Computer Model for Dynamic Skyline Behaviour

The development and experimental verification of a numerical model for the dynamic behavior of a cable logging system skyline is discussed. The model is intended to simulate the skyline behavior after a turn of logs breaks out of a "hang-up" on the ground. Output from the model may be used as a forcing function for a dynamic load on the tailspar or other component of the cable logging system. The numerical model uses finite difference and Runge-Kutta techniques. Output from the model consists of time-histories of the fluctuations in skyline tensions. From this output the frequencies of the skyline vibrations may be determined. The model was verified by experimental data collected while operating a small cable logging system in Oregon State University's McDonald Research Forest

Dynamic Characteristics of a Small Skyline Logging System with a Guyed Tailspar

A series of dynamic loading tests were conducted on a small skyline logging system (15.8 mm [5/8 inch] skyline) operating in a second-growth Douglas fir stand. The tests included free vibration tests and logging tests with turns weighing from 1.5 to 9 kN [340 to 2050 lbs]. Natural frequency and damping were evaluated from free vibration tests, and the free vibration portion of logging tests. Dynamic load magnitude was evaluated for logging tests with natural and artificial breakouts of turns with a range in turn weights, and for a series of logging tests with the same turn. The natural frequencies of the guylines were in good agreement with simple cable theory. However, the presence of the carriage on the skyline resulted in measured natural frequencies significantly lower than simple cable theory would predict. Damping of the tailspar system and the skyline averaged about 10% of critical damping, but was highly variable from test to test. Dynamic load magnitude, whether expressed as the load peak produced by turn break-out, or the maximum cyclic load, was highly variable, with coefficients of variation ranging from 31 to 79%. Even a series of logging tests with the same two-log turn produced maximum cyclic loads with a coefficient of variation of nearly 40%

Modeling Regional Carbon Dioxide Flux over California using the WRF‑ACASA Coupled Model

Many processes and interactions in the atmosphere and the biosphere influence the rate of carbon dioxide exchange between these two systems. However, it is difficult to estimate the carbon dioxide flux over regions with diverse ecosystems and complex terrains, such as California. Traditional carbon dioxide measurements are sparse and limited to specific ecosystems. Therefore, accurately estimating carbon dioxide flux on a regional scale remains a major challenge. In this study, we couple the Weather Research and Forecasting Model (WRF) with the Advanced Canopy-Atmosphere-Soil Algorithm (ACASA), a high complexity land surface model. Although WRF is a state-of-the-art regional atmospheric model with high spatial and temporal resolutions, the land surface schemes available in WRF lack the capability to simulate carbon dioxide. ACASA is a complex multilayer land surface model with interactive canopy physiology and full surface hydrological processes. It allows microenvironmental variables such as air and surface temperatures, wind speed, humidity, and carbon dioxide concentration to vary vertically. Carbon dioxide, sensible heat, water vapor, and momentum fluxes between the atmosphere and land surface are estimated in the ACASA model through turbulence equations with a third order closure scheme. It therefore permits counter-gradient transports that low-order turbulence closure models are unable to simulate. A new CO2 tracer module is introduced into the model framework to allow the atmospheric carbon dioxide concentration to vary according to terrestrial responses. In addition to the carbon dioxide simulation, the coupled WRF-ACASA model is also used to investigate the interactions of neighboring ecosystems in their response to atmospheric carbon dioxide concentration. The model simulations with and without the CO2 tracer for WRF-ACASA are compared with surface observations from the AmeriFlux network.This work is supported in part by the National Science Foundation under Awards No.ATM-0619139 and EF-1137306. The Joint Program on the Science and Policy of Global Change is funded by a number of federal agencies and a consortium of 40 industrial and foundation sponsors. (For the complete list see http://globalchange.mit.edu/sponsors/current.html)

Protein Delivery of an Artificial Transcription Factor Restores Widespread Ube3a Expression in an Angelman Syndrome Mouse Brain.

Angelman syndrome (AS) is a neurological genetic disorder caused by loss of expression of the maternal copy of UBE3A in the brain. Due to brain-specific genetic imprinting at this locus, the paternal UBE3A is silenced by a long antisense transcript. Inhibition of the antisense transcript could lead to unsilencing of paternal UBE3A, thus providing a therapeutic approach for AS. However, widespread delivery of gene regulators to the brain remains challenging. Here, we report an engineered zinc finger-based artificial transcription factor (ATF) that, when injected i.p. or s.c., crossed the blood-brain barrier and increased Ube3a expression in the brain of an adult mouse model of AS. The factor displayed widespread distribution throughout the brain. Immunohistochemistry of both the hippocampus and cerebellum revealed an increase in Ube3a upon treatment. An ATF containing an alternative DNA-binding domain did not activate Ube3a. We believe this to be the first report of an injectable engineered zinc finger protein that can cause widespread activation of an endogenous gene in the brain. These observations have important implications for the study and treatment of AS and other neurological disorders

The Admissions Process in Occupational Therapy Education: Investigating Academic and Non-academic Metrics in the Applicant Selection Process

The overall goal for any admissions process is to analyze criteria and identify the prospective students that have the highest potential for success in the program’s curriculum and in the field as a practicing clinician. The purpose of this study was to examine common academic and non-academic criteria utilized in occupational therapy (OT) admission processes and determine what criteria are used by programs with 100% student pass ratings on their National Board for Certification in Occupational Therapy (NBCOT) exam following completion of an OT program. Admissions criteria components and NBCOT pass rates were collected from the top 107 OT programs, as reported by US News and World Report, using publicly available websites for each program and the NBCOT webpage. Descriptive statistics were recorded regarding the frequency of utilizing various admissions criteria. Chi-square tests were utilized to examine the relationship between each admissions criteria component and the NBCOT pass rate. Admissions criteria frequently utilized by the top OT programs included a bachelor’s degree prior to matriculation (90.99% programs), minimum undergraduate GPA (55.86%), personal statement (90.09%), letters of recommendation (97.30%), observation hours (74.77%), and an interview (61.26%). Few programs required applicants to submit a minimum math/science GPA (11.71%) or a writing sample (40.54%). Results did not reveal a statistically significant difference between analyzed criteria groups. It is likely that NBCOT pass rates are impacted by other factors that were not publicly available or included in this study

Who\u27s That Knocking at My Door? Neural Bases of Sound Source Identification

When hearing knocking on a door, a listener typically identifies both the action (forceful and repeated impacts) and the object (a thick wooden board) causing the sound. The current work studied the neural bases of sound source identification by switching listeners\u27 attention toward these different aspects of a set of simple sounds during functional magnetic resonance imaging scanning: participants either discriminated the action or the material that caused the sounds, or they simply discriminated meaningless scrambled versions of them. Overall, discriminating action and material elicited neural activity in a left-lateralized frontoparietal network found in other studies of sound identification, wherein the inferior frontal sulcus and the ventral premotor cortex were under the control of selective attention and sensitive to task demand. More strikingly, discriminating materials elicited increased activity in cortical regions connecting auditory inputs to semantic, motor, and even visual representations, whereas discriminating actions did not increase activity in any regions. These results indicate that discriminating and identifying material requires deeper processing of the stimuli than discriminating actions. These results are consistent with previous studies suggesting that auditory perception is better suited to comprehend the actions than the objects producing sounds in the listeners\u27 environment

Impact of Canopy Representations on Regional Modeling of Evapotranspiration using the WRF-ACASA Coupled Model

In this study, we couple the Weather Research and Forecasting Model (WRF) with the Advanced Canopy-Atmosphere-Soil Algorithm (ACASA), a high complexity land surface model, to investigate the impact of canopy representation on regional evapotranspiration. The WRF-ACASA model uses a multilayer structure to represent the canopy, consequently allowing microenvironmental variables such as leaf area index (LAI), air and canopy temperature, wind speed and humidity to vary both horizontally and vertically. The improvement in canopy representation and canopy-atmosphere interaction allow for more realistic simulation of evapotranspiration on both regional and local scales. Accurate estimates of evapotranspiration (both potential and actual) are especially important for regions with limited water availability and high water demand, such as California. Water availability has been and will continue to be the most important issue facing California for years and perhaps decades to come. Terrestrial evapotranspiration is influenced by many processes and interactions in the atmosphere and the bio-sphere such as water, carbon, and momentum exchanges. The need to improve representation within of surface-atmosphere interactions remains an urgent priority within the modeling community.This work is supported in part by the National Science Foundation under Awards No.ATM-0619139 and EF-1137306. The Joint Program on the Science and Policy of Global Change is funded by a number of federal agencies and a consortium of 40 industrial and foundation sponsors. (For the complete list see http://globalchange.mit.edu/sponsors/current.html)