session. Participants completed the obstacle course after training and four weeks later. Average time, penalty, and Activity Balance Confidence Scale scores were computed for both groups across testing times. The older adults who trained, significantly improved their time through the obstacle course F (2, 28) = 9.41, p < 0.05, as well as reduced their penalty scores F (2, 28) = 21.03, p < 0.05, compared to those who did not train. There was no difference in balance confidence scores between groups across testing times F (2, 28) = 0.503, p > 0.05. Although the training group improved mobility through the obstacle course, there were no differences between the groups in balance confidence.

Buccello-Stout, Regina R.↗

Resolving Sensory Conflict: the Effect of Muscle Vibration on Postural Stability

The otolith-tilt reinterpretation hypothesis (OTTR) proposes that the central nervous system adapts to weightlessness by reinterpreting all otolith input as linear motion. While interpreting otolith input exclusively as linear motion is functionally useful in space, it is maladaptive upon return to Earth. Astronauts have reported experiencing illusory sensations during head movement which contributes to postural instability. The effect is assessed of muscle vibration in combination with a variety of sensory conflicts on postural equilibrium. The equilibrium of six healthy subjects was tested using the EquiTest sensory test protocol, with and without the confounding influence of triceps surea vibration. The data were analyzed with repeated measures with vibration, vision status, and platform status as independent variables. All main effects and an interaction between the presence of vision and platform sway referencing were found to be significant. Overall, a 4.5 pct. decrease in postural stability was observed with vibration. The trend of the difference scores between conditions with and without vibration suggests that vibration is most destabilizing when the triceps surea is able to change length during postural sway (i.e., conditions with a fixed support surface). The impact of sway referencing vision was virtually identical to that of eye closure, providing compelling evidence that sway referencing 'nulls out' useful cues about subject sway.

Layne, Charles S.↗

The Chancellor's Model School Project (CMSP)

What does it take to create and implement a 7th to 8th grade middle school program where the great majority of students achieve at high academic levels regardless of their previous elementary school backgrounds? This was the major question that guided the research and development of a 7-year long project effort entitled the Chancellor's Model School Project (CMSP) from September 1991 to August 1998. The CMSP effort conducted largely in two New York City public schools was aimed at creating and testing a prototype 7th and 8th grade model program that was organized and test-implemented in two distinct project phases: Phase I of the CMSP effort was conducted from 1991 to 1995 as a 7th to 8th grade extension of an existing K-6 elementary school, and Phase II was conducted from 1995 to 1998 as a 7th to 8th grade middle school program that became an integral part of a newly established 7-12th grade high school. In Phase I, the CMSP demonstrated that with a highly structured curriculum coupled with strong academic support and increased learning time, students participating in the CMSP were able to develop a strong foundation for rigorous high school coursework within the space of 2 years (at the 7th and 8th grades). Mathematics and Reading test score data during Phase I of the project, clearly indicated that significant academic gains were obtained by almost all students -- at both the high and low ends of the spectrum -- regardless of their previous academic performance in the K-6 elementary school experience. The CMSP effort expanded in Phase II to include a fully operating 7-12 high school model. Achievement gains at the 7th and 8th grade levels in Phase II were tempered by the fact that incoming 7th grade students' academic background at the CMSP High School was significantly lower than students participating in Phase 1. Student performance in Phase II was also affected by the broadening of the CMSP effort from a 7-8th grade program to a fully functioning 7-12 high school which as a consequence lessened the focus and structure available to the 7-8th grade students and teachers -- as compared to Phase I. Nevertheless, the CMSP does represent a unique curriculum model for 7th and 8th grade students in urban middle schools. Experience in both Phase I and Phase II of the project allowed the CMSP to be developed and tested along the broad range of parameters and characteristics that embody an operating public school in an urban environment.

Lopez, Gil↗