The Monsanto Papers 2018 Environment Glyphosate more commonly known as Roundup is the most widely used herbicide on the planet Its also the central cash cow for the agrochemical giant Monsanto Undeniably effective in controlling the growth of cropdestroying weeds the chemical is Watch now 844 Troubled Waters 2015 Environment In the midst of widespread pollution and the ill effects of climate change we tend to lose sight of another factor that threatens the vitality of our oceanic ecosystem overfishing Troubled Waters examines the longterm economic and environmental Watch now 892 The Dome 2017 Environment The Enewetak Atoll in the Marshall Islands a remote location nestled deep within the vast Pacific Ocean between Australia and Hawaii is a picturesque paradise in many respects Adorned by clear pale blue waters breathtaking skies and vivid Watch now 719 Black Snake Killaz 2017 Environment The Dakota Access Pipeline is designed to run from North Dakota to Illinois a 1200mile stretch of oil transport that could potentially impact many millions of lives An impassioned protest movement began to grow once the construction of the Watch now 741 The Rise of Vertical Farming 2017 Environment There are 74 billion people on the planet and all of them need to be fed Whats the most efficient and sustainable method for accomplishing this Traditional farming strategies have monopolized our natural resources and often prove wasteful and Watch now 878 Donald Trump The Koch Brothers and Their War on Climate Science 2017 Environment Our planet is riddled with floods rising sea levels severe weather drought and the highest temperatures in recorded history Up to 99 of climate scientists agree that the Watch now 715 Chernobyl The Exclusion Zone 2017 Environment Were used to seeing apocalyptic wastelands in our video games television shows and big screen movies But such an environment actually exists in the real world and its vacant landscape can be found near the border of Ukraine Its Chernobyl the Watch now 587 The Age of Mankind 2017 Environment According to Dutch scientist Paul Crutzen the planet is on the cusp of entering a new geological age the Anthropocene Produced by the VPRO Backlight documentary series The Age of Mankind verifies the evidence in support of Crutzens pronouncement Watch now 700 Shale Cowboys 2017 Environment The United States is on its way to complete energy independence thanks to the shale revolution Renewable energy sources like wind and solar are on the rise but thus far theyve been dwarfed by the plentiful reservoirs of shale gas and oil under the Watch now 698 Anthropocene 2016 Environment In geological terms were currently living in the Holocene stage of the Earths existence a period of time when all the elements have proven most beneficial to our species But our unfettered growth has left a massive footprint upon our planet and Watch now 870 Before the Flood 2016 Environment A devoted environmentalist actor Leonardo DiCaprio was named the United Nations Messenger on Climate Change in 2014 Hes by no means a scientist but his tremendous fame affords him the global platform and unfettered access required to effectively 763 Great Lakes Bad Lines 2016 Environment Many environmental documentaries recount the aftermath of a grave disaster Great Lakes Bad Lines is refreshingly different in this regard The film concerns the inevitable erosion and malfunction of Enbridge Line 5 a Canadianowned pipeline that Watch now 805 1 2 3 15

B I I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O


Houston Texans have enough assets to be active in trade talks by Jair Lopez 2 months ago Past trades have set the Houston Texans in great shape for the NFL trade deadline The Houston Texans will have the flexibility to be aggressive until the October 30 trade deadline due to last seasons trade that sent Pro Bowl left tackle Duane Brown to the Seattle Seahawks That trade netted them a 2018 third round pick which turned into rookie offensive lineman Martinas Rankin and a future 2019 second round pick In essence the Texans will have all their draft picks in the 2019 NFL Draft and possibly a very valuable second round pick from the Seahawks The Texans actually having a solid draft class in 2018 also gives them the ability to send draft picks for the right player The front office alongside the coaching staff has drafted several positions of need in the most recent draft addressing the secondary offensive line and tight end position Theyll be able to continue to monitor and develop safety Justin Reid offensive lineman Rankin and tight end Jordan Akins All three of the players have shown some promising upside in their first year in the league and the Texans could have possibly gotten good value in the midtolate rounds with wide receiver Keke Coutee tight end Jordan Thomas and linebackers Duke Ejiofor and Peter Kalambayi When teams hit on their draft picks theyre able to go in the trade market and be aggressive on veteran players knowing they have young talent on affordable rookie scale contracts for years to come Jason La Canfora from CBSSports reported that Pro Bowl cornerback Patrick Peterson could be one of the players that Arizona Cardinals could be willing to move in their rebuilding process La Canfora wrote RELATED PRODUCT JJ Watt Houston Texans Nike Alternate Game Jersey Red Peterson could be a potential blockbuster that would put the Cardinals in position to make significant noise in the next few drafts A player of Petersons caliber dont come available very often and with the injuries that have struck the secondary it would be prudent for Texans to inquire of his availability Josh Ferguson brings more depth to offense If the Cardinals are indeed looking to trade him having him in Houston could be beneficial due to the fact that the Texans arent the in the NFC conference with the Cardinals Load Comments

B I O O O O O O O B I O B I O O O O O O O O B I O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O


25 Great Pirate Bay Alternatives By Ernesto on August 22 2009 C 124 The end of the Pirate Bay is nearing Even if the deal with GGF doesnt go through the current owners are likely to sell to one of the other interested parties For many BitTorrent fans this means that they have to find an alternative Luckily there are plenty of good ones out there Replacing The Pirate Bay is easier said then done The tracker is currently responsible for approximately half of all public torrent transfers which represents a significant percentage of global Internet traffic However history has shown that BitTorrent users are an adaptive species that simply migrates to the next site when their home bases become uninhabitable While private trackers certainly have their place and will accommodate those lucky enough to get an invite for this article we are interested in sites that are open to everyone ranging from full Pirate Bay replacements to a doityourself setup If youre looking for high speed downloads you could also consider to try Usenet instead our Usenet guide Are you downloading torrents anonymous already Full Pirate Bay Alternatives The only full Pirate Bay alternatives are sites that index torrent files are open to everyone and also have a working tracker Unfortunately there are only a few sites out there that offer this full package there are four of them below We decided to include Demonoid here because it tracks many public torrents 1 Torrentbox 2 1337x 3 H33t 4 Demonoid semiprivate Torrent Indexers Torrent indexers are sites that have a searchable directory of torrent files but dont host a public tracker of their own Mininova has a tracker but they only allow featured torrents uploaded through their content distribution service The most used torrent indexers are 5 Mininova 6 isoHunt 7 Torrentreactor 8 BTjunkie Torrent MetaSeach Engines BitTorrent metasearch engines are yet another brand of torrent sites They dont have a tracker and dont host any torrent files on their servers Instead they search for and link to torrents hosted on third party sites 9 Torrentz 10 Nowtorrents 11 Qtorrents 12 TorrentFinder Private Trackers open signup Most of the larger private trackers require an invite to join but there are always a few that allow new members Below are four of these open private trackers and more can be found on Btracs 13 RTN 14 BiteMyTorrent 15 BitShock 16 TorrentIt Standalone BitTorrent Trackers Torrent indexers and metasearch engines can be used to find torrents but none of them will be of much use without a stable BitTorrent tracker Standalone BitTorrent trackers are much needed they handle the communication between downloaders but dont index any torrents themselves 17 OpenBitTorrent 18 PublicBitTorrent 19 The Hidden Tracker 20 DenisStalker DIY Pirate Bay Alternatives The last category of Pirate Bay alternatives are the doityourself projects By using the three ingredients below The Pirate Bay can be easily rebuilt It might take a few hours but then the path to world domination is clear 21 Pirate Bay Torrents Clone 22 Pirate Bay HTML Clone 23 Torrage Torrent API 24 Tracker Software Last but not Least Google the mother of all search engines has a filetypetorrent search command that allows you to find torrent files scattered across the Internet Also Googles custom search allows everyone to create their own torrent search engine Dont tell the MPAA and RIAA 25 Google If you think we missed any good alternatives please feel free to add your own in the comment section below while clearly noting which category they fit into

O O B I I O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I I O O O B I I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O B O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O B I I O O O O B I I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O


Russias Largest Torrent Site Celebrates 13 Years Online in a Chinese Restaurant By Andy on September 23 2017 C 54 Breaking RuTracker Russias largest torrent site is celebrating its 13th year online The huge site which creates torrents at a rate of more than 170000 per year has more than 15 million registered members Every single one over the age of 18 is invited to St Petersburg tonight to enjoy a Chinese meal together For most torrent fans around the world The Pirate Bay is the big symbol of international defiance Over the years the site has fought avoided and snubbed its nose at dozens of battles yet still remains online today But there is another site located somewhere in the east that has been online for nearly as long has millions more registered members and has proven just as defiant RuTracker for those who havent yet found it is a Russianfocused treasure trove of both local and international content For many years the site was frequented only by native speakers but with the wonders of tools like Google Translate anyone can use the site at the flick of the switch When people are struggling to find content its likely that RuTracker has it This position has attracted the negative attention of a wide range of copyright holders and thanks to legislation introduced during 2013 the site is now subject to complete blocking in Russia In fact RuTracker has proven so stubborn to copyright holder demands it is now permanently blocked in the region by all ISPs Surprisingly especially given the enthusiasm for blockades among copyright holders this doesnt seem to have dampened demand for the sites services According to SimiliarWeb against all the odds the site is still pulling in around 90 million visitors per month But the impressive stats dont stop there Impressive stats for a permanently blocked site This week RuTracker celebrates its 13th birthday a relative lifetime for a site that has been front and center of Russias most significant copyright battles trouble which doesnt look like stopping anytime soon Back in 2010 for example RUCenter Russias largest domain name registrar and webhosting provider pulled the plug on the sites former Torrentsru domain The Director of Public Relations at RUCenter said that the domain had been blocked on the orders of the Investigative Division of the regional prosecutors office in Moscow The site never got its domain back but carried on regardless despite the setbacks Back then the site had around 4000000 members but now seven years on its ranks have swelled to a reported 15382907 According to figures published by the site this week 778317 of those members signed up this year during a period the site was supposed to be completely inaccessible Needless to say its operators remain defiant Today we celebrate the 13th anniversary of our tracker which is the largest Russian and not only language media library on this planet A tracker strangely banished in the country where most of its audience is located in Russia a site announcement reads But despite the prohibitions with all these legislative obstacles with all these technical difficulties we see that our tracker still exists and is successfully developing And we still believe that the library should be open and free for all and not be subject to censorship or a victim of legislative and executive power lobbied by the monopolists of the media industry Its interesting to note the tone of the RuTracker announcement On any other day it couldve been written by the crew of The Pirate Bay who in their prime loved to stick a finger or two up to the copyright lobby and then rub their noses in it For the team at RuTracker that still appears to be one of the main goals Like The Pirate Bay but unlike many of the basic torrent indexers that have sprung up in recent years RuTracker relies on users to upload its content They certainly havent been sitting back RuTracker reveals that during the past year and despite all the problems users uploaded a total of 171819 torrents on average 470 torrents per day Interestingly the content most uploaded to the site also points to the growing internationalization of RuTracker During the past year the NBA NCAA section proved most popular closely followed by nonRussian rock music and NHL games NonRussian movies accounted for almost 2000 fresh torrents in just 12 months It is thanks to you this tracker lives the sites operators informed the users It is thanks to you that it was is and for sure will continue to offer the most comprehensive diverse and most importantly quality content in the Russian Internet You stayed with us when the tracker lost its original name torrentsru You stayed with us when access to a new name was blocked in Russia rutrackerorg You stayed with us when the sites trackers were blocked We will stay with you as long as you need us So as RuTracker plans for another year online all that remains is to celebrate its 13th birthday in style That will be achieved tonight when every adult member of RuTracker is invited to enjoy Chinese meal at the Tian Jin Chinese Restaurant in St Petersburg Turn up early seating is limited

O B I I O O O O O O O O O O O O O O O O O O O B I I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O B I I I I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O

largest torrent site
international defiance
located somewhere in the east


PC Gothic II PC By Torrents Games Share Email Comments Gothic II is a singleplayer roleplaying sequel in which you play as a lone hero who must do battle with bandits orcs and dragons in a sprawling 3D world Like in the first game you control a softspoken hero from a behindtheback perspective and follow one of three career paths in pursuit of his ultimate goalwhich in this case is to stave off an assault by orcs and dragons unleashed by the death of a demon the same one that he defeated at the end of the first game Your browser does not currently recognize any of the video formats available Click here to visit our frequently asked questions about HTML5 video Download torrent You need uTorrent for downloading torrent files Tags download Gothic 2 PC download Gothic 2 PC torrent download torrent Gothic 2 PC Gothic 2 PC download free Gothic 2 PC download torrent Gothic 2 PC free download Gothic 2 PC torrent Gothic 2 PC torrent download torrent download Gothic 2 PC torrent Gothic 2 PC torrent Gothic 2 PC download Email 53 Comments

O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O


A OneStop Shop for Principal Component Analysis Matt Brems Apr 17 2017 At the beginning of the textbook I used for my graduate stat theory class the authors George Casella and Roger Berger explained in the preface why they chose to write a textbook When someone discovers that you are writing a textbook one or both of two questions will be asked The first is Why are you writing a book and the second is How is your book different from whats out there The first question is fairly easy to answer You are writing a book because you are not entirely satisfied with the available texts I apply the authors logic here Principal component analysis PCA is an important technique to understand in the fields of statistics and data science but when putting a lesson together for my students I found that the resources online were too technical didnt fully address our needs andor provided conflicting information Its safe to say that Im not entirely satisfied with the available texts here As a result I wanted to put together the What When How and Why of PCA as well as links to some of the resources that can help to further explain this topic Specifically I want to present the rationale for this method the math under the hood some best practices and potential drawbacks to the method While I want to make PCA as accessible as possible the algorithm well cover is pretty technical Being familiar with some or all of the following will make this article and PCA as a method easier to understand matrix operationslinear algebra matrix multiplication matrix transposition matrix inverses matrix decomposition eigenvectorseigenvalues and statisticsmachine learning standardization variance covariance independence linear regression feature selection Ive embedded links to illustrations of these topics throughout the article but hopefully these will serve as a reminder rather than required reading to get through the article What is PCA Lets say that you want to predict what the gross domestic product GDP of the United States will be for 2017 You have lots of information available the US GDP for the first quarter of 2017 the US GDP for the entirety of 2016 2015 and so on You have any publiclyavailable economic indicator like the unemployment rate inflation rate and so on You have US Census data from 2010 estimating how many Americans work in each industry and American Community Survey data updating those estimates in between each census You know how many members of the House and Senate belong to each political party You could gather stock price data the number of IPOs occurring in a year and how many CEOs seem to be mounting a bid for public office Despite being an overwhelming number of variables to consider this just scratches the surface TLDR you have a lot of variables to consider If youve worked with a lot of variables before you know this can present problems Do you understand the relationships between each variable Do you have so many variables that you are in danger of overfitting your model to your data or that you might be violating assumptions of whichever modeling tactic youre using You might ask the question How do I take all of the variables Ive collected and focus on only a few of them In technical terms you want to reduce the dimension of your feature space By reducing the dimension of your feature space you have fewer relationships between variables to consider and you are less likely to overfit your model Note This doesnt immediately mean that overfitting etc are no longer concerns but were moving in the right direction Somewhat unsurprisingly reducing the dimension of the feature space is called dimensionality reduction There are many ways to achieve dimensionality reduction but most of these techniques fall into one of two classes Feature Elimination Feature Extraction Feature elimination is what it sounds like we reduce the feature space by eliminating features In the GDP example above instead of considering every single variable we might drop all variables except the three we think will best predict what the USs gross domestic product will look like Advantages of feature elimination methods include simplicity and maintaining interpretability of your variables As a disadvantage though you gain no information from those variables youve dropped If we only use last years GDP the proportion of the population in manufacturing jobs per the most recent American Community Survey numbers and unemployment rate to predict this years GDP were missing out on whatever the dropped variables could contribute to our model By eliminating features weve also entirely eliminated any benefits those dropped variables would bring Feature extraction however doesnt run into this problem Say we have ten independent variables In feature extraction we create ten new independent variables where each new independent variable is a combination of each of the ten old independent variables However we create these new independent variables in a specific way and order these new variables by how well they predict our dependent variable You might say Where does the dimensionality reduction come into play Well we keep as many of the new independent variables as we want but we drop the least important ones Because we ordered the new variables by how well they predict our dependent variable we know which variable is the most important and least important But and heres the kicker because these new independent variables are combinations of our old ones were still keeping the most valuable parts of our old variables even when we drop one or more of these new variables Principal component analysis is a technique for feature extraction so it combines our input variables in a specific way then we can drop the least important variables while still retaining the most valuable parts of all of the variables As an added benefit each of the new variables after PCA are all independent of one another This is a benefit because the assumptions of a linear model require our independent variables to be independent of one another If we decide to fit a linear regression model with these new variables see principal component regression below this assumption will necessarily be satisfied When should I use PCA Do you want to reduce the number of variables but arent able to identify variables to completely remove from consideration Do you want to ensure your variables are independent of one another Are you comfortable making your independent variables less interpretable If you answered yes to all three questions then PCA is a good method to use If you answered no to question 3 you should not use PCA How does PCA work The section after this discusses why PCA works but providing a brief summary before jumping into the algorithm may be helpful for context We are going to calculate a matrix that summarizes how our variables all relate to one another Well then break this matrix down into two separate components direction and magnitude We can then understand the directions of our data and its magnitude or how important each direction is The screenshot below from the setosaio applet displays the two main directions in this data the red direction and the green direction In this case the red direction is the more important one Well get into why this is the case later but given how the dots are arranged can you see why the red direction looks more important than the green direction Hint What would fitting a line of best fit to this data look like Our original data in the xyplane We will transform our original data to align with these important directions which are combinations of our original variables The screenshot below again from setosaio is the same exact data as above but transformed so that the x and y axes are now the red direction and green direction What would the line of best fit look like here Our original data transformed by PCA While the visual example here is twodimensional and thus we have two directions think about a case where our data has more dimensions By identifying which directions are most important we can compress or project our data into a smaller space by dropping the directions that are the least important By projecting our data into a smaller space were reducing the dimensionality of our feature space but because weve transformed our data in these different directions weve made sure to keep all original variables in our model Here I walk through an algorithm for conducting PCA I try to avoid being too technical but its impossible to ignore the details here so my goal is to walk through things as explicitly as possible A deeper intuition of why the algorithm works is presented in the next section Before starting you should have tabular data organized with n rows and p1 columns where there is one column corresponding to your dependent variable usually denoted Y and p columns corresponding to each of your independent variables the matrix of which is usually denoted X Separate your data into Y and X as defined above well mostly be working with X Take the matrix of independent variables X and for each column subtract the mean of that column from each entry This ensures that each column has a mean of zero Decide whether or not to standardize Given the columns of X are features with higher variance more important than features with lower variance or is the importance of features independent of the variance In this case importance means how well that feature predicts Y If the importance of features is independent of the variance of the features then divide each observation in a column by that columns standard deviation This combined with step 2 standardizes each column of X to make sure each column has mean zero and standard deviation 1 Call the centered and possibly standardized matrix Z Take the matrix Z transpose it and multiply the transposed matrix by Z Writing this out mathematically we would write this as Z ᵀ Z The resulting matrix is the covariance matrix of Z up to a constant This is probably the toughest step to follow stick with me here Calculate the eigenvectors and their corresponding eigenvalues of Z ᵀ Z This is quite easily done in most computing packages in fact the eigendecomposition of Z ᵀ Z is where we decompose Z ᵀ Z into PDP where P is the matrix of eigenvectors and D is the diagonal matrix with eigenvalues on the diagonal and values of zero everywhere else The eigenvalues on the diagonal of D will be associated with the corresponding column in P that is the first element of D is λ and the corresponding eigenvector is the first column of P This holds for all elements in D and their corresponding eigenvectors in P We will always be able to calculate PDP in this fashion Bonus for those interested we can always calculate PDP in this fashion because Z ᵀ Z is a symmetric positive semidefinite matrix Take the eigenvalues λ λ λ p and sort them from largest to smallest In doing so sort the eigenvectors in P accordingly For example if λ is the largest eigenvalue then take the second column of P and place it in the first column position Depending on the computing package this may be done automatically Call this sorted matrix of eigenvectors P The columns of P should be the same as the columns of P but perhaps in a different order Note that these eigenvectors are independent of one another Calculate Z ZP This new matrix Z is a centeredstandardized version of X but now each observation is a combination of the original variables where the weights are determined by the eigenvector As a bonus because our eigenvectors in P are independent of one another each column of Z is also independent of one another An example from setosaio where we transform five data points using PCA The left graph is our original data X the right graph would be our transformed data Z Note two things in this graphic The two charts show the exact same data but the right graph reflects the original data transformed so that our axes are now the principal components In both graphs the principal components are perpendicular to one another In fact every principal component will ALWAYS be orthogonal aka official math term for perpendicular to every other principal component Dont believe me Try to break the applet Because our principal components are orthogonal to one another they are statistically independent of one another which is why our columns of Z are independent of one another 8 Finally we need to determine how many features to keep versus how many to drop There are three common methods to determine this discussed below and followed by an explicit example Method 1 We arbitrarily select how many dimensions we want to keep Perhaps I want to visually represent things in two dimensions so I may only keep two features This is usecase dependent and there isnt a hardandfast rule for how many features I should pick Method 2 Calculate the proportion of variance explained briefly explained below for each feature pick a threshold and add features until you hit that threshold For example if you want to explain 80 of the total variability possibly explained by your model add features with the largest explained proportion of variance until your proportion of variance explained hits or exceeds 80 Method 3 This is closely related to Method 2 Calculate the proportion of variance explained for each feature sort features by proportion of variance explained and plot the cumulative proportion of variance explained as you keep more features This plot is called a scree plot shown below One can pick how many features to include by identifying the point where adding a new feature has a significant drop in variance explained relative to the previous feature and choosing features up until that point I call this the find the elbow method as looking at the bend or elbow in the scree plot determines where the biggest drop in proportion of variance explained occurs Because each eigenvalue is roughly the importance of its corresponding eigenvector the proportion of variance explained is the sum of the eigenvalues of the features you kept divided by the sum of the eigenvalues of all features Scree Plot for Genetic Data Consider this scree plot for genetic data Source here The red line indicates the proportion of variance explained by each feature which is calculated by taking that principal components eigenvalue divided by the sum of all eigenvalues The proportion of variance explained by including only principal component 1 is λλ λ λ p which is about 23 The proportion of variance explained by including only principal component 2 is λλ λ λ p or about 19 The proportion of variance explained by including both principal components 1 and 2 is λ λλ λ λ p which is about 42 This is where the yellow line comes in the yellow line indicates the cumulative proportion of variance explained if you included all principal components up to that point For example the yellow dot above PC2 indicates that including principal components 1 and 2 will explain about 42 of the total variance in the model Now lets go through some examples Method 1 We arbitrarily select a number of principal components to include Suppose I wanted to keep five principal components in my model In the genetic data case above these five principal components explains about 66 of the total variability that would be explained by including all 13 principal components Method 2 Suppose I wanted to include enough principal components to explain 90 of the total variability explained by all 13 principal components In the genetic data case above I would include the first 10 principal components and drop the final three variables from Z Method 3 Here we want to find the elbow In the scree plot above we see theres a big drop in proportion of variability explained between principal component 2 and principal component 3 In this case wed likely include the first two features and drop the remaining features As you can see this method is a bit subjective as elbow doesnt have a mathematically precise definition and in this case wed include a model that explains only about 42 of the total variability Note Some scree plots will have the size of eigenvectors on the Y axis rather than the proportion of variance This leads to equivalent results but requires the user to manually calculate the proportion of variance An example of this can be seen here Once weve dropped the transformed variables we want to drop were done Thats PCA But like why does PCA work While PCA is a very technical method relying on indepth linear algebra algorithms its a relatively intuitive method when you think about it First the covariance matrix Z ᵀ Z is a matrix that contains estimates of how every variable in Z relates to every other variable in Z Understanding how one variable is associated with another is quite powerful Second eigenvalues and eigenvectors are important Eigenvectors represent directions Think of plotting your data on a multidimensional scatterplot Then one can think of an individual eigenvector as a particular direction in your scatterplot of data Eigenvalues represent magnitude or importance Bigger eigenvalues correlate with more important directions Finally we make an assumption that more variability in a particular direction correlates with explaining the behavior of the dependent variable Lots of variability usually indicates signal whereas little variability usually indicates noise Thus the more variability there is in a particular direction is theoretically indicative of something important we want to detect The setosaio PCA applet is a great way to play around with data and convince yourself why it makes sense Thus PCA is a method that brings together A measure of how each variable is associated with one another Covariance matrix The directions in which our data are dispersed Eigenvectors The relative importance of these different directions Eigenvalues PCA combines our predictors and allows us to drop the eigenvectors that are relatively unimportant Are there extensions to PCA Yes more than I can address here in a reasonable amount of space The one Ive most frequently seen is principal component regression where we take our untransformed Y and regress it on the subset of Z that we didnt drop This is where the independence of the columns of Z comes in by regressing Y on Z we know that the required independence of independent variables will necessarily be satisfied However we will need to still check our other assumptions The other commonlyseen variant Ive seen is kernel PCA Conclusion I hope you found this article helpful Check out some of the resources below for more indepth discussions of PCA Let me know what you think especially if there are suggestions for improvement Ive been told that a Chinese translation of this article has been made available here Thanks Jakukyo Friel I want to offer many thanks to my friends Ritika Bhasker Joseph Nelson and Corey Smith for their suggestions and edits You should check Ritika and Joseph out on Medium their posts are far more entertaining than mine Corey is too focused on not getting his PhD research scooped to have a Medium presence I also want to give a huge ht to the setosaio applet for its visual and intuitive display of PCA Edit Thanks to Michael Matthews for noticing a typo in the formula for Z in Step 7 above He correctly pointed out that Z ZP not Z ᵀ P Thanks also to Chienlung Cheung for noticing another typo in Step 8 above and noted that I had conflated eigenvector with eigenvalue in one line

O O O O B I I O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O

principal component analysis
george casella


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B I I O B B O O O B I I O B O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O B O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O B O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O


Justia Trademarks Nonmetallic building materials TRUFORM ARMATURES Trademark Details TRUFORM ARMATURES Trademark Details Status 710 Cancelled Section 8 Serial Number 76700576 Registration Number 4118757 Word Mark TRUFORM ARMATURES Status 710 Cancelled Section 8 Status Date 20181102 Filing Date 20091127 Registration Number 4118757 Registration Date 20120327 Mark Drawing 4000 Standard character mark Typeset Published for Opposition Date 20101109 Attorney Name Terry L McCutcheon Law Office Assigned Location Code L20 Employee Name WEBSTER WILLIAM M Statements Disclaimer with Predetermined Text ARMATURES Goods and Services Sculptures and figurines composed primarily of a polymer foam material and that include rigid members made of the polymer foam materials or the polymer foam materials in combination with plastic plaster metal or combinations thereof able to be connected together using movable members made from aluminum other metals wires and other ductile materials Pseudo Mark TRUE FORM ARMATURES Classification Information International Class 019 Building materials nonmetallic nonmetallic rigid pipes for building asphalt pitch and bitumen nonmetallic transportable buildings monuments not of metal Building materials nonmetallic nonmetallic rigid pipes for building asphalt pitch and bitumen nonmetallic transportable buildings monuments not of metal US Class Codes 001 012 033 050 Class Status Code 2 Sec 8 Entire Registration Class Status Date 20181102 Primary Code 019 First Use Anywhere Date 20110415 First Use In Commerce Date 20110415 Correspondences Name TERRY L MCCUTCHEON Address Please log in with your Justia account to see this address Trademark Events Event Date Event Description 20091203 NEW APPLICATION OFFICE SUPPLIED DATA ENTERED IN TRAM 20091208 APPLICATION FILING RECEIPT MAILED 20100303 ASSIGNED TO EXAMINER 20100304 NONFINAL ACTION WRITTEN 20100305 NONFINAL ACTION MAILED 20100831 PAPER RECEIVED 20100914 ASSIGNED TO LIE 20100914 CORRESPONDENCE RECEIVED IN LAW OFFICE 20100914 AMENDMENT FROM APPLICANT ENTERED 20100929 APPROVED FOR PUB PRINCIPAL REGISTER 20101004 LAW OFFICE PUBLICATION REVIEW COMPLETED 20101020 NOTICE OF PUBLICATION 20101109 PUBLISHED FOR OPPOSITION 20110104 NOA MAILED SOU REQUIRED FROM APPLICANT 20110629 PAPER RECEIVED 20110630 CASE ASSIGNED TO INTENT TO USE PARALEGAL 20110629 USE AMENDMENT FILED 20110705 STATEMENT OF USE PROCESSING COMPLETE 20110722 SU NONFINAL ACTION WRITTEN 20110722 NONFINAL ACTION MAILED 20120120 PAPER RECEIVED 20120131 CORRESPONDENCE RECEIVED IN LAW OFFICE 20120131 AMENDMENT FROM APPLICANT ENTERED 20120213 ALLOWED PRINCIPAL REGISTER SOU ACCEPTED 20120217 LAW OFFICE REGISTRATION REVIEW COMPLETED 20120218 NOTICE OF ACCEPTANCE OF STATEMENT OF USE MAILED 20120327 REGISTEREDPRINCIPAL REGISTER 20181102 CANCELLED SEC 8 6YR Today on Verdict Federal Lawsuit Tests Constitutionality of Arizona Statute for Filling US Senate Vacancy Created by John McCains Death Part One in a Series In this first of a series of columns Illinois law dean and professor Vikram David Amar comments on a lawsuit filed in federal court in Arizona that challenges the way state officials are handling the vacancy in the US Senate created by Senator John McCains death four months ago Question 120 Find a Lawyer Lawyers Get Listed Now Get a free directory profile listing

B O O O O B I O O B I O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O


Imports in Cambodia decreased to 573910 KHR Billion in June from 597930 KHR Billion in May of 2018 Imports in Cambodia averaged 479110 KHR Billion from 2009 until 2018 reaching an all time high of 10591 KHR Billion in December of 2013 and a record low of 228510 KHR Billion in February of 2014 Historical Data API 1Y 5Y 10Y MAX Compare Cambodia Trade Last Previous Highest Lowest Unit Balance of Trade 65940 195420 36320 375300 KHR Billion Current Account 325210 227320 24880 325210 KRH Billion Current Account to GDP 710 880 820 1300 percent Imports 573910 597930 1059100 228510 KHR Billion Exports 507970 402510 742080 171060 KHR Billion Tourist Arrivals 40781300 41917100 70188600 28378700 Gold Reserves 1240 1240 1244 1240 Tonnes Terrorism Index 004 008 350 004 Exports by Country Exports by Category Imports by Country Imports by Category Cambodia Imports Cambodia mainly imports petroleum products fabrics vehicles wholesale yarn cigarettes electrical communications equipment and medicine Cambodias main import partners are China Thailand Hong Kong Viet Nam Taiwan and South Korea This page provides Cambodia Imports actual values historical data forecast chart statistics economic calendar and news Cambodia Imports actual data historical chart and calendar of releases was last updated on January of 2019 Actual Previous Highest Lowest Dates Unit Frequency 573910 597930 1059100 228510 2009 2018 KHR Billion Monthly Export Data API

B I I O O O O O O O O O O O O O O O B I I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O


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Time Estimate About 15 mins Topics Learning Objectives Overview of Objects Get to Know Objects Create a Custom Object Get to Know Fields Create a Custom Field Create a Record Customize Responsibly Resources Challenge 500 points Question feedback or help Understand Custom Standard Objects Attention Trailblazer Salesforce has two different desktop user interfaces Lightning Experience and Salesforce Classic This module is designed for Lightning Experience You can learn about switching between interfaces enabling Lightning Experience and more in the Lightning Experience Basics module here on Trailhead Learning Objectives After completing this unit youll be able to Describe the perks of using objects on the Salesforce platform Explain the difference between standard objects and custom objects List the types of custom fields an object can have Overview of Objects DreamHouse is a realty company that provides a way for customers to shop for homes and contact realtors online DreamHouse brokers use some of Salesforces standard functionality like contacts and leads to track home buyers But when it comes to selling houses there are a lot more things they want to track For example Salesforce doesnt include a standard way to track properties How is DreamHouse supposed to know which homes they have for sale or how much each home costs Luckily their Salesforce admin DAngelo knows that the Salesforce platform offers a solution Well work with DAngelo to see what hes building Lets start with the data model A data model is more or less what it sounds like Its a way to model what database tables look like in a way that makes sense to humans If youre not familiar with databases think about storing data in a spreadsheet For example DAngelo can use a spreadsheet to track all DreamHouses properties Columns can store the address cost and other important attributes Rows can store this information for each property that DreamHouse is selling Database tables are set up in a similar way But looking at data in tables isnt ideal for humans Thats where the data model comes in In Salesforce we think about database tables as objects we think about columns as fields and rows as records So instead of an account spreadsheet or table we have an Account object with fields and a bunch of identically structured records When we talk about the data model were talking about the collection of objects and fields in an app Lets learn more about objects and fields so you can start building your own data model Get to Know Objects Salesforce supports several different types of objects There are standard objects custom objects external objects platform events and BigObjects In this module we focus on the two most common types of objects standard and custom Standard objects are objects that are included with Salesforce Common business objects like Account Contact Lead and Opportunity are all standard objects Custom objects are objects that you create to store information thats specific to your company or industry For DreamHouse DAngelo wants to build a custom Property object that stores information about the homes his company is selling Objects are containers for your information but they also give you special functionality For example when you create a custom object the platform automatically builds things like the page layout for the user interface Create a Custom Object Lets work alongside DAngelo to see how he builds the Property object We need this object later so dont skip these steps Scroll to the bottom of this page Click the arrow next to Launch and select Create a Trailhead Playground Dont skip this step You need to use a fresh and clean Trailhead Playground for this module Once your TP is created it takes a minute press Launch Click the gear icon at the top of the page and launch setup Click the Object Manager tab Click Custom Object in the top right corner For Label enter Property Notice that the Object Name and Record Name fields autofill For Plural Label enter Properties Check the box for Launch New Custom Tab Wizard after saving this custom object Leave the rest of the values as default and click Save Select your desired Tab Style and click Next Next and Save Great job You just created your first custom object Now lets talk about adding fields to this object Get to Know Fields Every standard and custom object has fields attached to it Lets get familiar with the different types of fields Field Type What is it Can I get an example Identity A 15character casesensitive field thats automatically generated for every record You can find a records ID in its URL An account ID looks like 0015000000Gv7qJ System Readonly fields that provide information about a record from the system like when the record was created or when it was last changed CreatedDate LastModifiedById and LastModifiedDate Name All records need names so you can distinguish between them You can use text names or autonumbered names that automatically increment every time you create a record A contacts name can be Julie Bean A support cases name can be CA1024 Custom Fields you create on standard or custom objects are called custom fields You can create a custom field on the Contact object to store your contacts birthdays Identity system and name fields are standard on every object in Salesforce Each standard object also comes with a set of prebuilt standard fields You can customize standard objects by adding custom fields and you can add custom fields to your custom objects Every field has a data type A data type indicates what kind of information the field stores Salesforce supports a bunch of different data types but here are a few youll run into Checkbox for fields that are a simple yes or no a checkbox field is what you want Date or DateTime these field types represent dates or datetime combinations like birthdays or sales milestones Formula this special field type holds a value thats automatically calculated based on a formula that you write For example DAngelo can write a formula field that automatically calculates a real estate agents commission on a home sale Again there are quite a few field types but most of them are fairly selfexplanatory The important takeaway here is that you want to think about what kind of data youre trying to store when you create a custom field Create a Custom Field The Property object we just created is pretty barebones Lets add some custom fields to it Head back to your Trailhead Playground From Setup go to Object Manager Property In the sidebar click Fields Relationships Notice that there are already some fields there Theres a name field and some of the system fields we talked about earlier Click New in the top right For data type select Currency Click Next Fill out the following Field Label Price Description The listed sale price of the home Check the Required box Click Next Next again and then Save Youll see your new Price field in the list of Property fields In the Field Name column notice that it says Price__c The __c part is an easy way to tell that a particular field is a custom field Create a Record Lets create a property record to see what you did From the App Launcher at the top of the page select Sales Click the Properties tab in the navigation bar If you dont see it look under the dropdown Click New in the top corner Enter a name and price for the property and click Save Awesome Youll see something like this Customize Responsibly While it can seem easy to add and customize objects remember that whats going on under the hood is technically complicated Here are some best practices to keep in mind as you start customizing your own org Be thoughtful about names Once you start creating a bunch of objects it can be tempting to give them lazy names For example if DAngelo created another custom object to track condominiums he might be tempted to name it Property2 instead of Condominium Thats a recipe for confusion in your org Give your objects and fields descriptive unique names to improve clarity Help out your users Even with careful naming your users might not always be clear about the purpose of a particular object or field Include descriptions for your custom objects and fields For specialized or complicated customizations use help text to give more details Require fields when necessary Sometimes youll want to force your users to fill out a field when theyre creating a record on a certain object Every property needs a price right Make important fields required to avoid incomplete data Resources Customize Your Salesforce Org Store Information Thats Unique to Your Organization Circle of Success Getting Started with SF customizations Customer Success Community Remember this module is meant for Lightning Experience When you launch your handson org switch to Lightning Experience to complete this challenge

O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O B I O O O O O O O O O O O O B I B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O

dreamhouse
realty company
realtors online


EMI Goes Green Student course materials will no longer be available in printed format as common practice about EMIs efforts to go green and details about downloading student materials Due to the lapse in federal funding this website will not be actively managed More College List NEW Information Resources Institutional Resources Educational Resources Higher Ed Program Campus Emergency Management Resources The College List Emergency Management Programs Bachelor Degrees Adelphi University Bachelor of Science in Emergency Management Adelphi University BS in Emergency Services Administration American Public University Bachelor of Arts in Emergency and Disaster Management Anderson University Bachelor of Emergency Services Management Arizona State University Bachelor of Applied Science in Emergency ManagementHomeland Security Arizona State University Bachelor of Science Public Service and Public Policy Emergency ManagementHomeland Security Arkansas State University Bachelor of Science in 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Security University of Central Missouri Bachelor of Science Degree in Crisis and Disaster Management University of Central Florida BABS in Emergency Management University of Findlay Bachelor of Science in Environmental Safety and Occupational Health Management University of Nebraska at Omaha Bachelor of Science in Emergency Management University of Nebraska at Omaha Minor in Emergency Management University of North Texas Bachelor of Science Degree in Emergency Management University of North Texas BS in Emergency Admin and Planning Utah Valley University Bachelor of Science in Emergency Services AdministrationEmergency Management Upper Iowa University Bachelor of Science in Emergency Disaster Management Voorhees College Bachelor of Science Major in Emergency Management and Homeland Security Waldorf University BAS in Emergency Management with Optional Concentrations in Fire Science or Homeland Security Waldorf University BA in Emergency Management with Optional Concentrations in Fire Science or Homeland Security West Texas AM University Emergency Management Administration Bachelor of Applied Arts and Science Western Carolina University Online Bachelor of Science Degree in Emergency Management Western Illinois UniversityBachelor of Science Degree in Emergency Management

O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I I B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O

emergency management programs
bachelor degrees


Penthouses for sale in USA 27 listings Subscribe to notifications Order by price low to high price high to low newest first Elite penthouse with a pool and panoramic views in a new residence with a beach a spa a fitness center and jacuzzis Bal Harbour USA 18175000 Total area 721 m 4 bedrooms 7 bathrooms Penthouse with an elevator a rooftop terrace with a pool and panoramic views in a fullservice residence with a private beach Miami Beach 10900000 Total area 574 m 3 bedrooms 3 bathrooms Golden Visa Investment project in Athens with 92 yield 854295 Total area 500 m Operating Incomе 69073 IRR 1212 Threestorey penthouse with a rooftop pool a SPAcomplex and terraces with ocean views in an elite residence in Miami USA Price on request Total area 1780 m 6 bedrooms 9 bathrooms Comfortable penthouse in a new residential complex with a cinema a fitness center hotels and clubs not far from the beaches Sunrise USA 1100000 Total area 158 m 3 bedrooms 4 bathrooms Twolevel penthouse with a garage a private boat slip an elevator and picturesque views in a comfortable residence Fort Lauderdale USA 3450000 Total area 673 m 3 bedrooms 3 bathrooms Penthouse with terraces and balconies in a residence with gardens aroundtheclock security and a business center Coral Gables USA 2836000 Total area 352 m 5 bedrooms 4 bathrooms Threelevel penthouse with a swimming pool lounges and an elevator in a comfortable residence with a theatre and clubs Sunny Isles Beach Price on request Total area 1561 m 6 bedrooms 9 bathrooms Fullfloor penthouse with a media room and large terraces in a new highrise residence with aroundtheclock security and an aquapark Miami 18382000 Total area 1070 m 5 bedrooms Luxury penthouse with a large terrace a private entrance and an ocean view in a residence with a rooftop pool with a jacuzzi Miami Beach 6450000 Total area 444 m 3 bedrooms 3 bathrooms Penthouse with a swimming pool a rooftop terrace and a view of the city Dallas Texas USA 4800000 Total area 472 m 3 bedrooms 5 bathrooms Penthouse with panoramic windows and spectacular views of the river in a modern residential complex Portland Oregon USA 1320000 Total area 189 m 2 bedrooms 3 bathrooms Penthouse with fireplace glass walls and panoramic windows with the best views of the Skioto river Columbus Ohio USA 858000 Total area 243 m 2 bedrooms 3 bathrooms Duplex penthouse with a fireplace and private deck overlooking the Jamison Square Portland Oregon USA 1725000 Total area 222 m 3 bedrooms 3 bathrooms Trophy twolevel penthouse with spacious terraces in a highrise residence with a pool a cinema and a fitness center Manhattan New York 48000000 Total area 1114 m 8 bedrooms 8 bathrooms Duplex penthouse with panoramic views in a residential complex with a pool a fitness room a spa and a rooftop terrace Columbus Ohio USA 1249000 Total area 451 m 3 bedrooms 5 bathrooms Penthouse overlooking the waterfront Skioto in prestigious residential complex with private terrace and a gym Columbus Ohio USA 2700000 Total area 208 m 3 bedrooms 5 bathrooms Penthouse in Birmingham USA Two fireplaces spacious balcony four parking spaces 799000 3 bedrooms 4 bathrooms Furnished penthouse with a sauna a gym and a terrace with a private pool and a jacuzzi in a prestigious district of Charleston USA 3395000 Total area 436 m 4 bedrooms 5 bathrooms Twolevel penthouse in Atlanta USA Apartment with two balconies and panoramic views in a condominium with a conference room and a library 550000 Total area 187 m 2 bedrooms 3 bathrooms Penthouse with panoramic views of the city and the mountains in a highend residence Denver USA 5000000 Total area 596 m 3 bedrooms 4 bathrooms Modern penthouse with a terrace and a views of the city New York USA 39000000 Total area 836 m 10 bedrooms 10 bathrooms Spacious penthouse with a terrace in a residence with a fitness center a swimming pool and a library New York USA 37500000 Total area 540 m 4 bedrooms 5 bathrooms Modern twolevel penthouse with two elevators and panoramic views in a luxury comfortable residence with a pool and a spa New York USA 65000000 Total area 628 m 4 bedrooms 4 bathrooms Exclusive penthouse with a panoramic views of the city and park New York USA 65000000 Total area 628 m 4 bedrooms 4 bathrooms Modern twolevel penthouse with an elevator in a residence with a parking and a garden Washington DC USA 4795000 Total area 422 m 4 bedrooms 4 bathrooms Twolevel penthouse in Phoenix USA Apartment with a large balcony of 75 m and panoramic views 1149000 Total area 165 m 2 bedrooms 3 bathrooms Fullfloor penthouse with a view of the city in a residence with a swimming pool in the center of Dallas Texas USA 1550000 Total area 600 m Need to know in USA Prices from 3100 to 17700 USDm Document registration in 3045 days Loans from 3 per annum for up to 15 years Tax from 02 to 05 on purchases Property maintenance from 1 to 4 of the property price per annum Residence permit with investments from 500000 USD EB5 programme to attract foreign investors All publications 47 articles Tranios managers are here to help you select a property Kseniya Kolesnikova Real Estate Expert Tranio in USA 44 20 3608 1267 How we work Send a request When you submit a request you agree to our terms and conditions

B O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O


Take Action Against AntiTrans Legislation Now The 2018 legislative session is winding down and we while we have seen another wave of antitrans state bills introduced across the country fortunately most of these bills are either inactive or have failed Since the beginning of 2018 10 states have introduced 21 antitrans bills and 2 states are considering antitrans ballot initiatives Check back for updates or to get an email when there is an urgent action needed in your state LEGEND Health care bills Bills that restrict transgender peoples access to health care ID bills Bills that limit transgender peoples ability to update their identity documents like drivers licenses and birth certificates Discrimination carveouts Bills that allow discrimination against transgender people by creating special exceptions to existing laws Restroom bills Bills that restrict transgender peoples access to restrooms and other singlesex facilities Preemption bills Bills that override municipal and countylevel antidiscrimination laws Youth bills Bills that restrict transgender students rights at school or in child welfare settings Action Alert Check out the shaded text for opportunity to take action Read more about what the different bill statuses mean Jump to your state by clicking below Alaska Indiana Iowa Kentucky Massachusetts Missouri New Hampshire Oklahoma Pennsylvania South Dakota Tennessee Washington ALASKA No antitrans bills have been introduced in this state but there was a ballot initiative in Anchorage attacking trans people On April 3 2018 voters in Anchorage rejected the discriminatory Proposition 1 INDIANA Defeated Bills Senate Bill 65 Type of bill Youth What it does This bill prohibits teachers from talking about gender identity or sexual orientation without special permission from parents Status SOGI langugage removed in final version of bill IOWA Defeated Bills House File 2164 Type of bill Restroom What it does Allows businesses and schools to bar transgender people from restrooms that match their gender and expands exemptions that allow antiLGBTQ discrimination Status Died in committee Senate File 2296 Type of bill Restroom What it does Prohibits transgender students from accessing multiple occupancy restrooms that match their gender identity Status Died in committee KENTUCKY Defeated Bills House Bill 326 Type of bill Restroom Youth What it does Forces transgender students to use restrooms on the basis of their sex assigned at birth and allows people to sue schools if they encounter a transgender student in the restroom Status Died in committee MASSACHUSETTS No antitrans bills have been introduced in this state but there is a ballot initiative attacking trans people up for a vote in November 6 2018 to find out how you can get involved MISSOURI Defeated Bills House Bill 1755 Type of bill Restroom What it does Requires all public multiuser restrooms in the state to be genderdivided and prohibits local laws in conflict with this requirement Status Died in committee Senate Bill 690 Type of bill Restroom Youth What it does Requires transgender students to use restrooms in public schools according to their birth certificate Status Died in committee NEW HAMPSHIRE Defeated Bills House Bill 1341 Type of bill Health Care Youth What it does Makes it a form of child abuse to provide transitionrelated medical care including puberty blockers and hormone therapy to a minor Status Committee ruled inexpedient to legislate House Bill 1532 Type of bill Health Care Youth What it does Makes it illegal for physicians to provide transitionrelated surgical care to people under the age of 18 Status House voted against bill House Bill 1560 Type of bill Health Care What it does Prohibits people on New Hampshire Medicaid from getting coverage for transitionrelated care like hormone therapy and surgeries Status House voted against bill House Bill 1787 Type of bill Discrimination CarveOuts What it does Creates religious exemptions giving health care providers a broad license to discriminate against transgender people and to refuse to provide medically necessary transitionrelated and reproductive care Status Committee ruled inexpedient to legislate OKLAHOMA Defeated Bills Senate Bill 1223 Type of bill Restroom What it does Bars transgender students from using public school restrooms that match their gender and allows students to sue schools if they encounter a transgender person in the restroom Status Died in committee Senate Bill 1250 Type of bill Health Care What it does Creates sweeping exemptions allowing discrimination against transgender and other LGBTQ people in health care adoption access to restrooms and other areas Status Died in committee PENNSYLVANIA House Bill 1933 Type of bill Health Care What it does Prohibits Medicaid and the Childrens Health Insurance Program CHIP from covering care related to gendertransition including conseling doctors visits and hormone therapy Status Pending final house vote SOUTH DAKOTA Defeated Bills House Bill 1296 Type of bill Restrooms Youth What it does Attempts to target transgender students by requiring each school to adopt policies regarding transgender students restroom use Status Died in committee Senate Bill 202 Type of bill Restroom What it does Stigmatizes transgender people by requiring any place that doesnt have an explicit antitrans bathroom policy to include a sign on the door of its multiuser restrooms saying that a transgender person might be in there Status Died in committee Senate Bill 160 Type of bill Youth What it does Prohibits gender identity and gender expression education program for public school students in grades K7 Status Died in committee TENNESSEE Defeated Bills House Bill 0888 Type of bill Restroom Youth What it does Requires transgender K12 and college students to use restrooms in public schools according to their original birth certificate Status Died in committee House Bill 2620 Type of bill Restroom Youth What it does Requires the state to provide legal defense for schools and school employees that adopt antitrans restroom bans Status Died in committee Senate Bill 2480 Type of bill Restroom Youth What it does Requires the state to provide legal defense for schools and school employees that adopt antitrans restroom bans Status Died in committee House Bill 1488 Type of bill Restroom Youth What it does This bill would have required the state to defend schools in court if they are sued for excluding transgender students from restrooms matching their gender and required the state to cover legal costs Status Withdrawn WASHINGTON Defeated Bills House Bill 1011 Type of bill Restroom What it does Creates a carveout in the state nondiscrimination law allowing schools governments businesses and other entities to bar transgender people from restrooms matching their gender Status Died in committee Make sure you get urgent emails about bills from your state from NCTE by signing up here Note If any of the above is out of date please let us know here

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