text:
Stock_lurker The company stated they have signed a "number" of NDA's. Can't imagine a better source than that. Your posts continue to confound me. One day you have sold out and the next day you claim to have shares. likewise you seem to like to argue with anyone with a positive post. Either you have a split personality or you are a day trading short or you just like to hang around for no apparent reason.
bearofbleecker Any ground floor biotech's worth looking at should I suddenly find myself floating in cash?
I have said before I would be happy if MDVN sold Xtandi and distributed the majority of the cash to shareholders and kept talazaparib. They could hold back enough money for future expenses or perhaps shop for other compounds as well.
Two options, both quite good:
1. The other reported suitors get into a bidding war.
2. They go it alone growing at an estimated 30% a year while awaiting results from multiple late stage trials and possible expansion of Xtandi.
Having already received a round of bids makes sense given the new Sanofi offer was quickly followed by a rejection and than NDA agreement . They could have been told they have already been outbid and than invited to the table for further due diligence and possible new bid.
Partnership? They have one with Astellas already.
The only one dreaming here is you. You continue to ignore the obvious and assume the unlikely. You think MDVN folded because they were going to lose the vote? It was Sanofi that raised their bid (still to low) in order to participate. Something that has been sugested here for weeks. They have also agreed to discontinue their board takeover for six months. Does this sound to you like the vote was going their way? As for other bidders they have now confirmed there are a number of suitors. Your earlier posts that Sanofi would bribe Vanguard to vote their way is sadly one of your more typical paranoid ramblings. Of course you also told us you sold your position here so I would say you are batting 0.00
This is the first time MDVN has confirmed what had been reported earlier. That there are a "number" of suitors.
"MDVN) today announced that it has entered into confidentiality agreements with a number
of parties that have expressed interest in exploring a potential transaction and demonstrated that interest to the Board of Directors' satisfaction. Medivation also
confirmed that it entered into a confidentiality agreement with Sanofi and that Sanofi agreed to terminate its consent solicitation."
SEC form merely details what is already being reported in the news.
The sweetened offer removes the you got to be joking label from their original bid and allows them a peak at the books. Guess they should have read the posts here which had been advising that all along.
Why won't they extend the same to SNY? I have suggested before, and its the only think I can think of that makes sense, is that SNY seriously #$%$ them off. I suspect they threatened the company with exactly what they are doing now after a take it or leave it low ball offer. Otherwise there would be absolutely no harm done in negotiating or opening the books to them as is supposedly being done with others. It also fits with SNY's crazy takeover attempt without raising its bid. They want it and they don't want to pay more than $52.50.
@Hitest I will patiently await your thumbs down
Not sure how much talking to the board is going on while they are actively trying to oust them. There have been and most likely continues to be some bad feelings there.
SNY is a bit biased in its reporting of who else may be interested. As for forcing MDVN's hand if all other suitors disappear, remember this company was not seeking a sale. Going it alone is a very enticing option, there is no need to sell. Certainly not at a fire sale price.
If MDVN goes it alone with its five year estimated 35% annual growth think of what it will be worth a year or two from now. Meanwhile Sanofi's growth is estimated to be 7%. Who needs who? MDVN has been rumoured to be sought after by other companies for years. That will continue and the price will continue to go up.
Approaching the half way mark for voting. Getting to be a bit late for SNY to increase the bid. This was why I was curious if they get vote updates as it may spur them to change their questionable tactics if they were to see the vote going against them.
I am curious, does anyone know?. Does MDVN and SNY know how the votes are being cast or are they clueless until the final count?
I know they prefer not to sell but your statement of no intention to sell is not true. Everything is for sale at the right price. $52.50 was a joke and was treated as such. Hiring an adviser and entering into NDA's with others would suggest they will entertain SERIOUS offers. I have already voted and stuck with the current board, a board that has a proven record.
bettertrade you are correct. They can up there offer or withdraw their offer, the only thing stopping them is themselves. They have stated though they want to see the books before they up it. As I have stated several times, their strategy was (and continues to be) very poor. If they get 20% of the vote I will be very surprised without some major market melt down or an increased offer. But it may even be to late for that.
Here is how Sanofis last CVR has gone. Looks like a great company to do buisness with.
"But so far the CVR hasn't panned out too well for the acquired party. Already, $2 per share of additional value has been lost because two of the early milestones out of a total of six have not been reached. The remaining $10 per share of additional potential value has yet to be determined, but according to a May report by analysts at Jefferies, the likelihood of them being paid is low.
Also notable is ongoing litigation associated with the Genzyme CVR, which alleges that Sanofi has basically stalled the development of Lemtrada, a treatment for multiple sclerosis, resulting in the failure to meet any of its sales milestones. The litigation also claims that investors haven't gotten the $708 million they were owed in connection with the CVR."
stock-lurker Define declining revenues for us genius.


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text:
|Name: _________________________
|Period: ___________________
This test consists of 5 multiple choice questions, 5 short answer questions, and 10 short essay questions.
Multiple Choice Questions
1. How does Peter die?
(a) He is killed by Joseph.
(b) He has taken ill.
(c) He fell from one deck of the ship to the one below it.
(d) He is hit by a Oankali stinger.
2. Where does Lilith learn she is?
(a) On a space ship.
(b) Far underground near the continent of Australia.
(c) She does not yet know.
(d) Far underground near the continent of Antarctica.
3. What does Jdahya explain about the space ship?
(a) It grows as more space is needed.
(b) It is in charge of all the Earth captives.
(c) It is alive.
(d) It is able to burrow under the ground for protection against the nuclear wastes.
4. Why does Joseph come to Lilith's room?
(a) He wants to marry a human woman.
(b) He has become her lover.
(c) He has questions about the earth.
(d) He wants to help lead the group.
5. In Chapter 10 Lilith is changed so she can do what?
(a) Heal instantly.
(b) Open doors on the Oankali ship.
(c) Repell attackers with her mind.
(d) Levitate objects.
Short Answer Questions
1. What human does Lilith wake first?
2. What does Lilith find when she returns from gathering supplies in Chapter 8?
3. What does Nikanj say the other humans are saying about Joseph and Lilith?
4. Where does Nikanj have to go in Chapter 11?
5. Why does Lilith only wake women at first?
Short Essay Questions
1. What does Lilith do when several men try to rape a woman?
2. What does Jdahya tell Lilith about the sexes of the Oankali?
3. What does Lilith find out about her memory when she allows Nikanj to work on her?
4. In Chapter Nine, Nursery, why is Joseph angry at Lilith and what happens when they argue?
5. Who is in the room when Lilith wakes in Chapter 2 and what does she learn?
6. What does Lilith watch Jdahya do when they leave the room and what is his explanation of his action?
7. Who does Lilith meet in Chapter One of Dawn and how does she feel about Jdahya?
8. What does Jdahya tell Lilith the Oankali have discovered about the human species?
9. What does Lilith do before she wakes any humans and who does she decide to wake first?
10. What two men are the first to be awaken by Lilith, what do they think of Lilith's story and what does one of them say about their return to earth?
This section contains 947 words
(approx. 4 pages at 300 words per page)


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Home > Press > Abraxis BioScience and the California NanoSystems Institute Announce Partnership for Collaborative Research in the Development of New Nanobiotechnolog
Abraxis BioScience, Inc. (NASDAQ:ABBI), an integrated, global biopharmaceutical company, and the California NanoSystems Institute at UCLA today announced a partnership designed to collaborate on early research in nanobiotechnology for the advancement of new technologies in medicine.
Abraxis BioScience will collaborate with the CNSI and its team of leading researchers to capitalize on the explosion of scientific insight and create the future of nanotechnology within biotechnology. Abraxis has agreed to contribute $10 million over ten years to fund collaborative projects in the new CNSI building at UCLA. The Abraxis/CNSI Research Collaboration Lab space will focus on "translational science," where scientific discovery is intended to quickly be translated into practical application.
Abraxis BioScience has joined the CNSI Partners Program and is the Institute's first partner in the area of pharmaceuticals and biotechnology. The partnership provides CNSI and Abraxis researchers the opportunity to jointly pursue innovative approaches to the diagnosis and treatment of life-threatening diseases, leveraging the complementary resources and skills of both organizations. To further support the partnership, visiting scholars from other institutions will also be participating in the collaborative research programs.
"We are very excited about this research collaboration with the CNSI and believe this type of relationship emphasizes our commitment toward pursuing innovative research and forging new paradigms of drug discovery and personalized drug development," said Patrick Soon-Shiong, M.D., Chairman and Chief Executive Officer of Abraxis BioScience. "This relationship allows both organizations to gain access to important research that may have the potential to change the way diseases are treated."
"We are eager to collaborate with Abraxis BioScience. Cross-disciplinary collaboration is vital to our research efforts," said Dr. Fraser Stoddart, Director of the CNSI and Fred Kavli Chair of NanoSystems Sciences at UCLA. "The exciting thing about nanosystems research is that it is bringing about a sea change in the academic environment - it is breaking down the barriers between disciplines to achieve a seamless integration between chemistry, physics, biology and engineering in all of their different forms."
"Abraxis has an established history of developing innovative technology," said Dr. Leonard H. Rome, Associate Director of the CNSI and Senior Associate Dean for Research at the David Geffen School of Medicine, UCLA. "We are confident they will be a strong and committed partner in furthering important research and the development of drugs to treat life-threatening and debilitating illnesses."
About Abraxis BioScience, Inc.
Abraxis BioScience, Inc. is an integrated global biopharmaceutical company dedicated to meeting the needs of critically ill patients. The company develops, manufactures and markets one of the broadest portfolios of injectable products and leverages revolutionary technology such as its nab™ platform to discover and deliver breakthrough therapeutics that transform the treatment of cancer and other life-threatening diseases. The first FDA approved product to use this nab platform, ABRAXANE®, was launched in 2005 for the treatment of metastatic breast cancer. Abraxis trades on the Nasdaq Global Market under the symbol ABBI. For more information about the company and its products, please visit http://www.abraxisbio.com .
About the CNSI
The California NanoSystems Institute (CNSI) is a multidisciplinary research center at UCLA whose mission is to encourage university–industry collaboration and to enable the rapid commercialization of discoveries in nanosystems. CNSI members include some of the world's preeminent scientists, and the work conducted at the institute represents world-class expertise in five targeted areas of nanosystems-related research: renewable energy, environmental nanotechnology and nanotoxicology, nanobiotechnology and biomaterials, nanomechanical and nanofluidic systems, and nanoelectronics, photonics and architectonics. For additional information, visit http://www.cnsi.ucla.edu .
The statements contained in this press release that are not purely historical are forward-looking statements within the meaning of Section 21E of the Securities Exchange Act of 1934, as amended. Forward-looking statements in this press release include statements regarding our expectations, beliefs, hopes, goals, intentions, initiatives or strategies, including statements regarding the collaboration with CNSI. Because these forward-looking statements involve risks and uncertainties, there are important factors that could cause actual results to differ materially from those in the forward-looking statements. The development of technologies and products through the collaboration could be affected by a number of factors, including unexpected safety, efficacy or other issues, additional time requirements for data analyses and decision making, the impact of pharmaceutical industry regulation, the impact of competitive products and pricing and the impact of patents and other proprietary rights held by competitors and other third parties. Additional relevant information concerning risks can be found in Abraxis BioScience's Form 10-K for the year ended December 31, 2006 and other documents it has filed with the Securities and Exchange Commission.
The information contained in this press release is as of the date of this release. Abraxis assumes no obligations to update any forward-looking statements contained in this press release as the result of new information or future events or developments.
For more information, please click here
Abraxis BioScience, Inc.
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Santa Ana, CAUSA
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Comments about 'Utah employment up over last year'
- Oldest first
- Newest first
- Most recommended
And its going to get worse as jobs continue to disappear. The tech jobs the
governor bring in and funds with welfare are temporary jobs with limited dead
end growth for employees to serve in a life of assembly line boring and
repetitious jobs that don't pay any wages or benefits because the governor
promises the companies employees who can't demand prosperity or
The table is turning and technology has peaked and no manufacturing industry that produce useful consumer products. Toys, games, and fluff are no longer desirable or affordable for consumers. Toys, games, and tech gear are being recycled and not replaces the way it was 20 years ago before credit abuse and criminal lending has become the norm.
- 4:53 a.m. April 20, 2013
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The Basics of Map Creation with SAS/GRAPH®
Mike Zdeb, University@Albany School of Public Health, Rensselaer, NY
Maps can be created with SAS® by using either SAS/GIS® or the GMAP procedure (PROC), one of the procedures available within SAS/GRAPH. This paper shows you how to use the GMAP procedure, not SAS/GIS. Four different map types can be created using GMAP: choropleth, prism, surface, and block. This paper will discuss creating choropleth maps, i.e. "...2dimensional maps that represent data values as combinations of pattern and color that fill map areas" (definition from SAS/GRAPH Software Usage Version 6). Once you understand how to create a map after using a series of examples, you will also learn how to customize the output of GMAP using an annotate data set and also be introduced to some methods of producing web-based maps.
Choropleth maps are produced by using a combination of a map data set and a response data set. A map data set contains the information needed to draw map boundaries, e.g. countries, states, counties, zip codes, etc. A response data set contains the information that is to be displayed on the map, e.g. population, birth rates, death rates, etc. If you have licensed SAS/GRAPH, you have access to a number of map data sets that are provided with the software. Most of the map data sets provided with SAS/GRAPH contain geographic areas (boundaries) represented in terms of longitude and latitude, x and y coordinates respectively. The x and y coordinates are usually in radians, not in the more familiar metric of degrees. This distinction, radians versus degrees, will normally be of no concern when using SAS-supplied map data sets. However, on those occasions when labels or symbols are to be added to a map via an annotate data set, it is important to understand the metric being used for the map's x-y coordinates. In addition to x-y coordinates, map data sets also contain an identification (ID) variable. The ID identifies the geographic area associated with each pair of x-y coordinates. In many of the SAS-supplied map data sets, the name of the identification variable is ID. However, when the term ID variable in this paper, it is a generic reference to the variable that identifies a map area. Typical ID variables for maps of areas of the United States are state, county, zip code, census tract, etc. In order to map the response data, the response data set must also contain an ID variable that allows SAS/GRAPH to match response data to the map data set. The ID variable in the map and response data sets must have the same name and type (i.e. character or numeric). The action of GMAP is somewhat analogous to a match-merge performed in a data step. A matchmerge matches observations from two or more data sets using one or more by-variables. PROC GMAP matches observations from a response data set to those in a map data set using one or more ID variables. A data step match-merge results in a new data set, while PROC GMAP results in a geographical display of your response data. There may also be other variables in a map data set. All of the SAS-supplied map data sets contain the variable SEGMENT, used by PROC GMAP when a map area comprises more than one polygon. An example of such an area is the state of Hawaii where multiple polygons (islands) make up an area with a single ID variable, STATE. Several of the data sets also contain the variable DENSITY. That variable is useful in controlling the amount of detail to be displayed in map boundaries. You will probably never concern yourself with map segments. If you use any of the SAS-supplied maps of the United States or Canada, you will learn that the density variable is quite useful.
Though you might associate map boundaries with coordinates in terms of longitude and latitude, PROC GMAP will draw any shapes that you create in a map data set. Example 1 constructs a map data set that contains four rectangles. A response data set is created with one observation matched to each map area (i.e. rectangle). PROC GMAP creates a map. * example 1; * the map data set; data poly_map; input id x y @@; datalines; 1 0 0 1 1 0 1 1 1 1 2 1 0 2 2 0 2 2 1 2 3 0 1 3 1 1 3 1 2 3 4 1 1 4 2 1 4 2 2 4 ; run;
0 1 0 1
1 1 2 2
* the response data set; data poly_dat; input id z @@; datalines; 1 10 2 20 3 30 4 40 ; run; * fill patterns for map areas and a title to appear above the map; pattern1 c=black v=m3n0; pattern2 c=black v=m3n45; pattern3 c=black v=m3n135; pattern4 c=black v=m3n90; title 'EXAMPLE #1 - MAKE YOUR OWN MAP'; * create the map; proc gmap data=poly_dat map=poly_map; id id; choro z / discrete; run; quit;
The map data set contains the minimum set of variables needed to draw a map. There are x-y coordinates and an ID variable, i.e. RECTANGL. The patterns used to fill each rectangle are specified in a set of pattern statements. More about patterns available within PROC GMAP can be found in volume one of the SAS/GRAPH Software Reference. The various portions of the pattern definition (v=) control line density, angle, and crosshatching. It is important to specify a color (c=) within each pattern. Without a color, each pattern statement defines as many patterns as there are colors available on the output device being used. Thus, if no colors were specified, each rectangle would be filled with the first pattern in a series of different colors. If you have ever used PROC GPLOT, you'll notice that this is the same behavior as occurs with SYMBOL statements. Within PROC GMAP, the map and response (data=) data sets are specified. An ID statement specifies that the variable that links the data to the various map areas is RECTANGL. The option CHORO requests a choropleth map (as opposed to a PRISM, SURFACE, or BLOCK map). Only one PROC GMAP option is used, i.e. DISCRETE. This option tells the procedure 2
The LEVEL and MIDPOINTS options can also be used to control the display of data. Without the DISCRETE option. a default LIBREF with the name MAPS is created and it is available each time you use SAS. and 40) is displayed with a different pattern. Alabama. A data set option is used to limit the response data set to one observation. the first observation in the MAPS. choro state / nolegend.US is specified. title 'EXAMPLE #2 .us (obs=1) all. 30.US as both the map and response data set. or of individual states. so it is also used as the response data set. but the DISCRETE option will be used for maps produced in this paper USING A SAS-SUPPLIED MAP There are several SAS-supplied maps that can be used to produce maps of all of the United States. id state. (US) as both the map and response data sets. Each of the four values of the response variable (10. using the data set MAPS.us data=maps. an empty pattern is chosen (v=e). of groups of states. * use a SAS-supplied map data set proc gmap map=maps. our map would have displayed one state. When you install the SAS-supplied map data sets. We know the data set MAPS.US MAP Data set'.US data 3 . Since we want an outline map (no fill patterns). We also need a response data set with an ID variable named STATE. * example 2. The default behavior is equivalent to using the option MIDPOINTS. and a legend is produced at the bottom of the page. PROC GMAP only displays those areas that are found in both the map and response data sets unless the ALL option is used. * select an empty pattern (v=e) and a title. pattern v=e. run. Example 2 constructs an outline map of the United States. If that option had been left out. The map data set MAPS. We do not need a LIBNAME statement to specify the location of the of the SAS-suppled map dat sets. 20.US contains the variable STATE. quit. PROC GMAP uses its own set of rules to determine the values and number of levels of the response variable to be grouped and displayed.to treat the numeric variable Z as discrete rather than continuous.
4 . pattern c=black v=e r=62. title2 'NEW YORK STATE COUNTIES'.e. run. The next example uses a portion of one of the data sets to produce an outline map showing New York State counties (notice the author's affiliation). * create a <no fill' pattern (repeated 62 times . However. choro county / nolegend. USING A SUBSET OF A SAS-SUPPLIED MAP Several of the SAS-supplied map data sets allow you to produce county maps of any state. Once again. The DISCRETE option is not needed since the same pattern is used no matter what value GMAP decides to map via the default MIDPOINTS option. the same data set is used as both the map and response data sets. * example3. since a WHERE statement is used to select only New York State counties using the FIPS (Federal Information Processing System) county number. New York has 62 counties. quit.one for each NYS county) and titles. a data set option specifying OBS=1 (as used in example 2) cannot be used on the same data set. Therefore. title1 'EXAMPLE #3 . even when there is no data for an area in the response data set. there will be a number of different values for the variable being mapped.MAPS. id county. The ALL option is not needed since each county is present in both the map and response data sets.COUNTIES MAP Data set'.counties.set. the DISCRETE option is not needed. The NOLEGEND option is used to suppress display of the legend. proc gmap data=maps. The ALL option tells GMAP to draw all of the geographic areas in the map data set. Since only one value of the variable STATE is displayed. so the repeat option (r=) is used in the pattern statement to have the same pattern used for each county. i.counties map=maps. COUNTY. where state eq 36.
the values have already been projected. Both data sets define areas in terms of longitude and latitude. run. if you are familiar with New Yorkers.COUNTIES data sets. note ' EXAMPLE #4 .US versus the MAPS. In the MAPS.. while the COUNTIES data set contains unprojected points.You may have noticed (then again. where state eq 36.US data set. proc gproject data=maps.COUNTIES MAP Data set' j=l ' NEW YORK STATE COUNTIES' j=l ' PROJECTED WITH' j=l ' PROC GPROJECT'. both the x and y coordinates normally begin in the lower left corner of the page. quit. Latitude (our Y-variable) increases (in the northern hemisphere) as you move up from the equator. but longitude (our X-variable) increases as you travel from right-to-left (east-towest). choro county / nolegend. and y-values get larger as you go up. PROC GPROJECT is used to project the map data set.counties out=nys.. X-values get larger as you go from left-to-right. id state. * select an empty pattern (v=e). Example 4 shows how to correct the map produced in example 3. you may not have) that the map produced by example 3 is backward and distorted (then again.limit the map to New York state. if you are not familiar with New York. correcting both the direction and distortion * example 4. The reason that the map is backward is that longitude increases from right-to-left and GMAP draws the map using a standard x-y coordinate system where x increase from left-to-right. not a flat surface. Why did that occur if it did not in example 2? The answer lies in the type of x-y coordinates present in the MAPS. * create a map data set containing projected coordinates . When you draw a graph. id county.). proc gmap data=nys (obs=1) map=nys all. The map is distorted since the longitude/latitude coordinate system is based on spherical coordinates. run. 5 . pattern v=e.
* example 5 * create a format to group observations (counties) based on the population. note ' EXAMPLE #5' j=l ' NEW YORK STATE' j=l ' COUNTY POPULATION. the title 'consumed' a portion of the display area. id county. it is possible that text will over write a map. One caution with NOTES.150 . a FIPS county number and the population of each county as of the 2000 census. New York State counties. we have produced maps that displayed geographic areas.. A map of New York state offers a lot of room for text in the upper left side of the display area. 1332650 139750 63094 950265 60370 111738 69441 1537195 100224 61676 443728 146555 98726 96501 93765 007 015 023 031 039 047 055 063 071 079 087 095 103 111 119 200536 91070 48599 38851 48195 2465326 735343 219846 341367 95745 286753 31582 1419369 177749 923459 * fill patterns for the map areas (gray-scale fills).379 .235469 = '93.91070 = '51. Each time a text justification is specified (J=L). The ALL option is needed.070' 93765 . 001 294565 003 49927 005 009 83955 011 81963 013 017 51401 019 79894 021 025 48055 027 280150 029 033 51134 035 55073 037 041 5379 043 64427 045 049 26944 051 64328 053 057 49708 059 1334544 061 065 235469 067 458336 069 073 44171 075 122377 077 081 2229379 083 152538 085 089 111931 091 200635 093 097 19224 099 33342 101 105 73966 107 51784 109 113 63303 115 61042 117 121 43424 123 24621 . pattern1 v=s c=grayff. run. Without it.51134 = '5. quit.51. but no real data. proc gmap data=nys2000 map=nys. pattern4 v=s c=gray68.465.134' 51401 . a NOTE is used to label the map. run.326' . By default. only one county would be displayed.91. NOTES begin in the upper left corner of the display area. since they share the map area. the NOTE statement goes to a new line. USING REAL DATA Thus far. We can revert to the method used in example 2 (no repeated patterns. 6 .235. data nys2000.2465326 = '280.A WHERE statement is used in the GPROJECT procedure to select New York State counties. and an OBS=1 data set option on the response data set) since STATE selection was already done in PROC GPROJECT (not in GMAP as done in example 3). Since they 'share' rather than 'consume' the display area. * 2000 census population. more area is available for the map. value pop2000_ 5379 .401 .765 . A map data set is produced containing projected longitude and latitude. pattern3 v=s c=grayaa.469' 280150 . pattern2 v=s c=grayda. run. format pop2000 pop2000_.2. The next example will use the NYS data set produced using PROC GPROJECT in example 4 and display some 'real' data. The following data step produces the data set NYS2000 containing one observation for each New York State county and two variables. choro pop2000 / discrete. In examples 1 through 3. 2000'. input county pop2000 @@. datalines. Rather than use TITLE statements. This will not occur with TITLES since they do not share the map area. proc format.
pattern3 v=s c=grayaa. with the 256 available shades ranging from GRAYFF (white) to GRAY00 (black). * create instructions for legend location and appearance.PROC FORMAT is used to create a format that can be used to group the counties by population. The DISCRETE option is needed to control how GMAP forms groups. * example 6. pattern1 v=s c=grayff. This problem can be corrected using the COUTLINE= option. four patterns are created to fill the areas (counties) on the map with solid (v=s) shades of gray (c=). pattern2 v=s c=grayda. the legend will be moved to create more area for displaying the map. The DISCRETE option is needed even though the format will create four groups of counties. One problem with this map is that impossible to distinguish adjacent counties that are shaded with the same gray fill. Note that not all output devices can use gray scale shading. id county. legend1 origin=(5.10) pct mode=share across=1 label=none value=(j=r) shape=bar(3. 7 . When a solid pattern is specified.4) pct. and the format POP2000_ is used to define groups based on the population of each county. it is outlined in the same color used to fill the area. * fill patterns for the map areas (gray-scale fills). The white box outlined in white in the legend blends in with the background and adjacent counties in the map sometimes blend together. pattern4 v=s c=gray68. Since four groups are defined in the format. choro pop2000 / discrete legend=legend1 coutline=black. proc gmap data=nys2000 map=nys (where=(density lt 6)). The various grays are defined via hexadecimal notation. Since there is room in the lower right side of the display.
The value of HSA assigned to each observation is based upon the value of the variable COUNTY. 10% in the Y-direction). 2000'. It is present in the COUNTIES data set that was used to produce the data set NYS via PROC GPROJECT. in New York state. For example. If the variable DENSITY is not present in a map data set. X-y coordinates with a density of 6 provide the most detail to area boundaries. the observations with a density of 6 can be left out of map creation without losing much detail. quit. Subtle differences can be seen in the output from example 6 when compared to example 5. The ORIGIN option takes advantage of the empty area in the lower left side of the display area (origin coordinates are expressed in terms of percentage of display area. The three GMAP options result in an acceptable display of the data. counties can be aggregated into larger health service areas. 8 . The values of density range from 0 to 6. The elimination of the <extra coordinates' will reduce CPU time in creating a map and will speed up map creation on slow output devices. note ' EXAMPLE #6' j=l ' NEW YORK STATE' j=l ' COUNTY POPULATION. PROC GMAP must be told to use the legend with an option (LEGEND=1). run. it was stated that the variable DENSITY is present in some map data sets. They are most evident in looking at the islands in the lower right and top center of the maps. There is a SAS/GRAPH procedure that allows you to remove the shared borders between areas that are combined. a new geographic identifier (HSA) must be added to each observation in the data set. The MODE option tells the GMAP procedure that the legend will SHARE the display area rather than force the map to appear above the legend. in this case 5% in the X-direction. COMBINING MAP AREAS There are times when it is necessary to display data in areas that are combinations of smaller geographic areas. The other legend options control appearance. At the scale of a state.. Example 7 shows how PROC GREMOVE can be used to convert a county-based map data set into a health service area map. The data step that assigns an HSA to each observation is shown in the appendix. First. PROC GREDUCE can be used to create it. In the introduction to this paper. The legend statement offers control over both the appearance and placement of the legend. The variable HSA will group counties into health service areas and then be used to identify new areas to be mapped.format pop2000 pop2000_.
proc gremove data=hsatemp out=hsamap. the by-variable identifies the observations to be combined into new areas. run. proc gproject data=hsamap out=hsaproj. else if county in (27 71 79 87 105 111 119) then hsa='6'.counties. 9 .HEALTH SERVICE AREAS' j=l ' AREAS FORMED FROM COUNTIES' j=l ' USING PROC GREMOVE'. else if county in (1 19 21 25 31 33 35 39 41 57 77 83 91 93 95 113 115) then hsa='5'. else if county in (59 103) then hsa='8'. by hsa. note ' EXAMPLE #7 . Within GREMOVE. proc gmap data=hsaproj (obs=1) map=hsaproj all. Once the new variable HSA has been added to each observation in the map data set. * eliminate county boundaries with HSA areas using PROC GREMOVE. quit. choro hsa / discrete nolegend. PROC GREMOVE is used to create a new map data set with HSA rather than county boundaries. run. id hsa. Since HSA is used as a by-variable within GREMOVE. proc sort data=hsatemp. where state eq 36 and density lt 6. id county. * sort map data set in order by new geographic designation. id hsa. run. if county in (3 9 13 29 37 63 73 121) then hsa='1'. by hsa. pattern v=e. else if county in (5 47 61 81 85) then hsa='7'. else if county in (7 17 107) then hsa='4'.* example 7. run. set maps. else if county in (15 51 55 69 97 99 101 117 123) then hsa='2'. the data set is first sorted by HSA. * assign new geographic designation (HSA) to each New York State counties. data hsatemp. run. else if county in (11 23 43 45 49 53 65 67 75 89 109) then hsa='3'. while the ID variable identifies the areas to be combined.
The labels are placed at the center of each of the areas. length text $5. Adding labels to a graphic via an annotate data set can be accomplished in either display manager or batch mode. retain xsys ysys '2' hsys '3' position '5' function 'label' size 3 style "'Tahoma/bo'" when 'a' .ADDING AREA LABELS USING ANNOTATE The map produced in example 9 would be more informative if there were labels that showed the location of each of the eight health service areas. longitude and latitude in radians.e. via editing with a mouse. SAS/GRAPH offers a graphics editor if you are using SAS via the display manager. In example 8. It can be used to place text on a graphic produced by any of the SAS/GRAPH procedures.e. * add labels tp map areas. The x-y coordinates in the map data set are longitude and latitude expressed in radians. you know that adding text to a graphic is usually as simple as: choosing the <add text' tool. The annotate data set can be thought of as a script that contains a literal description of all the actions you would perform and decisions you would make if you were altering a graphic interactively. i. 10 . input text x y. labels are added to the HSA-based map that was produced in example 7. you also make a decision as to text appearance (font and size). If you have a lot of labels to add. data labels. typing the text. However. The easiest way to place a label at the center of each is to express the location of the HSA centers in the same metric. Annotation allows you to customize any output produced with SAS/GRAPH. Labels of map areas are not automatically provided within PROC GMAP. If you are using SAS in batch mode. If you have ever used a drawing program. * example 8. In addition to these tasks. they can be added using an annotate data set. The degree of customization is limited only by your knowledge of annotate data sets. this can be tedious. using a mouse to move the cursor to the point on the screen where the label is to be located. i. the editor is not available.
294420 0. and when.HEALTH SERVICE AREAS' j=l ' LABELS ADDED TO MAP AREAS' j=l ' USING AN ANNOTATE DATA SET'. a value of 'a' for WHEN places the label on the map after the map is drawn. run. data hsaproj labels.X and Y are map coordinates and POSITION indicates where on the x-y location the label is to be placed (a value of 5 calls for a label centered on the x-y location). proc gproject data=map_labl out=hsaproj. run. Y. * project all observations (map and labels). For now. If the variable HSYS is assigned a value of three.295074 0.710749 HSA-8 1. and POSITION define 'where' . Finally. YSYS. * combine the map data set with map labels.* the longitude/latitude of HSA area centroids. else output hsaproj. run. the value of the variable SIZE represents a percentage of the display area. where. all you need to know about XSYS and YSYS is that they are both assigned a value of two when the x-y coordinates in the annotate data set are in the same metric as the map data set. WHEN is not important. choro hsa/ discrete nolegend annotate=labels.742941 HSA-2 1.756707 HSA-4 1. id hsa. id hsa. * label the map via the annotate option. quit. and HSYS.321340 0. proc gmap data=hsaproj (obs=1) map=hsaproj all.713304 . how. With unfilled areas.STYLE chooses the font and SIZE the text height.738309 HSA-5 1. The first data step creates the annotate data set. The variable FUNCTION defines 'what' .371803 0. 11 . If areas are filled. run. pattern v=e.annotation will create a label. both the map and annotate data sets are in terms of longitude and latitude in radians. a value of <b' (before) will make the labels invisible since they will be under the filled areas.273433 0.348815 0. What you should realize though is that annotation gives you a lot of power to control the appearance of SAS/GRAPH output. if function eq 'label' then output labels.323836 0. In this example. data map_labl. set hsamap labels. set hsaproj. The only variables left to be explained are XSYS.744540 HSA-3 1. run. The variables STYLE and SIZE define 'how' . note ' EXAMPLE #8 . You should not expect to understand all the nuances of annotation from one example.288815 0.756696 HSA-6 1. there are a number of variables that answer the questions: what. In the data set. datalines. HSA-1 1.726438 HSA-7 1. * separate the labels from the map data set. Variables X.
. plotter.. PROC GMAP looks much the same as it did in example 8. it is combined with the map data set HSAMAP to form MAP_LABL. The combined data set is then projected via GPROJECT. Once you have more experience with SAS/GRAPH mapping and annotation. The above GOPTIONS statement instructs SAS/GRAPH to produce a GIF file (the destination) with the FILEREF GOUT. You must project the map and labels together to insure that the labels will be placed in the correct location on your output. The final step prior to mapping is to separate the projected map data set from the projected annotate data set. Selections made in a GOPTIONS statement govern both the destination the appearance of graphical output produced using SAS/GRAPH PROCs. SAS/GRAPH provides drivers for a large number of output devices. The XPIXELS and YPIXELS options are used to override the default resolution of 800 (XPIXELS) by 600 (YPIXELS). the output from PROC GMAP is directed to the graphics output window. etc. Just accept this notion for now. 12 ..Once the data set LABELS is created.' moment. GRAPHICS OUTPUT When running SAS/GRAPH in display manager mode.. goptions reset=all dev=gif xpixels=1280 ypixels=1024 gsfname=gout ftext='Tahoma/bo' htext=4 gunit=pct .eureka. I understand.. the if-then-else statement will correctly separate the data sets.. Since only observations from the original data set LABELS have a value for the variable FUNCTION. This is done in a data step. All the graphics shown in this paper were produced using the SAS-supplied GIF driver The GOPTIONS statement used to produce all the output was. except for the additional option ANNOTATE= that uses the data set LABELS to label the map areas. the GOPTIONS statement works in much the same manner as an OPTIONS statement. you must use a GOPTIONS statement and possibly one or more ODS (Output Delivery System) statements. If you are new to SAS/GRAPH. giving more detail to the GIF output files. If you are using SAS/GRAPH in batch mode or want to send output directly to a laser printer.. you will reach that '.
350761 = '146... PDF output can use postscript fonts. The NOTOC (no table of contents) option on the ODS PDF statement prevents the addition of a bookmark to the PDF output.522541 = '423. maps where map areas and/or the map legend are linked to additional information. if pop2000 le 144166 then legend_link = 'ALT="1ST QUARTILE" href=nj2000_q1.053 146.673 017 Hudson County 553. options orientation=landscape.761' 423394 . input county county_name & : $upcase20. ods listing close.089 102. datalines.099 608.gif'. The units of height are percent of the graphics output area.824 508.118 005 Burlington County 395.htm'.552 003 Bergen County 825. goptions reset=all ftext='Helvetica/bo' htext=4 gunit=pct rotate=landscape . The following statements placed prior to and after PROC GMAP will produce a PDF file in landscape mode (named as shown below): placed prior to PROC GMAP.394 007 Camden County 502.COUNTIES map data set to create a map where both New Jersey counties and the map legend are linked to HTML pages. The font Tahoma Bold (a TrueType font) is selected for all text with a height of 4..285-144. 001 Atlantic County 224. * create a link for each county.144166 = '64.. county_link = 'ALT="' || trim(county_name) || '" href=county' || put(county. In addition to creating static output. data njpop.082 254. proc format. placed after PROC GMAP.541' 608975 . * create a link for the legend. If you would like to create PDF output.206 793. run.You'll also need a FILENAME statement to associate the FILEREF GOUT with a real file name. * create a map with drill-down areas. else if pop2000 le 350761 then legend_link = 'ALT="2ND QUARTILE" href=nj2000_q2.380 884.htm'. filename gout 'c:\usamap.975-884.438-350. value pop2000_ 64285 . so Helvetica Bold is selected.e.932 009 Cape May County 95.884118 = '608.166' 146438 .118' .975 13 ..633 015 Gloucester County 230. you can create maps that have drill-down capabilities. you can use ODS. The HTEXT and GUNIT options are the same as those used when GIF output was created.438 013 Essex County 778. else legend_link = 'ALT="4TH QUARTILE" href=nj2000_q4.327 252. for example.htm'. The next example uses 2000 census data for the state of New Jersey and the MAPS.)..htm'. specified with GUNIT=PCT. * example 9. ods listing.394-522.) || '. ods pdf close.pdf' notoc. ods pdf file='c:\usamap.326 011 Cumberland County 138.z3. (pop1990 pop2000) (: comma8. i. else if pop2000 le 522541 then legend_link = 'ALT="3RD QUARTILE" href=nj2000_q3.htm'.066 423.
437 pattern1 v=ms c=grayfa. format pop2000 pop2000_.212 510.124 421.541 102. * select New Jersey (state number 34) from the MAPS.279 130. two new variables are added.916 489. 107. note j=l ' EXAMPLE #9' j=l ' NEW JERSEY COUNTIES' j=l ' 2000 CENSUS POPULATION' h=3 j=l ' (CLICK ON COUNTY OR LEGEND TO' j=l ' DRILL DOWN TO ADDITIONAL DATA)' . ods listing. legend1 mode=share origin=(5.4) across=1 .607 121.761 750. ods html path='z:\' (url=none) file='nj2000.824 671. proc gproject data=maps..301 470.049 64.294 240. ods listing close.285 297.counties out=nj asis. id county. quit. ods html close. goptions reset=all dev=gif xpixels=1024 ypixels=768 ftext='Tahoma/bo' htext=4 gunit=pct .776 325. choro pop2000 / discrete coutline=black legend=legend1 html=county_link html_legend=legend_link.COUNTIES map data set. pattern2 v=ms c=grayca. pattern4 v=ms c=gray5a.060 65.780 553.htm'.203 453. COUNTY_LINK and LEGEND_LINK. In the data step where the population data are turned into a SAS data set.50) label=none value=(h=3 j=r) shape=bar(3. * it will link to the GIF file with the actual map. The value of the variable COUNTY_LINK is formed using the county name as an ALT tag (causing the county name to appear on the screen when the mouse is dragged over a county area) and the county number as a link (used to create the name of the HTML 14 .162 615. run.490 144. where state eq 34. * use ODS to create an HTML file.943 493. run. A format is created to group the counties into four groups (quartiles) based on 2000 population.019 Hunterdon County 021 Mercer County 023 Middlesex County 025 Monmouth County 027 Morris County 029 Ocean County 031 Passaic County 033 Salem County 035 Somerset County 037 Sussex County 039 Union County 041 Warren County . pattern3 v=ms c=grayaa.353 433.166 522. proc gmap map=nj data=njpop .989 350.819 91. run. id county.
used in both examples 8 and 10. It is also possible to create drill-down links from features added to a map using annotation. a county name appears. retain xsys ysys '2' hsys '3' position '5' function 'label' size 3 style "'Tahoma/bo'" cbox 'black' 15 . * create a map with drill-down annotation. The URL=NONE option places no path information on the GIF file name in the IMG tag (requiring that both the HTML and GIF files be placed in the same location on the web site). The GIF device driver is specified in a GOPTIONS statement. length text $5. adding a drill-down link at the area (HSA) labels that are added with annotation. Note.file to which the county is linked). The output shown for example 9 is a screen capture of a map displayed on a web page and it illustrates what happens when the mouse cursor is placed over a county. you must use the SAS code in example 7 first to create the map data set HSAMAP. data labels. The HSA labels are change to white and black boxes are added behind the labels. as with example 8. but the SAS code shown above for example 9 will create a map with drill-down links. The next example uses the SAS code from example 8. * example 10. but no GSFNAME option is used (as was used in creating the figures shown for examples 1 through 8). An ODS statement is used to create an HTML file that will have a link (an IMG HTML tag) to the GIF file that contains the map. This explanation leaves out a lot of details.
16 . proc gproject data=map_labl out=hsaproj. * combine the map data set with map labels.742941 HSA-2 1. set hsaproj. goptions reset=all dev=gif xpixels=1024 ypixels=768 ftext='Tahoma/bo' htext=4 gunit=pct . quit. * add a variable named HTML. * label the map via the annotate option.348815 0.273433 0.371803 0. note ' EXAMPLE #10 .294420 0. id hsa. proc gmap data=hsaproj (obs=1) map=hsaproj all.295074 0. ods html path='z:\' (url=none) file='nys_hsa. * it will link to the GIF file with the actual map. data hsaproj labels. id hsa.htm"'. if function eq 'label' then output labels.htm'. else output hsaproj. HSA-1 1. run.738309 HSA-5 1.756696 HSA-6 1.713304 . choro hsa/ discrete nolegend annotate=labels.288815 0. run. run. datalines.710749 HSA-8 1. * the longitude/latitude of HSA area centroids.HEALTH SERVICE AREAS' j=l ' LABELS ADDED TO MAP AREAS' j=l ' USING AN ANNOTATE DATA SET' h=3 j=l ' (CLICK ON HSA LABEL TO DRILL' j=l ' DOWN TO ADDITIONAL DATA)' . run.color 'white' when 'a' .321340 0. * separate the labels from the map data set. set hsamap labels.744540 HSA-3 1. input text x y.756707 HSA-4 1. * project all observations (map and labels). run. pattern v=e.323836 0.726438 HSA-7 1. ods html close. data map_labl. ods listing close. html = 'HREF="' || text || '. * use ODS to create an HTML file.
761' 423394 . In example 9.541' 608975 . datalines. input county couname & : $upcase20. the JAVAMETA device driver and ODS are used.884118 = '608. the GIF device driver is specified in a GOPTIONS statement. value pop 64285 . and the HSA labels are all drill-down links.394-522.438-350.522541 = '423. (pop1990 pop2000) (: comma8. The GIF device driver and ODS were use din example 9.166' 146438 .350761 = '146. data njpop. proc format. As in example 9.118' . a county-based map of New Jersey was created and each county was linked to another HTML file. and ODS is used to create HTML output.285-144. The last type of output to be shown is a map with pop-up (not drill-down) information associated with map areas.ods listing. run. the CBOX variable is used to place a black box behind the text added with annotation. in the data step that create the data set LABELS. The figure produced by example 10 is a screen capture of the web displayed on web page. However. and the %-change in population from 1990 to 2000. Most of the code in example 10 is the same as that in example 8. and the text color is changed to white.975-884.144166 = '64. population in both 1990 and 2000. * create a map with pop-up information for map areas. The pop-up box will contain the county name. 17 . The SAS code from example 9 will be modified to create a map that has a pop-up box associated with each county. In example 11.). * example 11.
162 615. * create an HTML file.comma10.053 778.089 138.counties out=nj asis.5) .060 65. run.50) label=none shape=bar(3.824 95. data popup.437 * text to put in floating text box (after line with TIP).099 107.166 522.490 144. run.633 254.066 502. pattern3 v=ms c=grayaa. id county. 224.552 884.1)) || ']'.)) || ' ' || quote('% CHANGE : ' || put(pct. popvar = 'tip=['|| quote(couname) || ' ' || quote('POPULATION') || ' ' || quote('1990 : ' || put(pop1990. pattern2 v=ms c=grayca. proc gmap map=nj 18 .10.082 553.206 230.824 671.279 130.541 102.916 489.htm" codebase="z:\" parameters=("BackgroundColor"="0xFFFFFF" "DataTipStyle"="Stick_Fixed" "ZoomControlEnabled"="False").380 395.326 146.203 453. ods listing close.607 252.4) across=1 value=(h=3.932 102.353 433. proc gproject data=maps.673 608. set njpop.975 121. pct = 100*(pop2000 . run.049 64.989 350. pattern4 v=ms c=gray5a.327 825.943 493.776 325.285 297.780 553.124 421.001 Atlantic County 003 Bergen County 005 Burlington County 007 Camden County 009 Cape May County 011 Cumberland County 013 Essex County 015 Gloucester County 017 Hudson County 019 Hunterdon County 021 Mercer County 023 Middlesex County 025 Monmouth County 027 Morris County 029 Ocean County 031 Passaic County 033 Salem County 035 Somerset County 037 Sussex County 039 Union County 041 Warren County .761 750. * use the JAVAMETA device driver. legend1 mode=share origin=(5.819 91. where state eq 34.294 240. ods html body="z:\nj_pop.118 423.comma10.394 508. goptions reset=all device=javameta ftext='HelveticaBold' xpixels=1024 ypixels=768 htext=5 gunit=pct .212 510.301 470.)) || ' ' || quote('2000 : ' || put(pop2000. length popvar $200.pop1990) / pop1990. pattern1 v=ms c=grayfa.438 793.
The figure produced by example 11 is a screen capture of a web page. quit. note j=l ' EXAMPLE #11' j=l ' NEW JERSEY COUNTIES' j=l ' 2000 CENSUS POPULATION'. showing the pop-up box that appears when you place the mouse cursor on a county. Then ODS is used to create an HTML file. plus a new variable named POPVAR. The JAVAMETA device driver is specified in a GOPTIONS statement. format pop2000 pop.data=popup . After the census data are read into a SAS data set. This new data set contains the census data to be mapped (the 2000 population). Neither the codebase nor the parameter options will be explained here either. Note. ods listing. id county. choro pop2000 / discrete coutline=black legend=legend1 html=popvar. The value of this variable contains the information that is to appear in the pop-box associated with each county. The exact syntax needed to construct this variable is not explained here (it is available on the SAS web site). run. another data step is used to create data set POPUP. ods pdf close. you should also know that the display of the web page shown in example 11 requires the use of the METAVIEW applet that is distributed with SAS/GRAPH software.. The purpose of this example is to both show you another way of displaying map-based data and to get you interested in using SAS/GRAPH to create maps. 19 .
. If you want to display data on a state or county basis. http://support....com/techsup/download/sample/graph/gmap-examples-list.gov/geo/www/cob/bdy_files..sas. especially when used in conjunction with annotate data sets. Maps Made Easy Using SAS.pdf Many ESRI shapefiles are posted for free download at the US Census Bureau web site. the needed maps are supplied with SAS/GRAPH. http://www. there are enough features in PROC GMAP. http://support.com/apps/pubscat/bookdetails. Information on SAS-supplied maps can be found at.html For more information about the METAVIEW applet and the SAS code used in example 11. NY 12144 20 . The web site. Cary. as are those needed to produce maps of many different countries. Mike Zdeb U@Albany School of Public Health 1 University Place Rensselaer.RESOURCES Just as with other SAS/GRAPH procedures. look at. 1991 CONTACT INFORMATION The author can be contacted using e-mail .colorbrewer.sas....518-402-6479 or by regular mail.jsp?catid=1&pc=57495 that expands on the material covered in this paper and also includes a chapter on creating maps for posting on the web. census tracts or zip-based maps.. . If you are using Version 9 of SAS.. PROC MAPIMPORT. CONCLUSION PROC GMAP either by itself or in combination with several other SAS/GRAPH procedures allows you to create a number of different types of maps. it is sometimes difficult to select appropriate colors for map areas.com is designed to assist you in selecting colors for maps.edu by phone.sas.g.sas.. Information on this procedure is available in V9 help.html When creating maps. to produce both publication quality choropleth maps and maps with special features (drill-downs and pop-ups) for web posting... REFERENCES SAS Institute Inc.. http://www. a new procedure.. you will have to create your own map data sets. and also at. http://support.htm If you want to create maps of other areas. http://ftp.. NC: SAS Institute Inc..com/rnd/datavisualization/papers/SASMapping. PROC GMAP can produce 'publication quality' results.com/rnd/datavisualization/mapsonline/ Examples of PROC GMAP output and the sample code can be found at.com/rnd/datavisualization/webgraphs/v8v81Usage/metaviewapplet. there is a book. allows you to convert files in ESRI shapefile format into SAS/GRAPH map data sets. http://www..sas.. Finally. Though it does not have all the features of a true geographic information email@example.com... e..
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Home > News > NVE Receives GMR Sensor Order from Starkey Laboratories
October 13th, 2004
NVE Receives GMR Sensor Order from Starkey Laboratories
NVE Corporation has received an initial order from Starkey Laboratories Inc. for custom-designed ultra-miniature spintronic sensor integrated circuits. The NVE devices will replace electromechanical sensors in Starkey hearing aids. The order has a value of more than $100,000 with shipments scheduled to begin in early 2005.
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text:
New York, NYUSA
December 24, 2012
I like working out, going to comedy clubs, museums, going to book stores, just exploring new things.
writing on deadline lol (I'm a newspaper reporter)
all of the above?
My name is Mitch, and I'm a pretty laid back guy, who enjoys hanging with friends and family. I work as a sports reporter for a daily newspaper, which is a pretty cool job if you're into sports. I'm just looking for new social activities to do.
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U.S.--Latin American Relations / Edition 3by Michael J. Kryzanek
Pub. Date: 01/30/1996
Publisher: Greenwood Publishing Group, Incorporated
This completely revised and thoroughly updated Third Edition of Kryzanek's widely praised text includes a wealth of new data and analysis on the key events and controversies that have shaped U.S.-Latin American relations through the first half of the Clinton administration. New and updated material addresses NAFTA, the recent Mexican political and financial crisis, Haiti, and other headline events since the last edition in 1990. In addition, the work includes a new chapter examining current issues of U.S. hemispheric relations including NAFTA, the drug wars, immigration, the impact of the global economy and multilateral solutions to regional problems. An important text for scholars and students in Latin American studies and international relations.
Product Details
- 9780275950842
- Publisher:
- Greenwood Publishing Group, Incorporated
- Publication date:
- 01/30/1996
- Edition description:
- 3rd ed
- Pages:
- 292
- Product dimensions:
- 6.06(w) x 9.24(h) x 0.90(d)
- Lexile:
- 1610L (what's this?)
Table of ContentsIntroduction: The Political, Economic, and Social Setting
The Evolution of U.S.-Latin American Relations
The Monroe Doctrine and the Emergence of U.S. Power and The Contemporary Scene: The Reagan, Bush, and Clinton Approaches to the Hemisphere
Interventionism, Cooperation, and Revolution
Castroism and the Challenge to U.S. Power
Reagan's Reliance on Capital and Containment
Elements of Latin American Policy Making
Governmental Participants in Latin American Policy Making
Nongovernmental Participants in Latin American Policy Making
Shaping U.S.-Latin American Policy: The Human Element
Dilemmas of U.S.-Latin American Relations
The Fragile Hold of Democracy
Sources of Change in Our Sphere of Influence
Conclusion: The New Hemispheric Relationship
Selected Bibliography
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|By Business Wire
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|February 27, 2013 12:15 PM EST
Ultimate Software (Nasdaq: ULTI), a leading cloud provider of people management solutions, announced today that Buckeye Partners, L.P., one of the primary distributors of petroleum in the eastern and mid-western portions of the U.S., is benefiting from new insights into its workforce, better planning for future talent needs, and strengthening its overall HCM strategy with UltiPro and UltiPro Succession Management.
Buckeye Partners provides mid-stream energy logistics services, operating one of the largest independent petroleum products common carrier pipeline networks in North America. In addition to pipeline transportation services, the 1,300-employee company owns and operates more than 100 refined petroleum products terminals and a major natural gas storage facility in California, and markets liquid petroleum products in various regions around the world. Because of the company's continued success and expansion, executives at Buckeye Partners wanted to proactively plan for future business needs, especially related to the company's leadership.
The HR team was tasked with finding better ways to uncover talent gaps, identify high-performing individuals, understand and monitor retention risks, and help employees develop their readiness to step into key roles. With Buckeye's years of proven success with Ultimate's cloud-based features for HCM, company leadership chose to leverage UltiPro Succession Management to address its strategic people management objectives today and moving into the future.
"Our previous system for succession plans just did not meet the needs of our expanding business. We had very manual, cumbersome processes when preparing our people for new opportunities. Without an efficient, executable strategy, our business could be at risk when we lost key contributors," said Dianna Fernandez, manager of HRIS at Buckeye Partners, L.P. "With UltiPro, we now have an automated, effective, results-based platform for our succession management program."
Buckeye Partners rolled out UltiPro Succession Management rapidly and began the process of evaluating top talent and potential opportunities for advancement as its first initiative.
"Activating UltiPro Succession Management was easily the most successful deployment for technology that I've ever experienced. The time from our decision to deployment took just two weeks, and we could quickly convert years of manual data into ready-to-use business intelligence," said Fernandez. "Plus, UltiPro's end-to-end features are so flexible. We can easily configure Ultimate's cloud technology and make adjustments as our business requirements evolve."
With UltiPro Succession Management, businesses like Buckeye Partners can accomplish proactive, practical strategies for professional growth and career advancement for their workforce. Each employee can define an individual career path and ensure that he or she develops the skills, knowledge, and other talent factors necessary for personal growth and contribution to the company's success. Employees or managers can update a specific talent profile with relevant personal and career information, such as education, previous work history, skills, licenses/certifications, awards, languages, and willingness to relocate in the U.S. and/or internationally. This information populates the individual's talent card, providing a holistic view of the employee's talent characteristics.
Embedded reporting and business intelligence within UltiPro also deliver a range of essential information, such as succession readiness, successor impact, candidates with highest potential, talent factors, and more.
After employees update their talent profiles with relevant personal and career information, Buckeye collects qualitative feedback about each member of its leadership team from peers, HR, and executives. The quantitative and qualitative data is then merged, helping to identify scores for succession readiness and leading candidates for promotion.
"Having quantifiable talent and succession metrics are very important to our leadership, and the previous method of sorting through manual reports and spreadsheets to find this information was so complicated that it was ridiculous," said Fernandez. "UltiPro's unified HCM is helping us build a stronger future for our business. We can quickly map values for global locations, assess our talent pool, identify promotability, and provide executives with detailed analytics and the valuable data that they are looking for. It's very exciting for us that HR is helping drive results that have an impact on the entire business."
"To stay competitive and successful, it's now essential for businesses to identify talent factors about their employees holistically, including leadership potential, job performance, promotability, retention risk, and role importance," said Greg Swick, chief sales officer at Ultimate Software. "UltiPro Succession Management provides business-critical information so organizations can build internal talent pools and pinpoint the right individuals to fill key positions in the future. We're very happy that our longterm customer Buckeye Partners is leveraging UltiPro to create a solid strategy for organizational change, build bench strength, and reduce the risk of business disruption."
About Ultimate Software
Ultimate is a leading cloud provider of people management solutions, with more than 10 million people records in the cloud. Built on the belief that people are the most important ingredient of any business, Ultimate's award-winning UltiPro delivers HR, payroll, and talent management solutions that seamlessly connect people with the information and resources they need to work more effectively. Founded in 1990, the company is headquartered in Weston, Florida, and has more than 1,600 professionals focused on developing the highest quality solutions and services. In 2013, Ultimate was ranked #9 on FORTUNE'S list of the "100 Best Companies to Work For." Ultimate has more than 2,500 customers with employees in 136 countries, including Adobe Systems Incorporated, Culligan International, Major League Baseball, The New York Yankees Baseball Team, Pep Boys, and Texas Roadhouse. More information on Ultimate's products and services for people management can be found at www.ultimatesoftware.com.
UltiPro is a registered trademark of The Ultimate Software Group, Inc. All other trademarks referenced are the property of their respective owners.
Follow Ultimate Software on Twitter: www.twitter.com/UltimateHCM
Follow Ultimate Software on LinkedIn: http://linkd.in/UltimateHCM
It's 2016: buildings are smart, connected and the IoT is fundamentally altering how control and operating systems work and speak to each other. Platforms across the enterprise are networked via inexpensive sensors to collect massive amounts of data for analytics, information management, and insights that can be used to continuously improve operations. In his session at @ThingsExpo, Brian Chemel, Co-Founder and CTO of Digital Lumens, will explore: The benefits sensor-networked systems bring to ...
Jul. 24, 2016 08:30 AM EDT Reads: 1,456
Whether your IoT service is connecting cars, homes, appliances, wearable, cameras or other devices, one question hangs in the balance – how do you actually make money from this service? The ability to turn your IoT service into profit requires the ability to create a monetization strategy that is flexible, scalable and working for you in real-time. It must be a transparent, smoothly implemented strategy that all stakeholders – from customers to the board – will be able to understand and comprehe...
Jul. 24, 2016 08:30 AM EDT Reads: 2,046
Identity is in everything and customers are looking to their providers to ensure the security of their identities, transactions and data. With the increased reliance on cloud-based services, service providers must build security and trust into their offerings, adding value to customers and improving the user experience. Making identity, security and privacy easy for customers provides a unique advantage over the competition.
Jul. 24, 2016 08:15 AM EDT Reads: 1,033
SYS-CON Events announced today that Venafi, the Immune System for the Internet™ and the leading provider of Next Generation Trust Protection, will exhibit at @DevOpsSummit at 19th International Cloud Expo, which will take place on November 1–3, 2016, at the Santa Clara Convention Center in Santa Clara, CA. Venafi is the Immune System for the Internet™ that protects the foundation of all cybersecurity – cryptographic keys and digital certificates – so they can't be misused by bad guys in attacks...
Jul. 24, 2016 08:15 AM EDT Reads: 1,099
"Tintri was started in 2008 with the express purpose of building a storage appliance that is ideal for virtualized environments. We support a lot of different hypervisor platforms from VMware to OpenStack to Hyper-V," explained Dan Florea, Director of Product Management at Tintri, in this SYS-CON.tv interview at 18th Cloud Expo, held June 7-9, 2016, at the Javits Center in New York City, NY.
Jul. 24, 2016 08:15 AM EDT Reads: 1,806
Is your aging software platform suffering from technical debt while the market changes and demands new solutions at a faster clip? It's a bold move, but you might consider walking away from your core platform and starting fresh. ReadyTalk did exactly that. In his General Session at 19th Cloud Expo, Michael Chambliss, Head of Engineering at ReadyTalk, will discuss why and how ReadyTalk diverted from healthy revenue and over a decade of audio conferencing product development to start an innovati...
Jul. 24, 2016 08:00 AM EDT Reads: 877
For basic one-to-one voice or video calling solutions, WebRTC has proven to be a very powerful technology. Although WebRTC's core functionality is to provide secure, real-time p2p media streaming, leveraging native platform features and server-side components brings up new communication capabilities for web and native mobile applications, allowing for advanced multi-user use cases such as video broadcasting, conferencing, and media recording.
Jul. 24, 2016 07:45 AM EDT Reads: 692
Large scale deployments present unique planning challenges, system commissioning hurdles between IT and OT and demand careful system hand-off orchestration. In his session at @ThingsExpo, Jeff Smith, Senior Director and a founding member of Incenergy, will discuss some of the key tactics to ensure delivery success based on his experience of the last two years deploying Industrial IoT systems across four continents.
Jul. 24, 2016 07:00 AM EDT Reads: 1,412
There will be new vendors providing applications, middleware, and connected devices to support the thriving IoT ecosystem. This essentially means that electronic device manufacturers will also be in the software business. Many will be new to building embedded software or robust software. This creates an increased importance on software quality, particularly within the Industrial Internet of Things where business-critical applications are becoming dependent on products controlled by software. Qua...
Jul. 24, 2016 05:30 AM EDT Reads: 1,300
"There's a growing demand from users for things to be faster. When you think about all the transactions or interactions users will have with your product and everything that is between those transactions and interactions - what drives us at Catchpoint Systems is the idea to measure that and to analyze it," explained Leo Vasiliou, Director of Web Performance Engineering at Catchpoint Systems, in this SYS-CON.tv interview at 18th Cloud Expo, held June 7-9, 2016, at the Javits Center in New York Ci...
Jul. 24, 2016 04:45 AM EDT Reads: 1,870
SYS-CON Events has announced today that Roger Strukhoff has been named conference chair of Cloud Expo and @ThingsExpo 2016 Silicon Valley. The 19th Cloud Expo and 6th @ThingsExpo will take place on November 1-3, 2016, at the Santa Clara Convention Center in Santa Clara, CA. "The Internet of Things brings trillions of dollars of opportunity to developers and enterprise IT, no matter how you measure it," stated Roger Strukhoff. "More importantly, it leverages the power of devices and the Interne...
Jul. 24, 2016 04:45 AM EDT Reads: 1,972
The Internet of Things will challenge the status quo of how IT and development organizations operate. Or will it? Certainly the fog layer of IoT requires special insights about data ontology, security and transactional integrity. But the developmental challenges are the same: People, Process and Platform. In his session at @ThingsExpo, Craig Sproule, CEO of Metavine, demonstrated how to move beyond today's coding paradigm and shared the must-have mindsets for removing complexity from the develo...
Jul. 24, 2016 01:30 AM EDT Reads: 1,137
The IETF draft standard for M2M certificates is a security solution specifically designed for the demanding needs of IoT/M2M applications. In his session at @ThingsExpo, Brian Romansky, VP of Strategic Technology at TrustPoint Innovation, explained how M2M certificates can efficiently enable confidentiality, integrity, and authenticity on highly constrained devices.
Jul. 24, 2016 01:15 AM EDT Reads: 890
SYS-CON Events announced today that MangoApps will exhibit at the 19th International Cloud Expo, which will take place on November 1–3, 2016, at the Santa Clara Convention Center in Santa Clara, CA. MangoApps provides modern company intranets and team collaboration software, allowing workers to stay connected and productive from anywhere in the world and from any device.
Jul. 24, 2016 01:15 AM EDT Reads: 1,224
"We've discovered that after shows 80% if leads that people get, 80% of the conversations end up on the show floor, meaning people forget about it, people forget who they talk to, people forget that there are actual business opportunities to be had here so we try to help out and keep the conversations going," explained Jeff Mesnik, Founder and President of ContentMX, in this SYS-CON.tv interview at 18th Cloud Expo, held June 7-9, 2016, at the Javits Center in New York City, NY.
Jul. 23, 2016 11:45 PM EDT Reads: 1,230
Internet of @ThingsExpo has announced today that Chris Matthieu has been named tech chair of Internet of @ThingsExpo 2016 Silicon Valley. The 6thInternet of @ThingsExpo will take place on November 1–3, 2016, at the Santa Clara Convention Center in Santa Clara, CA.
Jul. 23, 2016 11:15 PM EDT Reads: 1,865
When people aren't talking about VMs and containers, they're talking about serverless architecture. Serverless is about no maintenance. It means you are not worried about low-level infrastructural and operational details. An event-driven serverless platform is a great use case for IoT. In his session at @ThingsExpo, Animesh Singh, an STSM and Lead for IBM Cloud Platform and Infrastructure, will detail how to build a distributed serverless, polyglot, microservices framework using open source tec...
Jul. 23, 2016 11:00 PM EDT Reads: 2,240
The 19th International Cloud Expo has announced that its Call for Papers is open. Cloud Expo, to be held November 1-3, 2016, at the Santa Clara Convention Center in Santa Clara, CA, brings together Cloud Computing, Big Data, Internet of Things, DevOps, Digital Transformation, Microservices and WebRTC to one location. With cloud computing driving a higher percentage of enterprise IT budgets every year, it becomes increasingly important to plant your flag in this fast-expanding business opportuni...
Jul. 23, 2016 10:15 PM EDT Reads: 2,445
From wearable activity trackers to fantasy e-sports, data and technology are transforming the way athletes train for the game and fans engage with their teams. In his session at @ThingsExpo, will present key data findings from leading sports organizations San Francisco 49ers, Orlando Magic NBA team. By utilizing data analytics these sports orgs have recognized new revenue streams, doubled its fan base and streamlined costs at its stadiums. John Paul is the CEO and Founder of VenueNext. Prior ...
Jul. 23, 2016 09:30 PM EDT Reads: 1,952
A critical component of any IoT project is what to do with all the data being generated. This data needs to be captured, processed, structured, and stored in a way to facilitate different kinds of queries. Traditional data warehouse and analytical systems are mature technologies that can be used to handle certain kinds of queries, but they are not always well suited to many problems, particularly when there is a need for real-time insights.
Jul. 23, 2016 08:45 PM EDT Reads: 1,672


text:
oops. I was too excited. YUMMY. going to make this tonight
Rating4/5 (from 1 ratings)4
YieldAbout 6-7 cups
2 Avocados, Peel-remove pit-cut up
1½ Red onion, Peel and cut up
2 tablespoon Grape seed oil , Pour in blender
2 Limes, Peel-leave whole
1 sprinkle Cayenne, Sprinkle in blender
1 dash Stevia powder or honey, Pour in blender
1 jalepeno pepper, place in blender
2 Lemons, Peel-leave whole
4 Medium sized tomatoes, Cut up and place in blender
Recipe Directions
Place all ingredients in Vitamix, or the like, blend until very smooth. Mix as much hulled sunflower seeds as you like into the dressing, after it's blended, for a crunch. I put this on leafy greens. The kale salad recipes on this site are just great, It's like the dressing for those with some things added. Maybe this could be a good cold soup as well-I'll try that next time.
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oops. I was too excited. YUMMY. going to make this tonight
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text: Brooklyn Decker, Rachael Leigh Cook, Jamie Chung, Josh Henderson By Shauna W February 3, 2013 12:52 PM Share on Facebook Share on Twitter Category: Share on Facebook Share on Twitter More Leave a comment Send to a friend! Print this page Pin it! Reddit This! Share on Tumblr! Best of Mix 93.1 Powerball Lottery Jackpot Now At $422 Million [POLL] Stuff The Bus With Mix 93-1 And Citizens National Bank Kim Kardashian Has No Chill, Raps Along to Kanye's 'Famous' Taylor Swift Lyric 'The LEGO Batman Movie' Gets a Hilarious New Trailer For Comic-Con Recommended for You ZergNet Best of the Web ZergNet