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You find the Path Eraser tool with the Pencil tool in the Tools panel. Like the Smooth tool, the Path Eraser tool works on any path, no matter how you created it. The Path Eraser tool does what its name suggests: It erases a path at the point where you ve dragged the Path Eraser tool over the path. You can use the Path Eraser tool to cut a path by first selecting the path and then dragging across a section with the Path Eraser tool. Illustrator removes the section you drag over. You can use the Path Eraser tool to cut a line, just as you would use the Scissors tool. If you just click one time on the path, Illustrator cuts the path exactly in that spot. Unlike Photoshop s clunky eraserlooking tool, this is much more refined and easier to use.

To use the Find Examples database, click any of the text buttons on the menu screen. FileMaker Pro enters Find mode and displays another screen showing the appropriate Find request. Because the requests are displayed in list view (each line represents a separate Find request), you can see all the necessary requests on this single screen. After examining the requests, click the status area s Continue button. The Find requests execute, and the results display. To return to the menu screen, click the Return to Menu button at the bottom of the screen.

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Reagents and Materials Sterile DMEM/10FB (see Section 3.4.1.1) EB medium (see Section 3.4.1.6) Neurosphere expansion medium (see Section 3.4.1.3) Collagenase IV solution (see Section 3.4.2.1) Dispase, 0.1 mg/mL (see Section 3.4.2.2) Glass beads, 3 mm Culture asks, 25 cm2 Culture asks, 25 cm2 , gelatin coated (see Section 3.4.3.2) Centrifuge tubes, 15 mL Nonsterile Agarose Procedure Stage 1 (Day 0). (a) Grow human ES cells to con uence in a 25-cm2 tissue culture ask (see 2, Section 2.5). (b) Aspirate medium from the ask and add 1 mL of collagenase IV solution, ensuring that the collagenase covers all the area of cell growth. (c) Place the ask in a 5% CO2 incubator at 37 C for 15 min. (d) Remove the ask from the incubator and check that the colonies are curling around the edges. (e) Add around 20 sterile glass beads to the ask, then shake from side to side to remove the cells from the surface. (f) Add 9 mL of DMEM/10FB to the ask and resuspend the cells by triturating 5 10 times. (g) Remove the cell suspension from the ask and place in a sterile 15-mL tube before centrifuging at 800 rpm (123 g) for 3 min at 4 C.

class ModEventFeed(Scraper): Enhance feed metadata by parsing content. ATOM_FEED_TMPL = < xml version= 1.0 encoding= utf-8 > <feed version= 0.3 xmlns= http://purl.org/atom/ns# xmlns:ev= http://purl.org/rss/1.0/modules/event/ > <title>%(feed.title)s</title> <link rel= alternate type= text/html href= %(feed.link)s /> <tagline>%(feed.tagline)s</tagline> <modified>%(feed.modified)s</modified> <author> <name>%(feed.author.name)s</name> <email>%(feed.author.email)s</email> <url>%(feed.author.url)s</url> </author> %(feed.entries)s </feed> ATOM_ENTRY_TMPL = <entry> <title>%(entry.title)s</title> <link rel= alternate type= text/html href= %(entry.link)s /> <issued>%(entry.issued)s</issued> <modified>%(entry.modified)s</modified> <id>%(entry.id)s</id> <ev:startdate>%(entry.ev_startdate)s</ev:startdate> <ev:enddate>%(entry.ev_enddate)s</ev:enddate> <summary type= text/html mode= escaped >%(entry.summary)s</summary> </entry>

introduces a new class of Excel functions, because it needs to return values in several cells. Array functions, introduced in 4, solve this dilemma; an array function can return values in more than one cell. Apart from the built-in functions, there are two other ways to calculate the linear regression formulas in Excel. These methods are more powerful than the built-in functions. One is a direct method, using somewhat complicated formulas for the parameters in the model. The other uses the Solver capability to calculate the parameters. Solver is a general-purpose tool included with Excel that finds optimal solutions to problems. Its ability to build linear regression models is just one example of its power. Measuring how well the best-fit line fits the data introduces the idea of correlation. Correlation is easy to calculate. As with many statistical measures, it does what it does well, but it comes with some warnings. It is easy to overinterpret correlation values. Multiple regression extends the best-fit line regression by using more than one input variable. Fortunately, multiple regression is quite feasible in Excel. Unfortunately, it does not produce pretty scatter plots, because there are too many dimensions. SQL can also be used to build basic linear regression models, when there are one or two input variables. Unfortunately, standard SQL does not have builtin functions to do this, so the equations have to be entered explicitly. These equations become more complicated as more variables are added, as we ll see with the two-variable example at the end of this chapter. The chapter begins not with complicated SQL statements, but rather with the best-fit line, which enables us to visualize linear regression.

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