So, you forgot your anniversary was coming up, and now you have to decide what you’re going to get your loved one. Wolfram|Alpha can now help point you in the right direction. The stereotypical anniversary gift for a man to give his wife is often thought to be jewelry, but you would be surprised to know that many traditional and modern wedding gifts have nothing to do with jewelry.
Since its creation, Wolfram|Alpha has constantly grown to cover more and more topic areas. Now, it includes some functionality that may be useful for people interested in lumber. Most of us are used to going into a local home improvement store and seeing large collections of construction lumber, but before it gets into those stores, it has to be cut from logs. An important step in the process is determining how much lumber can be obtained from a log of a given size. There is no single method for estimating this, but there are a number of empirical formulas that are commonly used to estimate the volume of lumber that can be obtained from a log given its diameter and length. Typically, these estimates are rounded to the nearest 5 or 10 board feet. Three of the most common empirical rules are the Doyle Rule, the Scribner Rule, and the International 1/4-inch log rule. Different regions tend to use different rules, so it’s up to users to decide which one they want to use.
We’ve blogged before about international food consumption data in Wolfram|Alpha, and queries about this data have proved to be a favorite among our users, with good reason: it’s fascinating to explore the world’s food supply and to visualize trends in consumption. In an attempt to fill in a more complete picture of global agricultural trends, we’ve added more data from the FAO—this time covering food production, harvest, and crop yields around the world. More »
One of the most commonly used materials all around us is wood. There are many different kinds of woods with wide ranging mechanical, physical, and thermal properties, which make them suitable for different applications. From building houses to making kitchenware, wood is an ideal and easy to use material. In general, wood is broadly available at reasonable prices and is easily formable, making it desirable for construction work. Of course, depending on the application, different properties of wood are desirable. For example, for building a house with wood, high strength is desired, whereas for making a cutting board, you probably want something that has a harder surface so it doesn’t get dented easily. Wolfram|Alpha now has a large database of all kinds of wood and their various properties.
There are various ways you can obtain data on woods using Wolfram|Alpha. If you need to quickly skim through the different kinds of woods, Wolfram|Alpha can generate a quick report of properties of a certain kind of wood.
It’s a bit of an understatement to say that trees play vital roles in each of our lives. Trees absorb carbon dioxide from the atmosphere and release oxygen back to it. Our houses are made primarily of wood. We line our properties with trees to give us shade and privacy and also to reduce the wind that reaches our homes. Even the syrup we put on our pancakes is made from tree sap. One important species of tree, the sugar maple (Acer saccharum), is prized for both its sap and wood production. Therefore, it is important to know the growth pattern of the tree. How tall is it when it is, say, 50 years old? Thanks to data given to us by the United States Forest Service, you can now ask Wolfram|Alpha that exact question.
We normally don’t think about how involved alloys are in our day-to-day lives, but the roads and bridges we take to get to work, our cars, cell phones, computers, and even our homes and furniture often contain alloys. And people who create these objects need access to reliable and trustworthy sources of information about the physical properties of all types of alloys, so they can choose the right material for a particular application.
That’s why we’re pleased to announce that Wolfram|Alpha can now provide detailed information about more than 11,000 kinds of alloys, in response to simple, natural-language queries: