Linking genebanks and farmers to urban high-value markets - The case of chili peppers in Peru and Bolivia [Poster]

Poster presented at Tropentag Conference. Stuttgart-Hohenheim (Germany), 17-19 Sep 201

Development of a Non-Iterative Balance Load Prediction Algorithm for the NASA Ames Unitary Plan Wind Tunnel

A non-iterative load prediction algorithm for strain-gage balances was developed for the NASA Ames Unitary Plan Wind Tunnels that computes balance loads from the electrical outputs of the balance bridges and a set of state variables. A state variable could be, for example, a balance temperature difference or the bellows pressure of a flow-through balance. The algorithm directly uses regression models of the balance loads for the load prediction that were obtained by applying global regression analysis to balance calibration data. This choice greatly simplifies both implementation and use of the load prediction process for complex balance configurations as no load iteration needs to be performed. The regression model of a balance load is constructed by using terms from a total of nine term groups. Four term groups are derived from a Taylor Series expansion of the relationship between the load, gage outputs, and state variables. The remaining five term groups are defined by using absolute values of the gage outputs and state variables. Terms from these groups should only be included in the regression model if calibration data from a balance with known bi-directional outputs is analyzed. It is illustrated in detail how global regression analysis may be applied to obtain the coefficients of the chosen regression model of a load component assuming that no linear or massive near-linear dependencies between the regression model terms exist. Data from the machine calibration of a six-component force balance is used to illustrate both application and accuracy of the non-iterative load prediction process

A holistic approach to enhance the use of neglected and underutilized species: the case of Andean grains in Bolivia and Peru

The IFAD-NUS project, implemented over the course of a decade in two phases, represents the first UN-supported global effort on neglected and underutilized species (NUS). This initiative, deployed and tested a holistic and innovative value chain framework using multi-stakeholder, participatory, inter-disciplinary, pro-poor gender- and nutrition-sensitive approaches. The project has been linking aspects often dealt with separately by R&D, such as genetic diversity, selection, cultivation, harvest, value addition, marketing, and final use, with the goal to contribute to conservation, better incomes, and improved nutrition and strengthened livelihood resilience. The project contributed to the greater conservation of Andean grains and their associated indigenous knowledge, through promoting wider use of their diversity by value chain actors, adoption of best cultivation practices, development of improved varieties, dissemination of high quality seed, and capacity development. Reduced drudgery in harvest and postharvest operations, and increased food safety were achieved through technological innovations. Development of innovative food products and inclusion of Andean grains in school meal programs is projected to have had a positive nutrition outcome for targeted communities. Increased income was recorded for all value chain actors, along with strengthened networking skills and self-reliance in marketing. The holistic approach taken in this study is advocated as an effective strategy to enhance the use of other neglected and underutilized species for conservation and livelihood benefits

Use of the Ames Check Standard Model for the Validation of Wall Interference Corrections

The new check standard model of the NASA Ames 11-ft Transonic Wind Tunnel was chosen for a future validation of the facility's wall interference correction system. The chosen validation approach takes advantage of the fact that test conditions experienced by a large model in the slotted part of the tunnel's test section will change significantly if a subset of the slots is temporarily sealed. Therefore, the model's aerodynamic coefficients have to be recorded, corrected, and compared for two different test section configurations in order to perform the validation. Test section configurations with highly accurate Mach number and dynamic pressure calibrations were selected for the validation. First, the model is tested with all test section slots in open configuration while keeping the model's center of rotation on the tunnel centerline. In the next step, slots on the test section floor are sealed and the model is moved to a new center of rotation that is 33 inches below the tunnel centerline. Then, the original angle of attack sweeps are repeated. Afterwards, wall interference corrections are applied to both test data sets and response surface models of the resulting aerodynamic coefficients in interference-free flow are generated. Finally, the response surface models are used to predict the aerodynamic coefficients for a family of angles of attack while keeping dynamic pressure, Mach number, and Reynolds number constant. The validation is considered successful if the corrected aerodynamic coefficients obtained from the related response surface model pair show good agreement. Residual differences between the corrected coefficient sets will be analyzed as well because they are an indicator of the overall accuracy of the facility's wall interference correction process

Neurophysiological mechanisms of motor cortical modulation associated with bimanual movement

The neural correlates of bilateral upper limb movement are poorly understood. It has been proposed that interhemispheric pathways contribute to the modulation of motor cortical excitability during bimanual movements, possibly via direct connections between primary motor areas (M1), or via a central cortical structure, such as the supplementary motor area (SMA). The ability of one hemisphere to facilitate activation in the other presents a unique opportunity for motor rehabilitation programs using bilateral movements. The focus of this thesis was to investigate the mechanisms underlying bimanual movements in a group of healthy control participants using functional magnetic resonance imaging (fMRI), and subsequently to identify the types of movements that are most likely to maximize M1 activity. It was hypothesized first, that movements involving more proximal muscles, which are known to have a greater number of transcallosal connections, would produce a larger facilitation of M1 activity; and secondly, that the greatest facilitation would occur during those phases of movements where homologous muscles are active simultaneously (i.e. in-phase bilateral movements). The current results demonstrate that the M1 regions and the SMA work together to modulate motor cortical excitability, and that the greatest modulation of activity is seen during movements involving proximal muscles. The findings presented may have clinical relevance to motor rehabilitation programs involving bilateral movements

El platanillo del arroz y su control.

Arroz-Oryza sativ