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Clear Prairie Dawn is an original humanist sans serif family based on my own printing. I designed it for use as a text face. As a humanist sans it shares some of the characteristics you might notice in other such faces as Optima, Gill Sans or Stone Sans. The italic is a designed italic, rather than merely a slanted roman, and incorporates many of the ideas that I found too lively for the roman fonts. The complete package consists of three weights in two styles each: Plain, Italic, Semibold, Semibold Italic, Bold and Bold Italic, plus a set of original ornaments. All the text fonts contain both oldstyle and lining figures.

The TYPE BY Quadraat Sans follows a trend which was originated by Jan van Krimpen who designed Romulus, a classical typeface and to which he added some sans serif variations. It was not until the late eighties that this idea became more popular. The well known designs from our days are ITC Stone or ff Scala for example. Both typefaces give designers the opportunity to make use of well adapted sans serif variations. Quadraat which started with a serif version follows this young tradition. Sans serif typefaces can look very much alike, especially in the bolder variations. This is certainly not the case with Quadraat Sans. Quadraat Sans is like its serif companion a typeface with a rather strong character of its own. Thus, it was not that easy for the designer Fred Smeijers to make a gesture as strong as its serif companion without neglecting traditional proportions. But he obviously succeeded in giving the sans version a lively and humane character. This can be most clearly seen in big word images and is still there in text sizes, although in a more discreet way. So Quadraat Sans has display qualities, is an efficient typeface and suitable for longer texts at the same time.

Download Quadrat Serial Bold

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I am trying to do mixed linear model for my study in R. I would like to know if my code is correct or not.MY design - I have 5 sites, 2 subsites within each site and 2 permanent quadrates within each site. So I have 5 sites, 10 subsites and 20 quadrats. I have measured colony size (of corals) at all the quadrats. My question is does the size structure vary between sites ? In my data quadrats are nested within subsite and subsites are nested within site. I will use site as my fixed factor and subsites and quadrats as my random effects. I can think of two possible ways of doing this:

Quantitative descriptions of valley cross profiles can capture the essence of valley morphology and provide an effective tool to differentiate between valleys formed by different processes (Li et al., 2001). Two principal models are widely used to achieve mathematical approximation of glacial valley transects: a power law adopted by Svensson (1959) and a second-order polynomial first applied by Wheeler (1984). Both approximations show advantages and limitations in depicting valley cross profiles. Power laws have more potential for understanding cross-sectional shape, whereas quadratic equations offer a more robust description (Harbor and Wheeler, 1992; Li et al., 2001).

2D scheme of multi-scale curvature analysis: Idealized cross sections of similar sized V-shaped (a) and U-shaped (b) valleys (bold blue) and thalweg subsections (bold red). Horizontal bars and thin, vertical dashed lines indicate valley parts investigated at different scales. Reference scale is marked by red bars, multi-scale valley analysis by blue bars and invalid analysis scale by light gray bars. Dotted lines indicate best-fit second order polynomials for valley cross sections (fine dots) and subsections (bold dots).

Drainage area cutoff plotted against quadrat width for the Sawtooth Mountains (a), the Sierra Nevada (b), and the Olympic Mountains (c). Minimum amount of valid grid cells per quadrat indicated by logarithmic color map (zero = blank). Partial quadrats are not included.

Identification of glacial (black quadrats) mountain regions of the Sawtooth Mountains, Idaho. Sample catchments are indicated by dotted outline (fluvial) and dashed outline (glacial). Red squares mark fluvial and glacial areas shown in Figs. 6 and 8. Field evidence for former glaciation: LGM ELA (white; Meyer et al. (2004) and glacial depositions (dark gray; (Stanford, 1982; Borgert et al., 1999; Kiilsgard et al., 2001, 2006; Thackray et al., 2004). See text for detailed discussion of areas marked with bold letters. Spatial reference: WGS84/UTM 11N (EPSG 32611).

Classification of glacial (black quadrats) mountain regions of the Southern Sierra Nevada, California. Sample catchments are indicated by dotted outline (fluvial) and dashed outline (glacial). Field evidence for former glaciation: glacial extent during LGM (white; Gillespie and Zehfuss (2004). See Results for detailed discussion of areas marked with bold letters. Spatial reference: WGS84/UTM 11N (EPSG 32611).

Classification of glacial (black quadrats) mountain regions of the Western Olympic Mountains, WA. Sample catchments are indicated by dotted outline (fluvial) and dashed outline (glacial). Field evidence for former glaciation: deposits of Fraser age (dark gray) and pre-Fraser age (light gray) alpine glaciations (Dragovich et al., 2002). See Results for detailed discussion of areas marked with bold letters. Spatial reference: WGS84/UTM 10N (EPSG 32610).

The drainage area cutoff of 0.1 km2 was determined based on the transition zone from divergent to convergent terrain and on considerations about the amount of valid grid cells per quadrat (Section 3.3, Fig. 3). The chosen quadrat size of 5 5 km is coherent with the width of the widest valleys in all three study areas and the drainage area cutoff ensures valid grid cells in every quadrat. The probability density plots of DMC provided in Fig. 9 show that especially the distribution of glacial DMC is greatly affected by the drainage area cutoff. DMC values close to zero are typical for fluvial valleys, but exist in glacial terrain as well. In the latter case, they are a result of flat terrain cells holding an upstream drainage area larger than the cutoff. They are less likely if the cutoff is raised, which leads to more negative glacial DMC, to larger differences in fluvial and glacial probability density functions, and to variations of the DMC thresholds. Although an increase in fluvial-glacial contrast would be favorable for distinction, we did not apply a higher drainage area cutoff because of the associated drop in the number of valid grid cells leading to empty quadrats for regionalization. Using only a slightly higher drainage area cutoff (e.g. 0.2 km2), we would have to approximately quadruple quadrat area to avoid empty quadrats. Hence, the number of interpretable grid cells clearly is a governing factor in our methodology. 17dc91bb1f