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Creating vector images with Adobe Illustrator Vector images, also called bitmap images, use mathematical formulas (in the form of points, curves, and lines) to display graphics, rather than dots that create a raster image. Vector images are suitable for print, but they have some limitations for web use. Illustrator is a vector-image drawing and editing program. In addition to tools that enable you to create, edit, print, and export graphics, the program has a web-publishing toolset for creating and publishing documents to the Web. ## Creating a Vector Photo To start, create a new document in Illustrator and create a basic shape in the canvas. Here, I create a very basic shape to illustrate how vectors can create an image with just a few basic design elements. In this illustration, the basic design includes two shapes: a rectangle and a circle. You can add more details in the shapes, such as highlights and shadows, but the basics are what you’re after. To create a basic image, use one of the following techniques: * **Draw a basic shape.** To create a vector image from a basic shape, create the basic shape and then use the Pathfinder panel to use the vector-shape to create the entire image. * **Use the Rectangle tool and drag to create a shape.** The Rectangle tool is one of the drawing tools in Illustrator. To create a new shape, click the tool and then click and drag to create the shape. You can change the size of the rectangle you create in two ways: * **Use the Rectangle tool.** Select the Rectangle tool from the toolbox and then select a starting and

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Have you ever found yourself wanting to learn a new Photoshop skill? In this post, I’ll show you how to: Learn how to use Adobe Photoshop for image editing Import graphics Resize graphics and images Change the depth of an image Make incredible patterned backgrounds Make numerous effects Design retouching brushes Scrapbooking with Photoshop Learn Photoshop skill by skill: How to create the perfect image with Photoshop Using Photoshop’s history panel to navigate and recover your projects Combining layers and masking to create limitless effects and design tricks Retouching with Photoshop Photoshop is easily the most powerful image editing program out there. But if you’re not familiar with Photoshop or don’t want to pay for Photoshop, you can still use Photoshop Elements. Photoshop and Photoshop Elements have almost the same features: They are both the same size. Their interface is similar, with just slight differences. They both allow you to edit video and photo files. And both are free. But the available features, number of presets and ease of use vary. Photoshop Elements is the cheaper, simpler app that you can use to edit images. The more comprehensive, more powerful Photoshop is the full-featured pro tool, allowing for more advanced features than Photoshop Elements. 1. Basic image editing with Photoshop To start editing images in Photoshop, choose File > New. The New dialog will appear with six options: Photoshop: Open a Photoshop project Photoshop Elements: Open a Photoshop Elements project Open a Photoshop Document: Open a Photoshop document New from Scratch: Open a new image Open Recent: Open a file in the most recently used folder Current Project: Open the active Photoshop file The New dialog will show a number of preset options: Chosen Type: A set of preset options Original Format: A preset file format that you can choose from Blank: Save an empty document This example uses the Photoshop preset options in the New dialog. 2. Import an image to Photoshop Select File > Import or press the keyboard shortcut Ctrl+I to open the Import dialog. The first option here is where you choose whether you want to import graphics from a file or a folder. a681f4349e

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// Copyright (c) 2014-2017, The Monero Project // // All rights reserved. // // Redistribution and use in source and binary forms, with or without modification, are // permitted provided that the following conditions are met: // // 1. Redistributions of source code must retain the above copyright notice, this list of // conditions and the following disclaimer. // // 2. Redistributions in binary form must reproduce the above copyright notice, this list // of conditions and the following disclaimer in the documentation and/or other // materials provided with the distribution. // // 3. Neither the name of the copyright holder nor the names of its contributors may be // used to endorse or promote products derived from this software without specific // prior written permission. // // THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS “AS IS” AND ANY // EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF // MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL // THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, // SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, // PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS // INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, // STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF // THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. #pragma once #include struct CFriendAddress; class CTxIn; class CTxOut; namespace canelibtor { // A callback to be called when receiving the Decrypted Message from Server // the function handle should throw exceptions when invalid data is received // the function should throw

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Q: Pandas groupby and sort Suppose I have a DataFrame, so we will call it df Name Age 37 12 43 3 37 12 33 7 43 3 … … I want to group the dataframe by the ‘Name’ column and sort the data by the ‘Age’ column, so I could get something like this: Name Age 37 12 33 7 43 3 … … I know how to do it in SQL, but I have tried to play around with groupby and sort, and was not able to do the task. For example, in SQL I would write something like: select Name, Age from ( select Name, Age from myData group by Name ) temp order by Age; A: You could use sort_values and then groupby df=df.sort_values(‘Age’,ascending=False) df=df.groupby(‘Name’,group_keys=False).first() df.reset_index(inplace=True) Name Age 0 37 12 1 33 7 2 43 3 3 37 12 4 43 3 Study of oedema in porcine skin treated with different commercial peels. Exfoliation is the first treatment step of many skin care regimes but

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