An Improved Method for Quantifying the Stiffness of Running Shoes

The purpose of running shoes is to protect feet from injury by stabilizing motion and cushioning impact. As material technology and product testing develop, shoes can offer more protection through advanced designs. A typical test for running shoes is a flexion test in which the shoe is bent through a fixed angle and the applied force is measured. Most tests bend the forefoot of a shoe, but this characterizes stiffness over a limited portion of the shoe. The goal of this research is to develop an improved flexion test by evaluating and quantifying the stiffness of running shoes in both the forefoot and mid-foot sections. To facilitate the measurement of shoe flexion at various locations, an apparatus was designed so that the distance between the fixed end of the shoe and the applied load is adjustable, adapting to a range of shoe sizes and bend lengths. Preliminary data agree with established tests and illustrate a difference in stiffness values at the two locations. As more testing is performed with more bend locations, a better shoe stiffness profile can be determined. The results generated with this testing method will be used to better evaluate shoe design and performance for injury prevention

Multifractal Analysis of Soil Surface Roughness

Soil surface roughness (SSR) is a parameter highly suited to the study of soil susceptibility to wind and water erosion. The development of a methodology for quantifying SSR is therefore instrumental to soil evaluation. We developed such a method, based on the multifractal analysis (MFA) of soil elevation measurements collected at the intersections on a 2- by 2-cm2 grid in a 200- by 200-cm2 plot. Samples were defined using the gliding box algorithm (GB), in which a box of a given size "glides" across the grid map in all possible directions. The advantage of the GB over the box counting algorithm is that it yields a greater number of large sample sizes, which usually leads to better statistical results. Standard deviation, semivariogram fractal dimension, and semivariogram crossover length were estimated for all scenarios to compare the results of SSR multifractal analysis to indices found with traditional techniques. For its high sensitivity to the spatial arrangement implicit in a data set, MFA appears to be better suited than classical indices to compare plots tilled under different management criteria. The results showed that MFA is able to effectively reflect the heterogeneity and complexity of agricultural SSR. Based on this type of analysis, two new indices have been defined to compare the multifractal spectrum characteristics of the raw data to the characteristics of a random field with the same average and SD

Overwinter Changes in Dry Aggregate Size Distribution Influencing Wind Erodibility in a Spring Wheat-Summerfallow Cropping System

A long-term study of the wind erodibility properties of a two-year spring wheat-summerfallow cropping systems was started in 1988 in south-central North Dakota as part of an USDA-ARS led effort to construct a process-oriented soil erosion predictive model. Observations were conducted on a conservation tillage experiment established in 1984 on soil classified in the U.S. as Typic-Pachic Haploborolls and in Canada as Brown to Dark Brown Chenozemic. The experiment included four residue-management treatments defined by targeted residue coverages: no-till, \u3e 60% cover; minimal-till, 30% to 60% cover and undercutter dominated; conventional-till, \u3c 30% cover and disk dominated; low-residue, \u3c 5 % cover. Fall and spring measurements of dry aggregate size distribution (ASD) of surface soil (0 to 4 cm depth), and overwinter changes in ASD are reported here. A rotary sieve produced six size fractions ranging from \u3c 0.42 mm to \u3e 19.2 mm diameter. Measurements of ASD are expressed as geometric mean diameter (GMD) or erodible fraction (EF: fraction \u3c 0.84 mm). Two major influences on overwinter changes in ASD were observed: (i) During the drier part of a multiyear weather cycle (1988 to 1990), disaggregative changes were observed, with a lowering of GMDs and an increase in EFs. Wetter years (1991 to 1993) brought mixed to aggregative ASD changes. (ii) The phase of the 21-month fallow period strongly affected overwinter ASD change, with large, aggregative changes (GMD up, EF down) observed over the first winter of the fallow period (stubble phase) and mixed aggregative to disaggregative changes observed in the second winter of fallow (residue phase). Tillage treatments had little apparent effect on overwinter ASD changes. Single and multiple regressions indicate that various factors would associate with significant fractions of variance in overwinter GMD change: (i) weather factors - (a) number of days with snowcover, (b) number of freeze-thaw cycles, and (c) precipitation in the fall; (ii) crop growth in years before the year of fallow; (iii) phase of the fallow period; and (iv) GMD level in the fall

Shadow analysis: A method for measuring soil surface roughness

Erosion potential and the effects of tillage can be evaluated from quantitative descriptions of soil surface roughness. The present study therefore aimed to fill the need for a reliable, low-cost and convenient method to measure that parameter. Based on the interpretation of micro-topographic shadows, this new procedure is primarily designed for use in the field after tillage. The principle underlying shadow analysis is the direct relationship between soil surface roughness and the shadows cast by soil structures under fixed sunlight conditions. The results obtained with this method were compared to the statistical indexes used to interpret field readings recorded by a pin meter. The tests were conducted on 4-m2 sandy loam and sandy clay loam plots divided into 1-m2 subplots tilled with three different tools: chisel, tiller and roller. The highly significant correlation between the statistical indexes and shadow analysis results obtained in the laboratory as well as in the field for all the soil–tool combinations proved that both variability (CV) and dispersion (SD) are accommodated by the new method. This procedure simplifies the interpretation of soil surface roughness and shortens the time involved in field operations by a factor ranging from 12 to 20